Destination Unknown? Study Choices and Graduate Destinations of Hungarian Youth in Slovakia

ERIC Educational Resources Information Center

Pásztor, Adél

2018-01-01

Focusing on Hungarian minority youth in a rural Slovakian setting, this article analyses their higher education aspirations and choices amidst significant economic, political and educational reforms. Relying on mixed methods and a longitudinal design, the research follows a cohort of high school students from their last year of secondary school…

Reach, engagement, and effectiveness: a systematic review of evaluation methodologies used in health promotion via social networking sites.

PubMed

Lim, Megan S C; Wright, Cassandra J C; Carrotte, Elise R; Pedrana, Alisa E

2016-02-01

Issue addressed Social networking sites (SNS) are increasingly popular platforms for health promotion. Advancements in SNS health promotion require quality evidence; however, interventions are often not formally evaluated. This study aims to describe evaluation practices used in SNS health promotion. Methods A systematic review was undertaken of Medline, PsycINFO, Scopus, EMBASE, CINAHL Plus, Communication and Mass Media Complete, and Cochrane Library databases. Articles published between 2006 and 2013 describing any health promotion intervention delivered using SNS were included. Results Forty-seven studies were included. There were two main evaluation approaches: closed designs (n=23), which used traditional research designs and formal recruitment procedures; and open designs (n=19), which evaluated the intervention in a real-world setting, allowing unknown SNS users to interact with the content without enrolling in research. Closed designs were unable to assess reach and engagement beyond their research sample. Open designs often relied on weaker study designs with no use of objective outcome measures and yielded low response rates. Conclusions Barriers to evaluation included low participation rates, high attrition, unknown representativeness and lack of comparison groups. Acceptability was typically assessed among those engaged with the intervention, with limited population data available to accurately assess intervention reach. Few studies were able to assess uptake of the intervention in a real-life setting while simultaneously assessing effectiveness of interventions with research rigour. So what? Through use of quasi-experimental or well designed before-after evaluations, in combination with detailed engagement metrics, it is possible to balance assessment of effectiveness and reach to evaluate SNS health promotion.

Using Incremental Rehearsal to Teach Letter Sounds to English Language Learners

ERIC Educational Resources Information Center

Rahn, Naomi L.; Wilson, Jennifer; Egan, Andrea; Brandes, Dana; Kunkel, Amy; Peterson, Meredith; McComas, Jennifer

2015-01-01

This study examined the effects of incremental rehearsal (IR) on letter sound expression for one kindergarten and one first grade English learner who were below district benchmark for letter sound fluency. A single-subject multiple-baseline design across sets of unknown letter sounds was used to evaluate the effect of IR on letter-sound expression…

Impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach.

PubMed

Chandrasekar, A; Rakkiyappan, R; Cao, Jinde

2015-10-01

This paper studies the impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach. The array of neural networks are coupled in a random fashion which is governed by Bernoulli random variable. The aim of this paper is to obtain the synchronization criteria, which is suitable for both exactly known and partly unknown transition probabilities such that the coupled neural network is synchronized with mixed time-delay. The considered impulsive effects can be synchronized at partly unknown transition probabilities. Besides, a multiple integral approach is also proposed to strengthen the Markovian jumping randomly coupled neural networks with partly unknown transition probabilities. By making use of Kronecker product and some useful integral inequalities, a novel Lyapunov-Krasovskii functional was designed for handling the coupled neural network with mixed delay and then impulsive synchronization criteria are solvable in a set of linear matrix inequalities. Finally, numerical examples are presented to illustrate the effectiveness and advantages of the theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

"Finding the Joy in the Unknown": Implementation of STEAM Teaching Practices in Middle School Science and Math Classrooms

ERIC Educational Resources Information Center

Quigley, Cassie F.; Herro, Dani

2016-01-01

In response to a desire to strengthen the economy, educational settings are emphasizing science, technology, engineering, and mathematics (STEM) curriculum and programs. Yet, because of the narrow approach to STEM, educational leaders continue to call for a more balanced approach to teaching and learning, which includes the arts, design, and…

Design and verification of a pangenome microarray oligonucleotide probe set for Dehalococcoides spp.

PubMed

Hug, Laura A; Salehi, Maryam; Nuin, Paulo; Tillier, Elisabeth R; Edwards, Elizabeth A

2011-08-01

Dehalococcoides spp. are an industrially relevant group of Chloroflexi bacteria capable of reductively dechlorinating contaminants in groundwater environments. Existing Dehalococcoides genomes revealed a high level of sequence identity within this group, including 98 to 100% 16S rRNA sequence identity between strains with diverse substrate specificities. Common molecular techniques for identification of microbial populations are often not applicable for distinguishing Dehalococcoides strains. Here we describe an oligonucleotide microarray probe set designed based on clustered Dehalococcoides genes from five different sources (strain DET195, CBDB1, BAV1, and VS genomes and the KB-1 metagenome). This "pangenome" probe set provides coverage of core Dehalococcoides genes as well as strain-specific genes while optimizing the potential for hybridization to closely related, previously unknown Dehalococcoides strains. The pangenome probe set was compared to probe sets designed independently for each of the five Dehalococcoides strains. The pangenome probe set demonstrated better predictability and higher detection of Dehalococcoides genes than strain-specific probe sets on nontarget strains with <99% average nucleotide identity. An in silico analysis of the expected probe hybridization against the recently released Dehalococcoides strain GT genome and additional KB-1 metagenome sequence data indicated that the pangenome probe set performs more robustly than the combined strain-specific probe sets in the detection of genes not included in the original design. The pangenome probe set represents a highly specific, universal tool for the detection and characterization of Dehalococcoides from contaminated sites. It has the potential to become a common platform for Dehalococcoides-focused research, allowing meaningful comparisons between microarray experiments regardless of the strain examined.

Adaptive Fuzzy Output-Constrained Fault-Tolerant Control of Nonlinear Stochastic Large-Scale Systems With Actuator Faults.

PubMed

Li, Yongming; Ma, Zhiyao; Tong, Shaocheng

2017-09-01

The problem of adaptive fuzzy output-constrained tracking fault-tolerant control (FTC) is investigated for the large-scale stochastic nonlinear systems of pure-feedback form. The nonlinear systems considered in this paper possess the unstructured uncertainties, unknown interconnected terms and unknown nonaffine nonlinear faults. The fuzzy logic systems are employed to identify the unknown lumped nonlinear functions so that the problems of structured uncertainties can be solved. An adaptive fuzzy state observer is designed to solve the nonmeasurable state problem. By combining the barrier Lyapunov function theory, adaptive decentralized and stochastic control principles, a novel fuzzy adaptive output-constrained FTC approach is constructed. All the signals in the closed-loop system are proved to be bounded in probability and the system outputs are constrained in a given compact set. Finally, the applicability of the proposed controller is well carried out by a simulation example.

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities.

PubMed

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities

NASA Astrophysics Data System (ADS)

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.

Improving Bayesian credibility intervals for classifier error rates using maximum entropy empirical priors.

PubMed

Gustafsson, Mats G; Wallman, Mikael; Wickenberg Bolin, Ulrika; Göransson, Hanna; Fryknäs, M; Andersson, Claes R; Isaksson, Anders

2010-06-01

Successful use of classifiers that learn to make decisions from a set of patient examples require robust methods for performance estimation. Recently many promising approaches for determination of an upper bound for the error rate of a single classifier have been reported but the Bayesian credibility interval (CI) obtained from a conventional holdout test still delivers one of the tightest bounds. The conventional Bayesian CI becomes unacceptably large in real world applications where the test set sizes are less than a few hundred. The source of this problem is that fact that the CI is determined exclusively by the result on the test examples. In other words, there is no information at all provided by the uniform prior density distribution employed which reflects complete lack of prior knowledge about the unknown error rate. Therefore, the aim of the study reported here was to study a maximum entropy (ME) based approach to improved prior knowledge and Bayesian CIs, demonstrating its relevance for biomedical research and clinical practice. It is demonstrated how a refined non-uniform prior density distribution can be obtained by means of the ME principle using empirical results from a few designs and tests using non-overlapping sets of examples. Experimental results show that ME based priors improve the CIs when employed to four quite different simulated and two real world data sets. An empirically derived ME prior seems promising for improving the Bayesian CI for the unknown error rate of a designed classifier. Copyright 2010 Elsevier B.V. All rights reserved.

Effects of Systematic and Strategic Analogy-Based Phonics on Grade 2 Students' Word Reading and Reading Comprehension

ERIC Educational Resources Information Center

White, Thomas G.

2005-01-01

Fifteen regular grade 2 teachers used a set of 150 written lessons that were designed to develop, over the course of a school year, low and normally achieving students' ability to decode by analogy (i.e., to read unknown words using known words). The lessons provided (1) a planned sequence for teaching phonic elements including common spelling…

Parameterizations for ensemble Kalman inversion

NASA Astrophysics Data System (ADS)

Chada, Neil K.; Iglesias, Marco A.; Roininen, Lassi; Stuart, Andrew M.

2018-05-01

The use of ensemble methods to solve inverse problems is attractive because it is a derivative-free methodology which is also well-adapted to parallelization. In its basic iterative form the method produces an ensemble of solutions which lie in the linear span of the initial ensemble. Choice of the parameterization of the unknown field is thus a key component of the success of the method. We demonstrate how both geometric ideas and hierarchical ideas can be used to design effective parameterizations for a number of applied inverse problems arising in electrical impedance tomography, groundwater flow and source inversion. In particular we show how geometric ideas, including the level set method, can be used to reconstruct piecewise continuous fields, and we show how hierarchical methods can be used to learn key parameters in continuous fields, such as length-scales, resulting in improved reconstructions. Geometric and hierarchical ideas are combined in the level set method to find piecewise constant reconstructions with interfaces of unknown topology.

Optimizing the choice of spin-squeezed states for detecting and characterizing quantum processes

DOE PAGES

Rozema, Lee A.; Mahler, Dylan H.; Blume-Kohout, Robin; ...

2014-11-07

Quantum metrology uses quantum states with no classical counterpart to measure a physical quantity with extraordinary sensitivity or precision. Most such schemes characterize a dynamical process by probing it with a specially designed quantum state. The success of such a scheme usually relies on the process belonging to a particular one-parameter family. If this assumption is violated, or if the goal is to measure more than one parameter, a different quantum state may perform better. In the most extreme case, we know nothing about the process and wish to learn everything. This requires quantum process tomography, which demands an informationallymore » complete set of probe states. It is very convenient if this set is group covariant—i.e., each element is generated by applying an element of the quantum system’s natural symmetry group to a single fixed fiducial state. In this paper, we consider metrology with 2-photon (“biphoton”) states and report experimental studies of different states’ sensitivity to small, unknown collective SU( 2) rotations [“ SU( 2) jitter”]. Maximally entangled N00 N states are the most sensitive detectors of such a rotation, yet they are also among the worst at fully characterizing an a priori unknown process. We identify (and confirm experimentally) the best SU( 2)-covariant set for process tomography; these states are all less entangled than the N00 N state, and are characterized by the fact that they form a 2-design.« less

Long-term monitoring of sudden oak death in Marin County and the East Bay Hills

Treesearch

Brice A. McPherson; Greg Biging; Maggi Kelly; David L. Wood

2017-01-01

Prior to 2000 the etiology, effects on host trees, and possible consequences for northern California’s forests of the syndrome known as sudden oak death were unknown. We designed a plot-based study to address these issues and to set a baseline for future evaluations.In March-April 2000 we established a total of 20 plots in two forested...

Predicting the Functional Impact of KCNQ1 Variants of Unknown Significance.

PubMed

Li, Bian; Mendenhall, Jeffrey L; Kroncke, Brett M; Taylor, Keenan C; Huang, Hui; Smith, Derek K; Vanoye, Carlos G; Blume, Jeffrey D; George, Alfred L; Sanders, Charles R; Meiler, Jens

2017-10-01

An emerging standard-of-care for long-QT syndrome uses clinical genetic testing to identify genetic variants of the KCNQ1 potassium channel. However, interpreting results from genetic testing is confounded by the presence of variants of unknown significance for which there is inadequate evidence of pathogenicity. In this study, we curated from the literature a high-quality set of 107 functionally characterized KCNQ1 variants. Based on this data set, we completed a detailed quantitative analysis on the sequence conservation patterns of subdomains of KCNQ1 and the distribution of pathogenic variants therein. We found that conserved subdomains generally are critical for channel function and are enriched with dysfunctional variants. Using this experimentally validated data set, we trained a neural network, designated Q1VarPred, specifically for predicting the functional impact of KCNQ1 variants of unknown significance. The estimated predictive performance of Q1VarPred in terms of Matthew's correlation coefficient and area under the receiver operating characteristic curve were 0.581 and 0.884, respectively, superior to the performance of 8 previous methods tested in parallel. Q1VarPred is publicly available as a web server at http://meilerlab.org/q1varpred. Although a plethora of tools are available for making pathogenicity predictions over a genome-wide scale, previous tools fail to perform in a robust manner when applied to KCNQ1. The contrasting and favorable results for Q1VarPred suggest a promising approach, where a machine-learning algorithm is tailored to a specific protein target and trained with a functionally validated data set to calibrate informatics tools. © 2017 American Heart Association, Inc.

A design study of a signal detection system. [for search of extraterrestrial radio sources

NASA Technical Reports Server (NTRS)

Healy, T. J.

1980-01-01

A system is described which can aid in the search for radio signals from extraterrestrial sources, or in other applications characterized by low signal-to-noise ratios and very high data rates. The system follows a multichannel (16 million bin) spectrum analyzer, and has critical processing, system control, and memory fuctions. The design includes a moderately rich set of algorithms to be used in parallel to detect signals of unknown form. A multi-threshold approach is used to obtain high and low signal sensitivities. Relatively compact and transportable memory systems are specified.

A dynamical approach in exploring the unknown mass in the Solar system using pulsar timing arrays

NASA Astrophysics Data System (ADS)

Guo, Y. J.; Lee, K. J.; Caballero, R. N.

2018-04-01

The error in the Solar system ephemeris will lead to dipolar correlations in the residuals of pulsar timing array for widely separated pulsars. In this paper, we utilize such correlated signals, and construct a Bayesian data-analysis framework to detect the unknown mass in the Solar system and to measure the orbital parameters. The algorithm is designed to calculate the waveform of the induced pulsar-timing residuals due to the unmodelled objects following the Keplerian orbits in the Solar system. The algorithm incorporates a Bayesian-analysis suit used to simultaneously analyse the pulsar-timing data of multiple pulsars to search for coherent waveforms, evaluate the detection significance of unknown objects, and to measure their parameters. When the object is not detectable, our algorithm can be used to place upper limits on the mass. The algorithm is verified using simulated data sets, and cross-checked with analytical calculations. We also investigate the capability of future pulsar-timing-array experiments in detecting the unknown objects. We expect that the future pulsar-timing data can limit the unknown massive objects in the Solar system to be lighter than 10-11-10-12 M⊙, or measure the mass of Jovian system to a fractional precision of 10-8-10-9.

Probabilistic Modeling of Aircraft Trajectories for Dynamic Separation Volumes

NASA Technical Reports Server (NTRS)

Lewis, Timothy A.

2016-01-01

With a proliferation of new and unconventional vehicles and operations expected in the future, the ab initio airspace design will require new approaches to trajectory prediction for separation assurance and other air traffic management functions. This paper presents an approach to probabilistic modeling of the trajectory of an aircraft when its intent is unknown. The approach uses a set of feature functions to constrain a maximum entropy probability distribution based on a set of observed aircraft trajectories. This model can be used to sample new aircraft trajectories to form an ensemble reflecting the variability in an aircraft's intent. The model learning process ensures that the variability in this ensemble reflects the behavior observed in the original data set. Computational examples are presented.

Parameterization of Model Validating Sets for Uncertainty Bound Optimizations. Revised

NASA Technical Reports Server (NTRS)

Lim, K. B.; Giesy, D. P.

2000-01-01

Given measurement data, a nominal model and a linear fractional transformation uncertainty structure with an allowance on unknown but bounded exogenous disturbances, easily computable tests for the existence of a model validating uncertainty set are given. Under mild conditions, these tests are necessary and sufficient for the case of complex, nonrepeated, block-diagonal structure. For the more general case which includes repeated and/or real scalar uncertainties, the tests are only necessary but become sufficient if a collinearity condition is also satisfied. With the satisfaction of these tests, it is shown that a parameterization of all model validating sets of plant models is possible. The new parameterization is used as a basis for a systematic way to construct or perform uncertainty tradeoff with model validating uncertainty sets which have specific linear fractional transformation structure for use in robust control design and analysis. An illustrative example which includes a comparison of candidate model validating sets is given.

A Study of False-Positive and False-Negative Error Rates in Cartridge Case Comparisons

DTIC Science & Technology

2014-04-07

materials for the study, in particular Vicki Sieve. 3 Abstract: This report provides the details for a study designed to...participate in ASCLD were provided with 15 sets of 3 known + 1 unknown cartridge cases fired from a collection of 25 new Ruger SR9 handguns . The...answer sheet allowing for the AFTE range of conclusions, and return shipping materials . They were also asked to assess how many of the 3 knowns were

Adaptive NN controller design for a class of nonlinear MIMO discrete-time systems.

PubMed

Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip

2015-05-01

An adaptive neural network tracking control is studied for a class of multiple-input multiple-output (MIMO) nonlinear systems. The studied systems are in discrete-time form and the discretized dead-zone inputs are considered. In addition, the studied MIMO systems are composed of N subsystems, and each subsystem contains unknown functions and external disturbance. Due to the complicated framework of the discrete-time systems, the existence of the dead zone and the noncausal problem in discrete-time, it brings about difficulties for controlling such a class of systems. To overcome the noncausal problem, by defining the coordinate transformations, the studied systems are transformed into a special form, which is suitable for the backstepping design. The radial basis functions NNs are utilized to approximate the unknown functions of the systems. The adaptation laws and the controllers are designed based on the transformed systems. By using the Lyapunov method, it is proved that the closed-loop system is stable in the sense that the semiglobally uniformly ultimately bounded of all the signals and the tracking errors converge to a bounded compact set. The simulation examples and the comparisons with previous approaches are provided to illustrate the effectiveness of the proposed control algorithm.

Multiplex Degenerate Primer Design for Targeted Whole Genome Amplification of Many Viral Genomes

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

Gardner, Shea N.; Jaing, Crystal J.; Elsheikh, Maher M.

Background . Targeted enrichment improves coverage of highly mutable viruses at low concentration in complex samples. Degenerate primers that anneal to conserved regions can facilitate amplification of divergent, low concentration variants, even when the strain present is unknown. Results . A tool for designing multiplex sets of degenerate sequencing primers to tile overlapping amplicons across multiple whole genomes is described. The new script, run_tiled_primers, is part of the PriMux software. Primers were designed for each segment of South American hemorrhagic fever viruses, tick-borne encephalitis, Henipaviruses, Arenaviruses, Filoviruses, Crimean-Congo hemorrhagic fever virus, Rift Valley fever virus, and Japanese encephalitis virus. Eachmore » group is highly diverse with as little as 5% genome consensus. Primer sets were computationally checked for nontarget cross reactions against the NCBI nucleotide sequence database. Primers for murine hepatitis virus were demonstrated in the lab to specifically amplify selected genes from a laboratory cultured strain that had undergone extensive passage in vitro and in vivo. Conclusions . This software should help researchers design multiplex sets of primers for targeted whole genome enrichment prior to sequencing to obtain better coverage of low titer, divergent viruses. Applications include viral discovery from a complex background and improved sensitivity and coverage of rapidly evolving strains or variants in a gene family.« less

Multiplex Degenerate Primer Design for Targeted Whole Genome Amplification of Many Viral Genomes

DOE PAGES

Gardner, Shea N.; Jaing, Crystal J.; Elsheikh, Maher M.; ...

2014-01-01

Background . Targeted enrichment improves coverage of highly mutable viruses at low concentration in complex samples. Degenerate primers that anneal to conserved regions can facilitate amplification of divergent, low concentration variants, even when the strain present is unknown. Results . A tool for designing multiplex sets of degenerate sequencing primers to tile overlapping amplicons across multiple whole genomes is described. The new script, run_tiled_primers, is part of the PriMux software. Primers were designed for each segment of South American hemorrhagic fever viruses, tick-borne encephalitis, Henipaviruses, Arenaviruses, Filoviruses, Crimean-Congo hemorrhagic fever virus, Rift Valley fever virus, and Japanese encephalitis virus. Eachmore » group is highly diverse with as little as 5% genome consensus. Primer sets were computationally checked for nontarget cross reactions against the NCBI nucleotide sequence database. Primers for murine hepatitis virus were demonstrated in the lab to specifically amplify selected genes from a laboratory cultured strain that had undergone extensive passage in vitro and in vivo. Conclusions . This software should help researchers design multiplex sets of primers for targeted whole genome enrichment prior to sequencing to obtain better coverage of low titer, divergent viruses. Applications include viral discovery from a complex background and improved sensitivity and coverage of rapidly evolving strains or variants in a gene family.« less

Identification of vehicle suspension parameters by design optimization

NASA Astrophysics Data System (ADS)

Tey, J. Y.; Ramli, R.; Kheng, C. W.; Chong, S. Y.; Abidin, M. A. Z.

2014-05-01

The design of a vehicle suspension system through simulation requires accurate representation of the design parameters. These parameters are usually difficult to measure or sometimes unavailable. This article proposes an efficient approach to identify the unknown parameters through optimization based on experimental results, where the covariance matrix adaptation-evolutionary strategy (CMA-es) is utilized to improve the simulation and experimental results against the kinematic and compliance tests. This speeds up the design and development cycle by recovering all the unknown data with respect to a set of kinematic measurements through a single optimization process. A case study employing a McPherson strut suspension system is modelled in a multi-body dynamic system. Three kinematic and compliance tests are examined, namely, vertical parallel wheel travel, opposite wheel travel and single wheel travel. The problem is formulated as a multi-objective optimization problem with 40 objectives and 49 design parameters. A hierarchical clustering method based on global sensitivity analysis is used to reduce the number of objectives to 30 by grouping correlated objectives together. Then, a dynamic summation of rank value is used as pseudo-objective functions to reformulate the multi-objective optimization to a single-objective optimization problem. The optimized results show a significant improvement in the correlation between the simulated model and the experimental model. Once accurate representation of the vehicle suspension model is achieved, further analysis, such as ride and handling performances, can be implemented for further optimization.

Opportunistic pathology-based screening for diabetes

PubMed Central

Simpson, Aaron J; Krowka, Renata; Kerrigan, Jennifer L; Southcott, Emma K; Wilson, J Dennis; Potter, Julia M; Nolan, Christopher J; Hickman, Peter E

2013-01-01

Objective To determine the potential of opportunistic glycated haemoglobin (HbA1c) testing of pathology samples to detect previously unknown diabetes. Design Pathology samples from participants collected for other reasons and suitable for HbA1c testing were utilised for opportunistic diabetes screening. HbA1c was measured with a Biorad Variant II turbo analyser and HbA1c levels of ≥6.5% (48 mmol/mol) were considered diagnostic for diabetes. Confirmation of previously unknown diabetes status was obtained by a review of hospital medical records and phone calls to general practitioners. Setting Hospital pathology laboratory receiving samples from hospital-based and community-based (CB) settings. Participants Participants were identified based on the blood sample collection location in the CB, emergency department (ED) and inpatient (IP) groups. Exclusions pretesting were made based on the electronic patient history of: age <18 years, previous diabetes diagnosis, query for diabetes status in the past 12 months, evidence of pregnancy and sample collected postsurgery or transfusion. Only one sample per individual participant was tested. Results Of the 22 396 blood samples collected, 4505 (1142 CB, 1113 ED, 2250 IP) were tested of which 327 (7.3%) had HbA1c levels ≥6.5% (48 mmol/mol). Of these 120 (2.7%) were determined to have previously unknown diabetes (11 (1%) CB, 21 (1.9%) ED, 88 (3.9%) IP). The prevalence of previously unknown diabetes was substantially higher (5.4%) in hospital-based (ED and IP) participants aged over 54 years. Conclusions Opportunistic testing of referred pathology samples can be an effective method of screening for diabetes, especially in hospital-based and older persons. PMID:24065696

A new approach to aid the characterisation and identification of metabolites of a model drug; partial isotope enrichment combined with novel formula elucidation software.

PubMed

Hobby, Kirsten; Gallagher, Richard T; Caldwell, Patrick; Wilson, Ian D

2009-01-01

This work describes the identification of 'isotopically enriched' metabolites of 4-cyanoaniline using the unique features of the software package 'Spectral Simplicity'. The software is capable of creating the theoretical mass spectra for partially isotope-enriched compounds, and subsequently performing an elemental composition analysis to give the elemental formula for the 'isotopically enriched' metabolite. A novel mass spectral correlation method, called 'FuzzyFit', was employed. 'FuzzyFit' utilises the expected experimental distribution of errors in both mass accuracy and isotope pattern and enables discrimination between statistically probable and improbable candidate formulae. The software correctly determined the molecular formulae of ten previously described metabolites of 4-cyanoaniline confirming the technique of partial isotope enrichment can produce results analogous to standard methodologies. Six previously unknown species were also identified, based on the presence of the unique 'designer' isotope ratio. Three of the unknowns were tentatively identified as N-acetylglutamine, O-methyl-N acetylglucuronide and a putative fatty acid conjugate. The discovery of a significant number of unknown species of a model drug with a comprehensive history of investigation highlights the potential for enhancement to the analytical process by the use of 'designer' isotope ratio compounds. The 'FuzzyFit' methodology significantly aided the elucidation of candidate formulae, by provision of a vastly simplified candidate formula data set. Copyright (c) 2008 John Wiley & Sons, Ltd.

A Multi-Resolution Nonlinear Mapping Technique for Design and Analysis Applications

NASA Technical Reports Server (NTRS)

Phan, Minh Q.

1998-01-01

This report describes a nonlinear mapping technique where the unknown static or dynamic system is approximated by a sum of dimensionally increasing functions (one-dimensional curves, two-dimensional surfaces, etc.). These lower dimensional functions are synthesized from a set of multi-resolution basis functions, where the resolutions specify the level of details at which the nonlinear system is approximated. The basis functions also cause the parameter estimation step to become linear. This feature is taken advantage of to derive a systematic procedure to determine and eliminate basis functions that are less significant for the particular system under identification. The number of unknown parameters that must be estimated is thus reduced and compact models obtained. The lower dimensional functions (identified curves and surfaces) permit a kind of "visualization" into the complexity of the nonlinearity itself.

3D tomographic reconstruction using geometrical models

NASA Astrophysics Data System (ADS)

Battle, Xavier L.; Cunningham, Gregory S.; Hanson, Kenneth M.

1997-04-01

We address the issue of reconstructing an object of constant interior density in the context of 3D tomography where there is prior knowledge about the unknown shape. We explore the direct estimation of the parameters of a chosen geometrical model from a set of radiographic measurements, rather than performing operations (segmentation for example) on a reconstructed volume. The inverse problem is posed in the Bayesian framework. A triangulated surface describes the unknown shape and the reconstruction is computed with a maximum a posteriori (MAP) estimate. The adjoint differentiation technique computes the derivatives needed for the optimization of the model parameters. We demonstrate the usefulness of the approach and emphasize the techniques of designing forward and adjoint codes. We use the system response of the University of Arizona Fast SPECT imager to illustrate this method by reconstructing the shape of a heart phantom.

A Multi-Resolution Nonlinear Mapping Technique for Design and Analysis Application

NASA Technical Reports Server (NTRS)

Phan, Minh Q.

1997-01-01

This report describes a nonlinear mapping technique where the unknown static or dynamic system is approximated by a sum of dimensionally increasing functions (one-dimensional curves, two-dimensional surfaces, etc.). These lower dimensional functions are synthesized from a set of multi-resolution basis functions, where the resolutions specify the level of details at which the nonlinear system is approximated. The basis functions also cause the parameter estimation step to become linear. This feature is taken advantage of to derive a systematic procedure to determine and eliminate basis functions that are less significant for the particular system under identification. The number of unknown parameters that must be estimated is thus reduced and compact models obtained. The lower dimensional functions (identified curves and surfaces) permit a kind of "visualization" into the complexity of the nonlinearity itself.

Parameter identifiability of linear dynamical systems

NASA Technical Reports Server (NTRS)

Glover, K.; Willems, J. C.

1974-01-01

It is assumed that the system matrices of a stationary linear dynamical system were parametrized by a set of unknown parameters. The question considered here is, when can such a set of unknown parameters be identified from the observed data? Conditions for the local identifiability of a parametrization are derived in three situations: (1) when input/output observations are made, (2) when there exists an unknown feedback matrix in the system and (3) when the system is assumed to be driven by white noise and only output observations are made. Also a sufficient condition for global identifiability is derived.

Extracting scene feature vectors through modeling, volume 3

NASA Technical Reports Server (NTRS)

Berry, J. K.; Smith, J. A.

1976-01-01

The remote estimation of the leaf area index of winter wheat at Finney County, Kansas was studied. The procedure developed consists of three activities: (1) field measurements; (2) model simulations; and (3) response classifications. The first activity is designed to identify model input parameters and develop a model evaluation data set. A stochastic plant canopy reflectance model is employed to simulate reflectance in the LANDSAT bands as a function of leaf area index for two phenological stages. An atmospheric model is used to translate these surface reflectances into simulated satellite radiance. A divergence classifier determines the relative similarity between model derived spectral responses and those of areas with unknown leaf area index. The unknown areas are assigned the index associated with the closest model response. This research demonstrated that the SRVC canopy reflectance model is appropriate for wheat scenes and that broad categories of leaf area index can be inferred from the procedure developed.

PCSK9: From Basic Science Discoveries to Clinical Trials.

PubMed

Shapiro, Michael D; Tavori, Hagai; Fazio, Sergio

2018-05-11

Unknown 15 years ago, PCSK9 (proprotein convertase subtilisin/kexin type 9) is now common parlance among scientists and clinicians interested in prevention and treatment of atherosclerotic cardiovascular disease. What makes this story so special is not its recent discovery nor the fact that it uncovered previously unknown biology but rather that these important scientific insights have been translated into an effective medical therapy in record time. Indeed, the translation of this discovery to novel therapeutic serves as one of the best examples of how genetic insights can be leveraged into intelligent target drug discovery. The PCSK9 saga is unfolding quickly but is far from complete. Here, we review major scientific understandings as they relate to the role of PCSK9 in lipoprotein metabolism and atherosclerotic cardiovascular disease and the impact that therapies designed to inhibit its action are having in the clinical setting. © 2018 American Heart Association, Inc.

M-MRAC Backstepping for Systems with Unknown Virtual Control Coefficients

NASA Technical Reports Server (NTRS)

Stepanyan, Vahram; Krishnakumar, Kalmanje

2015-01-01

The paper presents an over-parametrization free certainty equivalence state feedback backstepping adaptive control design method for systems of any relative degree with unmatched uncertainties and unknown virtual control coefficients. It uses a fast prediction model to estimate the unknown parameters, which is independent of the control design. It is shown that the system's input and output tracking errors can be systematically decreased by the proper choice of the design parameters. The benefits of the approach are demonstrated in numerical simulations.

Decentralized learning in Markov games.

PubMed

Vrancx, Peter; Verbeeck, Katja; Nowé, Ann

2008-08-01

Learning automata (LA) were recently shown to be valuable tools for designing multiagent reinforcement learning algorithms. One of the principal contributions of the LA theory is that a set of decentralized independent LA is able to control a finite Markov chain with unknown transition probabilities and rewards. In this paper, we propose to extend this algorithm to Markov games--a straightforward extension of single-agent Markov decision problems to distributed multiagent decision problems. We show that under the same ergodic assumptions of the original theorem, the extended algorithm will converge to a pure equilibrium point between agent policies.

How to Frame the Un-Known? The Odd Alliance of Design and "Fundamental Physics" in a Design School

ERIC Educational Resources Information Center

Gentes, Annie; Renon, Anne-Lyse; Bobroff, Julien

2017-01-01

This paper analyzes the introduction of fundamental physics in design education as a pedagogical method that trains designers to create with the un-known. It studies how three workshops offered design students to work on: superconductivity in 2011, quantum physics in 2013 and light and optics in 2014. The authors observe that introducing physics…

Design Pedagogy for an Unknown Future: A View from the Expanding Field of Design Scholarship and Professional Practice

ERIC Educational Resources Information Center

Wilson, Stephanie Elizabeth; Zamberlan, Lisa

2017-01-01

This article draws on current research investigating the notion of design for an unknown future. It reflects on recent thinking about the role of creativity in design practice and discusses implications for the development and assessment of creativity in the design studio. It begins with a review of literature on the issues and challenges…

Creative user-centered visualization design for energy analysts and modelers.

PubMed

Goodwin, Sarah; Dykes, Jason; Jones, Sara; Dillingham, Iain; Dove, Graham; Duffy, Alison; Kachkaev, Alexander; Slingsby, Aidan; Wood, Jo

2013-12-01

We enhance a user-centered design process with techniques that deliberately promote creativity to identify opportunities for the visualization of data generated by a major energy supplier. Visualization prototypes developed in this way prove effective in a situation whereby data sets are largely unknown and requirements open - enabling successful exploration of possibilities for visualization in Smart Home data analysis. The process gives rise to novel designs and design metaphors including data sculpting. It suggests: that the deliberate use of creativity techniques with data stakeholders is likely to contribute to successful, novel and effective solutions; that being explicit about creativity may contribute to designers developing creative solutions; that using creativity techniques early in the design process may result in a creative approach persisting throughout the process. The work constitutes the first systematic visualization design for a data rich source that will be increasingly important to energy suppliers and consumers as Smart Meter technology is widely deployed. It is novel in explicitly employing creativity techniques at the requirements stage of visualization design and development, paving the way for further use and study of creativity methods in visualization design.

An Error-Entropy Minimization Algorithm for Tracking Control of Nonlinear Stochastic Systems with Non-Gaussian Variables

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

Liu, Yunlong; Wang, Aiping; Guo, Lei

This paper presents an error-entropy minimization tracking control algorithm for a class of dynamic stochastic system. The system is represented by a set of time-varying discrete nonlinear equations with non-Gaussian stochastic input, where the statistical properties of stochastic input are unknown. By using Parzen windowing with Gaussian kernel to estimate the probability densities of errors, recursive algorithms are then proposed to design the controller such that the tracking error can be minimized. The performance of the error-entropy minimization criterion is compared with the mean-square-error minimization in the simulation results.

Observer-based state tracking control of uncertain stochastic systems via repetitive controller

NASA Astrophysics Data System (ADS)

Sakthivel, R.; Susana Ramya, L.; Selvaraj, P.

2017-08-01

This paper develops the repetitive control scheme for state tracking control of uncertain stochastic time-varying delay systems via equivalent-input-disturbance approach. The main purpose of this work is to design a repetitive controller to guarantee the tracking performance under the effects of unknown disturbances with bounded frequency and parameter variations. Specifically, a new set of linear matrix inequality (LMI)-based conditions is derived based on the suitable Lyapunov-Krasovskii functional theory for designing a repetitive controller which guarantees stability and desired tracking performance. More precisely, an equivalent-input-disturbance estimator is incorporated into the control design to reduce the effect of the external disturbances. Simulation results are provided to demonstrate the desired control system stability and their tracking performance. A practical stream water quality preserving system is also provided to show the effectiveness and advantage of the proposed approach.

The Study of the Relationship between Probabilistic Design and Axiomatic Design Methodology. Volume 2

NASA Technical Reports Server (NTRS)

Onwubiko, Chin-Yere; Onyebueke, Landon

1996-01-01

The structural design, or the design of machine elements, has been traditionally based on deterministic design methodology. The deterministic method considers all design parameters to be known with certainty. This methodology is, therefore, inadequate to design complex structures that are subjected to a variety of complex, severe loading conditions. A nonlinear behavior that is dependent on stress, stress rate, temperature, number of load cycles, and time is observed on all components subjected to complex conditions. These complex conditions introduce uncertainties; hence, the actual factor of safety margin remains unknown. In the deterministic methodology, the contingency of failure is discounted; hence, there is a use of a high factor of safety. It may be most useful in situations where the design structures are simple. The probabilistic method is concerned with the probability of non-failure performance of structures or machine elements. It is much more useful in situations where the design is characterized by complex geometry, possibility of catastrophic failure, sensitive loads and material properties. Also included: Comparative Study of the use of AGMA Geometry Factors and Probabilistic Design Methodology in the Design of Compact Spur Gear Set.

An efficient and flexible Abel-inversion method for noisy data

NASA Astrophysics Data System (ADS)

Antokhin, Igor I.

2016-12-01

We propose an efficient and flexible method for solving the Abel integral equation of the first kind, frequently appearing in many fields of astrophysics, physics, chemistry, and applied sciences. This equation represents an ill-posed problem, thus solving it requires some kind of regularization. Our method is based on solving the equation on a so-called compact set of functions and/or using Tikhonov's regularization. A priori constraints on the unknown function, defining a compact set, are very loose and can be set using simple physical considerations. Tikhonov's regularization in itself does not require any explicit a priori constraints on the unknown function and can be used independently of such constraints or in combination with them. Various target degrees of smoothness of the unknown function may be set, as required by the problem at hand. The advantage of the method, apart from its flexibility, is that it gives uniform convergence of the approximate solution to the exact solution, as the errors of input data tend to zero. The method is illustrated on several simulated models with known solutions. An example of astrophysical application of the method is also given.

Existence conditions for unknown input functional observers

NASA Astrophysics Data System (ADS)

Fernando, T.; MacDougall, S.; Sreeram, V.; Trinh, H.

2013-01-01

This article presents necessary and sufficient conditions for the existence and design of an unknown input Functional observer. The existence of the observer can be verified by computing a nullspace of a known matrix and testing some matrix rank conditions. The existence of the observer does not require the satisfaction of the observer matching condition (i.e. Equation (16) in Hou and Muller 1992, 'Design of Observers for Linear Systems with Unknown Inputs', IEEE Transactions on Automatic Control, 37, 871-875), is not limited to estimating scalar functionals and allows for arbitrary pole placement. The proposed observer always exists when a state observer exists for the unknown input system, and furthermore, the proposed observer can exist even in some instances when an unknown input state observer does not exist.

Supervising Athletic Trainers' Perceptions of Professional Socialization of Graduate Assistant Athletic Trainers in the Collegiate Setting

PubMed Central

Thrasher, Ashley B.; Walker, Stacy E.; Hankemeier, Dorice A.; Pitney, William A.

2015-01-01

Context: Many newly credentialed athletic trainers gain initial employment as graduate assistants (GAs) in the collegiate setting, yet their socialization into their role is unknown. Exploring the socialization process of GAs in the collegiate setting could provide insight into how that process occurs. Objective: To explore the professional socialization of GAs in the collegiate setting to determine how GAs are socialized and developed as athletic trainers. Design: Qualitative study. Setting: Individual phone interviews. Patients or Other Participants: Athletic trainers (N = 21) who had supervised GAs in the collegiate setting for a minimum of 8 years (16 men [76%], 5 women [24%]; years of supervision experience = 14.6 ± 6.6). Data Collection and Analysis: Data were collected via phone interviews, which were recorded and transcribed verbatim. Data were analyzed by a 4-person consensus team with a consensual qualitative-research design. The team independently coded the data and compared ideas until a consensus was reached, and a codebook was created. Trustworthiness was established through member checks and multianalyst triangulation. Results: Four themes emerged: (1) role orientation, (2) professional development and support, (3) role expectations, and (4) success. Role orientation occurred both formally (eg, review of policies and procedures) and informally (eg, immediate role immersion). Professional development and support consisted of the supervisor mentoring and intervening when appropriate. Role expectations included decision-making ability, independent practice, and professionalism; however, supervisors often expected GAs to function as experienced, full-time staff. Success of the GAs depended on their adaptability and on the proper selection of GAs by supervisors. Conclusions: Supervisors socialize GAs into the collegiate setting by providing orientation, professional development, mentoring, and intervention when necessary. Supervisors are encouraged to use these socialization tactics to enhance the professional development of GAs in the collegiate setting. PMID:25347237

Progressive compressive imager

NASA Astrophysics Data System (ADS)

Evladov, Sergei; Levi, Ofer; Stern, Adrian

2012-06-01

We have designed and built a working automatic progressive sampling imaging system based on the vector sensor concept, which utilizes a unique sampling scheme of Radon projections. This sampling scheme makes it possible to progressively add information resulting in tradeoff between compression and the quality of reconstruction. The uniqueness of our sampling is that in any moment of the acquisition process the reconstruction can produce a reasonable version of the image. The advantage of the gradual addition of the samples is seen when the sparsity rate of the object is unknown, and thus the number of needed measurements. We have developed the iterative algorithm OSO (Ordered Sets Optimization) which employs our sampling scheme for creation of nearly uniform distributed sets of samples, which allows the reconstruction of Mega-Pixel images. We present the good quality reconstruction from compressed data ratios of 1:20.

Automated extraction of decision rules for leptin dynamics--a rough sets approach.

PubMed

Brtka, Vladimir; Stokić, Edith; Srdić, Biljana

2008-08-01

A significant area in the field of medical informatics is concerned with the learning of medical models from low-level data. The goals of inducing models from data are twofold: analysis of the structure of the models so as to gain new insight into the unknown phenomena, and development of classifiers or outcome predictors for unseen cases. In this paper, we will employ approach based on the relation of indiscernibility and rough sets theory to study certain questions concerning the design of model based on if-then rules, from low-level data including 36 parameters, one of them leptin. To generate easy to read, interpret, and inspect model, we have used ROSETTA software system. The main goal of this work is to get new insight into phenomena of leptin levels while interplaying with other risk factors in obesity.

End-to-End Commitment

NASA Technical Reports Server (NTRS)

Newcomb, John

2004-01-01

The end-to-end test would verify the complex sequence of events from lander separation to landing. Due to the large distances involved and the significant delay time in sending a command and receiving verification, the lander needed to operate autonomously after it separated from the orbiter. It had to sense conditions, make decisions, and act accordingly. We were flying into a relatively unknown set of conditions-a Martian atmosphere of unknown pressure, density, and consistency to land on a surface of unknown altitude, and one which had an unknown bearing strength.

A comparison of Monte Carlo-based Bayesian parameter estimation methods for stochastic models of genetic networks

PubMed Central

Zaikin, Alexey; Míguez, Joaquín

2017-01-01

We compare three state-of-the-art Bayesian inference methods for the estimation of the unknown parameters in a stochastic model of a genetic network. In particular, we introduce a stochastic version of the paradigmatic synthetic multicellular clock model proposed by Ullner et al., 2007. By introducing dynamical noise in the model and assuming that the partial observations of the system are contaminated by additive noise, we enable a principled mechanism to represent experimental uncertainties in the synthesis of the multicellular system and pave the way for the design of probabilistic methods for the estimation of any unknowns in the model. Within this setup, we tackle the Bayesian estimation of a subset of the model parameters. Specifically, we compare three Monte Carlo based numerical methods for the approximation of the posterior probability density function of the unknown parameters given a set of partial and noisy observations of the system. The schemes we assess are the particle Metropolis-Hastings (PMH) algorithm, the nonlinear population Monte Carlo (NPMC) method and the approximate Bayesian computation sequential Monte Carlo (ABC-SMC) scheme. We present an extensive numerical simulation study, which shows that while the three techniques can effectively solve the problem there are significant differences both in estimation accuracy and computational efficiency. PMID:28797087

Making an unknown unknown a known unknown: Missing data in longitudinal neuroimaging studies.

PubMed

Matta, Tyler H; Flournoy, John C; Byrne, Michelle L

2017-10-28

The analysis of longitudinal neuroimaging data within the massively univariate framework provides the opportunity to study empirical questions about neurodevelopment. Missing outcome data are an all-to-common feature of any longitudinal study, a feature that, if handled improperly, can reduce statistical power and lead to biased parameter estimates. The goal of this paper is to provide conceptual clarity of the issues and non-issues that arise from analyzing incomplete data in longitudinal studies with particular focus on neuroimaging data. This paper begins with a review of the hierarchy of missing data mechanisms and their relationship to likelihood-based methods, a review that is necessary not just for likelihood-based methods, but also for multiple-imputation methods. Next, the paper provides a series of simulation studies with designs common in longitudinal neuroimaging studies to help illustrate missing data concepts regardless of interpretation. Finally, two applied examples are used to demonstrate the sensitivity of inferences under different missing data assumptions and how this may change the substantive interpretation. The paper concludes with a set of guidelines for analyzing incomplete longitudinal data that can improve the validity of research findings in developmental neuroimaging research. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Will Systems Biology Deliver Its Promise and Contribute to the Development of New or Improved Vaccines? What Really Constitutes the Study of "Systems Biology" and How Might Such an Approach Facilitate Vaccine Design.

PubMed

Germain, Ronald N

2017-10-16

A dichotomy exists in the field of vaccinology about the promise versus the hype associated with application of "systems biology" approaches to rational vaccine design. Some feel it is the only way to efficiently uncover currently unknown parameters controlling desired immune responses or discover what elements actually mediate these responses. Others feel that traditional experimental, often reductionist, methods for incrementally unraveling complex biology provide a more solid way forward, and that "systems" approaches are costly ways to collect data without gaining true insight. Here I argue that both views are inaccurate. This is largely because of confusion about what can be gained from classical experimentation versus statistical analysis of large data sets (bioinformatics) versus methods that quantitatively explain emergent properties of complex assemblies of biological components, with the latter reflecting what was previously called "physiology." Reductionist studies will remain essential for generating detailed insight into the functional attributes of specific elements of biological systems, but such analyses lack the power to provide a quantitative and predictive understanding of global system behavior. But by employing (1) large-scale screening methods for discovery of unknown components and connections in the immune system ( omics ), (2) statistical analysis of large data sets ( bioinformatics ), and (3) the capacity of quantitative computational methods to translate these individual components and connections into models of emergent behavior ( systems biology ), we will be able to better understand how the overall immune system functions and to determine with greater precision how to manipulate it to produce desired protective responses. Copyright © 2017 Cold Spring Harbor Laboratory Press; all rights reserved.

Disturbance observer-based adaptive sliding mode hybrid projective synchronisation of identical fractional-order financial systems

NASA Astrophysics Data System (ADS)

Khan, Ayub; Tyagi, Arti

2018-05-01

In this paper, we have studied the hybrid projective synchronisation for incommensurate, integer and commensurate fractional-order financial systems with unknown disturbance. To tackle the problem of unknown bounded disturbance, fractional-order disturbance observer is designed to approximate the unknown disturbance. Further, we have introduced simple sliding mode surface and designed adaptive sliding mode controllers incorporating with the designed fractional-order disturbance observer to achieve a bounded hybrid projective synchronisation between two identical fractional-order financial model with different initial conditions. It is shown that the slave system with disturbance can be synchronised with the projection of the master system generated through state transformation. Simulation results are presented to ensure the validity and effectiveness of the proposed sliding mode control scheme in the presence of external bounded unknown disturbance. Also, synchronisation error for commensurate, integer and incommensurate fractional-order financial systems is studied in numerical simulation.

[Local Regression Algorithm Based on Net Analyte Signal and Its Application in Near Infrared Spectral Analysis].

PubMed

Zhang, Hong-guang; Lu, Jian-gang

2016-02-01

Abstract To overcome the problems of significant difference among samples and nonlinearity between the property and spectra of samples in spectral quantitative analysis, a local regression algorithm is proposed in this paper. In this algorithm, net signal analysis method(NAS) was firstly used to obtain the net analyte signal of the calibration samples and unknown samples, then the Euclidean distance between net analyte signal of the sample and net analyte signal of calibration samples was calculated and utilized as similarity index. According to the defined similarity index, the local calibration sets were individually selected for each unknown sample. Finally, a local PLS regression model was built on each local calibration sets for each unknown sample. The proposed method was applied to a set of near infrared spectra of meat samples. The results demonstrate that the prediction precision and model complexity of the proposed method are superior to global PLS regression method and conventional local regression algorithm based on spectral Euclidean distance.

Prediction of new bioactive molecules using a Bayesian belief network.

PubMed

Abdo, Ammar; Leclère, Valérie; Jacques, Philippe; Salim, Naomie; Pupin, Maude

2014-01-27

Natural products and synthetic compounds are a valuable source of new small molecules leading to novel drugs to cure diseases. However identifying new biologically active small molecules is still a challenge. In this paper, we introduce a new activity prediction approach using Bayesian belief network for classification (BBNC). The roots of the network are the fragments composing a compound. The leaves are, on one side, the activities to predict and, on another side, the unknown compound. The activities are represented by sets of known compounds, and sets of inactive compounds are also used. We calculated a similarity between an unknown compound and each activity class. The more similar activity is assigned to the unknown compound. We applied this new approach on eight well-known data sets extracted from the literature and compared its performance to three classical machine learning algorithms. Experiments showed that BBNC provides interesting prediction rates (from 79% accuracy for high diverse data sets to 99% for low diverse ones) with a short time calculation. Experiments also showed that BBNC is particularly effective for homogeneous data sets but has been found to perform less well with structurally heterogeneous sets. However, it is important to stress that we believe that using several approaches whenever possible for activity prediction can often give a broader understanding of the data than using only one approach alone. Thus, BBNC is a useful addition to the computational chemist's toolbox.

Using Delaunay triangulation and Voronoi tessellation to predict the toxicities of binary mixtures containing hormetic compound

NASA Astrophysics Data System (ADS)

Qu, Rui; Liu, Shu-Shen; Zheng, Qiao-Feng; Li, Tong

2017-03-01

Concentration addition (CA) was proposed as a reasonable default approach for the ecological risk assessment of chemical mixtures. However, CA cannot predict the toxicity of mixture at some effect zones if not all components have definite effective concentrations at the given effect, such as some compounds induce hormesis. In this paper, we developed a new method for the toxicity prediction of various types of binary mixtures, an interpolation method based on the Delaunay triangulation (DT) and Voronoi tessellation (VT) as well as the training set of direct equipartition ray design (EquRay) mixtures, simply IDVequ. At first, the EquRay was employed to design the basic concentration compositions of five binary mixture rays. The toxic effects of single components and mixture rays at different times and various concentrations were determined by the time-dependent microplate toxicity analysis. Secondly, the concentration-toxicity data of the pure components and various mixture rays were acted as a training set. The DT triangles and VT polygons were constructed by various vertices of concentrations in the training set. The toxicities of unknown mixtures were predicted by the linear interpolation and natural neighbor interpolation of vertices. The IDVequ successfully predicted the toxicities of various types of binary mixtures.

Using Delaunay triangulation and Voronoi tessellation to predict the toxicities of binary mixtures containing hormetic compound

PubMed Central

Qu, Rui; Liu, Shu-Shen; Zheng, Qiao-Feng; Li, Tong

2017-01-01

Concentration addition (CA) was proposed as a reasonable default approach for the ecological risk assessment of chemical mixtures. However, CA cannot predict the toxicity of mixture at some effect zones if not all components have definite effective concentrations at the given effect, such as some compounds induce hormesis. In this paper, we developed a new method for the toxicity prediction of various types of binary mixtures, an interpolation method based on the Delaunay triangulation (DT) and Voronoi tessellation (VT) as well as the training set of direct equipartition ray design (EquRay) mixtures, simply IDVequ. At first, the EquRay was employed to design the basic concentration compositions of five binary mixture rays. The toxic effects of single components and mixture rays at different times and various concentrations were determined by the time-dependent microplate toxicity analysis. Secondly, the concentration-toxicity data of the pure components and various mixture rays were acted as a training set. The DT triangles and VT polygons were constructed by various vertices of concentrations in the training set. The toxicities of unknown mixtures were predicted by the linear interpolation and natural neighbor interpolation of vertices. The IDVequ successfully predicted the toxicities of various types of binary mixtures. PMID:28287626

Efficient Bayesian experimental design for contaminant source identification

NASA Astrophysics Data System (ADS)

Zhang, J.; Zeng, L.

2013-12-01

In this study, an efficient full Bayesian approach is developed for the optimal sampling well location design and source parameter identification of groundwater contaminants. An information measure, i.e., the relative entropy, is employed to quantify the information gain from indirect concentration measurements in identifying unknown source parameters such as the release time, strength and location. In this approach, the sampling location that gives the maximum relative entropy is selected as the optimal one. Once the sampling location is determined, a Bayesian approach based on Markov Chain Monte Carlo (MCMC) is used to estimate unknown source parameters. In both the design and estimation, the contaminant transport equation is required to be solved many times to evaluate the likelihood. To reduce the computational burden, an interpolation method based on the adaptive sparse grid is utilized to construct a surrogate for the contaminant transport. The approximated likelihood can be evaluated directly from the surrogate, which greatly accelerates the design and estimation process. The accuracy and efficiency of our approach are demonstrated through numerical case studies. Compared with the traditional optimal design, which is based on the Gaussian linear assumption, the method developed in this study can cope with arbitrary nonlinearity. It can be used to assist in groundwater monitor network design and identification of unknown contaminant sources. Contours of the expected information gain. The optimal observing location corresponds to the maximum value. Posterior marginal probability densities of unknown parameters, the thick solid black lines are for the designed location. For comparison, other 7 lines are for randomly chosen locations. The true values are denoted by vertical lines. It is obvious that the unknown parameters are estimated better with the desinged location.

Unknown Gases: Student-Designed Experiments in the Introductory Laboratory.

ERIC Educational Resources Information Center

Hanson, John; Hoyt, Tim

2002-01-01

Introductory students design and carry-out experimental procedures to determine the identity of three unknown gases from a list of eight possibilities: air, nitrogen, oxygen, argon, carbon dioxide, helium, methane, and hydrogen. Students are excited and motivated by the opportunity to come up with their own experimental approach to solving a…

Entanglement in channel discrimination with restricted measurements

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

Matthews, William; Piani, Marco; Watrous, John

2010-09-15

We study the power of measurements implementable with local quantum operations and classical communication (LOCC) measurements in the setting of quantum channel discrimination. More precisely, we consider discrimination procedures that attempt to identify an unknown channel, chosen uniformly from two known alternatives, that take the following form: (i) the input to the unknown channel is prepared in a possibly entangled state with an ancillary system, (ii) the unknown channel is applied to the input system, and (iii) an LOCC measurement is performed on the output and ancillary systems, resulting in a guess for which of the two channels was given.more » The restriction of the measurement in such a procedure to be an LOCC measurement is of interest because it isolates the entanglement in the initial input-ancillary systems as a resource in the setting of channel discrimination. We prove that there exist channel discrimination problems for which restricted procedures of this sort can be at either of the two extremes: they may be optimal within the set of all discrimination procedures (and simultaneously outperform all strategies that make no use of entanglement), or they may be no better than unentangled strategies (and simultaneously suboptimal within the set of all discrimination procedures).« less

Validation of the Design Methodology for Submarines: A Comparison of Analyses and Experiments. Part 1

DTIC Science & Technology

1993-06-15

1 not only Bmat has to be determined, but also Bw.ld. - Some unknown uncertainties have been chosen, namely: - Bres(slas-tilt) has been set to 0.98...resulting in real (corrected, only Bmat -0.96 and 7nm-0.95) collapse pressures of 6.75 MPa, 6.11 MPa and 6.11 MPa respectively (errors -5.5 percent...30.78 0.96 1 .0 0.98 0.98 1 .0 1 .0 0.95 0.90 24.3 I em TNO- report Date Page B-92-1132 15 June 1993 78 SheotI Method Remarks Psubhul Bmat 8 woeld

Ranking and combining multiple predictors without labeled data

PubMed Central

Parisi, Fabio; Strino, Francesco; Nadler, Boaz; Kluger, Yuval

2014-01-01

In a broad range of classification and decision-making problems, one is given the advice or predictions of several classifiers, of unknown reliability, over multiple questions or queries. This scenario is different from the standard supervised setting, where each classifier’s accuracy can be assessed using available labeled data, and raises two questions: Given only the predictions of several classifiers over a large set of unlabeled test data, is it possible to (i) reliably rank them and (ii) construct a metaclassifier more accurate than most classifiers in the ensemble? Here we present a spectral approach to address these questions. First, assuming conditional independence between classifiers, we show that the off-diagonal entries of their covariance matrix correspond to a rank-one matrix. Moreover, the classifiers can be ranked using the leading eigenvector of this covariance matrix, because its entries are proportional to their balanced accuracies. Second, via a linear approximation to the maximum likelihood estimator, we derive the Spectral Meta-Learner (SML), an unsupervised ensemble classifier whose weights are equal to these eigenvector entries. On both simulated and real data, SML typically achieves a higher accuracy than most classifiers in the ensemble and can provide a better starting point than majority voting for estimating the maximum likelihood solution. Furthermore, SML is robust to the presence of small malicious groups of classifiers designed to veer the ensemble prediction away from the (unknown) ground truth. PMID:24474744

Correction of static pressure on a research aircraft in accelerated flight using differential pressure measurements

NASA Astrophysics Data System (ADS)

Rodi, A. R.; Leon, D. C.

2012-11-01

A method is described that estimates the error in the static pressure measurement on an aircraft from differential pressure measurements on the hemispherical surface of a Rosemount model 858AJ air velocity probe mounted on a boom ahead of the aircraft. The theoretical predictions for how the pressure should vary over the surface of the hemisphere, involving an unknown sensitivity parameter, leads to a set of equations that can be solved for the unknowns - angle of attack, angle of sideslip, dynamic pressure and the error in static pressure - if the sensitivity factor can be determined. The sensitivity factor was determined on the University of Wyoming King Air research aircraft by comparisons with the error measured with a carefully designed sonde towed on connecting tubing behind the aircraft - a trailing cone - and the result was shown to have a precision of about ±10 Pa over a wide range of conditions, including various altitudes, power settings, and gear and flap extensions. Under accelerated flight conditions, geometric altitude data from a combined Global Navigation Satellite System (GNSS) and inertial measurement unit (IMU) system are used to estimate acceleration effects on the error, and the algorithm is shown to predict corrections to a precision of better than ±20 Pa under those conditions. Some limiting factors affecting the precision of static pressure measurement on a research aircraft are discussed.

Almost output regulation of LFT systems via gain-scheduling control

NASA Astrophysics Data System (ADS)

Yuan, Chengzhi; Duan, Chang; Wu, Fen

2018-05-01

Output regulation of general uncertain systems is a meaningful yet challenging problem. In spite of the rich literature in the field, the problem has not yet been addressed adequately due to the lack of an effective design mechanism. In this paper, we propose a new design framework for almost output regulation of uncertain systems described in the general form of linear fractional transformation (LFT) with time-varying parametric uncertainties and unknown external perturbations. A novel semi-LFT gain-scheduling output regulator structure is proposed, such that the associated control synthesis conditions guaranteeing both output regulation and ? disturbance attenuation performance are formulated as a set of linear matrix inequalities (LMIs) plus parameter-dependent linear matrix equations, which can be solved separately. A numerical example has been used to demonstrate the effectiveness of the proposed approach.

Prediction of Tubal Ectopic Pregnancy Using Offline Analysis of 3-Dimensional Transvaginal Ultrasonographic Data Sets: An Interobserver and Diagnostic Accuracy Study.

PubMed

Infante, Fernando; Espada Vaquero, Mercedes; Bignardi, Tommaso; Lu, Chuan; Testa, Antonia C; Fauchon, David; Epstein, Elisabeth; Leone, Francesco P G; Van den Bosch, Thierry; Martins, Wellington P; Condous, George

2018-06-01

To assess interobserver reproducibility in detecting tubal ectopic pregnancies by reading data sets from 3-dimensional (3D) transvaginal ultrasonography (TVUS) and comparing it with real-time 2-dimensional (2D) TVUS. Images were initially classified as showing pregnancies of unknown location or tubal ectopic pregnancies on real time 2D TVUS by an experienced sonologist, who acquired 5 3D volumes. Data sets were analyzed offline by 5 observers who had to classify each case as ectopic pregnancy or pregnancy of unknown location. The interobserver reproducibility was evaluated by the Fleiss κ statistic. The performance of each observer in predicting ectopic pregnancies was compared to that of the experienced sonologist. Women were followed until they were reclassified as follows: (1) failed pregnancy of unknown location; (2) intrauterine pregnancy; (3) ectopic pregnancy; or (4) persistent pregnancy of unknown location. Sixty-one women were included. The agreement between reading offline 3D data sets and the first real-time 2D TVUS was very good (80%-82%; κ = 0.89). The overall interobserver agreement among observers reading offline 3D data sets was moderate (κ = 0.52). The diagnostic performance of experienced observers reading offline 3D data sets had accuracy of 78.3% to 85.0%, sensitivity of 66.7% to 81.3%, specificity of 79.5% to 88.4%, positive predictive value of 57.1% to 72.2%, and negative predictive value of 87.5% to 91.3%, compared to the experienced sonologist's real-time 2D TVUS: accuracy of 94.5%, sensitivity of 94.4%, specificity of 94.5%, positive predictive value of 85.0%, and negative predictive value of 98.1%. The diagnostic accuracy of 3D TVUS by reading offline data sets for predicting ectopic pregnancies is dependent on experience. Reading only static 3D data sets without clinical information does not match the diagnostic performance of real time 2D TVUS combined with clinical information obtained during the scan. © 2017 by the American Institute of Ultrasound in Medicine.

Communication Problems for Patients Hospitalized with Chest Pain

PubMed Central

Simon, Steven R.; Lee, Thomas H.; Goldman, Lee; McDonough, Allison L.; Pearson, Steven D.

1998-01-01

In many settings, primary care physicians have begun to delegate inpatient care to hospitalists, but the impact of this change on patients' hospital experience is unknown. To determine the effect on physician-patient communication of having the regular outpatient physician (continuity physician) continue involvement in hospital care, we surveyed 1,059 consecutive patients hospitalized with chest pain. Patients whose continuity physicians remained involved in their hospital care were less likely to report communication problems regarding tests (20% vs 31%, p = .03), activity after discharge (42% vs 51%, p = .02), and health habits (31% vs 38%, p = .07). In a setting without a designated hospitalist system, communication problems were less frequent among patients whose continuity physicians were involved in their hospital care. New models of inpatient care delivery can maintain patient satisfaction but to do so must focus attention on improving physician-patient communication. PMID:9844081

A new polytopic approach for the unknown input functional observer design

NASA Astrophysics Data System (ADS)

Bezzaoucha, Souad; Voos, Holger; Darouach, Mohamed

2018-03-01

In this paper, a constructive procedure to design Functional Unknown Input Observers for nonlinear continuous time systems is proposed under the Polytopic Takagi-Sugeno framework. An equivalent representation for the nonlinear model is achieved using the sector nonlinearity transformation. Applying the Lyapunov theory and the ? attenuation, linear matrix inequalities conditions are deduced which are solved for feasibility to obtain the observer design matrices. To cope with the effect of unknown inputs, classical approach of decoupling the unknown input for the linear case is used. Both algebraic and solver-based solutions are proposed (relaxed conditions). Necessary and sufficient conditions for the existence of the functional polytopic observer are given. For both approaches, the general and particular cases (measurable premise variables, full state estimation with full and reduced order cases) are considered and it is shown that the proposed conditions correspond to the one presented for standard linear case. To illustrate the proposed theoretical results, detailed numerical simulations are presented for a Quadrotor Aerial Robots Landing and a Waste Water Treatment Plant. Both systems are highly nonlinear and represented in a T-S polytopic form with unmeasurable premise variables and unknown inputs.

Statistical and optimal learning with applications in business analytics

NASA Astrophysics Data System (ADS)

Han, Bin

Statistical learning is widely used in business analytics to discover structure or exploit patterns from historical data, and build models that capture relationships between an outcome of interest and a set of variables. Optimal learning on the other hand, solves the operational side of the problem, by iterating between decision making and data acquisition/learning. All too often the two problems go hand-in-hand, which exhibit a feedback loop between statistics and optimization. We apply this statistical/optimal learning concept on a context of fundraising marketing campaign problem arising in many non-profit organizations. Many such organizations use direct-mail marketing to cultivate one-time donors and convert them into recurring contributors. Cultivated donors generate much more revenue than new donors, but also lapse with time, making it important to steadily draw in new cultivations. The direct-mail budget is limited, but better-designed mailings can improve success rates without increasing costs. We first apply statistical learning to analyze the effectiveness of several design approaches used in practice, based on a massive dataset covering 8.6 million direct-mail communications with donors to the American Red Cross during 2009-2011. We find evidence that mailed appeals are more effective when they emphasize disaster preparedness and training efforts over post-disaster cleanup. Including small cards that affirm donors' identity as Red Cross supporters is an effective strategy, while including gift items such as address labels is not. Finally, very recent acquisitions are more likely to respond to appeals that ask them to contribute an amount similar to their most recent donation, but this approach has an adverse effect on donors with a longer history. We show via simulation that a simple design strategy based on these insights has potential to improve success rates from 5.4% to 8.1%. Given these findings, when new scenario arises, however, new data need to be acquired to update our model and decisions, which is studied under optimal learning framework. The goal becomes discovering a sequential information collection strategy that learns the best campaign design alternative as quickly as possible. Regression structure is used to learn about a set of unknown parameters, which alternates with optimization to design new data points. Such problems have been extensively studied in the ranking and selection (R&S) community, but traditional R&S procedures experience high computational costs when the decision space grows combinatorially. We present a value of information procedure for simultaneously learning unknown regression parameters and unknown sampling noise. We then develop an approximate version of the procedure, based on semi-definite programming relaxation, that retains good performance and scales better to large problems. We also prove the asymptotic consistency of the algorithm in the parametric model, a result that has not previously been available for even the known-variance case.

Newly designed 11-gene panel reveals first case of hereditary amyloidosis captured by massive parallel sequencing.

PubMed

Chyra Kufova, Zuzana; Sevcikova, Tereza; Januska, Jaroslav; Vojta, Petr; Boday, Arpad; Vanickova, Pavla; Filipova, Jana; Growkova, Katerina; Jelinek, Tomas; Hajduch, Marian; Hajek, Roman

2018-02-17

Amyloidosis is caused by deposition of abnormal protein fibrils, leading to damage of organ function. Hereditary amyloidosis represents a monogenic disease caused by germline mutations in 11 amyloidogenic precursor protein genes. One of the important but non-specific symptoms of amyloidosis is hypertrophic cardiomyopathy. Diagnostics of hereditary amyloidosis is complicated and the real cause can remain overlooked. We aimed to design hereditary amyloidosis gene panel and to introduce new next-generation sequencing (NGS) approach to investigate hereditary amyloidosis in a cohort of patients with hypertrophic cardiomyopathy of unknown significance. Design of target enrichment DNA library preparation using Haloplex Custom Kit containing 11 amyloidogenic genes was followed by MiSeq Illumina sequencing and bioinformatics identification of germline variants using tool VarScan in a cohort of 40 patients. We present design of NGS panel for 11 genes ( TTR , FGA , APOA1 , APOA2 , LYZ , GSN , CST3 , PRNP , APP , B2M , ITM2B ) connected to various forms of amyloidosis. We detected one mutation, which is responsible for hereditary amyloidosis. Some other single nucleotide variants are so far undescribed or rare variants or represent common polymorphisms in European population. We report one positive case of hereditary amyloidosis in a cohort of patients with hypertrophic cardiomyopathy of unknown significance and set up first panel for NGS in hereditary amyloidosis. This work may facilitate successful implementation of the NGS method by other researchers or clinicians and may improve the diagnostic process after validation. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Market-Based Coordination of Thermostatically Controlled Loads—Part I: A Mechanism Design Formulation

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

Li, Sen; Zhang, Wei; Lian, Jianming

This paper focuses on the coordination of a population of Thermostatically Controlled Loads (TCLs) with unknown parameters to achieve group objectives. The problem involves designing the bidding and market clearing strategy to motivate self-interested users to realize efficient energy allocation subject to a peak power constraint. Using the mechanism design approach, we propose a market-based coordination framework, which can effectively incorporate heterogeneous load dynamics, systematically deal with user preferences, account for the unknown load model parameters, and enable the real-world implementation with limited communication resources. This paper is divided into two parts. Part I presents a mathematical formulation of themore » problem and develops a coordination framework using the mechanism design approach. Part II presents a learning scheme to account for the unknown load model parameters, and evaluates the proposed framework through realistic simulations.« less

Design of experiment for earth rotation and baseline parameter determination from very long baseline interferometry

NASA Technical Reports Server (NTRS)

Dermanis, A.

1977-01-01

The possibility of recovering earth rotation and network geometry (baseline) parameters are emphasized. The numerical simulated experiments performed are set up in an environment where station coordinates vary with respect to inertial space according to a simulated earth rotation model similar to the actual but unknown rotation of the earth. The basic technique of VLBI and its mathematical model are presented. The parametrization of earth rotation chosen is described and the resulting model is linearized. A simple analysis of the geometry of the observations leads to some useful hints on achieving maximum sensitivity of the observations with respect to the parameters considered. The basic philosophy for the simulation of data and their analysis through standard least squares adjustment techniques is presented. A number of characteristic network designs based on present and candidate station locations are chosen. The results of the simulations for each design are presented together with a summary of the conclusions.

Polyester: simulating RNA-seq datasets with differential transcript expression.

PubMed

Frazee, Alyssa C; Jaffe, Andrew E; Langmead, Ben; Leek, Jeffrey T

2015-09-01

Statistical methods development for differential expression analysis of RNA sequencing (RNA-seq) requires software tools to assess accuracy and error rate control. Since true differential expression status is often unknown in experimental datasets, artificially constructed datasets must be utilized, either by generating costly spike-in experiments or by simulating RNA-seq data. Polyester is an R package designed to simulate RNA-seq data, beginning with an experimental design and ending with collections of RNA-seq reads. Its main advantage is the ability to simulate reads indicating isoform-level differential expression across biological replicates for a variety of experimental designs. Data generated by Polyester is a reasonable approximation to real RNA-seq data and standard differential expression workflows can recover differential expression set in the simulation by the user. Polyester is freely available from Bioconductor (http://bioconductor.org/). jtleek@gmail.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Overcoming the Challenges of Implementing a Multi-Mission Distributed Workflow System

NASA Technical Reports Server (NTRS)

Sayfi, Elias; Cheng, Cecilia; Lee, Hyun; Patel, Rajesh; Takagi, Atsuya; Yu, Dan

2009-01-01

A multi-mission approach to solving the same problems for various projects is enticing. However, the multi-mission approach leads to the need to develop a configurable, adaptable and distributed system to meet unique project requirements. That, in turn, leads to a set of challenges varying from handling synchronization issues to coming up with a smart design that allows the "unknowns" to be decided later. This paper discusses the challenges that the Multi-mission Automated Task Invocation Subsystem (MATIS) team has come up against while designing the distributed workflow system, as well as elaborates on the solutions that were implemented. The first is to design an easily adaptable system that requires no code changes as a result of configuration changes. The number of formal deliveries is often limited because each delivery costs time and money. Changes such as the sequence of programs being called, a change of a parameter value in the program that is being automated should not result in code changes or redelivery.

Unknown loads affect force production capacity in early phases of bench press throws.

PubMed

Hernández Davó, J L; Sabido Solana, R; Sarabia Marínm, J M; Sánchez Martos, Á; Moya Ramón, M

2015-10-01

Explosive strength training aims to improve force generation in early phases of movement due to its importance in sport performance. The present study examined the influence of lack of knowledge about the load lifted in explosive parameters during bench press throws. Thirteen healthy young men (22.8±2.0 years) participated in the study. Participants performed bench press throws with three different loads (30, 50 and 70% of 1 repetition maximum) in two different conditions (known and unknown loads). In unknown condition, loads were changed within sets in each repetition and participants did not know the load, whereas in known condition the load did not change within sets and participants had knowledge about the load lifted. Results of repeated-measures ANOVA revealed that unknown conditions involves higher power in the first 30, 50, 100 and 150 ms with the three loads, higher values of ratio of force development in those first instants, and differences in time to reach maximal rate of force development with 50 and 70% of 1 repetition maximum. This study showed that unknown conditions elicit higher values of explosive parameters in early phases of bench press throws, thereby this kind of methodology could be considered in explosive strength training.

Slope Estimation in Noisy Piecewise Linear Functions✩

PubMed Central

Ingle, Atul; Bucklew, James; Sethares, William; Varghese, Tomy

2014-01-01

This paper discusses the development of a slope estimation algorithm called MAPSlope for piecewise linear data that is corrupted by Gaussian noise. The number and locations of slope change points (also known as breakpoints) are assumed to be unknown a priori though it is assumed that the possible range of slope values lies within known bounds. A stochastic hidden Markov model that is general enough to encompass real world sources of piecewise linear data is used to model the transitions between slope values and the problem of slope estimation is addressed using a Bayesian maximum a posteriori approach. The set of possible slope values is discretized, enabling the design of a dynamic programming algorithm for posterior density maximization. Numerical simulations are used to justify choice of a reasonable number of quantization levels and also to analyze mean squared error performance of the proposed algorithm. An alternating maximization algorithm is proposed for estimation of unknown model parameters and a convergence result for the method is provided. Finally, results using data from political science, finance and medical imaging applications are presented to demonstrate the practical utility of this procedure. PMID:25419020

Slope Estimation in Noisy Piecewise Linear Functions.

PubMed

Ingle, Atul; Bucklew, James; Sethares, William; Varghese, Tomy

2015-03-01

This paper discusses the development of a slope estimation algorithm called MAPSlope for piecewise linear data that is corrupted by Gaussian noise. The number and locations of slope change points (also known as breakpoints) are assumed to be unknown a priori though it is assumed that the possible range of slope values lies within known bounds. A stochastic hidden Markov model that is general enough to encompass real world sources of piecewise linear data is used to model the transitions between slope values and the problem of slope estimation is addressed using a Bayesian maximum a posteriori approach. The set of possible slope values is discretized, enabling the design of a dynamic programming algorithm for posterior density maximization. Numerical simulations are used to justify choice of a reasonable number of quantization levels and also to analyze mean squared error performance of the proposed algorithm. An alternating maximization algorithm is proposed for estimation of unknown model parameters and a convergence result for the method is provided. Finally, results using data from political science, finance and medical imaging applications are presented to demonstrate the practical utility of this procedure.

Identification of unmeasured variables in the set of model constraints of the data reconciliation in a power unit

NASA Astrophysics Data System (ADS)

Szega, Marcin; Nowak, Grzegorz Tadeusz

2013-12-01

In generalized method of data reconciliation as equations of conditions beside substance and energy balances can be used equations which don't have precisely the status of conservation lows. Empirical coefficients in these equations are traded as unknowns' values. To this kind of equations, in application of the generalized method of data reconciliation in supercritical power unit, can be classified: steam flow capacity of a turbine for a group of stages, adiabatic internal efficiency of group of stages, equations for pressure drop in pipelines and equations for heat transfer in regeneration heat exchangers. Mathematical model of a power unit was developed in the code Thermoflex. Using this model the off-design calculation has been made in several points of loads for the power unit. Using these calculations identification of unknown values and empirical coefficients for generalized method of data reconciliation used in power unit has been made. Additional equations of conditions will be used in the generalized method of data reconciliation which will be used in optimization of measurement placement in redundant measurement system in power unit for new control systems

A robust approach towards unknown transformation, regional adjacency graphs, multigraph matching, segmentation video frames from unnamed aerial vehicles (UAV)

NASA Astrophysics Data System (ADS)

Gohatre, Umakant Bhaskar; Patil, Venkat P.

2018-04-01

In computer vision application, the multiple object detection and tracking, in real-time operation is one of the important research field, that have gained a lot of attentions, in last few years for finding non stationary entities in the field of image sequence. The detection of object is advance towards following the moving object in video and then representation of object is step to track. The multiple object recognition proof is one of the testing assignment from detection multiple objects from video sequence. The picture enrollment has been for quite some time utilized as a reason for the location the detection of moving multiple objects. The technique of registration to discover correspondence between back to back casing sets in view of picture appearance under inflexible and relative change. The picture enrollment is not appropriate to deal with event occasion that can be result in potential missed objects. In this paper, for address such problems, designs propose novel approach. The divided video outlines utilizing area adjancy diagram of visual appearance and geometric properties. Then it performed between graph sequences by using multi graph matching, then getting matching region labeling by a proposed graph coloring algorithms which assign foreground label to respective region. The plan design is robust to unknown transformation with significant improvement in overall existing work which is related to moving multiple objects detection in real time parameters.

Cross-Setting Correspondence in Sociometric Nominations among Children with Attention-Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Mikami, Amori Yee; Hoza, Betsy; Hinshaw, Stephen P.; Arnold, L. Eugene; Hechtman, Lily; Pelham, William E., Jr.

2015-01-01

Peer problems are common among children with emotional and behavioral disorders (EBD). However, the extent to which children's peer functioning varies across settings is unknown, as is the incremental power of peer functioning in different settings in predicting subsequent psychopathology. Participants were 57 children with…

Adaptive Neural Networks Decentralized FTC Design for Nonstrict-Feedback Nonlinear Interconnected Large-Scale Systems Against Actuator Faults.

PubMed

Li, Yongming; Tong, Shaocheng

The problem of active fault-tolerant control (FTC) is investigated for the large-scale nonlinear systems in nonstrict-feedback form. The nonstrict-feedback nonlinear systems considered in this paper consist of unstructured uncertainties, unmeasured states, unknown interconnected terms, and actuator faults (e.g., bias fault and gain fault). A state observer is designed to solve the unmeasurable state problem. Neural networks (NNs) are used to identify the unknown lumped nonlinear functions so that the problems of unstructured uncertainties and unknown interconnected terms can be solved. By combining the adaptive backstepping design principle with the combination Nussbaum gain function property, a novel NN adaptive output-feedback FTC approach is developed. The proposed FTC controller can guarantee that all signals in all subsystems are bounded, and the tracking errors for each subsystem converge to a small neighborhood of zero. Finally, numerical results of practical examples are presented to further demonstrate the effectiveness of the proposed control strategy.The problem of active fault-tolerant control (FTC) is investigated for the large-scale nonlinear systems in nonstrict-feedback form. The nonstrict-feedback nonlinear systems considered in this paper consist of unstructured uncertainties, unmeasured states, unknown interconnected terms, and actuator faults (e.g., bias fault and gain fault). A state observer is designed to solve the unmeasurable state problem. Neural networks (NNs) are used to identify the unknown lumped nonlinear functions so that the problems of unstructured uncertainties and unknown interconnected terms can be solved. By combining the adaptive backstepping design principle with the combination Nussbaum gain function property, a novel NN adaptive output-feedback FTC approach is developed. The proposed FTC controller can guarantee that all signals in all subsystems are bounded, and the tracking errors for each subsystem converge to a small neighborhood of zero. Finally, numerical results of practical examples are presented to further demonstrate the effectiveness of the proposed control strategy.

Learning Rates and Known-to-Unknown Flash-Card Ratios: Comparing Effectiveness While Holding Instructional Time Constant

ERIC Educational Resources Information Center

Forbes, Bethany E.; Skinner, Christopher H.; Black, Michelle P.; Yaw, Jared; Booher, Joshua; Delisle, Jean

2013-01-01

Using alternating treatments designs, we compared learning rates across 2 computer-based flash-card interventions (3?min each): a traditional drill intervention with 15 unknown words and an interspersal intervention with 12 known words and 3 unknown words. Each student acquired more words under the traditional drill intervention. Discussion…

Solving the Unknown with Algebra: Poster/Teaching Guide for Pre-Algebra Students. Expect the Unexpected with Math[R

ERIC Educational Resources Information Center

Actuarial Foundation, 2013

2013-01-01

"Solving the Unknown with Algebra" is a new math program aligned with the National Council of Teachers of Mathematics (NCTM) standards and designed to help students practice pre-algebra skills including using formulas, solving for unknowns, and manipulating equations. Developed by The Actuarial Foundation with Scholastic, this program provides…

Predictive Modeling of Estrogen Receptor Binding Agents Using Advanced Cheminformatics Tools and Massive Public Data.

PubMed

Ribay, Kathryn; Kim, Marlene T; Wang, Wenyi; Pinolini, Daniel; Zhu, Hao

2016-03-01

Estrogen receptors (ERα) are a critical target for drug design as well as a potential source of toxicity when activated unintentionally. Thus, evaluating potential ERα binding agents is critical in both drug discovery and chemical toxicity areas. Using computational tools, e.g., Quantitative Structure-Activity Relationship (QSAR) models, can predict potential ERα binding agents before chemical synthesis. The purpose of this project was to develop enhanced predictive models of ERα binding agents by utilizing advanced cheminformatics tools that can integrate publicly available bioassay data. The initial ERα binding agent data set, consisting of 446 binders and 8307 non-binders, was obtained from the Tox21 Challenge project organized by the NIH Chemical Genomics Center (NCGC). After removing the duplicates and inorganic compounds, this data set was used to create a training set (259 binders and 259 non-binders). This training set was used to develop QSAR models using chemical descriptors. The resulting models were then used to predict the binding activity of 264 external compounds, which were available to us after the models were developed. The cross-validation results of training set [Correct Classification Rate (CCR) = 0.72] were much higher than the external predictivity of the unknown compounds (CCR = 0.59). To improve the conventional QSAR models, all compounds in the training set were used to search PubChem and generate a profile of their biological responses across thousands of bioassays. The most important bioassays were prioritized to generate a similarity index that was used to calculate the biosimilarity score between each two compounds. The nearest neighbors for each compound within the set were then identified and its ERα binding potential was predicted by its nearest neighbors in the training set. The hybrid model performance (CCR = 0.94 for cross validation; CCR = 0.68 for external prediction) showed significant improvement over the original QSAR models, particularly for the activity cliffs that induce prediction errors. The results of this study indicate that the response profile of chemicals from public data provides useful information for modeling and evaluation purposes. The public big data resources should be considered along with chemical structure information when predicting new compounds, such as unknown ERα binding agents.

An archaeal genomic signature

NASA Technical Reports Server (NTRS)

Graham, D. E.; Overbeek, R.; Olsen, G. J.; Woese, C. R.

2000-01-01

Comparisons of complete genome sequences allow the most objective and comprehensive descriptions possible of a lineage's evolution. This communication uses the completed genomes from four major euryarchaeal taxa to define a genomic signature for the Euryarchaeota and, by extension, the Archaea as a whole. The signature is defined in terms of the set of protein-encoding genes found in at least two diverse members of the euryarchaeal taxa that function uniquely within the Archaea; most signature proteins have no recognizable bacterial or eukaryal homologs. By this definition, 351 clusters of signature proteins have been identified. Functions of most proteins in this signature set are currently unknown. At least 70% of the clusters that contain proteins from all the euryarchaeal genomes also have crenarchaeal homologs. This conservative set, which appears refractory to horizontal gene transfer to the Bacteria or the Eukarya, would seem to reflect the significant innovations that were unique and fundamental to the archaeal "design fabric." Genomic protein signature analysis methods may be extended to characterize the evolution of any phylogenetically defined lineage. The complete set of protein clusters for the archaeal genomic signature is presented as supplementary material (see the PNAS web site, www.pnas.org).

Adaptive Output-Feedback Neural Control of Switched Uncertain Nonlinear Systems With Average Dwell Time.

PubMed

Long, Lijun; Zhao, Jun

2015-07-01

This paper investigates the problem of adaptive neural tracking control via output-feedback for a class of switched uncertain nonlinear systems without the measurements of the system states. The unknown control signals are approximated directly by neural networks. A novel adaptive neural control technique for the problem studied is set up by exploiting the average dwell time method and backstepping. A switched filter and different update laws are designed to reduce the conservativeness caused by adoption of a common observer and a common update law for all subsystems. The proposed controllers of subsystems guarantee that all closed-loop signals remain bounded under a class of switching signals with average dwell time, while the output tracking error converges to a small neighborhood of the origin. As an application of the proposed design method, adaptive output feedback neural tracking controllers for a mass-spring-damper system are constructed.

Operationally Responsive Space Standard Bus Battery Thermal Balance Testing and Heat Dissipation Analysis

NASA Technical Reports Server (NTRS)

Marley, Mike

2008-01-01

The focus of this paper will be on the thermal balance testing for the Operationally Responsive Space Standard Bus Battery. The Standard Bus thermal design required that the battery be isolated from the bus itself. This required the battery to have its own thermal control, including heaters and a radiator surface. Since the battery was not ready for testing during the overall bus thermal balance testing, a separate test was conducted to verify the thermal design for the battery. This paper will discuss in detail, the test set up, test procedure, and results from this test. Additionally this paper will consider the methods taken to determine the heat dissipation of the battery during charge and discharge. It seems that the heat dissipation for Lithium Ion batteries is relatively unknown and hard to quantify. The methods used during test and the post test analysis to estimate the heat dissipation of the battery will be discussed.

Self-guided method to search maximal Bell violations for unknown quantum states

NASA Astrophysics Data System (ADS)

Yang, Li-Kai; Chen, Geng; Zhang, Wen-Hao; Peng, Xing-Xiang; Yu, Shang; Ye, Xiang-Jun; Li, Chuan-Feng; Guo, Guang-Can

2017-11-01

In recent decades, a great variety of research and applications concerning Bell nonlocality have been developed with the advent of quantum information science. Providing that Bell nonlocality can be revealed by the violation of a family of Bell inequalities, finding maximal Bell violation (MBV) for unknown quantum states becomes an important and inevitable task during Bell experiments. In this paper we introduce a self-guided method to find MBVs for unknown states using a stochastic gradient ascent algorithm (SGA), by parametrizing the corresponding Bell operators. For three investigated systems (two qubit, three qubit, and two qutrit), this method can ascertain the MBV of general two-setting inequalities within 100 iterations. Furthermore, we prove SGA is also feasible when facing more complex Bell scenarios, e.g., d -setting d -outcome Bell inequality. Moreover, compared to other possible methods, SGA exhibits significant superiority in efficiency, robustness, and versatility.

An Exploratory Analysis of Economic Factors in the Navy Total Force Strength Model (NTFSM)

DTIC Science & Technology

2015-12-01

NTFSM is still in the testing phase and its overall behavior is largely unknown. In particular, the analysts that NTFSM was designed to help are...NTFSM is still in the testing phase and its overall behavior is largely unknown. In particular, the analysts that NTFSM was designed to help are...7 B. NTFSM VERIFICATION AND TESTING ......................................... 8 C

Using Project-Based Learning to Design, Build, and Test Student-Made Photometer by Measuring the Unknown Concentration of Colored Substances

ERIC Educational Resources Information Center

Diawati, Chansyanah; Liliasari; Setiabudi, Agus; Buchari

2018-01-01

Students learned the principles and practice of photometry through project-based learning. They addressed the challenge of measuring the unknown concentration of a colored substance using a photometer they were required to design, build, and test. Then, they used that instrument to carry out the experiment and fulfill the challenge. A photometer…

Allocating monitoring effort in the face of unknown unknowns

USGS Publications Warehouse

Wintle, B.A.; Runge, M.C.; Bekessy, S.A.

2010-01-01

There is a growing view that to make efficient use of resources, ecological monitoring should be hypothesis-driven and targeted to address specific management questions. 'Targeted' monitoring has been contrasted with other approaches in which a range of quantities are monitored in case they exhibit an alarming trend or provide ad hoc ecological insights. The second form of monitoring, described as surveillance, has been criticized because it does not usually aim to discern between competing hypotheses, and its benefits are harder to identify a priori. The alternative view is that the existence of surveillance data may enable rapid corroboration of emerging hypotheses or help to detect important 'unknown unknowns' that, if undetected, could lead to catastrophic outcomes or missed opportunities. We derive a model to evaluate and compare the efficiency of investments in surveillance and targeted monitoring. We find that a decision to invest in surveillance monitoring may be defensible if: (1) the surveillance design is more likely to discover or corroborate previously unknown phenomena than a targeted design and (2) the expected benefits (or avoided costs) arising from discovery are substantially higher than those arising from a well-planned targeted design. Our examination highlights the importance of being explicit about the objectives, costs and expected benefits of monitoring in a decision analytic framework. ?? 2010 Blackwell Publishing Ltd/CNRS.

Adaptive Neural Output Feedback Control for Nonstrict-Feedback Stochastic Nonlinear Systems With Unknown Backlash-Like Hysteresis and Unknown Control Directions.

PubMed

Yu, Zhaoxu; Li, Shugang; Yu, Zhaosheng; Li, Fangfei

2018-04-01

This paper investigates the problem of output feedback adaptive stabilization for a class of nonstrict-feedback stochastic nonlinear systems with both unknown backlashlike hysteresis and unknown control directions. A new linear state transformation is applied to the original system, and then, control design for the new system becomes feasible. By combining the neural network's (NN's) parameterization, variable separation technique, and Nussbaum gain function method, an input-driven observer-based adaptive NN control scheme, which involves only one parameter to be updated, is developed for such systems. All closed-loop signals are bounded in probability and the error signals remain semiglobally bounded in the fourth moment (or mean square). Finally, the effectiveness and the applicability of the proposed control design are verified by two simulation examples.

Complete synchronization of uncertain chaotic systems via a single proportional adaptive controller: A comparative study

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

Ahmad, Israr, E-mail: iak-2000plus@yahoo.com; Saaban, Azizan Bin, E-mail: azizan.s@uum.edu.my; Ibrahim, Adyda Binti, E-mail: adyda@uum.edu.my

This paper addresses a comparative computational study on the synchronization quality, cost and converging speed for two pairs of identical chaotic and hyperchaotic systems with unknown time-varying parameters. It is assumed that the unknown time-varying parameters are bounded. Based on the Lyapunov stability theory and using the adaptive control method, a single proportional controller is proposed to achieve the goal of complete synchronizations. Accordingly, appropriate adaptive laws are designed to identify the unknown time-varying parameters. The designed control strategy is easy to implement in practice. Numerical simulations results are provided to verify the effectiveness of the proposed synchronization scheme.

Far transfer to language and math of a short software-based gaming intervention.

PubMed

Goldin, Andrea Paula; Hermida, María Julia; Shalom, Diego E; Elias Costa, Martín; Lopez-Rosenfeld, Matías; Segretin, María Soledad; Fernández-Slezak, Diego; Lipina, Sebastián J; Sigman, Mariano

2014-04-29

Executive functions (EF) in children can be trained, but it remains unknown whether training-related benefits elicit far transfer to real-life situations. Here, we investigate whether a set of computerized games might yield near and far transfer on an experimental and an active control group of low-SES otherwise typically developing 6-y-olds in a 3-mo pretest-training-posttest design that was ecologically deployed (at school). The intervention elicits transfer to some (but not all) facets of executive function. These changes cascade to real-world measures of school performance. The intervention equalizes academic outcomes across children who regularly attend school and those who do not because of social and familiar circumstances.

Experimental Determination of Unknown Masses and Their Positions in a Mechanical Black Box

ERIC Educational Resources Information Center

Chakrabarti, Bhupati; Pathare, Shirish; Huli, Saurabhee; Nachane, Madhura

2013-01-01

An experiment with a mechanical black box containing unknown masses is presented. The experiment involves the determination of these masses and their locations by performing some nondestructive tests. The set-ups are inexpensive and easy to fabricate. They are very useful to gain an understanding of some well-known principles of mechanics.

Efficient Learning Algorithms with Limited Information

ERIC Educational Resources Information Center

De, Anindya

2013-01-01

The thesis explores efficient learning algorithms in settings which are more restrictive than the PAC model of learning (Valiant) in one of the following two senses: (i) The learning algorithm has a very weak access to the unknown function, as in, it does not get labeled samples for the unknown function (ii) The error guarantee required from the…

Adaptive neural network output feedback control for stochastic nonlinear systems with unknown dead-zone and unmodeled dynamics.

PubMed

Tong, Shaocheng; Wang, Tong; Li, Yongming; Zhang, Huaguang

2014-06-01

This paper discusses the problem of adaptive neural network output feedback control for a class of stochastic nonlinear strict-feedback systems. The concerned systems have certain characteristics, such as unknown nonlinear uncertainties, unknown dead-zones, unmodeled dynamics and without the direct measurements of state variables. In this paper, the neural networks (NNs) are employed to approximate the unknown nonlinear uncertainties, and then by representing the dead-zone as a time-varying system with a bounded disturbance. An NN state observer is designed to estimate the unmeasured states. Based on both backstepping design technique and a stochastic small-gain theorem, a robust adaptive NN output feedback control scheme is developed. It is proved that all the variables involved in the closed-loop system are input-state-practically stable in probability, and also have robustness to the unmodeled dynamics. Meanwhile, the observer errors and the output of the system can be regulated to a small neighborhood of the origin by selecting appropriate design parameters. Simulation examples are also provided to illustrate the effectiveness of the proposed approach.

Power maximization of variable-speed variable-pitch wind turbines using passive adaptive neural fault tolerant control

NASA Astrophysics Data System (ADS)

Habibi, Hamed; Rahimi Nohooji, Hamed; Howard, Ian

2017-09-01

Power maximization has always been a practical consideration in wind turbines. The question of how to address optimal power capture, especially when the system dynamics are nonlinear and the actuators are subject to unknown faults, is significant. This paper studies the control methodology for variable-speed variable-pitch wind turbines including the effects of uncertain nonlinear dynamics, system fault uncertainties, and unknown external disturbances. The nonlinear model of the wind turbine is presented, and the problem of maximizing extracted energy is formulated by designing the optimal desired states. With the known system, a model-based nonlinear controller is designed; then, to handle uncertainties, the unknown nonlinearities of the wind turbine are estimated by utilizing radial basis function neural networks. The adaptive neural fault tolerant control is designed passively to be robust on model uncertainties, disturbances including wind speed and model noises, and completely unknown actuator faults including generator torque and pitch actuator torque. The Lyapunov direct method is employed to prove that the closed-loop system is uniformly bounded. Simulation studies are performed to verify the effectiveness of the proposed method.

Concurrent hyperthermia estimation schemes based on extended Kalman filtering and reduced-order modelling.

PubMed

Potocki, J K; Tharp, H S

1993-01-01

The success of treating cancerous tissue with heat depends on the temperature elevation, the amount of tissue elevated to that temperature, and the length of time that the tissue temperature is elevated. In clinical situations the temperature of most of the treated tissue volume is unknown, because only a small number of temperature sensors can be inserted into the tissue. A state space model based on a finite difference approximation of the bioheat transfer equation (BHTE) is developed for identification purposes. A full-order extended Kalman filter (EKF) is designed to estimate both the unknown blood perfusion parameters and the temperature at unmeasured locations. Two reduced-order estimators are designed as computationally less intensive alternatives to the full-order EKF. Simulation results show that the success of the estimation scheme depends strongly on the number and location of the temperature sensors. Superior results occur when a temperature sensor exists in each unknown blood perfusion zone, and the number of sensors is at least as large as the number of unknown perfusion zones. Unacceptable results occur when there are more unknown perfusion parameters than temperature sensors, or when the sensors are placed in locations that do not sample the unknown perfusion information.

Direct Position Determination of Unknown Signals in the Presence of Multipath Propagation

PubMed Central

Yu, Hongyi

2018-01-01

A novel geolocation architecture, termed “Multiple Transponders and Multiple Receivers for Multiple Emitters Positioning System (MTRE)” is proposed in this paper. Existing Direct Position Determination (DPD) methods take advantage of a rather simple channel assumption (line of sight channels with complex path attenuations) and a simplified MUltiple SIgnal Classification (MUSIC) algorithm cost function to avoid the high dimension searching. We point out that the simplified assumption and cost function reduce the positioning accuracy because of the singularity of the array manifold in a multi-path environment. We present a DPD model for unknown signals in the presence of Multi-path Propagation (MP-DPD) in this paper. MP-DPD adds non-negative real path attenuation constraints to avoid the mistake caused by the singularity of the array manifold. The Multi-path Propagation MUSIC (MP-MUSIC) method and the Active Set Algorithm (ASA) are designed to reduce the dimension of searching. A Multi-path Propagation Maximum Likelihood (MP-ML) method is proposed in addition to overcome the limitation of MP-MUSIC in the sense of a time-sensitive application. An iterative algorithm and an approach of initial value setting are given to make the MP-ML time consumption acceptable. Numerical results validate the performances improvement of MP-MUSIC and MP-ML. A closed form of the Cramér–Rao Lower Bound (CRLB) is derived as a benchmark to evaluate the performances of MP-MUSIC and MP-ML. PMID:29562601

Platelet Activation in Patients with Atherosclerotic Renal Artery Stenosis Undergoing Stent Revascularization

PubMed Central

Adlakha, Satjit; Reed, Grant; Brewster, Pamela; Kennedy, David; Burket, Mark W.; Colyer, William; Yu, Haifeng; Zhang, Dong; Shapiro, Joseph I.; Cooper, Christopher J.

2011-01-01

Summary Background and objectives Soluble CD40 ligand (sCD40L) is a marker of platelet activation; whether platelet activation occurs in the setting of renal artery stenosis and stenting is unknown. Additionally, the effect of embolic protection devices and glycoprotein IIb/IIIa inhibitors on platelet activation during renal artery intervention is unknown. Design, setting, participants, & measurements Plasma levels of sCD40L were measured in healthy controls, patients with atherosclerosis without renal stenosis, and patients with renal artery stenosis before, immediately after, and 24 hours after renal artery stenting. Results Soluble CD40L levels were higher in renal artery stenosis patients than normal controls (347.5 ± 27.0 versus 65.2 ± 1.4 pg/ml, P < 0.001), but were similar to patients with atherosclerosis without renal artery stenosis. Platelet-rich emboli were captured in 26% (9 of 35) of embolic protection device patients, and in these patients sCD40L was elevated before the procedure. Embolic protection device use was associated with a nonsignificant increase in sCD40L, whereas sCD40L declined with abciximab after the procedure (324.9 ± 42.5 versus 188.7 ± 31.0 pg/ml, P = 0.003) and at 24 hours. Conclusions Atherosclerotic renal artery stenosis is associated with platelet activation, but this appears to be related to atherosclerosis, not renal artery stenosis specifically. Embolization of platelet-rich thrombi is common in renal artery stenting and is inhibited with abciximab. PMID:21817131

Direct Position Determination of Unknown Signals in the Presence of Multipath Propagation.

PubMed

Du, Jianping; Wang, Ding; Yu, Wanting; Yu, Hongyi

2018-03-17

A novel geolocation architecture, termed "Multiple Transponders and Multiple Receivers for Multiple Emitters Positioning System (MTRE)" is proposed in this paper. Existing Direct Position Determination (DPD) methods take advantage of a rather simple channel assumption (line of sight channels with complex path attenuations) and a simplified MUltiple SIgnal Classification (MUSIC) algorithm cost function to avoid the high dimension searching. We point out that the simplified assumption and cost function reduce the positioning accuracy because of the singularity of the array manifold in a multi-path environment. We present a DPD model for unknown signals in the presence of Multi-path Propagation (MP-DPD) in this paper. MP-DPD adds non-negative real path attenuation constraints to avoid the mistake caused by the singularity of the array manifold. The Multi-path Propagation MUSIC (MP-MUSIC) method and the Active Set Algorithm (ASA) are designed to reduce the dimension of searching. A Multi-path Propagation Maximum Likelihood (MP-ML) method is proposed in addition to overcome the limitation of MP-MUSIC in the sense of a time-sensitive application. An iterative algorithm and an approach of initial value setting are given to make the MP-ML time consumption acceptable. Numerical results validate the performances improvement of MP-MUSIC and MP-ML. A closed form of the Cramér-Rao Lower Bound (CRLB) is derived as a benchmark to evaluate the performances of MP-MUSIC and MP-ML.

Stability of Nonlinear Systems with Unknown Time-varying Feedback Delay

NASA Astrophysics Data System (ADS)

Chunodkar, Apurva A.; Akella, Maruthi R.

2013-12-01

This paper considers the problem of stabilizing a class of nonlinear systems with unknown bounded delayed feedback wherein the time-varying delay is 1) piecewise constant 2) continuous with a bounded rate. We also consider application of these results to the stabilization of rigid-body attitude dynamics. In the first case, the time-delay in feedback is modeled specifically as a switch among an arbitrarily large set of unknown constant values with a known strict upper bound. The feedback is a linear function of the delayed states. In the case of linear systems with switched delay feedback, a new sufficiency condition for average dwell time result is presented using a complete type Lyapunov-Krasovskii (L-K) functional approach. Further, the corresponding switched system with nonlinear perturbations is proven to be exponentially stable inside a well characterized region of attraction for an appropriately chosen average dwell time. In the second case, the concept of the complete type L-K functional is extended to a class of nonlinear time-delay systems with unknown time-varying time-delay. This extension ensures stability robustness to time-delay in the control design for all values of time-delay less than the known upper bound. Model-transformation is used in order to partition the nonlinear system into a nominal linear part that is exponentially stable with a bounded perturbation. We obtain sufficient conditions which ensure exponential stability inside a region of attraction estimate. A constructive method to evaluate the sufficient conditions is presented together with comparison with the corresponding constant and piecewise constant delay. Numerical simulations are performed to illustrate the theoretical results of this paper.

Automated cell analysis tool for a genome-wide RNAi screen with support vector machine based supervised learning

NASA Astrophysics Data System (ADS)

Remmele, Steffen; Ritzerfeld, Julia; Nickel, Walter; Hesser, Jürgen

2011-03-01

RNAi-based high-throughput microscopy screens have become an important tool in biological sciences in order to decrypt mostly unknown biological functions of human genes. However, manual analysis is impossible for such screens since the amount of image data sets can often be in the hundred thousands. Reliable automated tools are thus required to analyse the fluorescence microscopy image data sets usually containing two or more reaction channels. The herein presented image analysis tool is designed to analyse an RNAi screen investigating the intracellular trafficking and targeting of acylated Src kinases. In this specific screen, a data set consists of three reaction channels and the investigated cells can appear in different phenotypes. The main issue of the image processing task is an automatic cell segmentation which has to be robust and accurate for all different phenotypes and a successive phenotype classification. The cell segmentation is done in two steps by segmenting the cell nuclei first and then using a classifier-enhanced region growing on basis of the cell nuclei to segment the cells. The classification of the cells is realized by a support vector machine which has to be trained manually using supervised learning. Furthermore, the tool is brightness invariant allowing different staining quality and it provides a quality control that copes with typical defects during preparation and acquisition. A first version of the tool has already been successfully applied for an RNAi-screen containing three hundred thousand image data sets and the SVM extended version is designed for additional screens.

A Method for Calculating Strain Energy Release Rates in Preliminary Design of Composite Skin/Stringer Debonding Under Multi-Axial Loading

NASA Technical Reports Server (NTRS)

Krueger, Ronald; Minguet, Pierre J.; OBrien, T. Kevin

1999-01-01

Three simple procedures were developed to determine strain energy release rates, G, in composite skin/stringer specimens for various combinations of unaxial and biaxial (in-plane/out-of-plane) loading conditions. These procedures may be used for parametric design studies in such a way that only a few finite element computations will be necessary for a study of many load combinations. The results were compared with mixed mode strain energy release rates calculated directly from nonlinear two-dimensional plane-strain finite element analyses using the virtual crack closure technique. The first procedure involved solving three unknown parameters needed to determine the energy release rates. Good agreement was obtained when the external loads were used in the expression derived. This superposition technique was only applicable if the structure exhibits a linear load/deflection behavior. Consequently, a second technique was derived which was applicable in the case of nonlinear load/deformation behavior. The technique involved calculating six unknown parameters from a set of six simultaneous linear equations with data from six nonlinear analyses to determine the energy release rates. This procedure was not time efficient, and hence, less appealing. A third procedure was developed to calculate mixed mode energy release rates as a function of delamination lengths. This procedure required only one nonlinear finite element analysis of the specimen with a single delamination length to obtain a reference solution for the energy release rates and the scale factors. The delamination was extended in three separate linear models of the local area in the vicinity of the delamination subjected to unit loads to obtain the distribution of G with delamination lengths. This set of sub-problems was Although additional modeling effort is required to create the sub- models, this local technique is efficient for parametric studies.

Mixed linear-non-linear inversion of crustal deformation data: Bayesian inference of model, weighting and regularization parameters

NASA Astrophysics Data System (ADS)

Fukuda, Jun'ichi; Johnson, Kaj M.

2010-06-01

We present a unified theoretical framework and solution method for probabilistic, Bayesian inversions of crustal deformation data. The inversions involve multiple data sets with unknown relative weights, model parameters that are related linearly or non-linearly through theoretic models to observations, prior information on model parameters and regularization priors to stabilize underdetermined problems. To efficiently handle non-linear inversions in which some of the model parameters are linearly related to the observations, this method combines both analytical least-squares solutions and a Monte Carlo sampling technique. In this method, model parameters that are linearly and non-linearly related to observations, relative weights of multiple data sets and relative weights of prior information and regularization priors are determined in a unified Bayesian framework. In this paper, we define the mixed linear-non-linear inverse problem, outline the theoretical basis for the method, provide a step-by-step algorithm for the inversion, validate the inversion method using synthetic data and apply the method to two real data sets. We apply the method to inversions of multiple geodetic data sets with unknown relative data weights for interseismic fault slip and locking depth. We also apply the method to the problem of estimating the spatial distribution of coseismic slip on faults with unknown fault geometry, relative data weights and smoothing regularization weight.

What Do We Know about "How" to Promote Physical Activity to Adolescents? A Mapping Review

ERIC Educational Resources Information Center

Bush, Paula Louise; García Bengoechea, Enrique

2015-01-01

To date, adolescent physical activity (PA) intervention research has focused on the school setting and suggests a need to extend interventions beyond this setting to influence teenagers' overall level of PA. But, the relative effectiveness of PA promotion strategies that can be part of such multi-setting interventions remains unknown. We completed…

Learning with Nature and Learning from Others: Nature as Setting and Resource for Early Childhood Education

ERIC Educational Resources Information Center

MacQuarrie, Sarah; Nugent, Clare; Warden, Claire

2015-01-01

Nature-based learning is an increasingly popular type of early childhood education. Despite this, children's experiences--in particular, their form and function within different settings and how they are viewed by practitioners--are relatively unknown. Accordingly, the use of nature as a setting and a resource for learning was researched. A…

National Dam Safety Program. Moon Valley Dam (MO 11597), Missouri - Kansas City Basin, Boone County, Missouri. Phase I Inspection Report.

DTIC Science & Technology

1981-08-01

Design 6 2.2 Construction 6 2.3 Operation 6 2.4 Geology 6 2.5 Evaluation 6 SECTION 3 - VISUAL INSPECTION 3.1 Findings 7 3.2 Evaluation 9 SECTION 4...Downstream of Dam 9 Erosion Behind East Wingwall 10 Erosion and Debris Behind West Wingwall 11 Diagonal Crack in East Wingwall 12 West Wingwall...2.0 H to approximately 1.0 V on 6.0 H. (6) Zoning - Unknown. (7) Impervious core - Unknown. (8) Cutoff - Unknown. ( 9 ) Grout curtain - Unknown. h

Technical support for creating an artificial intelligence system for feature extraction and experimental design

NASA Technical Reports Server (NTRS)

Glick, B. J.

1985-01-01

Techniques for classifying objects into groups or clases go under many different names including, most commonly, cluster analysis. Mathematically, the general problem is to find a best mapping of objects into an index set consisting of class identifiers. When an a priori grouping of objects exists, the process of deriving the classification rules from samples of classified objects is known as discrimination. When such rules are applied to objects of unknown class, the process is denoted classification. The specific problem addressed involves the group classification of a set of objects that are each associated with a series of measurements (ratio, interval, ordinal, or nominal levels of measurement). Each measurement produces one variable in a multidimensional variable space. Cluster analysis techniques are reviewed and methods for incuding geographic location, distance measures, and spatial pattern (distribution) as parameters in clustering are examined. For the case of patterning, measures of spatial autocorrelation are discussed in terms of the kind of data (nominal, ordinal, or interval scaled) to which they may be applied.

A method for paraplegic upper-body posture estimation during standing: a pilot study for rehabilitation purposes.

PubMed

Pages, Gaël; Ramdani, Nacim; Fraisse, Philippe; Guiraud, David

2009-06-01

This paper presents a contribution for restoring standing in paraplegia while using functional electrical stimulation (FES). Movement generation induced by FES remains mostly open looped and stimulus intensities are tuned empirically. To design an efficient closed-loop control, a preliminary study has been carried out to investigate the relationship between body posture and voluntary upper body movements. A methodology is proposed to estimate body posture in the sagittal plane using force measurements exerted on supporting handles during standing. This is done by setting up constraints related to the geometric equations of a two-dimensional closed chain model and the hand-handle interactions. All measured quantities are subject to an uncertainty assumed unknown but bounded. The set membership estimation problem is solved via interval analysis. Guaranteed uncertainty bounds are computed for the estimated postures. In order to test the feasibility of our methodology, experiments were carried out with complete spinal cord injured patients.

Multiple concurrent recursive least squares identification with application to on-line spacecraft mass-property identification

NASA Technical Reports Server (NTRS)

Wilson, Edward (Inventor)

2006-01-01

The present invention is a method for identifying unknown parameters in a system having a set of governing equations describing its behavior that cannot be put into regression form with the unknown parameters linearly represented. In this method, the vector of unknown parameters is segmented into a plurality of groups where each individual group of unknown parameters may be isolated linearly by manipulation of said equations. Multiple concurrent and independent recursive least squares identification of each said group run, treating other unknown parameters appearing in their regression equation as if they were known perfectly, with said values provided by recursive least squares estimation from the other groups, thereby enabling the use of fast, compact, efficient linear algorithms to solve problems that would otherwise require nonlinear solution approaches. This invention is presented with application to identification of mass and thruster properties for a thruster-controlled spacecraft.

Minimal-Approximation-Based Decentralized Backstepping Control of Interconnected Time-Delay Systems.

PubMed

Choi, Yun Ho; Yoo, Sung Jin

2016-12-01

A decentralized adaptive backstepping control design using minimal function approximators is proposed for nonlinear large-scale systems with unknown unmatched time-varying delayed interactions and unknown backlash-like hysteresis nonlinearities. Compared with existing decentralized backstepping methods, the contribution of this paper is to design a simple local control law for each subsystem, consisting of an actual control with one adaptive function approximator, without requiring the use of multiple function approximators and regardless of the order of each subsystem. The virtual controllers for each subsystem are used as intermediate signals for designing a local actual control at the last step. For each subsystem, a lumped unknown function including the unknown nonlinear terms and the hysteresis nonlinearities is derived at the last step and is estimated by one function approximator. Thus, the proposed approach only uses one function approximator to implement each local controller, while existing decentralized backstepping control methods require the number of function approximators equal to the order of each subsystem and a calculation of virtual controllers to implement each local actual controller. The stability of the total controlled closed-loop system is analyzed using the Lyapunov stability theorem.

The impact of simulation-based learning on students' English for Nursing Purposes (ENP) reading proficiency: a quasi-experimental study.

PubMed

Chang, Hsiao-Yun Annie; Chan, Luke; Siren, Betty

2013-06-01

This is a report of a study which evaluated simulation-based learning as a teaching strategy for improving participants' ENP reading proficiency in the senior college program of students whose first language is Chinese, not English. Simulation-based learning is known to be one of most effective teaching strategies in the healthcare professional curricula, which brings a clinical setting into the classroom. However, developing English reading skills for English written nursing journals through simulation-based learning in the nursing curricula, is largely unknown. We used a quasi-experimental approach with nonequivalent control group design to collect the causal connections between intervention and outcomes. 101 students were enrolled in this study (response rate 92.6%) of these 48 students volunteered for the intervention group, and 53 students for the control group. The findings indicated that the intervention group had significantly higher mean scores in ENP reading proficiency with unknown words in the article (p=.004), vocabulary (p<.001), and comprehension (p<.001) compared to the control group. Also, the intervention students showed more improvement in their English reading, both from quantitative and qualitative findings. Simulation-based learning may have some advantages in improving the English reading ability on English written nursing journals among nursing students. However, the benefits to the students of this study is still to be determined, and further exploration is needed with well designed research and a universal method of outcome measurement. Copyright © 2012 Elsevier Ltd. All rights reserved.

Planning Robotic Manipulation Strategies for Sliding Objects

NASA Astrophysics Data System (ADS)

Peshkin, Michael A.

Automated planning of grasping or manipulation requires an understanding of both the physics and the geometry of manipulation, and a representation of that knowledge which facilitates the search for successful strategies. We consider manipulation on a level conveyor belt or tabletop, on which a part may slide when touched by a robot. Manipulation plans for a given part must succeed in the face of two types of uncertainty: that of the details of surfaces in contact, and that of the initial configuration of the part. In general the points of contact between the part and the surface it slides on will be unknown, so the motion of the part in response to a push cannot be predicted exactly. Using a simple variational principle (which is derived), we find the set of possible motions of a part for a given push, for all collections of points of contact. The answer emerges as a locus of centers of rotation (CORs). Manipulation plans made using this locus will succeed despite unknown details of contact. Results of experimental tests of the COR loci are presented. Uncertainty in the initial configuration of a part is usually also present. To plan in the presence of uncertainty, configuration maps are defined, which map all configurations of a part before an elementary operation to all possible outcomes, thus encapsulating the physics and geometry of the operation. The configuration map for an operation sequence is a product of configuration maps of elementary operations. Using COR loci we compute configuration maps for elementary sliding operations. Appropriate search techniques are applied to find operation sequences which succeed in the presence of uncertainty in the initial configuration and unknown details of contact. Such operation sequences may be used as parts feeder designs or as manipulation or grasping strategies for robots. As an example we demonstrate the automated design of a class of passive parts feeders consisting of multiple sequential fences across a conveyor belt.

Exploring the ancestry differentiation and inference capacity of the 28-plex AISNPs.

PubMed

Hao, Wei-Qi; Liu, Jing; Jiang, Li; Han, Jun-Ping; Wang, Ling; Li, Jiu-Ling; Ma, Quan; Liu, Chao; Wang, Hui-Jun; Li, Cai-Xia

2018-06-07

Inferring an unknown DNA's ancestry using a set of ancestry-informative single nucleotide polymorphisms (SNPs) in forensic science is useful to provide investigative leads. This is especially true when there is no DNA database match or specified suspect. Thus, a set of SNPs with highly robust and balanced differential power is strongly demanded in forensic science. In addition, it is also necessary to build a genotyping database for estimating the ancestry of an individual or an unknown DNA. For the differentiation of Africans, Europeans, East Asians, Native Americans, and Oceanians, the Global Nano set that includes just 31 SNPs was developed by de la Puente et al. Its ability for differentiation and balance was evaluated using the genotype data of the 1000 Genomes Phase III project and the Stanford University HGDP-CEPH. Just 402 samples were genotyped and analyzed as a reference set based on statistical methods. To validate the differentiating capacity using more samples, we developed a single-tube 28-plex SNP assay in which the SNPs were chosen from the 31 allelic loci of the Global AIMs Nano set. Three tri-allelic SNPs used to differentiate mixed-source DNA contribute little to population differentiation and were excluded here. Then, 998 individuals from 21 populations were typed, and these genotypes were combined with the genotype data obtained from 1000 Genomes Phase III and the Stanford University HGDP-CEPH (3090 total samples,43 populations) to estimate the power of this multiplex assay and build a database for the further inference of an individual or an unknown DNA sample in forensic practice.

Monoterpene Unknowns Identified Using IR, [to the first power]H-NMR, [to the thirteenth power]C-NMR, DEPT, COSY, and HETCOR

ERIC Educational Resources Information Center

Alty, Lisa T.

2005-01-01

A study identifies a compound from a set of monoterpenes using infrared (IR) and one-dimensional (1D) nuclear magnetic resonance (NMR) techniques. After identifying the unknown, each carbon and proton signal can be interpreted and assigned to the structure using the information in the two-dimensional (2D) NMR spectra, correlation spectroscopy…

Unknown syndrome: abnormal facies, hypothyroidism, postaxial polydactyly, and severe retardation: a third patient.

PubMed Central

Cavalcanti, D P

1989-01-01

Young and Simpson in 1987 and Fryns and Moerman in 1988 each reported a case of a new unknown syndrome with hypothyroidism, severe global retardation, and abnormal facies, including microcephaly, blepharophimosis, bulbous nose, thin upper lip, low set ears, and micrognathia. A male infant with a similar pattern of malformations and postaxial polydactyly is reported here. Images PMID:2614801

National Dam Safety Program. Highland Park Reservoir Dam (Inventory Number N.Y. 790), Genesee River Basin, Monroe County, New York. Phase I Inspection Report,

DTIC Science & Technology

1981-09-14

34 rga Highland Park Reservoir Dam Vi’.sual I. .. ’. •Genesee River Basin, ’!ydrolozy. ". ". . . Scabi tyMo r e C u t.,.- Js eps’ •; ::or.ation -3 :..i :n...dam impounds a municipal water storage reservoir. g. Design and Construction History The dam was designed and built around 1875. h. Normal Operating... History : Date Constructed Around 1875 Date(s) Reconstructed N/A Designer Unknown Constructed by Unknown Owner Water Department, City of Rochester, New

Vision System for Coarsely Estimating Motion Parameters for Unknown Fast Moving Objects in Space

PubMed Central

Chen, Min; Hashimoto, Koichi

2017-01-01

Motivated by biological interests in analyzing navigation behaviors of flying animals, we attempt to build a system measuring their motion states. To do this, in this paper, we build a vision system to detect unknown fast moving objects within a given space, calculating their motion parameters represented by positions and poses. We proposed a novel method to detect reliable interest points from images of moving objects, which can be hardly detected by general purpose interest point detectors. 3D points reconstructed using these interest points are then grouped and maintained for detected objects, according to a careful schedule, considering appearance and perspective changes. In the estimation step, a method is introduced to adapt the robust estimation procedure used for dense point set to the case for sparse set, reducing the potential risk of greatly biased estimation. Experiments are conducted against real scenes, showing the capability of the system of detecting multiple unknown moving objects and estimating their positions and poses. PMID:29206189

A Return to Innovative Engineering Design, Critical Thinking and Systems Engineering

NASA Technical Reports Server (NTRS)

Camarda, Charles J.

2007-01-01

I believe we are facing a critical time where innovative engineering design is of paramount importance to the success of our aerospace industry. However, the very qualities and attributes necessary for enhancing, educating, and mentoring a creative spirit are in decline in important areas. The importance of creativity and innovation in this country was emphasized by a special edition of the Harvard Business Review OnPoint entitled: "The Creative Company" which compiled a series of past and present articles on the subject of creativity and innovation and stressed its importance to our national economy. There is also a recognition of a lack of engineering, critical thinking and problem-solving skills in our education systems and a trend toward trying to enhance those skills by developing K-12 educational programs such as Project Lead the Way, "Science for All Americans", Benchmarks 2061 , etc. In addition, with respect to spacecraft development, we have a growing need for young to mid-level engineers with appropriate experience and skills in spacecraft design, development, analysis, testing, and systems engineering. As the Director of Engineering at NASA's Johnson Space Center, I realized that sustaining engineering support of an operational human spacecraft such as the Space Shuttle is decidedly different than engineering design and development skills necessary for designing a new spacecraft such as the Crew Exploration Vehicle of the Constellation Program. We learned a very important lesson post Columbia in that the Space Shuttle is truly an experimental and not an operational vehicle and the strict adherence to developed rules and processes and chains of command of an inherently bureaucratic organizational structure will not protect us from a host of known unknowns let alone unknown unknowns. There are no strict rules, processes, or procedures for understanding anomalous results of an experiment, anomalies with an experimental spacecraft like Shuttle, or in the conceptual design of a spacecraft. Engineering design is as much an art as it is a science. The critical thinking skills necessary to uncover lurking problems in an experimental design and creatively develop solutions are some of the same skills necessary to design a new spacecraft. Thus, I believe engineers unfamiliar with or removed from design and development need time to transition and develop the required skill set to be effective spacecraft designers. I believe the creative process necessary in design can be enhanced and even taught as early as grades K-12 and should continue to be nurtured and developed at the university level and beyond. I am going to present a strategy for developing learning teams to address complex multidisciplinary problems and to creatively develop solutions to those problems rapidly at minimal cost. I will frame a real problem, the development of on-orbit thermal protection system repair of the Space Shuttle, and step through the series of skills necessary to enhance the creative process. The case study I will illustrate is based on a real project, the R&D Reinforced Carbon-Carbon (RCC) Repair Team's development of on-orbit repair concepts for damaged Space Shuttle RCC nose cap and/or leading edges.

Transition support for new graduate and novice nurses in critical care settings: An integrative review of the literature.

PubMed

Innes, Tiana; Calleja, Pauline

2018-05-01

Transition into critical care areas for new graduate nurses may be more difficult than transitioning into other areas due to the specialised knowledge needed. It is unknown which aspects of transition programs best support new graduate nurses improve competence and confidence to transition into critical care nursing specialties. Identifying these aspects would assist to design and implement best practice transition programs for new graduates in critical care areas. Themes identified in the literature include; having a designated resource person, workplace culture, socialisation, knowledge and skill acquisition, orientation, and rotation. Allocation of a quality resource person/s, supportive workplace culture, positive socialisation experiences, knowledge and skill acquisition and structured orientation based on new graduates' learning needs all positively supported increased confidence, competence and transition into nursing practice. Rotations between areas within graduate programs can potentially have both positive and negative impacts on the transition process. Negative impacts of including a rotation component in a transition program should be carefully considered alongside perceived benefits when designing new graduate nurse transition programs. Copyright © 2018. Published by Elsevier Ltd.

OPC model generation procedure for different reticle vendors

NASA Astrophysics Data System (ADS)

Jost, Andrew M.; Belova, Nadya; Callan, Neal P.

2003-12-01

The challenge of delivering acceptable semiconductor products to customers in timely fashion becomes more difficult as design complexity increases. The requirements of current generation designs tax OPC engineers greater than ever before since the readiness of high-quality OPC models can delay new process qualifications or lead to respins, which add to the upward-spiraling costs of new reticle sets, extend time-to-market, and disappoint customers. In their efforts to extend the printability of new designs, OPC engineers generally focus on the data-to-wafer path, ignoring data-to-mask effects almost entirely. However, it is unknown whether reticle makers' disparate processes truly yield comparable reticles, even with identical tools. This approach raises the question of whether a single OPC model is applicable to all reticle vendors. LSI Logic has developed a methodology for quantifying vendor-to-vendor reticle manufacturing differences and adapting OPC models for use at several reticle vendors. This approach allows LSI Logic to easily adapt existing OPC models for use with several reticle vendors and obviates the generation of unnecessary models, allowing OPC engineers to focus their efforts on the most critical layers.

Far transfer to language and math of a short software-based gaming intervention

PubMed Central

Goldin, Andrea Paula; Hermida, María Julia; Shalom, Diego E.; Elias Costa, Martín; Lopez-Rosenfeld, Matías; Segretin, María Soledad; Fernández-Slezak, Diego; Lipina, Sebastián J.; Sigman, Mariano

2014-01-01

Executive functions (EF) in children can be trained, but it remains unknown whether training-related benefits elicit far transfer to real-life situations. Here, we investigate whether a set of computerized games might yield near and far transfer on an experimental and an active control group of low-SES otherwise typically developing 6-y-olds in a 3-mo pretest–training–posttest design that was ecologically deployed (at school). The intervention elicits transfer to some (but not all) facets of executive function. These changes cascade to real-world measures of school performance. The intervention equalizes academic outcomes across children who regularly attend school and those who do not because of social and familiar circumstances. PMID:24711403

Development of an unsteady wake theory appropriate for aeroelastic analyses of rotors in hover and forward flight

NASA Technical Reports Server (NTRS)

Peters, David A.

1988-01-01

The purpose of this research is the development of an unsteady aerodynamic model for rotors such that it can be used in conventional aeroelastic analysis (e.g., eigenvalue determination and control system design). For this to happen, the model must be in a state-space formulation such that the states of the flow can be defined, calculated and identified as part of the analysis. The fluid mechanics of the problem is given by a closed-form inversion of an acceleration potential. The result is a set of first-order differential equations in time for the unknown flow coefficients. These equations are hierarchical in the sense that they may be truncated at any number of radial or azimuthal terms.

The Importance of Flexibility of Pronunciation in Learning to Decode: A Training Study in Set for Variability

ERIC Educational Resources Information Center

Zipke, Marcy

2016-01-01

The ability to flexibly approach the pronunciation of unknown words, or set "for variability", has been shown to contribute to word recognition skills. However, this is the first study that has attempted to teach students strategies for increasing their set for variability. Beginning readers (N = 15) were instructed to correct oral…

Shotgun Protein Sequencing with Meta-contig Assembly*

PubMed Central

Guthals, Adrian; Clauser, Karl R.; Bandeira, Nuno

2012-01-01

Full-length de novo sequencing from tandem mass (MS/MS) spectra of unknown proteins such as antibodies or proteins from organisms with unsequenced genomes remains a challenging open problem. Conventional algorithms designed to individually sequence each MS/MS spectrum are limited by incomplete peptide fragmentation or low signal to noise ratios and tend to result in short de novo sequences at low sequencing accuracy. Our shotgun protein sequencing (SPS) approach was developed to ameliorate these limitations by first finding groups of unidentified spectra from the same peptides (contigs) and then deriving a consensus de novo sequence for each assembled set of spectra (contig sequences). But whereas SPS enables much more accurate reconstruction of de novo sequences longer than can be recovered from individual MS/MS spectra, it still requires error-tolerant matching to homologous proteins to group smaller contig sequences into full-length protein sequences, thus limiting its effectiveness on sequences from poorly annotated proteins. Using low and high resolution CID and high resolution HCD MS/MS spectra, we address this limitation with a Meta-SPS algorithm designed to overlap and further assemble SPS contigs into Meta-SPS de novo contig sequences extending as long as 100 amino acids at over 97% accuracy without requiring any knowledge of homologous protein sequences. We demonstrate Meta-SPS using distinct MS/MS data sets obtained with separate enzymatic digestions and discuss how the remaining de novo sequencing limitations relate to MS/MS acquisition settings. PMID:22798278

Shotgun protein sequencing with meta-contig assembly.

PubMed

Guthals, Adrian; Clauser, Karl R; Bandeira, Nuno

2012-10-01

Full-length de novo sequencing from tandem mass (MS/MS) spectra of unknown proteins such as antibodies or proteins from organisms with unsequenced genomes remains a challenging open problem. Conventional algorithms designed to individually sequence each MS/MS spectrum are limited by incomplete peptide fragmentation or low signal to noise ratios and tend to result in short de novo sequences at low sequencing accuracy. Our shotgun protein sequencing (SPS) approach was developed to ameliorate these limitations by first finding groups of unidentified spectra from the same peptides (contigs) and then deriving a consensus de novo sequence for each assembled set of spectra (contig sequences). But whereas SPS enables much more accurate reconstruction of de novo sequences longer than can be recovered from individual MS/MS spectra, it still requires error-tolerant matching to homologous proteins to group smaller contig sequences into full-length protein sequences, thus limiting its effectiveness on sequences from poorly annotated proteins. Using low and high resolution CID and high resolution HCD MS/MS spectra, we address this limitation with a Meta-SPS algorithm designed to overlap and further assemble SPS contigs into Meta-SPS de novo contig sequences extending as long as 100 amino acids at over 97% accuracy without requiring any knowledge of homologous protein sequences. We demonstrate Meta-SPS using distinct MS/MS data sets obtained with separate enzymatic digestions and discuss how the remaining de novo sequencing limitations relate to MS/MS acquisition settings.

Optimising in situ gamma measurements to identify the presence of radioactive particles in land areas.

PubMed

Rostron, Peter D; Heathcote, John A; Ramsey, Michael H

2014-12-01

High-coverage in situ surveys with gamma detectors are the best means of identifying small hotspots of activity, such as radioactive particles, in land areas. Scanning surveys can produce rapid results, but the probabilities of obtaining false positive or false negative errors are often unknown, and they may not satisfy other criteria such as estimation of mass activity concentrations. An alternative is to use portable gamma-detectors that are set up at a series of locations in a systematic sampling pattern, where any positive measurements are subsequently followed up in order to determine the exact location, extent and nature of the target source. The preliminary survey is typically designed using settings of detector height, measurement spacing and counting time that are based on convenience, rather than using settings that have been calculated to meet requirements. This paper introduces the basis of a repeatable method of setting these parameters at the outset of a survey, for pre-defined probabilities of false positive and false negative errors in locating spatially small radioactive particles in land areas. It is shown that an un-collimated detector is more effective than a collimated detector that might typically be used in the field. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Tune-stabilized, non-scaling, fixed-field, alternating gradient accelerator

DOEpatents

Johnstone, Carol J [Warrenville, IL

2011-02-01

A FFAG is a particle accelerator having turning magnets with a linear field gradient for confinement and a large edge angle to compensate for acceleration. FODO cells contain focus magnets and defocus magnets that are specified by a number of parameters. A set of seven equations, called the FFAG equations relate the parameters to one another. A set of constraints, call the FFAG constraints, constrain the FFAG equations. Selecting a few parameters, such as injection momentum, extraction momentum, and drift distance reduces the number of unknown parameters to seven. Seven equations with seven unknowns can be solved to yield the values for all the parameters and to thereby fully specify a FFAG.

The Entertainment-Education Strategy in Sexual Assault Prevention: A Comparison of Theoretical Foundations and a Test of Effectiveness in a College Campus Setting.

PubMed

Hust, Stacey J T; Adams, Paula M; Willoughby, Jessica Fitts; Ren, Chunbo; Lei, Ming; Ran, Weina; Marett, Emily Garrigues

2017-09-01

Among the existing sexual assault prevention efforts on college campuses, few use mass communication strategies designed to simultaneously entertain and educate. Although many entertainment-education efforts are guided by social cognitive theory, other theories may be useful in entertainment-education design. Previous research has found that social cognitive theory and social norms theory can successfully influence participants' perceived norms and efficacy related to sexual assault reduction; however, whether such results can be replicated in a naturalistic setting and the extent to which the guiding theoretical foundation may influence outcomes remain unknown. We used a pre- and posttest field experiment with college students in residence halls to assess how different theoretical foundations may influence effects. Over the course of a semester, the participants viewed eight mini-magazines developed using (1) social cognitive theory, (2) social norms theory, (3) a combination of both theoretical frameworks, or (4) a control condition with no sexual assault prevention messaging. Participants in the combined content condition had greater levels of self-efficacy related to sexual assault prevention and more accurate norm perceptions. There were also effects for the mini-magazines developed with only one theoretical framework. Overall, we found that multiple theories can effectively guide entertainment-education message development.

Am I who I say I am? Unobtrusive self-representation and personality recognition on Facebook

PubMed Central

2017-01-01

Across social media platforms users (sub)consciously represent themselves in a way which is appropriate for their intended audience. This has unknown impacts on studies with unobtrusive designs based on digital (social) platforms, and studies of contemporary social phenomena in online settings. A lack of appropriate methods to identify, control for, and mitigate the effects of self-representation, the propensity to express socially responding characteristics or self-censorship in digital settings, hinders the ability of researchers to confidently interpret and generalize their findings. This article proposes applying boosted regression modelling to fill this research gap. A case study of paid Amazon Mechanical Turk workers (n = 509) is presented where workers completed psychometric surveys and provided anonymized access to their Facebook timelines. Our research finds indicators of self-representation on Facebook, facilitating suggestions for its mitigation. We validate the use of LIWC for Facebook personality studies, as well as find discrepancies with extant literature about the use of LIWC-only approaches in unobtrusive designs. Using survey data and LIWC sentiment categories as predictors, the boosted regression model classified the Five Factor personality model with an average accuracy of 74.6%. The contribution of this work is an accurate prediction of psychometric information based on short, informal text. PMID:28926569

Am I who I say I am? Unobtrusive self-representation and personality recognition on Facebook.

PubMed

Hall, Margeret; Caton, Simon

2017-01-01

Across social media platforms users (sub)consciously represent themselves in a way which is appropriate for their intended audience. This has unknown impacts on studies with unobtrusive designs based on digital (social) platforms, and studies of contemporary social phenomena in online settings. A lack of appropriate methods to identify, control for, and mitigate the effects of self-representation, the propensity to express socially responding characteristics or self-censorship in digital settings, hinders the ability of researchers to confidently interpret and generalize their findings. This article proposes applying boosted regression modelling to fill this research gap. A case study of paid Amazon Mechanical Turk workers (n = 509) is presented where workers completed psychometric surveys and provided anonymized access to their Facebook timelines. Our research finds indicators of self-representation on Facebook, facilitating suggestions for its mitigation. We validate the use of LIWC for Facebook personality studies, as well as find discrepancies with extant literature about the use of LIWC-only approaches in unobtrusive designs. Using survey data and LIWC sentiment categories as predictors, the boosted regression model classified the Five Factor personality model with an average accuracy of 74.6%. The contribution of this work is an accurate prediction of psychometric information based on short, informal text.

A RSM-based predictive model to characterize heat treating parameters of D2 steel using combined Barkhausen noise and hysteresis loop methods

NASA Astrophysics Data System (ADS)

Kahrobaee, Saeed; Hejazi, Taha-Hossein

2017-07-01

Austenitizing and tempering temperatures are the effective characteristics in heat treating process of AISI D2 tool steel. Therefore, controlling them enables the heat treatment process to be designed more accurately which results in more balanced mechanical properties. The aim of this work is to develop a multiresponse predictive model that enables finding these characteristics based on nondestructive tests by a set of parameters of the magnetic Barkhausen noise technique and hysteresis loop method. To produce various microstructural changes, identical specimens from the AISI D2 steel sheet were austenitized in the range 1025-1130 °C, for 30 min, oil-quenched and finally tempered at various temperatures between 200 °C and 650 °C. A set of nondestructive data have been gathered based on general factorial design of experiments and used for training and testing the multiple response surface model. Finally, an optimization model has been proposed to achieve minimal error prediction. Results revealed that applying Barkhausen and hysteresis loop methods, simultaneously, coupling to the multiresponse model, has a potential to be used as a reliable and accurate nondestructive tool for predicting austenitizing and tempering temperatures (which, in turn, led to characterizing the microstructural changes) of the parts with unknown heat treating conditions.

Principal component analysis for designed experiments.

PubMed

Konishi, Tomokazu

2015-01-01

Principal component analysis is used to summarize matrix data, such as found in transcriptome, proteome or metabolome and medical examinations, into fewer dimensions by fitting the matrix to orthogonal axes. Although this methodology is frequently used in multivariate analyses, it has disadvantages when applied to experimental data. First, the identified principal components have poor generality; since the size and directions of the components are dependent on the particular data set, the components are valid only within the data set. Second, the method is sensitive to experimental noise and bias between sample groups. It cannot reflect the experimental design that is planned to manage the noise and bias; rather, it estimates the same weight and independence to all the samples in the matrix. Third, the resulting components are often difficult to interpret. To address these issues, several options were introduced to the methodology. First, the principal axes were identified using training data sets and shared across experiments. These training data reflect the design of experiments, and their preparation allows noise to be reduced and group bias to be removed. Second, the center of the rotation was determined in accordance with the experimental design. Third, the resulting components were scaled to unify their size unit. The effects of these options were observed in microarray experiments, and showed an improvement in the separation of groups and robustness to noise. The range of scaled scores was unaffected by the number of items. Additionally, unknown samples were appropriately classified using pre-arranged axes. Furthermore, these axes well reflected the characteristics of groups in the experiments. As was observed, the scaling of the components and sharing of axes enabled comparisons of the components beyond experiments. The use of training data reduced the effects of noise and bias in the data, facilitating the physical interpretation of the principal axes. Together, these introduced options result in improved generality and objectivity of the analytical results. The methodology has thus become more like a set of multiple regression analyses that find independent models that specify each of the axes.

Persistent Surveillance of Transient Events with Unknown Statistics

DTIC Science & Technology

2016-12-18

different bird species by a documentary maker is shown in Fig. 1. Additional examples of scenarios following this setting include robots patrolling the...persistent monitoring application in which a documentary maker would like to monitor three different species of birds appearing in three discrete, species...specific locations. Bird sightings at each location follow a stochastic process with a rate that is initially unknown to the documentary maker and must

Do Social Conditions Affect Capuchin Monkeys' (Cebus apella) Choices in a Quantity Judgment Task?

PubMed

Beran, Michael J; Perdue, Bonnie M; Parrish, Audrey E; Evans, Theodore A

2012-01-01

Beran et al. (2012) reported that capuchin monkeys closely matched the performance of humans in a quantity judgment test in which information was incomplete but a judgment still had to be made. In each test session, subjects first made quantity judgments between two known options. Then, they made choices where only one option was visible. Both humans and capuchin monkeys were guided by past outcomes, as they shifted from selecting a known option to selecting an unknown option at the point at which the known option went from being more than the average rate of return to less than the average rate of return from earlier choices in the test session. Here, we expanded this assessment of what guides quantity judgment choice behavior in the face of incomplete information to include manipulations to the unselected quantity. We manipulated the unchosen set in two ways: first, we showed the monkeys what they did not get (the unchosen set), anticipating that "losses" would weigh heavily on subsequent trials in which the same known quantity was presented. Second, we sometimes gave the unchosen set to another monkey, anticipating that this social manipulation might influence the risk-taking responses of the focal monkey when faced with incomplete information. However, neither manipulation caused difficulty for the monkeys who instead continued to use the rational strategy of choosing known sets when they were as large as or larger than the average rate of return in the session, and choosing the unknown (riskier) set when the known set was not sufficiently large. As in past experiments, this was true across a variety of daily ranges of quantities, indicating that monkeys were not using some absolute quantity as a threshold for selecting (or not) the known set, but instead continued to use the daily average rate of return to determine when to choose the known versus the unknown quantity.

Using re-randomization to increase the recruitment rate in clinical trials - an assessment of three clinical areas.

PubMed

Kahan, Brennan C

2016-12-13

Patient recruitment in clinical trials is often challenging, and as a result, many trials are stopped early due to insufficient recruitment. The re-randomization design allows patients to be re-enrolled and re-randomized for each new treatment episode that they experience. Because it allows multiple enrollments for each patient, this design has been proposed as a way to increase the recruitment rate in clinical trials. However, it is unknown to what extent recruitment could be increased in practice. We modelled the expected recruitment rate for parallel-group and re-randomization trials in different settings based on estimates from real trials and datasets. We considered three clinical areas: in vitro fertilization, severe asthma exacerbations, and acute sickle cell pain crises. We compared the two designs in terms of the expected time to complete recruitment, and the sample size recruited over a fixed recruitment period. Across the different scenarios we considered, we estimated that re-randomization could reduce the expected time to complete recruitment by between 4 and 22 months (relative reductions of 19% and 45%), or increase the sample size recruited over a fixed recruitment period by between 29% and 171%. Re-randomization can increase recruitment most for trials with a short follow-up period, a long trial recruitment duration, and patients with high rates of treatment episodes. Re-randomization has the potential to increase the recruitment rate in certain settings, and could lead to quicker and more efficient trials in these scenarios.

Deterministic Joint Assisted Cloning of Unknown Two-Qubit Entangled States

NASA Astrophysics Data System (ADS)

Zhan, You-Bang

2012-06-01

We present two schemes for perfect cloning unknown two-qubit and general two-qubit entangled states with assistance from two state preparers, respectively. In the schemes, the sender wish to teleport an unknown two-qubit (or general two-qubit) entangled state which from two state preparers to a remote receiver, and then create a perfect copy of the unknown state at her place. The schemes include two stages. The first stage of the schemes requires usual teleportation. In the second stage, to help the sender realize the quantum cloning, two state preparers perform two-qubit projective measurements on their own qubits which from the sender, then the sender can acquire a perfect copy of the unknown state. To complete the assisted cloning schemes, several novel sets of mutually orthogonal basis vectors are introduced. It is shown that, only if two state preparers collaborate with each other, and perform projective measurements under suitable measuring basis on their own qubit respectively, the sender can create a copy of the unknown state by means of some appropriate unitary operations. The advantage of the present schemes is that the total success probability for assisted cloning a perfect copy of the unknown state can reach 1.

Realtime motion planning for a mobile robot in an unknown environment using a neurofuzzy based approach

NASA Astrophysics Data System (ADS)

Zheng, Taixiong

2005-12-01

A neuro-fuzzy network based approach for robot motion in an unknown environment was proposed. In order to control the robot motion in an unknown environment, the behavior of the robot was classified into moving to the goal and avoiding obstacles. Then, according to the dynamics of the robot and the behavior character of the robot in an unknown environment, fuzzy control rules were introduced to control the robot motion. At last, a 6-layer neuro-fuzzy network was designed to merge from what the robot sensed to robot motion control. After being trained, the network may be used for robot motion control. Simulation results show that the proposed approach is effective for robot motion control in unknown environment.

Decentralised output feedback control of Markovian jump interconnected systems with unknown interconnections

NASA Astrophysics Data System (ADS)

Li, Li-Wei; Yang, Guang-Hong

2017-07-01

The problem of decentralised output feedback control is addressed for Markovian jump interconnected systems with unknown interconnections and general transition rates (TRs) allowed to be unknown or known with uncertainties. A class of decentralised dynamic output feedback controllers are constructed, and a cyclic-small-gain condition is exploited to dispose the unknown interconnections so that the resultant closed-loop system is stochastically stable and satisfies an H∞ performance. With slack matrices to cope with the nonlinearities incurred by unknown and uncertain TRs in control synthesis, a novel controller design condition is developed in linear matrix inequality formalism. Compared with the existing works, the proposed approach leads to less conservatism. Finally, two examples are used to illustrate the effectiveness of the new results.

Unified User Interface to Support Effective and Intuitive Data Discovery, Dissemination, and Analysis at NASA GES DISC

NASA Technical Reports Server (NTRS)

Petrenko, M.; Hegde, M.; Bryant, K.; Johnson, J. E.; Ritrivi, A.; Shen, S.; Volmer, B.; Pham, L. B.

2015-01-01

Goddard Earth Sciences Data and Information Services Center (GES DISC) has been providing access to scientific data sets since 1990s. Beginning as one of the first Earth Observing System Data and Information System (EOSDIS) archive centers, GES DISC has evolved to offer a wide range of science-enabling services. With a growing understanding of needs and goals of its science users, GES DISC continues to improve and expand on its broad set of data discovery and access tools, sub-setting services, and visualization tools. Nonetheless, the multitude of the available tools, a partial overlap of functionality, and independent and uncoupled interfaces employed by these tools often leave the end users confused as of what tools or services are the most appropriate for a task at hand. As a result, some the services remain underutilized or largely unknown to the users, significantly reducing the availability of the data and leading to a great loss of scientific productivity. In order to improve the accessibility of GES DISC tools and services, we have designed and implemented UUI, the Unified User Interface. UUI seeks to provide a simple, unified, and intuitive one-stop shop experience for the key services available at GES DISC, including sub-setting (Simple Subset Wizard), granule file search (Mirador), plotting (Giovanni), and other services. In this poster, we will discuss the main lessons, obstacles, and insights encountered while designing the UUI experience. We will also present the architecture and technology behind UUI, including NodeJS, Angular, and Mongo DB, as well as speculate on the future of the tool at GES DISC as well as in a broader context of the Space Science Informatics.

Distributed Optimization Design of Continuous-Time Multiagent Systems With Unknown-Frequency Disturbances.

PubMed

Wang, Xinghu; Hong, Yiguang; Yi, Peng; Ji, Haibo; Kang, Yu

2017-05-24

In this paper, a distributed optimization problem is studied for continuous-time multiagent systems with unknown-frequency disturbances. A distributed gradient-based control is proposed for the agents to achieve the optimal consensus with estimating unknown frequencies and rejecting the bounded disturbance in the semi-global sense. Based on convex optimization analysis and adaptive internal model approach, the exact optimization solution can be obtained for the multiagent system disturbed by exogenous disturbances with uncertain parameters.

Molecular Level Design Principle behind Optimal Sizes of Photosynthetic LH2 Complex: Taming Disorder through Cooperation of Hydrogen Bonding and Quantum Delocalization.

PubMed

Jang, Seogjoo; Rivera, Eva; Montemayor, Daniel

2015-03-19

The light harvesting 2 (LH2) antenna complex from purple photosynthetic bacteria is an efficient natural excitation energy carrier with well-known symmetric structure, but the molecular level design principle governing its structure-function relationship is unknown. Our all-atomistic simulations of nonnatural analogues of LH2 as well as those of a natural LH2 suggest that nonnatural sizes of LH2-like complexes could be built. However, stable and consistent hydrogen bonding (HB) between bacteriochlorophyll and the protein is shown to be possible only near naturally occurring sizes, leading to significantly smaller disorder than for nonnatural ones. Extensive quantum calculations of intercomplex exciton transfer dynamics, sampled for a large set of disorder, reveal that taming the negative effect of disorder through a reliable HB as well as quantum delocalization of the exciton is a critical mechanism that makes LH2 highly functional, which also explains why the natural sizes of LH2 are indeed optimal.

Optimized growth and reorientation of anisotropic material based on evolution equations

NASA Astrophysics Data System (ADS)

Jantos, Dustin R.; Junker, Philipp; Hackl, Klaus

2018-07-01

Modern high-performance materials have inherent anisotropic elastic properties. The local material orientation can thus be considered to be an additional design variable for the topology optimization of structures containing such materials. In our previous work, we introduced a variational growth approach to topology optimization for isotropic, linear-elastic materials. We solved the optimization problem purely by application of Hamilton's principle. In this way, we were able to determine an evolution equation for the spatial distribution of density mass, which can be evaluated in an iterative process within a solitary finite element environment. We now add the local material orientation described by a set of three Euler angles as additional design variables into the three-dimensional model. This leads to three additional evolution equations that can be separately evaluated for each (material) point. Thus, no additional field unknown within the finite element approach is needed, and the evolution of the spatial distribution of density mass and the evolution of the Euler angles can be evaluated simultaneously.

Design and analysis of adaptive Super-Twisting sliding mode control for a microgyroscope.

PubMed

Feng, Zhilin; Fei, Juntao

2018-01-01

This paper proposes a novel adaptive Super-Twisting sliding mode control for a microgyroscope under unknown model uncertainties and external disturbances. In order to improve the convergence rate of reaching the sliding surface and the accuracy of regulating and trajectory tracking, a high order Super-Twisting sliding mode control strategy is employed, which not only can combine the advantages of the traditional sliding mode control with the Super-Twisting sliding mode control, but also guarantee that the designed control system can reach the sliding surface and equilibrium point in a shorter finite time from any initial state and avoid chattering problems. In consideration of unknown parameters of micro gyroscope system, an adaptive algorithm based on Lyapunov stability theory is designed to estimate the unknown parameters and angular velocity of microgyroscope. Finally, the effectiveness of the proposed scheme is demonstrated by simulation results. The comparative study between adaptive Super-Twisting sliding mode control and conventional sliding mode control demonstrate the superiority of the proposed method.

Modeling of load lifting process with unknown center of gravity position

NASA Astrophysics Data System (ADS)

Kamanin, Y. N.; Zhukov, M. I.; Panichkin, A. V.; Redelin, R. A.

2018-03-01

The article proposes a new type of lifting beams that allows one to lift loads where the position of the center of gravity is unknown beforehand. The benefit of implementing this type of traverse is confirmed by the high demand for this product from the industrial enterprises and lack of their availability on the market. In conducted studies, the main kinematic and dynamic dependencies of the load lifting process with an unknown position of the center of gravity were described allowing for design and verification calculations of the traverse with flexible slings and an adjustable bail to be carried out. The obtained results can be useful to engineers and employees of enterprises engaged in the design and manufacturing of the lifting equipment and scientists doing research in “Carrying and lifting machines”.

Class Identification Efficacy in Piecewise GMM with Unknown Turning Points

ERIC Educational Resources Information Center

Ning, Ling; Luo, Wen

2018-01-01

Piecewise GMM with unknown turning points is a new procedure to investigate heterogeneous subpopulations' growth trajectories consisting of distinct developmental phases. Unlike the conventional PGMM, which relies on theory or experiment design to specify turning points a priori, the new procedure allows for an optimal location of turning points…

Approach for establishing approximate load carrying capacity for bridges with unknown material and unknown design properties.

DOT National Transportation Integrated Search

2011-07-01

There are 16 small to medium simple span bridges in Larimer County, Colorado that are currently load rated solely based on visual inspections. Most of these bridges are prestressed concrete bridges. The objective of this project is to load rate these...

Robust Fault Detection for Switched Fuzzy Systems With Unknown Input.

PubMed

Han, Jian; Zhang, Huaguang; Wang, Yingchun; Sun, Xun

2017-10-03

This paper investigates the fault detection problem for a class of switched nonlinear systems in the T-S fuzzy framework. The unknown input is considered in the systems. A novel fault detection unknown input observer design method is proposed. Based on the proposed observer, the unknown input can be removed from the fault detection residual. The weighted H∞ performance level is considered to ensure the robustness. In addition, the weighted H₋ performance level is introduced, which can increase the sensibility of the proposed detection method. To verify the proposed scheme, a numerical simulation example and an electromechanical system simulation example are provided at the end of this paper.

Visionary Expectations and Novice Designers--Prototyping in Design Education

ERIC Educational Resources Information Center

Schaeffer, Jennie Andersson; Palmgren, Marianne

2017-01-01

In information design education, we strive to find methods that provide students with opportunities to explore different ways of learning and designing. We seek to support development of contextual competences that will be helpful in navigating an unknown future of design in society. A challenge in today's design education is to formulate and use…

Van: An Open Letter

ERIC Educational Resources Information Center

Tieman, John Samuel

2011-01-01

This essay is an open letter from a classroom teacher to a concerned citizen. The letter lists a variety of problems caused largely by standardization and the more corrosive effects of positivism. Many of these problems are unknown to those outside the immediate school setting. While the letter focuses on a specific setting, an inner city school…

Strategies for Editing Virulent Staphylococcal Phages Using CRISPR-Cas10.

PubMed

Bari, S M Nayeemul; Walker, Forrest C; Cater, Katie; Aslan, Barbaros; Hatoum-Aslan, Asma

2017-12-15

Staphylococci are prevalent skin-dwelling bacteria that are also leading causes of antibiotic-resistant infections. Viruses that infect and lyse these organisms (virulent staphylococcal phages) can be used as alternatives to conventional antibiotics and represent promising tools to eliminate or manipulate specific species in the microbiome. However, since over half their genes have unknown functions, virulent staphylococcal phages carry inherent risk to cause unknown downstream side effects. Further, their swift and destructive reproductive cycle make them intractable by current genetic engineering techniques. CRISPR-Cas10 is an elaborate prokaryotic immune system that employs small RNAs and a multisubunit protein complex to detect and destroy phages and other foreign nucleic acids. Some staphylococci naturally possess CRISPR-Cas10 systems, thus providing an attractive tool already installed in the host chromosome to harness for phage genome engineering. However, the efficiency of CRISPR-Cas10 immunity against virulent staphylococcal phages and corresponding utility as a tool to facilitate their genome editing has not been explored. Here, we show that the CRISPR-Cas10 system native to Staphylococcus epidermidis exhibits robust immunity against diverse virulent staphylococcal phages. On the basis of this activity, a general two-step approach was developed to edit these phages that relies upon homologous recombination machinery encoded in the host. Variations of this approach to edit toxic phage genes and access phages that infect CRISPR-less staphylococci are also presented. This versatile set of genetic tools enables the systematic study of phage genes of unknown functions and the design of genetically defined phage-based antimicrobials that can eliminate or manipulate specific Staphylococcus species.

Spatial-temporal epidemiology of human Salmonella Enteritidis infections with major phage types (PTs 1, 4, 5b, 8, 13, and 13a) in Ontario, Canada, 2008-2009.

PubMed

Varga, Csaba; Pearl, David L; McEwen, Scott A; Sargeant, Jan M; Pollari, Frank; Guerin, Michele T

2015-12-17

In Ontario and Canada, the incidence of human Salmonella enterica serotype Enteritidis (S. Enteritidis) infections have increased steadily during the last decade. Our study evaluated the spatial and temporal epidemiology of the major phage types (PTs) of S. Enteritidis infections to aid public health practitioners design effective prevention and control programs. Data on S. Enteritidis infections between January 1, 2008 and December 31, 2009 were obtained from Ontario's disease surveillance system. Salmonella Enteritidis infections with major phage types were classified by their annual health region-level incidence rates (IRs), monthly IRs, clinical symptoms, and exposure settings. A scan statistic was employed to detect retrospective phage type-specific spatial, temporal, and space-time clusters of S. Enteritidis infections. Space-time cluster cases' exposure settings were evaluated to identify common exposures. 1,336 cases were available for analysis. The six most frequently reported S. Enteritidis PTs were 8 (n = 398), 13a (n = 218), 13 (n = 198), 1 (n = 132), 5b (n = 83), and 4 (n = 76). Reported rates of S. Enteritidis infections with major phage types varied by health region and month. International travel and unknown exposure settings were the most frequently reported settings for PT 5b, 4, and 1 cases, whereas unknown exposure setting, private home, food premise, and international travel were the most frequently reported settings for PT 8, 13, and 13a cases. Diarrhea, abdominal pain, and fever were the most commonly reported clinical symptoms. A number of phage type-specific spatial, temporal, and space-time clusters were identified. Space-time clusters of PTs 1, 4, and 5b occurred mainly during the winter and spring months in the North West, North East, Eastern, Central East, and Central West regions. Space-time clusters of PTs 13 and 13a occurred at different times of the year in the Toronto region. Space-time clusters of PT 8 occurred at different times of the year in the North West and South West regions. Phage type-specific differences in exposure settings, and spatial-temporal clustering of S. Enteritidis infections were demonstrated that might guide public health surveillance of disease outbreaks. Our study methodology could be applied to other foodborne disease surveillance data to detect retrospective high disease rate clusters, which could aid public health authorities in developing effective prevention and control programs.

Neural-Network-Based Adaptive Decentralized Fault-Tolerant Control for a Class of Interconnected Nonlinear Systems.

PubMed

Li, Xiao-Jian; Yang, Guang-Hong

2018-01-01

This paper is concerned with the adaptive decentralized fault-tolerant tracking control problem for a class of uncertain interconnected nonlinear systems with unknown strong interconnections. An algebraic graph theory result is introduced to address the considered interconnections. In addition, to achieve the desirable tracking performance, a neural-network-based robust adaptive decentralized fault-tolerant control (FTC) scheme is given to compensate the actuator faults and system uncertainties. Furthermore, via the Lyapunov analysis method, it is proven that all the signals of the resulting closed-loop system are semiglobally bounded, and the tracking errors of each subsystem exponentially converge to a compact set, whose radius is adjustable by choosing different controller design parameters. Finally, the effectiveness and advantages of the proposed FTC approach are illustrated with two simulated examples.

High-Resolution Melting Curve Analysis of the 16S Ribosomal Gene to Detect and Identify Pathogenic and Saprophytic Leptospira species in Colombian Isolates

PubMed Central

Peláez Sánchez, Ronald G.; Quintero, Juan Álvaro López; Pereira, Martha María; Agudelo-Flórez, Piedad

2017-01-01

It is important to identify the circulating Leptospira agent to enhance the performance of serodiagnostic tests by incorporating specific antigens of native species, develop vaccines that take into account the species/serovars circulating in different regions, and optimize prevention and control strategies. The objectives of this study were to develop a polymerase chain reaction (PCR)–high-resolution melting (HRM) assay for differentiating between species of the genus Leptospira and to verify its usefulness in identifying unknown samples to species level. A set of primers from the initial region of the 16S ribosomal gene was designed to detect and differentiate the 22 species of Leptospira. Eleven reference strains were used as controls to establish the reference species and differential melting curves. Twenty-five Colombian Leptospira isolates were studied to evaluate the usefulness of the PCR–HRM assay in identifying unknown samples to species level. This identification was confirmed by sequencing and phylogenetic analysis of the 16S ribosomal gene. Eleven Leptospira species were successfully identified, except for Leptospira meyeri/Leptospira yanagawae because the sequences were 100% identical. The 25 isolates from humans, animals, and environmental water sources were identified as Leptospira santarosai (twelve), Leptospira interrogans (nine), and L. meyeri/L. yanagawae (four). The species verification was 100% concordant between PCR–HRM and phylogenetic analysis of the 16S ribosomal gene. The PCR–HRM assay designed in this study is a useful tool for identifying Leptospira species from isolates. PMID:28500802

Diagnostic workup for fever of unknown origin: a multicenter collaborative retrospective study

PubMed Central

Naito, Toshio; Mizooka, Masafumi; Mitsumoto, Fujiko; Kanazawa, Kenji; Torikai, Keito; Ohno, Shiro; Morita, Hiroyuki; Ukimura, Akira; Mishima, Nobuhiko; Otsuka, Fumio; Ohyama, Yoshio; Nara, Noriko; Murakami, Kazunari; Mashiba, Kouichi; Akazawa, Kenichiro; Yamamoto, Koji; Senda, Shoichi; Yamanouchi, Masashi; Tazuma, Susumu; Hayashi, Jun

2013-01-01

Objective Fever of unknown origin (FUO) can be caused by many diseases, and varies depending on region and time period. Research on FUO in Japan has been limited to single medical institution or region, and no nationwide study has been conducted. We identified diseases that should be considered and useful diagnostic testing in patients with FUO. Design A nationwide retrospective study. Setting 17 hospitals affiliated with the Japanese Society of Hospital General Medicine. Participants This study included patients ≥18 years diagnosed with ‘classical fever of unknown origin’ (axillary temperature ≥38°C at least twice over a ≥3-week period without elucidation of a cause at three outpatient visits or during 3 days of hospitalisation) between January and December 2011. Results A total of 121 patients with FUO were enrolled. The median age was 59 years (range 19–94 years). Causative diseases were infectious disease in 28 patients (23.1%), non-infectious inflammatory disease in 37 (30.6%), malignancy in 13 (10.7%), other in 15 (12.4%) and unknown in 28 (23.1%). The median interval from fever onset to evaluation at each hospital was 28 days. The longest time required for diagnosis involved a case of familial Mediterranean fever. Tests performed included blood cultures in 86.8%, serum procalcitonin in 43.8% and positron emission tomography in 29.8% of patients. Conclusions With the widespread use of CT, FUO due to deep-seated abscess or solid tumour is decreasing markedly. Owing to the influence of the ageing population, polymyalgia rheumatica was the most frequent cause (9 patients). Four patients had FUO associated with HIV/AIDS, an important cause of FUO in Japan. In a relatively small number of cases, cause remained unclear. This may have been due to bias inherent in a retrospective study. This study identified diseases that should be considered in the differential diagnosis of FUO. PMID:24362014

Model-free adaptive sliding mode controller design for generalized projective synchronization of the fractional-order chaotic system via radial basis function neural networks

NASA Astrophysics Data System (ADS)

Wang, L. M.

2017-09-01

A novel model-free adaptive sliding mode strategy is proposed for a generalized projective synchronization (GPS) between two entirely unknown fractional-order chaotic systems subject to the external disturbances. To solve the difficulties from the little knowledge about the master-slave system and to overcome the bad effects of the external disturbances on the generalized projective synchronization, the radial basis function neural networks are used to approach the packaged unknown master system and the packaged unknown slave system (including the external disturbances). Consequently, based on the slide mode technology and the neural network theory, a model-free adaptive sliding mode controller is designed to guarantee asymptotic stability of the generalized projective synchronization error. The main contribution of this paper is that a control strategy is provided for the generalized projective synchronization between two entirely unknown fractional-order chaotic systems subject to the unknown external disturbances, and the proposed control strategy only requires that the master system has the same fractional orders as the slave system. Moreover, the proposed method allows us to achieve all kinds of generalized projective chaos synchronizations by turning the user-defined parameters onto the desired values. Simulation results show the effectiveness of the proposed method and the robustness of the controlled system.

Approximation-based adaptive tracking control of pure-feedback nonlinear systems with multiple unknown time-varying delays.

PubMed

Wang, Min; Ge, Shuzhi Sam; Hong, Keum-Shik

2010-11-01

This paper presents adaptive neural tracking control for a class of non-affine pure-feedback systems with multiple unknown state time-varying delays. To overcome the design difficulty from non-affine structure of pure-feedback system, mean value theorem is exploited to deduce affine appearance of state variables x(i) as virtual controls α(i), and of the actual control u. The separation technique is introduced to decompose unknown functions of all time-varying delayed states into a series of continuous functions of each delayed state. The novel Lyapunov-Krasovskii functionals are employed to compensate for the unknown functions of current delayed state, which is effectively free from any restriction on unknown time-delay functions and overcomes the circular construction of controller caused by the neural approximation of a function of u and [Formula: see text] . Novel continuous functions are introduced to overcome the design difficulty deduced from the use of one adaptive parameter. To achieve uniformly ultimate boundedness of all the signals in the closed-loop system and tracking performance, control gains are effectively modified as a dynamic form with a class of even function, which makes stability analysis be carried out at the present of multiple time-varying delays. Simulation studies are provided to demonstrate the effectiveness of the proposed scheme.

A Real-Time Reaction Obstacle Avoidance Algorithm for Autonomous Underwater Vehicles in Unknown Environments

PubMed Central

Yan, Zheping; Li, Jiyun; Zhang, Gengshi; Wu, Yi

2018-01-01

A novel real-time reaction obstacle avoidance algorithm (RRA) is proposed for autonomous underwater vehicles (AUVs) that must adapt to unknown complex terrains, based on forward looking sonar (FLS). To accomplish this algorithm, obstacle avoidance rules are planned, and the RRA processes are split into five steps Introduction only lists 4 so AUVs can rapidly respond to various environment obstacles. The largest polar angle algorithm (LPAA) is designed to change detected obstacle’s irregular outline into a convex polygon, which simplifies the obstacle avoidance process. A solution is designed to solve the trapping problem existing in U-shape obstacle avoidance by an outline memory algorithm. Finally, simulations in three unknown obstacle scenes are carried out to demonstrate the performance of this algorithm, where the obtained obstacle avoidance trajectories are safety, smooth and near-optimal. PMID:29393915

A Real-Time Reaction Obstacle Avoidance Algorithm for Autonomous Underwater Vehicles in Unknown Environments.

PubMed

Yan, Zheping; Li, Jiyun; Zhang, Gengshi; Wu, Yi

2018-02-02

A novel real-time reaction obstacle avoidance algorithm (RRA) is proposed for autonomous underwater vehicles (AUVs) that must adapt to unknown complex terrains, based on forward looking sonar (FLS). To accomplish this algorithm, obstacle avoidance rules are planned, and the RRA processes are split into five steps Introduction only lists 4 so AUVs can rapidly respond to various environment obstacles. The largest polar angle algorithm (LPAA) is designed to change detected obstacle's irregular outline into a convex polygon, which simplifies the obstacle avoidance process. A solution is designed to solve the trapping problem existing in U-shape obstacle avoidance by an outline memory algorithm. Finally, simulations in three unknown obstacle scenes are carried out to demonstrate the performance of this algorithm, where the obtained obstacle avoidance trajectories are safety, smooth and near-optimal.

Teleporting an unknown quantum state with unit fidelity and unit probability via a non-maximally entangled channel and an auxiliary system

NASA Astrophysics Data System (ADS)

Rashvand, Taghi

2016-11-01

We present a new scheme for quantum teleportation that one can teleport an unknown state via a non-maximally entangled channel with certainly, using an auxiliary system. In this scheme depending on the state of the auxiliary system, one can find a class of orthogonal vectors set as a basis which by performing von Neumann measurement in each element of this class Alice can teleport an unknown state with unit fidelity and unit probability. A comparison of our scheme with some previous schemes is given and we will see that our scheme has advantages that the others do not.

Launching the dialogue: Safety and innovation as partners for success in advanced manufacturing.

PubMed

Geraci, C L; Tinkle, S S; Brenner, S A; Hodson, L L; Pomeroy-Carter, C A; Neu-Baker, N

2018-06-01

Emerging and novel technologies, materials, and information integrated into increasingly automated and networked manufacturing processes or into traditional manufacturing settings are enhancing the efficiency and productivity of manufacturing. Globally, there is a move toward a new era in manufacturing that is characterized by: (1) the ability to create and deliver more complex designs of products; (2) the creation and use of materials with new properties that meet a design need; (3) the employment of new technologies, such as additive and digital techniques that improve on conventional manufacturing processes; and (4) a compression of the time from initial design concept to the creation of a final product. Globally, this movement has many names, but "advanced manufacturing" has become the shorthand for this complex integration of material and technology elements that enable new ways to manufacture existing products, as well as new products emerging from new technologies and new design methods. As the breadth of activities associated with advanced manufacturing suggests, there is no single advanced manufacturing industry. Instead, aspects of advanced manufacturing can be identified across a diverse set of business sectors that use manufacturing technologies, ranging from the semiconductors and electronics to the automotive and pharmaceutical industries. The breadth and diversity of advanced manufacturing may change the occupational and environmental risk profile, challenge the basic elements of comprehensive health and safety (material, process, worker, environment, product, and general public health and safety), and provide an opportunity for development and dissemination of occupational and environmental health and safety (OEHS) guidance and best practices. It is unknown how much the risk profile of different elements of OEHS will change, thus requiring an evolution of health and safety practices. These changes may be accomplished most effectively through multi-disciplinary, multi-sector, public-private dialogue that identifies issues and offers solutions.

An Alternative to the Physiological Psychology Laboratory: Identification of an Unknown Drug Through Behavioral Testing.

ERIC Educational Resources Information Center

Schumacher, Susan J.

1982-01-01

A laboratory project introduced physiological psychology students to research by requiring them to identify an unknown drug given to laboratory animals. Students read material about drugs and animal drug studies, designed behavioral tests, constructed the testing apparatus, conducted the tests, and wrote progress reports. (SR)

Approximation-Based Adaptive Neural Tracking Control of Nonlinear MIMO Unknown Time-Varying Delay Systems With Full State Constraints.

PubMed

Li, Da-Peng; Li, Dong-Juan; Liu, Yan-Jun; Tong, Shaocheng; Chen, C L Philip

2017-10-01

This paper deals with the tracking control problem for a class of nonlinear multiple input multiple output unknown time-varying delay systems with full state constraints. To overcome the challenges which cause by the appearances of the unknown time-varying delays and full-state constraints simultaneously in the systems, an adaptive control method is presented for such systems for the first time. The appropriate Lyapunov-Krasovskii functions and a separation technique are employed to eliminate the effect of unknown time-varying delays. The barrier Lyapunov functions are employed to prevent the violation of the full state constraints. The singular problems are dealt with by introducing the signal function. Finally, it is proven that the proposed method can both guarantee the good tracking performance of the systems output, all states are remained in the constrained interval and all the closed-loop signals are bounded in the design process based on choosing appropriate design parameters. The practicability of the proposed control technique is demonstrated by a simulation study in this paper.

Experimental Design for Estimating Unknown Hydraulic Conductivity in a Confined Aquifer using a Genetic Algorithm and a Reduced Order Model

NASA Astrophysics Data System (ADS)

Ushijima, T.; Yeh, W.

2013-12-01

An optimal experimental design algorithm is developed to select locations for a network of observation wells that provides the maximum information about unknown hydraulic conductivity in a confined, anisotropic aquifer. The design employs a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. Because that the formulated problem is non-convex and contains integer variables (necessitating a combinatorial search), for a realistically-scaled model, the problem may be difficult, if not impossible, to solve through traditional mathematical programming techniques. Genetic Algorithms (GAs) are designed to search out the global optimum; however because a GA requires a large number of calls to a groundwater model, the formulated optimization problem may still be infeasible to solve. To overcome this, Proper Orthogonal Decomposition (POD) is applied to the groundwater model to reduce its dimension. The information matrix in the full model space can then be searched without solving the full model.

Machine learning-based patient specific prompt-gamma dose monitoring in proton therapy

NASA Astrophysics Data System (ADS)

Gueth, P.; Dauvergne, D.; Freud, N.; Létang, J. M.; Ray, C.; Testa, E.; Sarrut, D.

2013-07-01

Online dose monitoring in proton therapy is currently being investigated with prompt-gamma (PG) devices. PG emission was shown to be correlated with dose deposition. This relationship is mostly unknown under real conditions. We propose a machine learning approach based on simulations to create optimized treatment-specific classifiers that detect discrepancies between planned and delivered dose. Simulations were performed with the Monte-Carlo platform Gate/Geant4 for a spot-scanning proton therapy treatment and a PG camera prototype currently under investigation. The method first builds a learning set of perturbed situations corresponding to a range of patient translation. This set is then used to train a combined classifier using distal falloff and registered correlation measures. Classifier performances were evaluated using receiver operating characteristic curves and maximum associated specificity and sensitivity. A leave-one-out study showed that it is possible to detect discrepancies of 5 mm with specificity and sensitivity of 85% whereas using only distal falloff decreases the sensitivity down to 77% on the same data set. The proposed method could help to evaluate performance and to optimize the design of PG monitoring devices. It is generic: other learning sets of deviations, other measures and other types of classifiers could be studied to potentially reach better performance. At the moment, the main limitation lies in the computation time needed to perform the simulations.

Systematic Review of Service-Learning in Youth Physical Activity Settings

ERIC Educational Resources Information Center

Carson, Russell L.; Raguse, Allison L.

2014-01-01

The extent to which service-learning exists in the field of kinesiology broadly, and more specifically related to the physical activity of youth, remains largely unknown. The purpose of this study was to conduct a systematic review of the service-learning literature in kinesiology, with a specific focus on youth physical activity settings.…

Subitizing Reflects Visuo-Spatial Object Individuation Capacity

ERIC Educational Resources Information Center

Piazza, Manuela; Fumarola, Antonia; Chinello, Alessandro; Melcher, David

2011-01-01

Subitizing is the immediate apprehension of the exact number of items in small sets. Despite more than a 100 years of research around this phenomenon, its nature and origin are still unknown. One view posits that it reflects a number estimation process common for small and large sets, which precision decreases as the number of items increases,…

Factors That May Explain Differences between Home and Clinic Meal Preparation Task Assessments in Frail Older Adults

ERIC Educational Resources Information Center

Provencher, Veronique; Demers, Louise; Gelinas, Isabelle

2012-01-01

Meal preparation assessments conducted in clinical environments (such as rehabilitation settings) might not reflect frail patients' performance at home. In addition, factors that may explain differences in performance between settings remain unknown. The aim of this study was to compare home and clinic performance on meal preparation tasks in…

The Inverse Bagging Algorithm: Anomaly Detection by Inverse Bootstrap Aggregating

NASA Astrophysics Data System (ADS)

Vischia, Pietro; Dorigo, Tommaso

2017-03-01

For data sets populated by a very well modeled process and by another process of unknown probability density function (PDF), a desired feature when manipulating the fraction of the unknown process (either for enhancing it or suppressing it) consists in avoiding to modify the kinematic distributions of the well modeled one. A bootstrap technique is used to identify sub-samples rich in the well modeled process, and classify each event according to the frequency of it being part of such sub-samples. Comparisons with general MVA algorithms will be shown, as well as a study of the asymptotic properties of the method, making use of a public domain data set that models a typical search for new physics as performed at hadronic colliders such as the Large Hadron Collider (LHC).

Direct Adaptive Control of Systems with Actuator Failures: State of the Art and Continuing Challenges

NASA Technical Reports Server (NTRS)

Tao, Gang; Joshi, Suresh M.

2008-01-01

In this paper, the problem of controlling systems with failures and faults is introduced, and an overview of recent work on direct adaptive control for compensation of uncertain actuator failures is presented. Actuator failures may be characterized by some unknown system inputs being stuck at some unknown (fixed or varying) values at unknown time instants, that cannot be influenced by the control signals. The key task of adaptive compensation is to design the control signals in such a manner that the remaining actuators can automatically and seamlessly take over for the failed ones, and achieve desired stability and asymptotic tracking. A certain degree of redundancy is necessary to accomplish failure compensation. The objective of adaptive control design is to effectively use the available actuation redundancy to handle failures without the knowledge of the failure patterns, parameters, and time of occurrence. This is a challenging problem because failures introduce large uncertainties in the dynamic structure of the system, in addition to parametric uncertainties and unknown disturbances. The paper addresses some theoretical issues in adaptive actuator failure compensation: actuator failure modeling, redundant actuation requirements, plant-model matching, error system dynamics, adaptation laws, and stability, tracking, and performance analysis. Adaptive control designs can be shown to effectively handle uncertain actuator failures without explicit failure detection. Some open technical challenges and research problems in this important research area are discussed.

Meteor showers of the southern hemisphere

NASA Astrophysics Data System (ADS)

Molau, Sirko; Kerr, Steve

2014-04-01

We present the results of an exhaustive meteor shower search in the southern hemisphere. The underlying data set is a subset of the IMO Video Meteor Database comprising 50,000 single station meteors obtained by three Australian cameras between 2001 and 2012. The detection technique was similar to previous single station analysis. In the data set we find 4 major and 6 minor northern hemisphere meteor showers, and 12 segments of the Antihelion source (including the Northern and Southern Taurids and six streams from the MDC working list). We present details for 14 southern hemisphere showers plus the Centaurid and Puppid-Velid complex, with the η Aquariids and the Southern δ Aquariids being the strongest southern showers. Two of the showers (θ^2 Sagittariids and τ Cetids) were previously unknown and have received preliminary designations by the MDC. Overall we find that the fraction of southern meteor showers south of -30deg declination (roughly 25%) is clearly smaller than the fraction of northern meteor showers north of +30deg declination (more than 50%) obtained in our previous analysis.

Towards a hybrid energy efficient multi-tree-based optimized routing protocol for wireless networks.

PubMed

Mitton, Nathalie; Razafindralambo, Tahiry; Simplot-Ryl, David; Stojmenovic, Ivan

2012-12-13

This paper considers the problem of designing power efficient routing with guaranteed delivery for sensor networks with unknown geographic locations. We propose HECTOR, a hybrid energy efficient tree-based optimized routing protocol, based on two sets of virtual coordinates. One set is based on rooted tree coordinates, and the other is based on hop distances toward several landmarks. In HECTOR, the node currently holding the packet forwards it to its neighbor that optimizes ratio of power cost over distance progress with landmark coordinates, among nodes that reduce landmark coordinates and do not increase distance in tree coordinates. If such a node does not exist, then forwarding is made to the neighbor that reduces tree-based distance only and optimizes power cost over tree distance progress ratio. We theoretically prove the packet delivery and propose an extension based on the use of multiple trees. Our simulations show the superiority of our algorithm over existing alternatives while guaranteeing delivery, and only up to 30% additional power compared to centralized shortest weighted path algorithm.

Towards a Hybrid Energy Efficient Multi-Tree-Based Optimized Routing Protocol for Wireless Networks

PubMed Central

Mitton, Nathalie; Razafindralambo, Tahiry; Simplot-Ryl, David; Stojmenovic, Ivan

2012-01-01

This paper considers the problem of designing power efficient routing with guaranteed delivery for sensor networks with unknown geographic locations. We propose HECTOR, a hybrid energy efficient tree-based optimized routing protocol, based on two sets of virtual coordinates. One set is based on rooted tree coordinates, and the other is based on hop distances toward several landmarks. In HECTOR, the node currently holding the packet forwards it to its neighbor that optimizes ratio of power cost over distance progress with landmark coordinates, among nodes that reduce landmark coordinates and do not increase distance in tree coordinates. If such a node does not exist, then forwarding is made to the neighbor that reduces tree-based distance only and optimizes power cost over tree distance progress ratio. We theoretically prove the packet delivery and propose an extension based on the use of multiple trees. Our simulations show the superiority of our algorithm over existing alternatives while guaranteeing delivery, and only up to 30% additional power compared to centralized shortest weighted path algorithm. PMID:23443398

Statistically Optimized Inversion Algorithm for Enhanced Retrieval of Aerosol Properties from Spectral Multi-Angle Polarimetric Satellite Observations

NASA Technical Reports Server (NTRS)

Dubovik, O; Herman, M.; Holdak, A.; Lapyonok, T.; Taure, D.; Deuze, J. L.; Ducos, F.; Sinyuk, A.

2011-01-01

The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL microsatellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation.

Self-evaluation on Motion Adaptation for Service Robots

NASA Astrophysics Data System (ADS)

Funabora, Yuki; Yano, Yoshikazu; Doki, Shinji; Okuma, Shigeru

We suggest self motion evaluation method to adapt to environmental changes for service robots. Several motions such as walking, dancing, demonstration and so on are described with time series patterns. These motions are optimized with the architecture of the robot and under certain surrounding environment. Under unknown operating environment, robots cannot accomplish their tasks. We propose autonomous motion generation techniques based on heuristic search with histories of internal sensor values. New motion patterns are explored under unknown operating environment based on self-evaluation. Robot has some prepared motions which realize the tasks under the designed environment. Internal sensor values observed under the designed environment with prepared motions show the interaction results with the environment. Self-evaluation is composed of difference of internal sensor values between designed environment and unknown operating environment. Proposed method modifies the motions to synchronize the interaction results on both environment. New motion patterns are generated to maximize self-evaluation function without external information, such as run length, global position of robot, human observation and so on. Experimental results show that the possibility to adapt autonomously patterned motions to environmental changes.

Optimally setting up directed searches for continuous gravitational waves in Advanced LIGO O1 data

NASA Astrophysics Data System (ADS)

Ming, Jing; Papa, Maria Alessandra; Krishnan, Badri; Prix, Reinhard; Beer, Christian; Zhu, Sylvia J.; Eggenstein, Heinz-Bernd; Bock, Oliver; Machenschalk, Bernd

2018-02-01

In this paper we design a search for continuous gravitational waves from three supernova remnants: Vela Jr., Cassiopeia A (Cas A) and G347.3. These systems might harbor rapidly rotating neutron stars emitting quasiperiodic gravitational radiation detectable by the advanced LIGO detectors. Our search is designed to use the volunteer computing project Einstein@Home for a few months and assumes the sensitivity and duty cycles of the advanced LIGO detectors during their first science run. For all three supernova remnants, the sky positions of their central compact objects are well known but the frequency and spin-down rates of the neutron stars are unknown which makes the searches computationally limited. In a previous paper we have proposed a general framework for deciding on what target we should spend computational resources and in what proportion, what frequency and spin-down ranges we should search for every target, and with what search setup. Here we further expand this framework and apply it to design a search directed at detecting continuous gravitational wave signals from the most promising three supernova remnants identified as such in the previous work. Our optimization procedure yields broad frequency and spin-down searches for all three objects, at an unprecedented level of sensitivity: The smallest detectable gravitational wave strain h0 for Cas A is expected to be 2 times smaller than the most sensitive upper limits published to date, and our proposed search, which was set up and ran on the volunteer computing project Einstein@Home, covers a much larger frequency range.

Sliding Mode Observer-Based Current Sensor Fault Reconstruction and Unknown Load Disturbance Estimation for PMSM Driven System.

PubMed

Zhao, Kaihui; Li, Peng; Zhang, Changfan; Li, Xiangfei; He, Jing; Lin, Yuliang

2017-12-06

This paper proposes a new scheme of reconstructing current sensor faults and estimating unknown load disturbance for a permanent magnet synchronous motor (PMSM)-driven system. First, the original PMSM system is transformed into two subsystems; the first subsystem has unknown system load disturbances, which are unrelated to sensor faults, and the second subsystem has sensor faults, but is free from unknown load disturbances. Introducing a new state variable, the augmented subsystem that has sensor faults can be transformed into having actuator faults. Second, two sliding mode observers (SMOs) are designed: the unknown load disturbance is estimated by the first SMO in the subsystem, which has unknown load disturbance, and the sensor faults can be reconstructed using the second SMO in the augmented subsystem, which has sensor faults. The gains of the proposed SMOs and their stability analysis are developed via the solution of linear matrix inequality (LMI). Finally, the effectiveness of the proposed scheme was verified by simulations and experiments. The results demonstrate that the proposed scheme can reconstruct current sensor faults and estimate unknown load disturbance for the PMSM-driven system.

Adaptive Fault-Tolerant Control of Uncertain Nonlinear Large-Scale Systems With Unknown Dead Zone.

PubMed

Chen, Mou; Tao, Gang

2016-08-01

In this paper, an adaptive neural fault-tolerant control scheme is proposed and analyzed for a class of uncertain nonlinear large-scale systems with unknown dead zone and external disturbances. To tackle the unknown nonlinear interaction functions in the large-scale system, the radial basis function neural network (RBFNN) is employed to approximate them. To further handle the unknown approximation errors and the effects of the unknown dead zone and external disturbances, integrated as the compounded disturbances, the corresponding disturbance observers are developed for their estimations. Based on the outputs of the RBFNN and the disturbance observer, the adaptive neural fault-tolerant control scheme is designed for uncertain nonlinear large-scale systems by using a decentralized backstepping technique. The closed-loop stability of the adaptive control system is rigorously proved via Lyapunov analysis and the satisfactory tracking performance is achieved under the integrated effects of unknown dead zone, actuator fault, and unknown external disturbances. Simulation results of a mass-spring-damper system are given to illustrate the effectiveness of the proposed adaptive neural fault-tolerant control scheme for uncertain nonlinear large-scale systems.

Using Conductivity Measurements to Determine the Identities and Concentrations of Unknown Acids: An Inquiry Laboratory Experiment

ERIC Educational Resources Information Center

Smith, K. Christopher; Garza, Ariana

2015-01-01

This paper describes a student designed experiment using titrations involving conductivity measurements to identify unknown acids as being either HCl or H[subscript 2]SO[subscript 4], and to determine the concentrations of the acids, thereby improving the utility of standard acid-base titrations. Using an inquiry context, students gain experience…

Market-Based Coordination of Thermostatically Controlled Loads—Part II: Unknown Parameters and Case Studies

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

Li, Sen; Zhang, Wei; Lian, Jianming

This two-part paper considers the coordination of a population of Thermostatically Controlled Loads (TCLs) with unknown parameters to achieve group objectives. The problem involves designing the bidding and market clearing strategy to motivate self-interested users to realize efficient energy allocation subject to a peak power constraint. The companion paper (Part I) formulates the problem and proposes a load coordination framework using the mechanism design approach. To address the unknown parameters, Part II of this paper presents a joint state and parameter estimation framework based on the expectation maximization algorithm. The overall framework is then validated using real-world weather data andmore » price data, and is compared with other approaches in terms of aggregated power response. Simulation results indicate that our coordination framework can effectively improve the efficiency of the power grid operations and reduce power congestion at key times.« less

Development of a GC/Quadrupole-Orbitrap Mass Spectrometer, Part I: Design and Characterization

PubMed Central

2015-01-01

Identification of unknown compounds is of critical importance in GC/MS applications (metabolomics, environmental toxin identification, sports doping, petroleomics, and biofuel analysis, among many others) and remains a technological challenge. Derivation of elemental composition is the first step to determining the identity of an unknown compound by MS, for which high accuracy mass and isotopomer distribution measurements are critical. Here, we report on the development of a dedicated, applications-grade GC/MS employing an Orbitrap mass analyzer, the GC/Quadrupole-Orbitrap. Built from the basis of the benchtop Orbitrap LC/MS, the GC/Quadrupole-Orbitrap maintains the performance characteristics of the Orbitrap, enables quadrupole-based isolation for sensitive analyte detection, and includes numerous analysis modalities to facilitate structural elucidation. We detail the design and construction of the instrument, discuss its key figures-of-merit, and demonstrate its performance for the characterization of unknown compounds and environmental toxins. PMID:25208235

An evaluation of open set recognition for FLIR images

NASA Astrophysics Data System (ADS)

Scherreik, Matthew; Rigling, Brian

2015-05-01

Typical supervised classification algorithms label inputs according to what was learned in a training phase. Thus, test inputs that were not seen in training are always given incorrect labels. Open set recognition algorithms address this issue by accounting for inputs that are not present in training and providing the classifier with an option to reject" unknown samples. A number of such techniques have been developed in the literature, many of which are based on support vector machines (SVMs). One approach, the 1-vs-set machine, constructs a slab" in feature space using the SVM hyperplane. Inputs falling on one side of the slab or within the slab belong to a training class, while inputs falling on the far side of the slab are rejected. We note that rejection of unknown inputs can be achieved by thresholding class posterior probabilities. Another recently developed approach, the Probabilistic Open Set SVM (POS-SVM), empirically determines good probability thresholds. We apply the 1-vs-set machine, POS-SVM, and closed set SVMs to FLIR images taken from the Comanche SIG dataset. Vehicles in the dataset are divided into three general classes: wheeled, armored personnel carrier (APC), and tank. For each class, a coarse pose estimate (front, rear, left, right) is taken. In a closed set sense, we analyze these algorithms for prediction of vehicle class and pose. To test open set performance, one or more vehicle classes are held out from training. By considering closed and open set performance separately, we may closely analyze both inter-class discrimination and threshold effectiveness.

Parametric system identification of catamaran for improving controller design

NASA Astrophysics Data System (ADS)

Timpitak, Surasak; Prempraneerach, Pradya; Pengwang, Eakkachai

2018-01-01

This paper presents an estimation of simplified dynamic model for only surge- and yaw- motions of catamaran by using system identification (SI) techniques to determine associated unknown parameters. These methods will enhance the performance of designing processes for the motion control system of Unmanned Surface Vehicle (USV). The simulation results demonstrate an effective way to solve for damping forces and to determine added masses by applying least-square and AutoRegressive Exogenous (ARX) methods. Both methods are then evaluated according to estimated parametric errors from the vehicle’s dynamic model. The ARX method, which yields better estimated accuracy, can then be applied to identify unknown parameters as well as to help improving a controller design of a real unmanned catamaran.

Supervised Detection of Anomalous Light Curves in Massive Astronomical Catalogs

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

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

Nun, Isadora; Pichara, Karim; Protopapas, Pavlos

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

Active vibration control for piezoelectricity cantilever beam: an adaptive feedforward control method

NASA Astrophysics Data System (ADS)

Zhu, Qiao; Yue, Jun-Zhou; Liu, Wei-Qun; Wang, Xu-Dong; Chen, Jun; Hu, Guang-Di

2017-04-01

This work is focused on the active vibration control of piezoelectric cantilever beam, where an adaptive feedforward controller (AFC) is utilized to reject the vibration with unknown multiple frequencies. First, the experiment setup and its mathematical model are introduced. Due to that the channel between the disturbance and the vibration output is unknown in practice, a concept of equivalent input disturbance (EID) is employed to put an equivalent disturbance into the input channel. In this situation, the vibration control can be achieved by setting the control input be the identified EID. Then, for the EID with known multiple frequencies, the AFC is introduced to perfectly reject the vibration but is sensitive to the frequencies. In order to accurately identify the unknown frequencies of EID in presence of the random disturbances and un-modeled nonlinear dynamics, the time-frequency-analysis (TFA) method is employed to precisely identify the unknown frequencies. Consequently, a TFA-based AFC algorithm is proposed to the active vibration control with unknown frequencies. Finally, four cases are given to illustrate the efficiency of the proposed TFA-based AFC algorithm by experiment.

Trust, but Verify: Standard Setting That Honors and Validates Professional Teacher Judgment. Subtitle: A Tenuous Titanic Tale of Testy Testing and Titillating Touchstones (A Screen Play with an Unknown Number of Acts).

ERIC Educational Resources Information Center

Matter, M. Kevin

The Cherry Creek School district (Englewood, Colorado) is a growing district of 37,000 students in the Denver area. The 1988 Colorado State School Finance Act required district-set proficiencies (standards), and forced agreement on a set of values for student knowledge and skills. State-adopted standards added additional requirements for the…

The Emergence of an Amplified Mindset of Design: Implications for Postgraduate Design Education

ERIC Educational Resources Information Center

Moreira, Mafalda; Murphy, Emma; McAra-McWilliam, Irene

2016-01-01

In a global scenario of complexity, research shows that emerging design practices are changing and expanding, creating a complex and ambiguous disciplinary landscape. This directly impacts on the field of design education, calling for new, flexible models able to tackle future practitioners' needs, unknown markets and emergent societal cultures.…

A Bayesian Retrieval of Greenland Ice Sheet Internal Temperature from Ultra-wideband Software-defined Microwave Radiometer (UWBRAD) Measurements

NASA Astrophysics Data System (ADS)

Duan, Y.; Durand, M. T.; Jezek, K. C.; Yardim, C.; Bringer, A.; Aksoy, M.; Johnson, J. T.

2017-12-01

The ultra-wideband software-defined microwave radiometer (UWBRAD) is designed to provide ice sheet internal temperature product via measuring low frequency microwave emission. Twelve channels ranging from 0.5 to 2.0 GHz are covered by the instrument. A Greenland air-borne demonstration was demonstrated in September 2016, provided first demonstration of Ultra-wideband radiometer observations of geophysical scenes, including ice sheets. Another flight is planned for September 2017 for acquiring measurements in central ice sheet. A Bayesian framework is designed to retrieve the ice sheet internal temperature from simulated UWBRAD brightness temperature (Tb) measurements over Greenland flight path with limited prior information of the ground. A 1-D heat-flow model, the Robin Model, was used to model the ice sheet internal temperature profile with ground information. Synthetic UWBRAD Tb observations was generated via the partially coherent radiation transfer model, which utilizes the Robin model temperature profile and an exponential fit of ice density from Borehole measurement as input, and corrupted with noise. The effective surface temperature, geothermal heat flux, the variance of upper layer ice density, and the variance of fine scale density variation at deeper ice sheet were treated as unknown variables within the retrieval framework. Each parameter is defined with its possible range and set to be uniformly distributed. The Markov Chain Monte Carlo (MCMC) approach is applied to make the unknown parameters randomly walk in the parameter space. We investigate whether the variables can be improved over priors using the MCMC approach and contribute to the temperature retrieval theoretically. UWBRAD measurements near camp century from 2016 was also treated with the MCMC to examine the framework with scattering effect. The fine scale density fluctuation is an important parameter. It is the most sensitive yet highly unknown parameter in the estimation framework. Including the fine scale density fluctuation greatly improved the retrieval results. The ice sheet vertical temperature profile, especially the 10m temperature, can be well retrieved via the MCMC process. Future retrieval work will apply the Bayesian approach to UWBRAD airborne measurements.

SYNTHESIS OF NOVEL ALL-DIELECTRIC GRATING FILTERS USING GENETIC ALGORITHMS

NASA Technical Reports Server (NTRS)

Zuffada, Cinzia; Cwik, Tom; Ditchman, Christopher

1997-01-01

We are concerned with the design of inhomogeneous, all dielectric (lossless) periodic structures which act as filters. Dielectric filters made as stacks of inhomogeneous gratings and layers of materials are being used in optical technology, but are not common at microwave frequencies. The problem is then finding the periodic cell's geometric configuration and permittivity values which correspond to a specified reflectivity/transmittivity response as a function of frequency/illumination angle. This type of design can be thought of as an inverse-source problem, since it entails finding a distribution of sources which produce fields (or quantities derived from them) of given characteristics. Electromagnetic sources (electric and magnetic current densities) in a volume are related to the outside fields by a well known linear integral equation. Additionally, the sources are related to the fields inside the volume by a constitutive equation, involving the material properties. Then, the relationship linking the fields outside the source region to those inside is non-linear, in terms of material properties such as permittivity, permeability and conductivity. The solution of the non-linear inverse problem is cast here as a combination of two linear steps, by explicitly introducing the electromagnetic sources in the computational volume as a set of unknowns in addition to the material unknowns. This allows to solve for material parameters and related electric fields in the source volume which are consistent with Maxwell's equations. Solutions are obtained iteratively by decoupling the two steps. First, we invert for the permittivity only in the minimization of a cost function and second, given the materials, we find the corresponding electric fields through direct solution of the integral equation in the source volume. The sources thus computed are used to generate the far fields and the synthesized triter response. The cost function is obtained by calculating the deviation between the synthesized value of reflectivity/transmittivity and the desired one. Solution geometries for the periodic cell are sought as gratings (ensembles of columns of different heights and widths), or combinations of homogeneous layers of different dielectric materials and gratings. Hence the explicit unknowns of the inversion step are the material permittivities and the relative boundaries separating homogeneous parcels of the periodic cell.

Supervising athletic trainers' perceptions of professional socialization of graduate assistant athletic trainers in the collegiate setting.

PubMed

Thrasher, Ashley B; Walker, Stacy E; Hankemeier, Dorice A; Pitney, William A

2015-03-01

Many newly credentialed athletic trainers gain initial employment as graduate assistants (GAs) in the collegiate setting, yet their socialization into their role is unknown. Exploring the socialization process of GAs in the collegiate setting could provide insight into how that process occurs. To explore the professional socialization of GAs in the collegiate setting to determine how GAs are socialized and developed as athletic trainers. Qualitative study. Individual phone interviews. Athletic trainers (N = 21) who had supervised GAs in the collegiate setting for a minimum of 8 years (16 men [76%], 5 women [24%]; years of supervision experience = 14.6 ± 6.6). Data were collected via phone interviews, which were recorded and transcribed verbatim. Data were analyzed by a 4-person consensus team with a consensual qualitative-research design. The team independently coded the data and compared ideas until a consensus was reached, and a codebook was created. Trustworthiness was established through member checks and multianalyst triangulation. Four themes emerged: (1) role orientation, (2) professional development and support, (3) role expectations, and (4) success. Role orientation occurred both formally (eg, review of policies and procedures) and informally (eg, immediate role immersion). Professional development and support consisted of the supervisor mentoring and intervening when appropriate. Role expectations included decision-making ability, independent practice, and professionalism; however, supervisors often expected GAs to function as experienced, full-time staff. Success of the GAs depended on their adaptability and on the proper selection of GAs by supervisors. Supervisors socialize GAs into the collegiate setting by providing orientation, professional development, mentoring, and intervention when necessary. Supervisors are encouraged to use these socialization tactics to enhance the professional development of GAs in the collegiate setting.

[Study on discrimination of varieties of fire resistive coating for steel structure based on near-infrared spectroscopy].

PubMed

Xue, Gang; Song, Wen-qi; Li, Shu-chao

2015-01-01

In order to achieve the rapid identification of fire resistive coating for steel structure of different brands in circulating, a new method for the fast discrimination of varieties of fire resistive coating for steel structure by means of near infrared spectroscopy was proposed. The raster scanning near infrared spectroscopy instrument and near infrared diffuse reflectance spectroscopy were applied to collect the spectral curve of different brands of fire resistive coating for steel structure and the spectral data were preprocessed with standard normal variate transformation(standard normal variate transformation, SNV) and Norris second derivative. The principal component analysis (principal component analysis, PCA)was used to near infrared spectra for cluster analysis. The analysis results showed that the cumulate reliabilities of PC1 to PC5 were 99. 791%. The 3-dimentional plot was drawn with the scores of PC1, PC2 and PC3 X 10, which appeared to provide the best clustering of the varieties of fire resistive coating for steel structure. A total of 150 fire resistive coating samples were divided into calibration set and validation set randomly, the calibration set had 125 samples with 25 samples of each variety, and the validation set had 25 samples with 5 samples of each variety. According to the principal component scores of unknown samples, Mahalanobis distance values between each variety and unknown samples were calculated to realize the discrimination of different varieties. The qualitative analysis model for external verification of unknown samples is a 10% recognition ration. The results demonstrated that this identification method can be used as a rapid, accurate method to identify the classification of fire resistive coating for steel structure and provide technical reference for market regulation.

Assessing disease severity: accuracy and reliability of rater estimates in relation to number of diagrams in a standard area diagram set

USDA-ARS?s Scientific Manuscript database

Error in rater estimates of plant disease severity occur, and standard area diagrams (SADs) help improve accuracy and reliability. The effects of diagram number in a SAD set on accuracy and reliability is unknown. The objective of this study was to compare estimates of pecan scab severity made witho...

Does Context Matter? An Analysis of Training in Multicultural Assessment, Consultation, and Intervention between School Psychologists in Urban and Rural Contexts

ERIC Educational Resources Information Center

Newell, Markeda; Looser, Joshua

2018-01-01

The purpose of this study was to analyze the extent of training in multicultural assessment, intervention, and consultation of school psychologists in urban and rural contexts. Although there is greater cultural and sociodemographic diversity in urban settings as compared to rural settings, it is unknown whether school psychologists in urban…

Effects of Interventions Based in Behavior Analysis on Motor Skill Acquisition: A Meta-Analysis

ERIC Educational Resources Information Center

Alstot, Andrew E.; Kang, Minsoo; Alstot, Crystal D.

2013-01-01

Techniques based in applied behavior analysis (ABA) have been shown to be useful across a variety of settings to improve numerous behaviors. Specifically within physical activity settings, several studies have examined the effect of interventions based in ABA on a variety of motor skills, but the overall effects of these interventions are unknown.…

Aerosols and Clouds: In Cahoots to Change Climate

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

Berg, Larry

Key knowledge gaps persist despite advances in the scientific understanding of how aerosols and clouds evolve and affect climate. The Two-Column Aerosol Project, or TCAP, was designed to provide a detailed set of observations to tackle this area of unknowns. Led by PNNL atmospheric scientist Larry Berg, ARM's Climate Research Facility was deployed in Cape Cod, Massachusetts for the 12-month duration of TCAP, which came to a close in June 2013. "We are developing new tools to look at particle chemistry, like our mass spectrometer used in TCAP that can tell us the individual chemical composition of an aerosol," saidmore » Berg. "Then, we'll run our models and compare it with the data that we have to make sure we're getting correct answers and make sure our climate models are reflecting the best information."« less

The utility of ductal lavage in breast cancer detection and risk assessment

PubMed Central

Domchek, Susan M

2002-01-01

Ductal lavage (DL) permits noninvasive retrieval of epithelial cells from the breast. Clinical development of this technique has been fueled largely by its potential, as yet unproven, to improve detection of breast cancer and definition of individual risk for development of breast cancer. Early studies demonstrate the feasibility of performing this technique, provide data on cellular yield and findings, and demonstrate the ability to measure molecular markers in DL fluid. However, the sensitivity and specificity of DL for the detection of breast cancer remains unknown, as does the significance of atypia, particularly mild atypia, when found in DL fluid. Although DL appears safe and the device is approved by the US Food and Drug Administration, DL is still best utilized in the setting of clinical trials designed to resolve issues of sensitivity, specificity, and localization. PMID:11879562

Aerosols and Clouds: In Cahoots to Change Climate

ScienceCinema

Berg, Larry

2018-01-16

Key knowledge gaps persist despite advances in the scientific understanding of how aerosols and clouds evolve and affect climate. The Two-Column Aerosol Project, or TCAP, was designed to provide a detailed set of observations to tackle this area of unknowns. Led by PNNL atmospheric scientist Larry Berg, ARM's Climate Research Facility was deployed in Cape Cod, Massachusetts for the 12-month duration of TCAP, which came to a close in June 2013. "We are developing new tools to look at particle chemistry, like our mass spectrometer used in TCAP that can tell us the individual chemical composition of an aerosol," said Berg. "Then, we'll run our models and compare it with the data that we have to make sure we're getting correct answers and make sure our climate models are reflecting the best information."

Pharmacists as agents of change for rational drug therapy.

PubMed

Lipton, H L; Byrns, P J; Soumerai, S B; Chrischilles, E A

1995-01-01

We analyze what is known and unknown about the contribution of the pharmacist as patient educator, physician consultant, and agent to affect patient outcomes in ambulatory settings. The need for pharmacist services is discussed, as are the theoretical underpinnings and quality of the scientific evidence to support their efficacy. The analysis is conducted in the context of a shift in pharmacists' roles from product to patient orientation as well as recent U.S. legislation mandating enhanced pharmacists' roles via drug utilization review for all Medicaid patients. We conclude with a research and action agenda, calling for stronger research designs in evaluating pharmacists' interventions. The shifting paradigm in the pharmacy profession, coupled with the implementation of the Omnibus Budget Reconciliation Act of 1990, provide unique opportunities for rigorous evaluations of pharmacists as agents of change for rational drug therapy.

How Much Is that Exam Grade Really Worth? An Estimation of Student Risk Aversion to Their Unknown Final College Course Grades

ERIC Educational Resources Information Center

Nalley, Lanier; McKenzie, Andrew

2011-01-01

This study created an experimental design with which students can empirically assess their risk behavior with respect to exam grades within an expected utility framework. Specifically, the authors analyzed students' risk preferences associated with taking exams and earning a "risky" unknown grade versus not taking exams and instead…

Decision-theoretic designs for a series of trials with correlated treatment effects using the Sarmanov multivariate beta-binomial distribution.

PubMed

Hee, Siew Wan; Parsons, Nicholas; Stallard, Nigel

2018-03-01

The motivation for the work in this article is the setting in which a number of treatments are available for evaluation in phase II clinical trials and where it may be infeasible to try them concurrently because the intended population is small. This paper introduces an extension of previous work on decision-theoretic designs for a series of phase II trials. The program encompasses a series of sequential phase II trials with interim decision making and a single two-arm phase III trial. The design is based on a hybrid approach where the final analysis of the phase III data is based on a classical frequentist hypothesis test, whereas the trials are designed using a Bayesian decision-theoretic approach in which the unknown treatment effect is assumed to follow a known prior distribution. In addition, as treatments are intended for the same population it is not unrealistic to consider treatment effects to be correlated. Thus, the prior distribution will reflect this. Data from a randomized trial of severe arthritis of the hip are used to test the application of the design. We show that the design on average requires fewer patients in phase II than when the correlation is ignored. Correspondingly, the time required to recommend an efficacious treatment for phase III is quicker. © 2017 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ultra Safe And Secure Blasting System

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

Hart, M M

2009-07-27

The Ultra is a blasting system that is designed for special applications where the risk and consequences of unauthorized demolition or blasting are so great that the use of an extraordinarily safe and secure blasting system is justified. Such a blasting system would be connected and logically welded together through digital code-linking as part of the blasting system set-up and initialization process. The Ultra's security is so robust that it will defeat the people who designed and built the components in any attempt at unauthorized detonation. Anyone attempting to gain unauthorized control of the system by substituting components or tappingmore » into communications lines will be thwarted in their inability to provide encrypted authentication. Authentication occurs through the use of codes that are generated by the system during initialization code-linking and the codes remain unknown to anyone, including the authorized operator. Once code-linked, a closed system has been created. The system requires all components connected as they were during initialization as well as a unique code entered by the operator for function and blasting.« less

Sensor fault diagnosis of singular delayed LPV systems with inexact parameters: an uncertain system approach

NASA Astrophysics Data System (ADS)

Hassanabadi, Amir Hossein; Shafiee, Masoud; Puig, Vicenc

2018-01-01

In this paper, sensor fault diagnosis of a singular delayed linear parameter varying (LPV) system is considered. In the considered system, the model matrices are dependent on some parameters which are real-time measurable. The case of inexact parameter measurements is considered which is close to real situations. Fault diagnosis in this system is achieved via fault estimation. For this purpose, an augmented system is created by including sensor faults as additional system states. Then, an unknown input observer (UIO) is designed which estimates both the system states and the faults in the presence of measurement noise, disturbances and uncertainty induced by inexact measured parameters. Error dynamics and the original system constitute an uncertain system due to inconsistencies between real and measured values of the parameters. Then, the robust estimation of the system states and the faults are achieved with H∞ performance and formulated with a set of linear matrix inequalities (LMIs). The designed UIO is also applicable for fault diagnosis of singular delayed LPV systems with unmeasurable scheduling variables. The efficiency of the proposed approach is illustrated with an example.

Excitons in scintillator materials: Optical properties and electron-energy loss spectra of NaI, LaBr 3, BaI 2, and SrI 2

DOE PAGES

Schleife, Andre; Zhang, Xiao; Li, Qi; ...

2016-11-03

In this paper, materials for scintillator radiation detectors need to fulfill a diverse set of requirements such as radiation hardness and highly specific response to incoming radiation, rendering them a target of current materials design efforts. Even though they are amenable to cutting-edge theoretical spectroscopy techniques, surprisingly many fundamental properties of scintillator materials are still unknown or not well explored. In this work, we use first-principles approaches to thoroughly study the optical properties of four scintillator materials: NaI, LaBr 3, BaI 2, and SrI 2. By solving the Bethe–Salpeter equation for the optical polarization function we study the influence ofmore » excitonic effects on dielectric and electron-energy loss functions. This work sheds light into fundamental optical properties of these four scintillator materials and lays the ground-work for future work that is geared toward accurate modeling and computational materials design of advanced radiation detectors with unprecedented energy resolution.« less

A Component-Based Vocabulary-Extensible Sign Language Gesture Recognition Framework.

PubMed

Wei, Shengjing; Chen, Xiang; Yang, Xidong; Cao, Shuai; Zhang, Xu

2016-04-19

Sign language recognition (SLR) can provide a helpful tool for the communication between the deaf and the external world. This paper proposed a component-based vocabulary extensible SLR framework using data from surface electromyographic (sEMG) sensors, accelerometers (ACC), and gyroscopes (GYRO). In this framework, a sign word was considered to be a combination of five common sign components, including hand shape, axis, orientation, rotation, and trajectory, and sign classification was implemented based on the recognition of five components. Especially, the proposed SLR framework consisted of two major parts. The first part was to obtain the component-based form of sign gestures and establish the code table of target sign gesture set using data from a reference subject. In the second part, which was designed for new users, component classifiers were trained using a training set suggested by the reference subject and the classification of unknown gestures was performed with a code matching method. Five subjects participated in this study and recognition experiments under different size of training sets were implemented on a target gesture set consisting of 110 frequently-used Chinese Sign Language (CSL) sign words. The experimental results demonstrated that the proposed framework can realize large-scale gesture set recognition with a small-scale training set. With the smallest training sets (containing about one-third gestures of the target gesture set) suggested by two reference subjects, (82.6 ± 13.2)% and (79.7 ± 13.4)% average recognition accuracy were obtained for 110 words respectively, and the average recognition accuracy climbed up to (88 ± 13.7)% and (86.3 ± 13.7)% when the training set included 50~60 gestures (about half of the target gesture set). The proposed framework can significantly reduce the user's training burden in large-scale gesture recognition, which will facilitate the implementation of a practical SLR system.

Sliding Mode Observer-Based Current Sensor Fault Reconstruction and Unknown Load Disturbance Estimation for PMSM Driven System

PubMed Central

Li, Xiangfei; Lin, Yuliang

2017-01-01

This paper proposes a new scheme of reconstructing current sensor faults and estimating unknown load disturbance for a permanent magnet synchronous motor (PMSM)-driven system. First, the original PMSM system is transformed into two subsystems; the first subsystem has unknown system load disturbances, which are unrelated to sensor faults, and the second subsystem has sensor faults, but is free from unknown load disturbances. Introducing a new state variable, the augmented subsystem that has sensor faults can be transformed into having actuator faults. Second, two sliding mode observers (SMOs) are designed: the unknown load disturbance is estimated by the first SMO in the subsystem, which has unknown load disturbance, and the sensor faults can be reconstructed using the second SMO in the augmented subsystem, which has sensor faults. The gains of the proposed SMOs and their stability analysis are developed via the solution of linear matrix inequality (LMI). Finally, the effectiveness of the proposed scheme was verified by simulations and experiments. The results demonstrate that the proposed scheme can reconstruct current sensor faults and estimate unknown load disturbance for the PMSM-driven system. PMID:29211017

PhylArray: phylogenetic probe design algorithm for microarray.

PubMed

Militon, Cécile; Rimour, Sébastien; Missaoui, Mohieddine; Biderre, Corinne; Barra, Vincent; Hill, David; Moné, Anne; Gagne, Geneviève; Meier, Harald; Peyretaillade, Eric; Peyret, Pierre

2007-10-01

Microbial diversity is still largely unknown in most environments, such as soils. In order to get access to this microbial 'black-box', the development of powerful tools such as microarrays are necessary. However, the reliability of this approach relies on probe efficiency, in particular sensitivity, specificity and explorative power, in order to obtain an image of the microbial communities that is close to reality. We propose a new probe design algorithm that is able to select microarray probes targeting SSU rRNA at any phylogenetic level. This original approach, implemented in a program called 'PhylArray', designs a combination of degenerate and non-degenerate probes for each target taxon. Comparative experimental evaluations indicate that probes designed with PhylArray yield a higher sensitivity and specificity than those designed by conventional approaches. Applying the combined PhyArray/GoArrays strategy helps to optimize the hybridization performance of short probes. Finally, hybridizations with environmental targets have shown that the use of the PhylArray strategy can draw attention to even previously unknown bacteria.

Decentralized adaptive neural control for high-order interconnected stochastic nonlinear time-delay systems with unknown system dynamics.

PubMed

Si, Wenjie; Dong, Xunde; Yang, Feifei

2018-03-01

This paper is concerned with the problem of decentralized adaptive backstepping state-feedback control for uncertain high-order large-scale stochastic nonlinear time-delay systems. For the control design of high-order large-scale nonlinear systems, only one adaptive parameter is constructed to overcome the over-parameterization, and neural networks are employed to cope with the difficulties raised by completely unknown system dynamics and stochastic disturbances. And then, the appropriate Lyapunov-Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions of high-order large-scale systems for the first time. At last, on the basis of Lyapunov stability theory, the decentralized adaptive neural controller was developed, and it decreases the number of learning parameters. The actual controller can be designed so as to ensure that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges in the small neighborhood of zero. The simulation example is used to further show the validity of the design method. Copyright © 2018 Elsevier Ltd. All rights reserved.

Distributed robust adaptive control of high order nonlinear multi agent systems.

PubMed

Hashemi, Mahnaz; Shahgholian, Ghazanfar

2018-03-01

In this paper, a robust adaptive neural network based controller is presented for multi agent high order nonlinear systems with unknown nonlinear functions, unknown control gains and unknown actuator failures. At first, Neural Network (NN) is used to approximate the nonlinear uncertainty terms derived from the controller design procedure for the followers. Then, a novel distributed robust adaptive controller is developed by combining the backstepping method and the Dynamic Surface Control (DSC) approach. The proposed controllers are distributed in the sense that the designed controller for each follower agent only requires relative state information between itself and its neighbors. By using the Young's inequality, only few parameters need to be tuned regardless of NN nodes number. Accordingly, the problems of dimensionality curse and explosion of complexity are counteracted, simultaneously. New adaptive laws are designed by choosing the appropriate Lyapunov-Krasovskii functionals. The proposed approach proves the boundedness of all the closed-loop signals in addition to the convergence of the distributed tracking errors to a small neighborhood of the origin. Simulation results indicate that the proposed controller is effective and robust. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive Actor-Critic Design-Based Integral Sliding-Mode Control for Partially Unknown Nonlinear Systems With Input Disturbances.

PubMed

Fan, Quan-Yong; Yang, Guang-Hong

2016-01-01

This paper is concerned with the problem of integral sliding-mode control for a class of nonlinear systems with input disturbances and unknown nonlinear terms through the adaptive actor-critic (AC) control method. The main objective is to design a sliding-mode control methodology based on the adaptive dynamic programming (ADP) method, so that the closed-loop system with time-varying disturbances is stable and the nearly optimal performance of the sliding-mode dynamics can be guaranteed. In the first step, a neural network (NN)-based observer and a disturbance observer are designed to approximate the unknown nonlinear terms and estimate the input disturbances, respectively. Based on the NN approximations and disturbance estimations, the discontinuous part of the sliding-mode control is constructed to eliminate the effect of the disturbances and attain the expected equivalent sliding-mode dynamics. Then, the ADP method with AC structure is presented to learn the optimal control for the sliding-mode dynamics online. Reconstructed tuning laws are developed to guarantee the stability of the sliding-mode dynamics and the convergence of the weights of critic and actor NNs. Finally, the simulation results are presented to illustrate the effectiveness of the proposed method.

Sensitivity and Specificity of Polysomnographic Criteria for Defining Insomnia

PubMed Central

Edinger, Jack D.; Ulmer, Christi S.; Means, Melanie K.

2013-01-01

Study Objectives: In recent years, polysomnography-based eligibility criteria have been increasingly used to identify candidates for insomnia research, and this has been particularly true of studies evaluating pharmacologic therapy for primary insomnia. However, the sensitivity and specificity of PSG for identifying individuals with insomnia is unknown, and there is no consensus on the criteria sets which should be used for participant selection. In the current study, an archival data set was used to test the sensitivity and specificity of PSG measures for identifying individuals with primary insomnia in both home and lab settings. We then evaluated the sensitivity and specificity of the eligibility criteria employed in a number of recent insomnia trials for identifying primary insomnia sufferers in our sample. Design: Archival data analysis. Settings: Study participants' homes and a clinical sleep laboratory. Participants: Adults: 76 with primary insomnia and 78 non-complaining normal sleepers. Measurements and Results: ROC and cross-tabs analyses were used to evaluate the sensitivity and specificity of PSG-derived total sleep time, latency to persistent sleep, wake after sleep onset, and sleep efficiency for discriminating adults with primary insomnia from normal sleepers. None of the individual criteria accurately discriminated PI from normal sleepers, and none of the criteria sets used in recent trials demonstrated acceptable sensitivity and specificity for identifying primary insomnia. Conclusions: The use of quantitative PSG-based selection criteria in insomnia research may exclude many who meet current diagnostic criteria for an insomnia disorder. Citation: Edinger JD; Ulmer CS; Means MK. Sensitivity and specificity of polysomnographic criteria for defining insomnia. J Clin Sleep Med 2013;9(5):481-491. PMID:23674940

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

PubMed

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

2012-07-01

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

Marbles for the Imagination

NASA Technical Reports Server (NTRS)

Shue, Jack

2004-01-01

The end-to-end test would verify the complex sequence of events from lander separation to landing. Due to the large distances involved and the significant delay time in sending a command and receiving verification, the lander needed to operate autonomously after it separated from the orbiter. It had to sense conditions, make decisions, and act accordingly. We were flying into a relatively unknown set of conditions-a Martian atmosphere of unknown pressure, density, and consistency to land on a surface of unknown altitude, and one which had an unknown bearing strength. In order to touch down safely on Mars the lander had to orient itself for descent and entry, modulate itself to maintain proper lift, pop a parachute, jettison its aeroshell, deploy landing legs and radar, ignite a terminal descent engine, and fly a given trajectory to the surface. Once on the surface, it would determine its orientation, raise the high-gain antenna, perform a sweep to locate Earth, and begin transmitting information. It was this complicated, autonomous sequence that the end-to-end test was to simulate.

Analysis of multinomial models with unknown index using data augmentation

USGS Publications Warehouse

Royle, J. Andrew; Dorazio, R.M.; Link, W.A.

2007-01-01

Multinomial models with unknown index ('sample size') arise in many practical settings. In practice, Bayesian analysis of such models has proved difficult because the dimension of the parameter space is not fixed, being in some cases a function of the unknown index. We describe a data augmentation approach to the analysis of this class of models that provides for a generic and efficient Bayesian implementation. Under this approach, the data are augmented with all-zero detection histories. The resulting augmented dataset is modeled as a zero-inflated version of the complete-data model where an estimable zero-inflation parameter takes the place of the unknown multinomial index. Interestingly, data augmentation can be justified as being equivalent to imposing a discrete uniform prior on the multinomial index. We provide three examples involving estimating the size of an animal population, estimating the number of diabetes cases in a population using the Rasch model, and the motivating example of estimating the number of species in an animal community with latent probabilities of species occurrence and detection.

Point Pairing Method Based on the Principle of Material Frame Indifference for the Characterization of Unknown Space Objects using Non-Resolved Photometry Data

DTIC Science & Technology

2013-09-01

provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB...the satellite. The material constitutive laws of interest are the bidirectional reflectance distribution functions ( BRDF ) for diffuse and specular...solar panel can be related to each other using the BRDF definition. This creates a set of three independent equations and three unknowns, which can be

Developing safety performance functions incorporating reliability-based risk measures.

PubMed

Ibrahim, Shewkar El-Bassiouni; Sayed, Tarek

2011-11-01

Current geometric design guides provide deterministic standards where the safety margin of the design output is generally unknown and there is little knowledge of the safety implications of deviating from these standards. Several studies have advocated probabilistic geometric design where reliability analysis can be used to account for the uncertainty in the design parameters and to provide a risk measure of the implication of deviation from design standards. However, there is currently no link between measures of design reliability and the quantification of safety using collision frequency. The analysis presented in this paper attempts to bridge this gap by incorporating a reliability-based quantitative risk measure such as the probability of non-compliance (P(nc)) in safety performance functions (SPFs). Establishing this link will allow admitting reliability-based design into traditional benefit-cost analysis and should lead to a wider application of the reliability technique in road design. The present application is concerned with the design of horizontal curves, where the limit state function is defined in terms of the available (supply) and stopping (demand) sight distances. A comprehensive collision and geometric design database of two-lane rural highways is used to investigate the effect of the probability of non-compliance on safety. The reliability analysis was carried out using the First Order Reliability Method (FORM). Two Negative Binomial (NB) SPFs were developed to compare models with and without the reliability-based risk measures. It was found that models incorporating the P(nc) provided a better fit to the data set than the traditional (without risk) NB SPFs for total, injury and fatality (I+F) and property damage only (PDO) collisions. Copyright © 2011 Elsevier Ltd. All rights reserved.

What Bacteria Are Living in My Food?: An Open-Ended Practical Series Involving Identification of Unknown Foodborne Bacteria Using Molecular Techniques

ERIC Educational Resources Information Center

Prasad, Prascilla; Turner, Mark S.

2011-01-01

This open-ended practical series titled "Molecular Identification of Unknown Food Bacteria" which extended over a 6-week period was designed with the aims of giving students an opportunity to gain an understanding of naturally occurring food bacteria and skills in contemporary molecular methods using real food samples. The students first isolated…

8. Photocopy of photograph, date unknown (original print on file ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

8. Photocopy of photograph, date unknown (original print on file at U.S. Army Intelligence Security Command, Fort Belvoir, Virginia). VIEW OF SULLINS COLLEGE, BRISTOL, VIRGINIA. SULLINS COLLEGE PRESIDENT WILLIAM MARTIN FOUNDED ARLINGTON HALL JUNIOR COLLEGE, AND APPEARS TO HAVE LOOSELY BASED THE DESIGN OF THE NEW SCHOOL'S BUILDINGS UPON THOSE AT SULLINS. - Arlington Hall Station, 4000 Arlington Boulevard, Arlington, Arlington County, VA

Fictional privacy among Facebook users.

PubMed

Lemieux, Robert

2012-08-01

The current study involved the creation of a fictional Facebook account with limited information and was designed to assess whether participants would accept the friendship of an ambiguous, unknown person. Results indicated that 325 Facebook members (72% of the sample) willingly accepted the friendship of the unknown individual. Results are discussed in relation to privacy concerns, norms of reciprocity, and allowing access to potentially embarrassing information and/or pictures.

New Ideas for an Old Enzyme: A Short, Question-Based Laboratory Project for the Purification and Identification of an Unknown LDH Isozyme

ERIC Educational Resources Information Center

Coleman, Aaron B.

2010-01-01

Enzyme purification projects are an excellent way to introduce many aspects of protein biochemistry, but can be difficult to carry out under the constraints of a typical undergraduate laboratory course. We have designed a short laboratory project for the purification and identification of an "unknown" lactate dehydrogenase (LDH) isozyme that can…

CPAP IMPACT: a protocol for a randomised trial of bubble continuous positive airway pressure versus standard care for high-risk children with severe pneumonia using adaptive design methods

PubMed Central

Smith, Andrew G; Eckerle, Michelle; Mvalo, Tisungane; Weir, Brian; Martinson, Francis; Chalira, Alfred; Lufesi, Norman; Mofolo, Innocent; Hosseinipour, Mina

2017-01-01

Introduction Pneumonia is a leading cause of mortality among children in low-resource settings. Mortality is greatest among children with high-risk conditions including HIV infection or exposure, severe malnutrition and/or severe hypoxaemia. WHO treatment recommendations include low-flow oxygen for children with severe pneumonia. Bubble continuous positive airway pressure (bCPAP) is a non-invasive support modality that provides positive end-expiratory pressure and oxygen. bCPAP is effective in the treatment of neonates in low-resource settings; its efficacy is unknown for high-risk children with severe pneumonia in low-resource settings. Methods and analysis CPAP IMPACT is a randomised clinical trial comparing bCPAP to low-flow oxygen in the treatment of severe pneumonia among high-risk children 1–59 months of age. High-risk children are stratified into two subgroups: (1) HIV infection or exposure and/or severe malnutrition; (2) severe hypoxaemia. The trial is being conducted in a Malawi district hospital and will enrol 900 participants. The primary outcome is in-hospital mortality rate of children treated with standard care as compared with bCPAP. Ethics and dissemination CPAP IMPACT has approval from the Institutional Review Boards of all investigators. An urgent need exists to determine whether bCPAP decreases mortality among high-risk children with severe pneumonia to inform resource utilisation in low-resource settings. Trial registration number NCT02484183; Pre-results. PMID:28883928

GLRT-based array receivers for the detection of a known signal with unknown parameters corrupted by noncircular interferences

NASA Astrophysics Data System (ADS)

Chevalier, Pascal; Oukaci, Abdelkader; Delmas, Jean-Pierre

2011-12-01

The detection of a known signal with unknown parameters in the presence of noise plus interferences (called total noise) whose covariance matrix is unknown is an important problem which has received much attention these last decades for applications such as radar, satellite localization or time acquisition in radio communications. However, most of the available receivers assume a second order (SO) circular (or proper) total noise and become suboptimal in the presence of SO noncircular (or improper) interferences, potentially present in the previous applications. The scarce available receivers which take the potential SO noncircularity of the total noise into account have been developed under the restrictive condition of a known signal with known parameters or under the assumption of a random signal. For this reason, following a generalized likelihood ratio test (GLRT) approach, the purpose of this paper is to introduce and to analyze the performance of different array receivers for the detection of a known signal, with different sets of unknown parameters, corrupted by an unknown noncircular total noise. To simplify the study, we limit the analysis to rectilinear known useful signals for which the baseband signal is real, which concerns many applications.

Efficient Bayesian experimental design for contaminant source identification

NASA Astrophysics Data System (ADS)

Zhang, Jiangjiang; Zeng, Lingzao; Chen, Cheng; Chen, Dingjiang; Wu, Laosheng

2015-01-01

In this study, an efficient full Bayesian approach is developed for the optimal sampling well location design and source parameters identification of groundwater contaminants. An information measure, i.e., the relative entropy, is employed to quantify the information gain from concentration measurements in identifying unknown parameters. In this approach, the sampling locations that give the maximum expected relative entropy are selected as the optimal design. After the sampling locations are determined, a Bayesian approach based on Markov Chain Monte Carlo (MCMC) is used to estimate unknown parameters. In both the design and estimation, the contaminant transport equation is required to be solved many times to evaluate the likelihood. To reduce the computational burden, an interpolation method based on the adaptive sparse grid is utilized to construct a surrogate for the contaminant transport equation. The approximated likelihood can be evaluated directly from the surrogate, which greatly accelerates the design and estimation process. The accuracy and efficiency of our approach are demonstrated through numerical case studies. It is shown that the methods can be used to assist in both single sampling location and monitoring network design for contaminant source identifications in groundwater.

Minimal-Approximation-Based Distributed Consensus Tracking of a Class of Uncertain Nonlinear Multiagent Systems With Unknown Control Directions.

PubMed

Choi, Yun Ho; Yoo, Sung Jin

2017-03-28

A minimal-approximation-based distributed adaptive consensus tracking approach is presented for strict-feedback multiagent systems with unknown heterogeneous nonlinearities and control directions under a directed network. Existing approximation-based consensus results for uncertain nonlinear multiagent systems in lower-triangular form have used multiple function approximators in each local controller to approximate unmatched nonlinearities of each follower. Thus, as the follower's order increases, the number of the approximators used in its local controller increases. However, the proposed approach employs only one function approximator to construct the local controller of each follower regardless of the order of the follower. The recursive design methodology using a new error transformation is derived for the proposed minimal-approximation-based design. Furthermore, a bounding lemma on parameters of Nussbaum functions is presented to handle the unknown control direction problem in the minimal-approximation-based distributed consensus tracking framework and the stability of the overall closed-loop system is rigorously analyzed in the Lyapunov sense.

Does Kinematic Alignment and Flexion of a Femoral Component Designed for Mechanical Alignment Reduce the Proximal and Lateral Reach of the Trochlea?

PubMed

Brar, Abheetinder S; Howell, Stephen M; Hull, Maury L; Mahfouz, Mohamed R

2016-08-01

Kinematically aligned total knee arthroplasty uses a femoral component designed for mechanical alignment (MA) and sets the component in more internal, valgus, and flexion rotation than MA. It is unknown how much kinematic alignment (KA) and flexion of the femoral component reduce the proximal and lateral reach of the trochlea; two reductions that could increase the risk of abnormal patella tracking. We simulated MA and KA of the femoral component in 0° of flexion on 20 3-dimensional bone models of normal femurs. The mechanically and kinematically aligned components were then aligned in 5°, 10°, and 15° of flexion and downsized until the flange contacted the anterior femur. The reductions in the proximal and lateral reach from the proximal point of the trochlea of the MA component set in 0° of flexion were computed. KA at 0° of flexion did not reduce the proximal reach and reduced the lateral reach an average of 3 mm. Flexion of the MA and KA femoral component 5°, 10°, and 15° reduced the proximal reach an average of 4 mm, 8 mm, and 12 mm, respectively (0.8 mm/degree of flexion), and reduced the lateral reach an average of 1 mm and 4 mm regardless of the degree of flexion, respectively. Arthroplasty surgeons and biomechanical engineers striving to optimize patella tracking might consider developing surgical techniques to minimize flexion of the femoral component when performing KA and MA total knee arthroplasty to promote early patella engagement and consider designing a femoral component with a trochlea shaped specifically for KA. Copyright © 2016 Elsevier Inc. All rights reserved.

Digital tripwire: a small automated human detection system

NASA Astrophysics Data System (ADS)

Fischer, Amber D.; Redd, Emmett; Younger, A. Steven

2009-05-01

A low cost, lightweight, easily deployable imaging sensor that can dependably discriminate threats from other activities within its field of view and, only then, alert the distant duty officer by transmitting a visual confirmation of the threat would provide a valuable asset to modern defense. At present, current solutions suffer from a multitude of deficiencies - size, cost, power endurance, but most notably, an inability to assess an image and conclude that it contains a threat. The human attention span cannot maintain critical surveillance over banks of displays constantly conveying such images from the field. DigitalTripwire is a small, self-contained, automated human-detection system capable of running for 1-5 days on two AA batteries. To achieve such long endurance, the DigitalTripwire system utilizes an FPGA designed with sleep functionality. The system uses robust vision algorithms, such as a partially unsupervised innovative backgroundmodeling algorithm, which employ several data reduction strategies to operate in real-time, and achieve high detection rates. When it detects human activity, either mounted or dismounted, it sends an alert including images to notify the command center. In this paper, we describe the hardware and software design of the DigitalTripwire system. In addition, we provide detection and false alarm rates across several challenging data sets demonstrating the performance of the vision algorithms in autonomously analyzing the video stream and classifying moving objects into four primary categories - dismounted human, vehicle, non-human, or unknown. Performance results across several challenging data sets are provided.

Using ADOPT Algorithm and Operational Data to Discover Precursors to Aviation Adverse Events

NASA Technical Reports Server (NTRS)

Janakiraman, Vijay; Matthews, Bryan; Oza, Nikunj

2018-01-01

The US National Airspace System (NAS) is making its transition to the NextGen system and assuring safety is one of the top priorities in NextGen. At present, safety is managed reactively (correct after occurrence of an unsafe event). While this strategy works for current operations, it may soon become ineffective for future airspace designs and high density operations. There is a need for proactive management of safety risks by identifying hidden and "unknown" risks and evaluating the impacts on future operations. To this end, NASA Ames has developed data mining algorithms that finds anomalies and precursors (high-risk states) to safety issues in the NAS. In this paper, we describe a recently developed algorithm called ADOPT that analyzes large volumes of data and automatically identifies precursors from real world data. Precursors help in detecting safety risks early so that the operator can mitigate the risk in time. In addition, precursors also help identify causal factors and help predict the safety incident. The ADOPT algorithm scales well to large data sets and to multidimensional time series, reduce analyst time significantly, quantify multiple safety risks giving a holistic view of safety among other benefits. This paper details the algorithm and includes several case studies to demonstrate its application to discover the "known" and "unknown" safety precursors in aviation operation.

Application of AI techniques to infer vegetation characteristics from directional reflectance(s)

NASA Technical Reports Server (NTRS)

Kimes, D. S.; Smith, J. A.; Harrison, P. A.; Harrison, P. R.

1994-01-01

Traditionally, the remote sensing community has relied totally on spectral knowledge to extract vegetation characteristics. However, there are other knowledge bases (KB's) that can be used to significantly improve the accuracy and robustness of inference techniques. Using AI (artificial intelligence) techniques a KB system (VEG) was developed that integrates input spectral measurements with diverse KB's. These KB's consist of data sets of directional reflectance measurements, knowledge from literature, and knowledge from experts which are combined into an intelligent and efficient system for making vegetation inferences. VEG accepts spectral data of an unknown target as input, determines the best techniques for inferring the desired vegetation characteristic(s), applies the techniques to the target data, and provides a rigorous estimate of the accuracy of the inference. VEG was developed to: infer spectral hemispherical reflectance from any combination of nadir and/or off-nadir view angles; infer percent ground cover from any combination of nadir and/or off-nadir view angles; infer unknown view angle(s) from known view angle(s) (known as view angle extension); and discriminate between user defined vegetation classes using spectral and directional reflectance relationships developed from an automated learning algorithm. The errors for these techniques were generally very good ranging between 2 to 15% (proportional root mean square). The system is designed to aid scientists in developing, testing, and applying new inference techniques using directional reflectance data.

Ovarian reserve and subsequent ART outcomes following methotrexate therapy for ectopic pregnancy and pregnancy of unknown location

PubMed Central

Hill, Micah J.; Cooper, Janelle C.; Levy, Gary; Alford, Connie; Richter, Kevin S.; DeCherney, Alan H.; Katz, Charles; Levens, Eric D.; Wolff, Erin F.

2013-01-01

Objective It is unclear whether the stimulated state of the ovaries as part of ART results in an increased vulnerability to the effects of methotrexate. The objective of this study was to assess ovarian reserve following methotrexate treatment for ectopic pregnancy or pregnancy of unknown location after ART. Design Retrospective cohort study. Setting Large ART practice. Patients Methotrexate or surgery following ART. Interventions None. Main Outcome Measures Follicle stimulating hormone (FSH), antral follicle count (AFC), and oocyte yield were compared between subjects treated with methotrexate and surgery. Secondary outcomes were clinical pregnancy and live birth. Results There were 153 patients in the methotrexate group and 36 patients in the surgery group. Neither group demonstrated differences in ovarian reserve or oocyte yield comparing before and after treatment values. The change in ovarian reserve and oocyte yield after treatment were similar between the two groups. The number of doses of methotrexate was not correlated with changes in ovarian reserve, indicating no dose-dependent effect. Time between treatment and repeat ART was not correlated with outcomes. Live birth in subsequent cycles was similar in the two groups. Conclusions Ovarian reserve and subsequent ART cycle outcomes were reassuring following methotrexate and surgical management of ectopic pregnancy. An adverse impact of methotrexate was not detected in this large fertility cohort as has been previously described. PMID:24269042

A functional gene array for detection of bacterial virulence elements

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

Jaing, C

2007-11-01

We report our development of the first of a series of microarrays designed to detect pathogens with known mechanisms of virulence and antibiotic resistance. By targeting virulence gene families as well as genes unique to specific biothreat agents, these arrays will provide important data about the pathogenic potential and drug resistance profiles of unknown organisms in environmental samples. To validate our approach, we developed a first generation array targeting genes from Escherichia coli strains K12 and CFT073, Enterococcus faecalis and Staphylococcus aureus. We determined optimal probe design parameters for microorganism detection and discrimination, measured the required target concentration, and assessedmore » tolerance for mismatches between probe and target sequences. Mismatch tolerance is a priority for this application, due to DNA sequence variability among members of gene families. Arrays were created using the NimbleGen Maskless Array Synthesizer at Lawrence Livermore National Laboratory. Purified genomic DNA from combinations of one or more of the four target organisms, pure cultures of four related organisms, and environmental aerosol samples with spiked-in genomic DNA were hybridized to the arrays. Based on the success of this prototype, we plan to design further arrays in this series, with the goal of detecting all known virulence and antibiotic resistance gene families in a greatly expanded set of organisms.« less

NIR Color vs Launch Date: A 20-year Analysis of Space Weathering Effects on the Boeing 376 Spacecraft

NASA Astrophysics Data System (ADS)

Frith, J.; Anz-Meador, P.; Lederer, S.; Cowardin, H.; Buckalew, B.

The Boeing HS-376 spin stabilized spacecraft was a popular design that was launched continuously into geosynchronous orbit starting in 1980 with the last launch occurring in 2002. Over 50 of the HS-376 buses were produced to fulfill a variety of different communication missions for countries all over the world. The design of the bus is easily approximated as a telescoping cylinder that is covered with solar cells and an Earth facing antenna that is despun at the top of the cylinder. The similarity in design and the number of spacecraft launched over a long period of time make the HS-376 a prime target for studying the effects of solar weathering on solar panels as a function of time. A selection of primarily non-operational HS-376 spacecraft launched over a 20 year time period were observed using the United Kingdom Infrared Telescope on Mauna Kea and multi-band near-infrared photometry produced. Each spacecraft was observed for an entire night cycling through ZYJHK filters and time-varying colors produced to compare near-infrared color as a function of launch date. The resulting analysis shown here may help in the future to set launch date constraints on the parent object of unidentified debris objects or other unknown spacecraft.

NIR Color vs Launch Date: A 20-Year Analysis of Space Weathering Effects on the Boeing 376 Spacecraft

NASA Technical Reports Server (NTRS)

Frith, James; Anz-Meador, Philip; Lederer, Sue; Cowardin, Heather; Buckalew, Brent

2015-01-01

The Boeing HS-376 spin stabilized spacecraft was a popular design that was launched continuously into geosynchronous orbit starting in 1980 with the last launch occurring in 2002. Over 50 of the HS-376 buses were produced to fulfill a variety of different communication missions for countries all over the world. The design of the bus is easily approximated as a telescoping cylinder that is covered with solar cells and an Earth facing antenna that is despun at the top of the cylinder. The similarity in design and the number of spacecraft launched over a long period of time make the HS-376 a prime target for studying the effects of solar weathering on solar panels as a function of time. A selection of primarily non-operational HS-376 spacecraft launched over a 20 year time period were observed using the United Kingdom Infrared Telescope on Mauna Kea and multi-band near-infrared photometry produced. Each spacecraft was observed for an entire night cycling through ZYJHK filters and time-varying colors produced to compare near-infrared color as a function of launch date. The resulting analysis shown here may help in the future to set launch date constraints on the parent object of unidentified debris objects or other unknown spacecraft.

Optimal Policy of Cross-Layer Design for Channel Access and Transmission Rate Adaptation in Cognitive Radio Networks

NASA Astrophysics Data System (ADS)

He, Hao; Wang, Jun; Zhu, Jiang; Li, Shaoqian

2010-12-01

In this paper, we investigate the cross-layer design of joint channel access and transmission rate adaptation in CR networks with multiple channels for both centralized and decentralized cases. Our target is to maximize the throughput of CR network under transmission power constraint by taking spectrum sensing errors into account. In centralized case, this problem is formulated as a special constrained Markov decision process (CMDP), which can be solved by standard linear programming (LP) method. As the complexity of finding the optimal policy by LP increases exponentially with the size of action space and state space, we further apply action set reduction and state aggregation to reduce the complexity without loss of optimality. Meanwhile, for the convenience of implementation, we also consider the pure policy design and analyze the corresponding characteristics. In decentralized case, where only local information is available and there is no coordination among the CR users, we prove the existence of the constrained Nash equilibrium and obtain the optimal decentralized policy. Finally, in the case that the traffic load parameters of the licensed users are unknown for the CR users, we propose two methods to estimate the parameters for two different cases. Numerical results validate the theoretic analysis.

A validation procedure for a LADAR system radiometric simulation model

NASA Astrophysics Data System (ADS)

Leishman, Brad; Budge, Scott; Pack, Robert

2007-04-01

The USU LadarSIM software package is a ladar system engineering tool that has recently been enhanced to include the modeling of the radiometry of Ladar beam footprints. This paper will discuss our validation of the radiometric model and present a practical approach to future validation work. In order to validate complicated and interrelated factors affecting radiometry, a systematic approach had to be developed. Data for known parameters were first gathered then unknown parameters of the system were determined from simulation test scenarios. This was done in a way to isolate as many unknown variables as possible, then build on the previously obtained results. First, the appropriate voltage threshold levels of the discrimination electronics were set by analyzing the number of false alarms seen in actual data sets. With this threshold set, the system noise was then adjusted to achieve the appropriate number of dropouts. Once a suitable noise level was found, the range errors of the simulated and actual data sets were compared and studied. Predicted errors in range measurements were analyzed using two methods: first by examining the range error of a surface with known reflectivity and second by examining the range errors for specific detectors with known responsivities. This provided insight into the discrimination method and receiver electronics used in the actual system.

Analysis of suspicious powders following the post 9/11 anthrax scare.

PubMed

Wills, Brandon; Leikin, Jerrold; Rhee, James; Saeedi, Bijan

2008-06-01

Following the 9/11 terrorist attacks, SET Environmental, Inc., a Chicago-based environmental and hazardous materials management company received a large number of suspicious powders for analysis. Samples of powders were submitted to SET for anthrax screening and/or unknown identification (UI). Anthrax screening was performed on-site using a ruggedized analytical pathogen identification device (R.A.P.I.D.) (Idaho Technologies, Salt Lake City, UT). UI was performed at SET headquarters (Wheeling, IL) utilizing a combination of wet chemistry techniques, infrared spectroscopy, and gas chromatography/mass spectroscopy. Turnaround time was approximately 2-3 hours for either anthrax or UI. Between October 10, 2001 and October 11, 2002, 161 samples were analyzed. Of these, 57 were for anthrax screening only, 78 were for anthrax and UI, and 26 were for UI only. Sources of suspicious powders included industries (66%), U.S. Postal Service (19%), law enforcement (9%), and municipalities (7%). There were 0/135 anthrax screens that were positive. There were no positive anthrax screens performed by SET in the Chicago area following the post-9/11 anthrax scare. The only potential biological or chemical warfare agent identified (cyanide) was provided by law enforcement. Rapid anthrax screening and identification of unknown substances at the scene are useful to prevent costly interruption of services and potential referral for medical evaluation.

High-resolution melting (HRM) assay for the detection of recurrent BRCA1/BRCA2 germline mutations in Tunisian breast/ovarian cancer families.

PubMed

Riahi, Aouatef; Kharrat, Maher; Lariani, Imen; Chaabouni-Bouhamed, Habiba

2014-12-01

Germline deleterious mutations in the BRCA1/BRCA2 genes are associated with an increased risk for the development of breast and ovarian cancer. Given the large size of these genes the detection of such mutations represents a considerable technical challenge. Therefore, the development of cost-effective and rapid methods to identify these mutations became a necessity. High resolution melting analysis (HRM) is a rapid and efficient technique extensively employed as high-throughput mutation scanning method. The purpose of our study was to assess the specificity and sensitivity of HRM for BRCA1 and BRCA2 genes scanning. As a first step we estimate the ability of HRM for detection mutations in a set of 21 heterozygous samples harboring 8 different known BRCA1/BRCA2 variations, all samples had been preliminarily investigated by direct sequencing, and then we performed a blinded analysis by HRM in a set of 68 further sporadic samples of unknown genotype. All tested heterozygous BRCA1/BRCA2 variants were easily identified. However the HRM assay revealed further alteration that we initially had not searched (one unclassified variant). Furthermore, sequencing confirmed all the HRM detected mutations in the set of unknown samples, including homozygous changes, indicating that in this cohort, with the optimized assays, the mutations detections sensitivity and specificity were 100 %. HRM is a simple, rapid and efficient scanning method for known and unknown BRCA1/BRCA2 germline mutations. Consequently the method will allow for the economical screening of recurrent mutations in Tunisian population.

Nonlinear adaptive control system design with asymptotically stable parameter estimation error

NASA Astrophysics Data System (ADS)

Mishkov, Rumen; Darmonski, Stanislav

2018-01-01

The paper presents a new general method for nonlinear adaptive system design with asymptotic stability of the parameter estimation error. The advantages of the approach include asymptotic unknown parameter estimation without persistent excitation and capability to directly control the estimates transient response time. The method proposed modifies the basic parameter estimation dynamics designed via a known nonlinear adaptive control approach. The modification is based on the generalised prediction error, a priori constraints with a hierarchical parameter projection algorithm, and the stable data accumulation concepts. The data accumulation principle is the main tool for achieving asymptotic unknown parameter estimation. It relies on the parametric identifiability system property introduced. Necessary and sufficient conditions for exponential stability of the data accumulation dynamics are derived. The approach is applied in a nonlinear adaptive speed tracking vector control of a three-phase induction motor.

Adaptive sliding control of non-autonomous active suspension systems with time-varying loadings

NASA Astrophysics Data System (ADS)

Chen, Po-Chang; Huang, An-Chyau

2005-04-01

An adaptive sliding controller is proposed in this paper for controlling a non-autonomous quarter-car suspension system with time-varying loadings. The bound of the car-body loading is assumed to be available. Then, the reference coordinate is placed at the static position under the nominal loading so that the system dynamic equation is derived. Due to spring nonlinearities, the system property becomes asymmetric after coordinate transformation. Besides, in practical cases, system parameters are not easy to be obtained precisely for controller design. Therefore, in this paper, system uncertainties are lumped into two unknown time-varying functions. Since the variation bound of one of the unknown functions is not available, conventional adaptive schemes and robust designs are not applicable. To deal with this problem, the function approximation technique is employed to represent the unknown function as a finite combination of basis functions. The Lyapunov direct method can thus be used to find adaptive laws for updating coefficients in the approximating series and to prove stability of the closed-loop system. Since the position and velocity measurements of the unsprung mass are lumped into the unknown function, there is no need to install sensors on the axle and wheel assembly in the actual implementation. Simulation results are presented to show the performance of the proposed strategy.

Analysis of condensation on a horizontal cylinder with unknown wall temperature and comparison with the Nusselt model of film condensation

NASA Technical Reports Server (NTRS)

Bahrami, Parviz A.

1996-01-01

Theoretical analysis and numerical computations are performed to set forth a new model of film condensation on a horizontal cylinder. The model is more general than the well-known Nusselt model of film condensation and is designed to encompass all essential features of the Nusselt model. It is shown that a single parameter, constructed explicitly and without specification of the cylinder wall temperature, determines the degree of departure from the Nusselt model, which assumes a known and uniform wall temperature. It is also known that the Nusselt model is reached for very small, as well as very large, values of this parameter. In both limiting cases the cylinder wall temperature assumes a uniform distribution and the Nusselt model is approached. The maximum deviations between the two models is rather small for cases which are representative of cylinder dimensions, materials and conditions encountered in practice.

Channel Simulation in Quantum Metrology

NASA Astrophysics Data System (ADS)

Laurenza, Riccardo; Lupo, Cosmo; Spedalieri, Gaetana; Braunstein, Samuel L.; Pirandola, Stefano

2018-04-01

In this review we discuss how channel simulation can be used to simplify the most general protocols of quantum parameter estimation, where unlimited entanglement and adaptive joint operations may be employed. Whenever the unknown parameter encoded in a quantum channel is completely transferred in an environmental program state simulating the channel, the optimal adaptive estimation cannot beat the standard quantum limit. In this setting, we elucidate the crucial role of quantum teleportation as a primitive operation which allows one to completely reduce adaptive protocols over suitable teleportation-covariant channels and derive matching upper and lower bounds for parameter estimation. For these channels,wemay express the quantum Cramér Rao bound directly in terms of their Choi matrices. Our review considers both discrete- and continuous-variable systems, also presenting some new results for bosonic Gaussian channels using an alternative sub-optimal simulation. It is an open problem to design simulations for quantum channels that achieve the Heisenberg limit.

Distributed Adaptive Containment Control for a Class of Nonlinear Multiagent Systems With Input Quantization.

PubMed

Wang, Chenliang; Wen, Changyun; Hu, Qinglei; Wang, Wei; Zhang, Xiuyu

2018-06-01

This paper is devoted to distributed adaptive containment control for a class of nonlinear multiagent systems with input quantization. By employing a matrix factorization and a novel matrix normalization technique, some assumptions involving control gain matrices in existing results are relaxed. By fusing the techniques of sliding mode control and backstepping control, a two-step design method is proposed to construct controllers and, with the aid of neural networks, all system nonlinearities are allowed to be unknown. Moreover, a linear time-varying model and a similarity transformation are introduced to circumvent the obstacle brought by quantization, and the controllers need no information about the quantizer parameters. The proposed scheme is able to ensure the boundedness of all closed-loop signals and steer the containment errors into an arbitrarily small residual set. The simulation results illustrate the effectiveness of the scheme.

Mapping organelle motion reveals a vesicular conveyor belt spatially replenishing secretory vesicles in stimulated chromaffin cells.

PubMed

Maucort, Guillaume; Kasula, Ravikiran; Papadopulos, Andreas; Nieminen, Timo A; Rubinsztein-Dunlop, Halina; Meunier, Frederic A

2014-01-01

How neurosecretory cells spatially adjust their secretory vesicle pools to replenish those that have fused and released their hormonal content is currently unknown. Here we designed a novel set of image analyses to map the probability of tracked organelles undergoing a specific type of movement (free, caged or directed). We then applied our analysis to time-lapse z-stack confocal imaging of secretory vesicles from bovine Chromaffin cells to map the global changes in vesicle motion and directionality occurring upon secretagogue stimulation. We report a defined region abutting the cortical actin network that actively transports secretory vesicles and is dissipated by actin and microtubule depolymerizing drugs. The directionality of this "conveyor belt" towards the cell surface is activated by stimulation. Actin and microtubule networks therefore cooperatively probe the microenvironment to transport secretory vesicles to the periphery, providing a mechanism whereby cells globally adjust their vesicle pools in response to secretagogue stimulation.

Adaptive Neural Control of Uncertain MIMO Nonlinear Systems With State and Input Constraints.

PubMed

Chen, Ziting; Li, Zhijun; Chen, C L Philip

2017-06-01

An adaptive neural control strategy for multiple input multiple output nonlinear systems with various constraints is presented in this paper. To deal with the nonsymmetric input nonlinearity and the constrained states, the proposed adaptive neural control is combined with the backstepping method, radial basis function neural network, barrier Lyapunov function (BLF), and disturbance observer. By ensuring the boundedness of the BLF of the closed-loop system, it is demonstrated that the output tracking is achieved with all states remaining in the constraint sets and the general assumption on nonsingularity of unknown control coefficient matrices has been eliminated. The constructed adaptive neural control has been rigorously proved that it can guarantee the semiglobally uniformly ultimate boundedness of all signals in the closed-loop system. Finally, the simulation studies on a 2-DOF robotic manipulator system indicate that the designed adaptive control is effective.

An exploration of the relationship between knowledge and performance-related variables in high-fidelity simulation: designing instruction that promotes expertise in practice.

PubMed

Hauber, Roxanne P; Cormier, Eileen; Whyte, James

2010-01-01

Increasingly, high-fidelity patient simulation (HFPS) is becoming essential to nursing education. Much remains unknown about how classroom learning is connected to student decision-making in simulation scenarios and the degree to which transference takes place between the classroom setting and actual practice. The present study was part of a larger pilot study aimed at determining the relationship between nursing students' clinical ability to prioritize their actions and the associated cognitions and physiologic outcomes of care using HFPS. In an effort to better explain the knowledge base being used by nursing students in HFPS, the investigators explored the relationship between common measures of knowledge and performance-related variables. Findings are discussed within the context of the expert performance approach and concepts from cognitive psychology, such as cognitive architecture, cognitive load, memory, and transference.

Indication for Dialysis Initiation and Mortality in Patients With Chronic Kidney Failure: A Retrospective Cohort Study

PubMed Central

Rivara, Matthew B.; Chen, Chang Huei; Nair, Anupama; Cobb, Denise; Himmelfarb, Jonathan; Mehrotra, Rajnish

2016-01-01

Background Initiation of maintenance dialysis for patients with chronic kidney failure is a period of high risk for adverse patient outcomes. Whether indications for dialysis initiation are associated with mortality among this population is unknown. Study Design Retrospective cohort study. Setting & Participants 461 patients who initiated dialysis (hemodialysis, 437; peritoneal dialysis, 24) from January 1st, 2004 through December 31st, 2012 and were treated in facilities operated by a single dialysis organization. Follow-up for the primary outcome was through December 31st, 2013. Predictor Clinically documented primary indication for dialysis initiation, as categorized into four groups: laboratory evidence of kidney function decline (reference category), uremic symptoms, volume overload or hypertension, and other/unknown. Outcomes All-cause mortality Results Over a median follow-up of 2.4 years, 183 (40%) patients died. Crude mortality rates were 10.0 (95% CI, 6.8–14.7), 12.7 (95% CI, 10.2–15.7), 21.7 (95% CI, 16.4–28.6), and 12.2 (95% CI, 6.8–14.7) per 100 patient-years among patients initiating dialysis primarily for laboratory evidence of kidney function decline, uremic symptoms, volume overload or hypertension, and other/unknown reason, respectively. Following adjustment for demographic variables, coexisting illnesses, and estimated glomerular filtration rate, initiation of dialysis for uremic symptoms, volume overload or hypertension, or for other/unknown reasons were associated with 1.12 (95% CI, 0.72–1.77), 1.71 (95% CI, 1.03–2.84), and 1.28 (95% CI, 0.73–2.26) times higher risk, respectively, for subsequent mortality compared to initiation for laboratory evidence of kidney function decline. Limitations Possibility of residual confounding by unmeasured variables; reliance on clinical documentation to ascertain exposure Conclusions Patients initiating dialysis due to volume overload may have increased risk for mortality compared to patients initiating dialysis due to laboratory evidence of kidney function decline. Further studies are needed to identify and test interventions that might reduce this risk. PMID:27637132

Etiology and clinical presentation of birth defects: population based study

PubMed Central

Carey, John C; Byrne, Janice L B; Krikov, Sergey; Botto, Lorenzo D

2017-01-01

Objective To assess causation and clinical presentation of major birth defects. Design Population based case cohort. Setting Cases of birth defects in children born 2005-09 to resident women, ascertained through Utah’s population based surveillance system. All records underwent clinical re-review. Participants 5504 cases among 270 878 births (prevalence 2.03%), excluding mild isolated conditions (such as muscular ventricular septal defects, distal hypospadias). Main outcome measures The primary outcomes were the proportion of birth defects with a known etiology (chromosomal, genetic, human teratogen, twinning) or unknown etiology, by morphology (isolated, multiple, minors only), and by pathogenesis (sequence, developmental field defect, or known pattern of birth defects). Results Definite cause was assigned in 20.2% (n=1114) of cases: chromosomal or genetic conditions accounted for 94.4% (n=1052), teratogens for 4.1% (n=46, mostly poorly controlled pregestational diabetes), and twinning for 1.4% (n=16, conjoined or acardiac). The 79.8% (n=4390) remaining were classified as unknown etiology; of these 88.2% (n=3874) were isolated birth defects. Family history (similarly affected first degree relative) was documented in 4.8% (n=266). In this cohort, 92.1% (5067/5504) were live born infants (isolated and non-isolated birth defects): 75.3% (4147/5504) were classified as having an isolated birth defect (unknown or known etiology). Conclusions These findings underscore the gaps in our knowledge regarding the causes of birth defects. For the causes that are known, such as smoking or diabetes, assigning causation in individual cases remains challenging. Nevertheless, the ongoing impact of these exposures on fetal development highlights the urgency and benefits of population based preventive interventions. For the causes that are still unknown, better strategies are needed. These can include greater integration of the key elements of etiology, morphology, and pathogenesis into epidemiologic studies; greater collaboration between researchers (such as developmental biologists), clinicians (such as medical geneticists), and epidemiologists; and better ways to objectively measure fetal exposures (beyond maternal self reports) and closer (prenatally) to the critical period of organogenesis. PMID:28559234

Design and analysis of a spectro-angular surface plasmon resonance biosensor operating in the visible spectrum

NASA Astrophysics Data System (ADS)

Filion-Côté, Sandrine; Roche, Philip J. R.; Foudeh, Amir M.; Tabrizian, Maryam; Kirk, Andrew G.

2014-09-01

Surface plasmon resonance (SPR) sensing is one of the most widely used methods to implement biosensing due to its sensitivity and capacity for label-free detection. Whilst most commercial SPR sensors operate in the angular regime, it has recently been shown that an increase in sensitivity and a greater robustness against noise can be achieved by measuring the reflectivity when varying both the angle and wavelength simultaneously, in a so-called spectro-angular SPR biosensor. A single value decomposition method is used to project the two-dimensional spectro-angular reflection signal onto a basis set and allow the image obtained from an unknown refractive index sample to be compared very accurately with a pre-calculated reference set. Herein we demonstrate that a previously reported system operated in the near infra-red has a lower detection limit when operating in the visible spectrum due to the improved spatial resolution and numerical precision of the image sensor. The SPR biosensor presented here has an experimental detection limit of 9.8 × 10-7 refractive index unit. To validate the system as a biosensor, we also performed the detection of synthetic RNA from pathogenic Legionella pneumophila with the developed biosensing platform.

Effects of a Word-Learning Training on Children With Cochlear Implants

PubMed Central

Lund, Emily

2014-01-01

Preschool children with hearing loss who use cochlear implants demonstrate vocabulary delays when compared to their peers without hearing loss. These delays may be a result of deficient word-learning abilities; children with cochlear implants perform more poorly on rapid word-learning tasks than children with normal hearing. This study explored the malleability of rapid word learning of preschoolers with cochlear implants by evaluating the effects of a word-learning training on rapid word learning. A single-subject, multiple probe design across participants measured the impact of the training on children’s rapid word-learning performance. Participants included 5 preschool children with cochlear implants who had an expressive lexicon of less than 150 words. An investigator guided children to identify, repeat, and learn about unknown sets of words in 2-weekly sessions across 10 weeks. The probe measure, a rapid word-learning task with a different set of words than those taught during training, was collected in the baseline, training, and maintenance conditions. All participants improved their receptive rapid word-learning performance in the training condition. The functional relation indicates that the receptive rapid word-learning performance of children with cochlear implants is malleable. PMID:23981321

Serial analysis of gene expression (SAGE) in bovine trypanotolerance: preliminary results

PubMed Central

2003-01-01

In Africa, trypanosomosis is a tsetse-transmitted disease which represents the most important constraint to livestock production. Several indigenous West African taurine (Bos taurus) breeds, such as the Longhorn (N'Dama) cattle are well known to control trypanosome infections. This genetic ability named "trypanotolerance" results from various biological mechanisms under multigenic control. The methodologies used so far have not succeeded in identifying the complete pool of genes involved in trypanotolerance. New post genomic biotechnologies such as transcriptome analyses are efficient in characterising the pool of genes involved in the expression of specific biological functions. We used the serial analysis of gene expression (SAGE) technique to construct, from Peripheral Blood Mononuclear Cells of an N'Dama cow, 2 total mRNA transcript libraries, at day 0 of a Trypanosoma congolense experimental infection and at day 10 post-infection, corresponding to the peak of parasitaemia. Bioinformatic comparisons in the bovine genomic databases allowed the identification of 187 up- and down- regulated genes, EST and unknown functional genes. Identification of the genes involved in trypanotolerance will allow to set up specific microarray sets for further metabolic and pharmacological studies and to design field marker-assisted selection by introgression programmes. PMID:12927079

Serial analysis of gene expression (SAGE) in bovine trypanotolerance: preliminary results.

PubMed

Berthier, David; Quéré, Ronan; Thevenon, Sophie; Belemsaga, Désiré; Piquemal, David; Marti, Jacques; Maillard, Jean-Charles

2003-01-01

In Africa, trypanosomosis is a tsetse-transmitted disease which represents the most important constraint to livestock production. Several indigenous West African taurine Bos taurus) breeds, such as the Longhorn (N'Dama) cattle are well known to control trypanosome infections. This genetic ability named "trypanotolerance" results from various biological mechanisms under multigenic control. The methodologies used so far have not succeeded in identifying the complete pool of genes involved in trypanotolerance. New post genomic biotechnologies such as transcriptome analyses are efficient in characterising the pool of genes involved in the expression of specific biological functions. We used the serial analysis of gene expression (SAGE) technique to construct, from Peripheral Blood Mononuclear Cells of an N'Dama cow, 2 total mRNA transcript libraries, at day 0 of a Trypanosoma congolense experimental infection and at day 10 post-infection, corresponding to the peak of parasitaemia. Bioinformatic comparisons in the bovine genomic databases allowed the identification of 187 up- and down- regulated genes, EST and unknown functional genes. Identification of the genes involved in trypanotolerance will allow to set up specific microarray sets for further metabolic and pharmacological studies and to design field marker-assisted selection by introgression programmes.

MoCha: Molecular Characterization of Unknown Pathways.

PubMed

Lobo, Daniel; Hammelman, Jennifer; Levin, Michael

2016-04-01

Automated methods for the reverse-engineering of complex regulatory networks are paving the way for the inference of mechanistic comprehensive models directly from experimental data. These novel methods can infer not only the relations and parameters of the known molecules defined in their input datasets, but also unknown components and pathways identified as necessary by the automated algorithms. Identifying the molecular nature of these unknown components is a crucial step for making testable predictions and experimentally validating the models, yet no specific and efficient tools exist to aid in this process. To this end, we present here MoCha (Molecular Characterization), a tool optimized for the search of unknown proteins and their pathways from a given set of known interacting proteins. MoCha uses the comprehensive dataset of protein-protein interactions provided by the STRING database, which currently includes more than a billion interactions from over 2,000 organisms. MoCha is highly optimized, performing typical searches within seconds. We demonstrate the use of MoCha with the characterization of unknown components from reverse-engineered models from the literature. MoCha is useful for working on network models by hand or as a downstream step of a model inference engine workflow and represents a valuable and efficient tool for the characterization of unknown pathways using known data from thousands of organisms. MoCha and its source code are freely available online under the GPLv3 license.

New insight into pecan boron nutrition

USDA-ARS?s Scientific Manuscript database

Alternate bearing by individual pecan [Carya illinoinensis (Wangenh.) K. Koch] trees is problematic for nut producers and processors. There are many unknowns regarding alternate bearing physiology, such as the relationship between boron and fruit set, nutmeat quality, and kernel maladies. Evidence...

Binding Free Energy Calculations for Lead Optimization: Assessment of Their Accuracy in an Industrial Drug Design Context.

PubMed

Homeyer, Nadine; Stoll, Friederike; Hillisch, Alexander; Gohlke, Holger

2014-08-12

Correctly ranking compounds according to their computed relative binding affinities will be of great value for decision making in the lead optimization phase of industrial drug discovery. However, the performance of existing computationally demanding binding free energy calculation methods in this context is largely unknown. We analyzed the performance of the molecular mechanics continuum solvent, the linear interaction energy (LIE), and the thermodynamic integration (TI) approach for three sets of compounds from industrial lead optimization projects. The data sets pose challenges typical for this early stage of drug discovery. None of the methods was sufficiently predictive when applied out of the box without considering these challenges. Detailed investigations of failures revealed critical points that are essential for good binding free energy predictions. When data set-specific features were considered accordingly, predictions valuable for lead optimization could be obtained for all approaches but LIE. Our findings lead to clear recommendations for when to use which of the above approaches. Our findings also stress the important role of expert knowledge in this process, not least for estimating the accuracy of prediction results by TI, using indicators such as the size and chemical structure of exchanged groups and the statistical error in the predictions. Such knowledge will be invaluable when it comes to the question which of the TI results can be trusted for decision making.

Addition of Escherichia coli K-12 growth observation and gene essentiality data to the EcoCyc database.

PubMed

Mackie, Amanda; Paley, Suzanne; Keseler, Ingrid M; Shearer, Alexander; Paulsen, Ian T; Karp, Peter D

2014-03-01

The sets of compounds that can support growth of an organism are defined by the presence of transporters and metabolic pathways that convert nutrient sources into cellular components and energy for growth. A collection of known nutrient sources can therefore serve both as an impetus for investigating new metabolic pathways and transporters and as a reference for computational modeling of known metabolic pathways. To establish such a collection for Escherichia coli K-12, we have integrated data on the growth or nongrowth of E. coli K-12 obtained from published observations using a variety of individual media and from high-throughput phenotype microarrays into the EcoCyc database. The assembled collection revealed a substantial number of discrepancies between the high-throughput data sets, which we investigated where possible using low-throughput growth assays on soft agar and in liquid culture. We also integrated six data sets describing 16,119 observations of the growth of single-gene knockout mutants of E. coli K-12 into EcoCyc, which are relevant to antimicrobial drug design, provide clues regarding the roles of genes of unknown function, and are useful for validating metabolic models. To make this information easily accessible to EcoCyc users, we developed software for capturing, querying, and visualizing cellular growth assays and gene essentiality data.

Effects of 4-Week Training Intervention with Unknown Loads on Power Output Performance and Throwing Velocity in Junior Team Handball Players.

PubMed

Sabido, Rafael; Hernández-Davó, Jose Luis; Botella, Javier; Moya, Manuel

2016-01-01

To compare the effect of 4-week unknown vs known loads strength training intervention on power output performance and throwing velocity in junior team handball players. Twenty-eight junior team-handball players (17.2 ± 0.6 years, 1.79 ± 0.07 m, 75.6 ± 9.4 kg)were divided into two groups (unknown loads: UL; known loads: KL). Both groups performed two sessions weekly consisting of four sets of six repetitions of the bench press throw exercise, using the 30%, 50% and 70% of subjects' individual 1 repetition maximum (1RM). In each set, two repetitions with each load were performed, but the order of the loads was randomised. In the KL group, researchers told the subjects the load to mobilise prior each repetition, while in the UL group, researchers did not provide any information. Maximal dynamic strength (1RM bench press), power output (with 30, 50 and 70% of 1RM) and throwing velocity (7 m standing throw and 9 m jumping throw) were assessed pre- and post-training intervention. Both UL and KL group improved similarly their 1RM bench press as well as mean and peak power with all loads. There were significant improvements in power developed in all the early time intervals measured (150 ms) with the three loads (30, 50, 70% 1RM) in the UL group, while KL only improved with 30% 1RM (all the time intervals) and with 70% 1RM (at certain time intervals). Only the UL group improved throwing velocity in both standing (4.7%) and jumping (5.3%) throw (p > 0.05). The use of unknown loads has led to greater gains in power output in the early time intervals as well as to increases in throwing velocity compared with known loads. Therefore unknown loads are of significant practical use to increase both strength and in-field performance in a short period of training.

Information spread in networks: Games, optimal control, and stabilization

NASA Astrophysics Data System (ADS)

Khanafer, Ali

This thesis focuses on designing efficient mechanisms for controlling information spread in networks. We consider two models for information spread. The first one is the well-known distributed averaging dynamics. The second model is a nonlinear one that describes virus spread in computer and biological networks. We seek to design optimal, robust, and stabilizing controllers under practical constraints. For distributed averaging networks, we study the interaction between a network designer and an adversary. We consider two types of attacks on the network. In Attack-I, the adversary strategically disconnects a set of links to prevent the nodes from reaching consensus. Meanwhile, the network designer assists the nodes in reaching consensus by changing the weights of a limited number of links in the network. We formulate two problems to describe this competition where the order in which the players act is reversed in the two problems. Although the canonical equations provided by the Pontryagin's Maximum Principle (MP) seem to be intractable, we provide an alternative characterization for the optimal strategies that makes connection to potential theory. Further, we provide a sufficient condition for the existence of a saddle-point equilibrium (SPE) for the underlying zero-sum game. In Attack-II, the designer and the adversary are both capable of altering the measurements of all nodes in the network by injecting global signals. We impose two constraints on both players: a power constraint and an energy constraint. We assume that the available energy to each player is not sufficient to operate at maximum power throughout the horizon of the game. We show the existence of an SPE and derive the optimal strategies in closed form for this attack scenario. As an alternative to the "network designer vs. adversary" framework, we investigate the possibility of stabilizing unknown network diffusion processes using a distributed mechanism, where the uncertainty is due to an attack on the network. To this end, we propose a distributed version of the classical logic-based supervisory control scheme. Given a network of agents whose dynamics contain unknown parameters, the distributed supervisory control scheme is used to assist the agents to converge to a certain set-point without requiring them to have explicit knowledge of that set-point. Unlike the classical supervisory control scheme where a centralized supervisor makes switching decisions among the candidate controllers, in our scheme, each agent is equipped with a local supervisor that switches among the available controllers. The switching decisions made at a certain agent depend only on the information from its neighboring agents. We provide sufficient conditions for stabilization and apply our framework to the distributed averaging problem in the presence of large modeling uncertainty. For infected networks, we study the stability properties of a susceptible-infected-susceptible (SIS) diffusion model, so-called the n-intertwined Markov model, over arbitrary network topologies. Similar to the majority of infection spread dynamics, this model exhibits a threshold phenomenon. When the curing rates in the network are high, the all-healthy state is the unique equilibrium over the network. Otherwise, an endemic equilibrium state emerges, where some infection remains within the network. Using notions from positive systems theory, we provide conditions for the global asymptotic stability of the equilibrium points in both cases over strongly and weakly connected directed networks based on the value of the basic reproduction number, a fundamental quantity in the study of epidemics. Furthermore, we demonstrate that the n-intertwined Markov model can be viewed as a best-response dynamical system of a concave game among the nodes. This characterization allows us to cast new infection spread dynamics; additionally, we provide a sufficient condition, for the global convergence to the all-healthy state, that can be checked in a distributed fashion. Moreover, we investigate the problem of stabilizing the network when the curing rates of a limited number of nodes can be controlled. In particular, we characterize the number of controllers required for a class of undirected graphs. We also design optimal controllers capable of minimizing the total infection in the network at minimum cost. Finally, we outline a set of open problems in the area of information spread control.

34 CFR Appendix to Part 5 - Unknown Title

Code of Federal Regulations, 2010 CFR

2010-07-01

... the Department. Research protocol, design, processing, and other technical information to the extent... report submitted for comment prior to acceptance. Research protocol, design, processing, and other...-10) Pt. 5, App. Appendix to Part 5 [The following are some examples of specific records (or specific...

Robust approximation-free prescribed performance control for nonlinear systems and its application

NASA Astrophysics Data System (ADS)

Sun, Ruisheng; Na, Jing; Zhu, Bin

2018-02-01

This paper presents a robust prescribed performance control approach and its application to nonlinear tail-controlled missile systems with unknown dynamics and uncertainties. The idea of prescribed performance function (PPF) is incorporated into the control design, such that both the steady-state and transient control performance can be strictly guaranteed. Unlike conventional PPF-based control methods, we further tailor a recently proposed systematic control design procedure (i.e. approximation-free control) using the transformed tracking error dynamics, which provides a proportional-like control action. Hence, the function approximators (e.g. neural networks, fuzzy systems) that are widely used to address the unknown nonlinearities in the nonlinear control designs are not needed. The proposed control design leads to a robust yet simplified function approximation-free control for nonlinear systems. The closed-loop system stability and the control error convergence are all rigorously proved. Finally, comparative simulations are conducted based on nonlinear missile systems to validate the improved response and the robustness of the proposed control method.

Formation tracker design of multiple mobile robots with wheel perturbations: adaptive output-feedback approach

NASA Astrophysics Data System (ADS)

Yoo, Sung Jin

2016-11-01

This paper presents a theoretical design approach for output-feedback formation tracking of multiple mobile robots under wheel perturbations. It is assumed that these perturbations are unknown and the linear and angular velocities of the robots are unmeasurable. First, adaptive state observers for estimating unmeasurable velocities of the robots are developed under the robots' kinematics and dynamics including wheel perturbation effects. Then, we derive a virtual-structure-based formation tracker scheme according to the observer dynamic surface design procedure. The main difficulty of the output-feedback control design is to manage the coupling problems between unmeasurable velocities and unknown wheel perturbation effects. These problems are avoided by using the adaptive technique and the function approximation property based on fuzzy logic systems. From the Lyapunov stability analysis, it is shown that point tracking errors of each robot and synchronisation errors for the desired formation converge to an adjustable neighbourhood of the origin, while all signals in the controlled closed-loop system are semiglobally uniformly ultimately bounded.

Analytical solution of tt¯ dilepton equations

NASA Astrophysics Data System (ADS)

Sonnenschein, Lars

2006-03-01

The top quark antiquark production system in the dilepton decay channel is described by a set of equations which is nonlinear in the unknown neutrino momenta. Its most precise and least time consuming solution is of major importance for measurements of top quark properties like the top quark mass and tt¯ spin correlations. The initial system of equations can be transformed into two polynomial equations with two unknowns by means of elementary algebraic operations. These two polynomials of multidegree two can be reduced to one univariate polynomial of degree four by means of resultants. The obtained quartic equation is solved analytically.

From Intensity Profile to Surface Normal: Photometric Stereo for Unknown Light Sources and Isotropic Reflectances.

PubMed

Lu, Feng; Matsushita, Yasuyuki; Sato, Imari; Okabe, Takahiro; Sato, Yoichi

2015-10-01

We propose an uncalibrated photometric stereo method that works with general and unknown isotropic reflectances. Our method uses a pixel intensity profile, which is a sequence of radiance intensities recorded at a pixel under unknown varying directional illumination. We show that for general isotropic materials and uniformly distributed light directions, the geodesic distance between intensity profiles is linearly related to the angular difference of their corresponding surface normals, and that the intensity distribution of the intensity profile reveals reflectance properties. Based on these observations, we develop two methods for surface normal estimation; one for a general setting that uses only the recorded intensity profiles, the other for the case where a BRDF database is available while the exact BRDF of the target scene is still unknown. Quantitative and qualitative evaluations are conducted using both synthetic and real-world scenes, which show the state-of-the-art accuracy of smaller than 10 degree without using reference data and 5 degree with reference data for all 100 materials in MERL database.

Teaching-learning-based Optimization Algorithm for Parameter Identification in the Design of IIR Filters

NASA Astrophysics Data System (ADS)

Singh, R.; Verma, H. K.

2013-12-01

This paper presents a teaching-learning-based optimization (TLBO) algorithm to solve parameter identification problems in the designing of digital infinite impulse response (IIR) filter. TLBO based filter modelling is applied to calculate the parameters of unknown plant in simulations. Unlike other heuristic search algorithms, TLBO algorithm is an algorithm-specific parameter-less algorithm. In this paper big bang-big crunch (BB-BC) optimization and PSO algorithms are also applied to filter design for comparison. Unknown filter parameters are considered as a vector to be optimized by these algorithms. MATLAB programming is used for implementation of proposed algorithms. Experimental results show that the TLBO is more accurate to estimate the filter parameters than the BB-BC optimization algorithm and has faster convergence rate when compared to PSO algorithm. TLBO is used where accuracy is more essential than the convergence speed.

Robust Control Design for Uncertain Nonlinear Dynamic Systems

NASA Technical Reports Server (NTRS)

Kenny, Sean P.; Crespo, Luis G.; Andrews, Lindsey; Giesy, Daniel P.

2012-01-01

Robustness to parametric uncertainty is fundamental to successful control system design and as such it has been at the core of many design methods developed over the decades. Despite its prominence, most of the work on robust control design has focused on linear models and uncertainties that are non-probabilistic in nature. Recently, researchers have acknowledged this disparity and have been developing theory to address a broader class of uncertainties. This paper presents an experimental application of robust control design for a hybrid class of probabilistic and non-probabilistic parametric uncertainties. The experimental apparatus is based upon the classic inverted pendulum on a cart. The physical uncertainty is realized by a known additional lumped mass at an unknown location on the pendulum. This unknown location has the effect of substantially altering the nominal frequency and controllability of the nonlinear system, and in the limit has the capability to make the system neutrally stable and uncontrollable. Another uncertainty to be considered is a direct current motor parameter. The control design objective is to design a controller that satisfies stability, tracking error, control power, and transient behavior requirements for the largest range of parametric uncertainties. This paper presents an overview of the theory behind the robust control design methodology and the experimental results.

Dose uncertainties associated with a set density override of unknown hip prosthetic composition.

PubMed

Rijken, James D; Colyer, Christopher J

2017-09-01

The dosimetric uncertainties associated with radiotherapy through hip prostheses while overriding the implant to a set density within the TPS has not yet been reported. In this study, the uncertainty in dose within a PTV resulting from this planning choice was investigated. A set of metallic hip prosthetics (stainless steel, titanium, and two different Co-Cr-Mo alloys) were CT scanned in a water bath. Within the TPS, the prosthetic pieces were overridden to densities between 3 and 10 g/cm 3 and irradiated on a linear accelerator. Measured dose maps were compared to the TPS to determine which density was most appropriate to override each metal. This was shown to be in disagreement with the reported literature values of density which was attributed to the TPS dose calculation algorithm and total mass attenuation coefficient differences in water and metal. The dose difference was then calculated for a set density override of 6 g/cm 3 in the TPS and used to estimate the dose uncertainty beyond the prosthesis. For beams passing through an implant, the dosimetric uncertainty in regions of the PTV may be as high as 10% if the implant composition remains unknown and a set density override is used. These results highlight limitations of such assumptions and the need for careful consideration by radiation oncologist, therapist, and physics staff. © 2017 Adelaide Radiotherapy Centre. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Perceived Frequency of Peer-Assisted Learning in the Laboratory and Collegiate Clinical Settings

PubMed Central

Henning, Jolene M.; Weidner, Thomas G.; Snyder, Melissa; Dudley, William N.

2012-01-01

Context: Peer-assisted learning (PAL) has been recommended as an educational strategy to improve students' skill acquisition and supplement the role of the clinical instructor (CI). How frequently students actually engage in PAL in different settings is unknown. Objective: To determine the perceived frequency of planned and unplanned PAL (peer modeling, peer feedback and assessment, peer mentoring) in different settings. Design: Cross-sectional study. Setting: Laboratory and collegiate clinical settings. Patients or Other Participants: A total of 933 students, 84 administrators, and 208 CIs representing 52 (15%) accredited athletic training education programs. Intervention(s): Three versions (student, CI, administrator) of the Athletic Training Peer Assisted Learning Survey (AT-PALS) were administered. Cronbach α values ranged from .80 to .90. Main Outcome Measure(s): Administrators' and CIs' perceived frequency of 3 PAL categories under 2 conditions (planned, unplanned) and in 2 settings (instructional laboratory, collegiate clinical). Self-reported frequency of students' engagement in 3 categories of PAL in 2 settings. Results: Administrators and CIs perceived that unplanned PAL (0.39 ± 0.22) occurred more frequently than planned PAL (0.29 ± 0.19) regardless of category or setting (F1,282 = 83.48, P < .001). They perceived that PAL occurred more frequently in the collegiate clinical (0.46 ± 0.22) than laboratory (0.21 ± 0.24) setting regardless of condition or category (F1,282 = 217.17, P < .001). Students reported engaging in PAL more frequently in the collegiate clinical (3.31 ± 0.56) than laboratory (3.26 ± 0.62) setting regardless of category (F1,860 = 13.40, P < .001). We found a main effect for category (F2,859 = 1318.02, P < .001), with students reporting they engaged in peer modeling (4.01 ± 0.60) more frequently than peer mentoring (2.99 ± 0.88) (P < .001) and peer assessment and feedback (2.86 ± 0.64) (P < .001). Conclusions: Participants perceived that students engage in unplanned PAL in the collegiate clinical setting with a stronger inclination toward engagement in peer modeling. Educators should develop planned PAL activities to capitalize on the inherent desire of the students to collaborate with their peers. PMID:22488288

Target Capturing Control for Space Robots with Unknown Mass Properties: A Self-Tuning Method Based on Gyros and Cameras.

PubMed

Li, Zhenyu; Wang, Bin; Liu, Hong

2016-08-30

Satellite capturing with free-floating space robots is still a challenging task due to the non-fixed base and unknown mass property issues. In this paper gyro and eye-in-hand camera data are adopted as an alternative choice for solving this problem. For this improved system, a new modeling approach that reduces the complexity of system control and identification is proposed. With the newly developed model, the space robot is equivalent to a ground-fixed manipulator system. Accordingly, a self-tuning control scheme is applied to handle such a control problem including unknown parameters. To determine the controller parameters, an estimator is designed based on the least-squares technique for identifying the unknown mass properties in real time. The proposed method is tested with a credible 3-dimensional ground verification experimental system, and the experimental results confirm the effectiveness of the proposed control scheme.

Target Capturing Control for Space Robots with Unknown Mass Properties: A Self-Tuning Method Based on Gyros and Cameras

PubMed Central

Li, Zhenyu; Wang, Bin; Liu, Hong

2016-01-01

Satellite capturing with free-floating space robots is still a challenging task due to the non-fixed base and unknown mass property issues. In this paper gyro and eye-in-hand camera data are adopted as an alternative choice for solving this problem. For this improved system, a new modeling approach that reduces the complexity of system control and identification is proposed. With the newly developed model, the space robot is equivalent to a ground-fixed manipulator system. Accordingly, a self-tuning control scheme is applied to handle such a control problem including unknown parameters. To determine the controller parameters, an estimator is designed based on the least-squares technique for identifying the unknown mass properties in real time. The proposed method is tested with a credible 3-dimensional ground verification experimental system, and the experimental results confirm the effectiveness of the proposed control scheme. PMID:27589748

Nonlinear unbiased minimum-variance filter for Mars entry autonomous navigation under large uncertainties and unknown measurement bias.

PubMed

Xiao, Mengli; Zhang, Yongbo; Fu, Huimin; Wang, Zhihua

2018-05-01

High-precision navigation algorithm is essential for the future Mars pinpoint landing mission. The unknown inputs caused by large uncertainties of atmospheric density and aerodynamic coefficients as well as unknown measurement biases may cause large estimation errors of conventional Kalman filters. This paper proposes a derivative-free version of nonlinear unbiased minimum variance filter for Mars entry navigation. This filter has been designed to solve this problem by estimating the state and unknown measurement biases simultaneously with derivative-free character, leading to a high-precision algorithm for the Mars entry navigation. IMU/radio beacons integrated navigation is introduced in the simulation, and the result shows that with or without radio blackout, our proposed filter could achieve an accurate state estimation, much better than the conventional unscented Kalman filter, showing the ability of high-precision Mars entry navigation algorithm. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Searching for 'Unknown Unknowns'

NASA Technical Reports Server (NTRS)

Parsons, Vickie S.

2005-01-01

The NASA Engineering and Safety Center (NESC) was established to improve safety through engineering excellence within NASA programs and projects. As part of this goal, methods are being investigated to enable the NESC to become proactive in identifying areas that may be precursors to future problems. The goal is to find unknown indicators of future problems, not to duplicate the program-specific trending efforts. The data that is critical for detecting these indicators exist in a plethora of dissimilar non-conformance and other databases (without a common format or taxonomy). In fact, much of the data is unstructured text. However, one common database is not required if the right standards and electronic tools are employed. Electronic data mining is a particularly promising tool for this effort into unsupervised learning of common factors. This work in progress began with a systematic evaluation of available data mining software packages, based on documented decision techniques using weighted criteria. The four packages, which were perceived to have the most promise for NASA applications, are being benchmarked and evaluated by independent contractors. Preliminary recommendations for "best practices" in data mining and trending are provided. Final results and recommendations should be available in the Fall 2005. This critical first step in identifying "unknown unknowns" before they become problems is applicable to any set of engineering or programmatic data.

35. Photocopy of photograph (original print located in LBNL Photo ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

35. Photocopy of photograph (original print located in LBNL Photo Lab Collection). Photographer unknown. April 27, 1960. BEV-2050. CLYDE WIEGAND; ANTI-PROTON SET-UP. B-51. - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

32. Photocopy of photograph (original print located in LBNL Photo ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

32. Photocopy of photograph (original print located in LBNL Photo Lab Collection). Photographer unknown. October 6, 1955. BEV-937. ANTI-PROTON SET-UP, EXTERIOR VIEW. B-51. - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

31. Photocopy of photograph (original print located in LBNL Photo ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

31. Photocopy of photograph (original print located in LBNL Photo Lab Collection). Photographer unknown. October 6, 1955. BEV-933. ANTI-PROTON SET-UP, INTERIOR VIEW. B-51. - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

Backstepping Design of Adaptive Neural Fault-Tolerant Control for MIMO Nonlinear Systems.

PubMed

Gao, Hui; Song, Yongduan; Wen, Changyun

In this paper, an adaptive controller is developed for a class of multi-input and multioutput nonlinear systems with neural networks (NNs) used as a modeling tool. It is shown that all the signals in the closed-loop system with the proposed adaptive neural controller are globally uniformly bounded for any external input in . In our control design, the upper bound of the NN modeling error and the gains of external disturbance are characterized by unknown upper bounds, which is more rational to establish the stability in the adaptive NN control. Filter-based modification terms are used in the update laws of unknown parameters to improve the transient performance. Finally, fault-tolerant control is developed to accommodate actuator failure. An illustrative example applying the adaptive controller to control a rigid robot arm shows the validation of the proposed controller.In this paper, an adaptive controller is developed for a class of multi-input and multioutput nonlinear systems with neural networks (NNs) used as a modeling tool. It is shown that all the signals in the closed-loop system with the proposed adaptive neural controller are globally uniformly bounded for any external input in . In our control design, the upper bound of the NN modeling error and the gains of external disturbance are characterized by unknown upper bounds, which is more rational to establish the stability in the adaptive NN control. Filter-based modification terms are used in the update laws of unknown parameters to improve the transient performance. Finally, fault-tolerant control is developed to accommodate actuator failure. An illustrative example applying the adaptive controller to control a rigid robot arm shows the validation of the proposed controller.

The Protein Interactome of Mycobacteriophage Giles Predicts Functions for Unknown Proteins.

PubMed

Mehla, Jitender; Dedrick, Rebekah M; Caufield, J Harry; Siefring, Rachel; Mair, Megan; Johnson, Allison; Hatfull, Graham F; Uetz, Peter

2015-08-01

Mycobacteriophages are viruses that infect mycobacterial hosts and are prevalent in the environment. Nearly 700 mycobacteriophage genomes have been completely sequenced, revealing considerable diversity and genetic novelty. Here, we have determined the protein complement of mycobacteriophage Giles by mass spectrometry and mapped its genome-wide protein interactome to help elucidate the roles of its 77 predicted proteins, 50% of which have no known function. About 22,000 individual yeast two-hybrid (Y2H) tests with four different Y2H vectors, followed by filtering and retest screens, resulted in 324 reproducible protein-protein interactions, including 171 (136 nonredundant) high-confidence interactions. The complete set of high-confidence interactions among Giles proteins reveals new mechanistic details and predicts functions for unknown proteins. The Giles interactome is the first for any mycobacteriophage and one of just five known phage interactomes so far. Our results will help in understanding mycobacteriophage biology and aid in development of new genetic and therapeutic tools to understand Mycobacterium tuberculosis. Mycobacterium tuberculosis causes over 9 million new cases of tuberculosis each year. Mycobacteriophages, viruses of mycobacterial hosts, hold considerable potential to understand phage diversity, evolution, and mycobacterial biology, aiding in the development of therapeutic tools to control mycobacterial infections. The mycobacteriophage Giles protein-protein interaction network allows us to predict functions for unknown proteins and shed light on major biological processes in phage biology. For example, Giles gp76, a protein of unknown function, is found to associate with phage packaging and maturation. The functions of mycobacteriophage-derived proteins may suggest novel therapeutic approaches for tuberculosis. Our ORFeome clone set of Giles proteins and the interactome data will be useful resources for phage interactomics. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Effectively identifying compound-protein interactions by learning from positive and unlabeled examples.

PubMed

Cheng, Zhanzhan; Zhou, Shuigeng; Wang, Yang; Liu, Hui; Guan, Jihong; Chen, Yi-Ping Phoebe

2016-05-18

Prediction of compound-protein interactions (CPIs) is to find new compound-protein pairs where a protein is targeted by at least a compound, which is a crucial step in new drug design. Currently, a number of machine learning based methods have been developed to predict new CPIs in the literature. However, as there is not yet any publicly available set of validated negative CPIs, most existing machine learning based approaches use the unknown interactions (not validated CPIs) selected randomly as the negative examples to train classifiers for predicting new CPIs. Obviously, this is not quite reasonable and unavoidably impacts the CPI prediction performance. In this paper, we simply take the unknown CPIs as unlabeled examples, and propose a new method called PUCPI (the abbreviation of PU learning for Compound-Protein Interaction identification) that employs biased-SVM (Support Vector Machine) to predict CPIs using only positive and unlabeled examples. PU learning is a class of learning methods that leans from positive and unlabeled (PU) samples. To the best of our knowledge, this is the first work that identifies CPIs using only positive and unlabeled examples. We first collect known CPIs as positive examples and then randomly select compound-protein pairs not in the positive set as unlabeled examples. For each CPI/compound-protein pair, we extract protein domains as protein features and compound substructures as chemical features, then take the tensor product of the corresponding compound features and protein features as the feature vector of the CPI/compound-protein pair. After that, biased-SVM is employed to train classifiers on different datasets of CPIs and compound-protein pairs. Experiments over various datasets show that our method outperforms six typical classifiers, including random forest, L1- and L2-regularized logistic regression, naive Bayes, SVM and k-nearest neighbor (kNN), and three types of existing CPI prediction models. Source code, datasets and related documents of PUCPI are available at: http://admis.fudan.edu.cn/projects/pucpi.html.

An Efficient Solution Method for Multibody Systems with Loops Using Multiple Processors

NASA Technical Reports Server (NTRS)

Ghosh, Tushar K.; Nguyen, Luong A.; Quiocho, Leslie J.

2015-01-01

This paper describes a multibody dynamics algorithm formulated for parallel implementation on multiprocessor computing platforms using the divide-and-conquer approach. The system of interest is a general topology of rigid and elastic articulated bodies with or without loops. The algorithm divides the multibody system into a number of smaller sets of bodies in chain or tree structures, called "branches" at convenient joints called "connection points", and uses an Order-N (O (N)) approach to formulate the dynamics of each branch in terms of the unknown spatial connection forces. The equations of motion for the branches, leaving the connection forces as unknowns, are implemented in separate processors in parallel for computational efficiency, and the equations for all the unknown connection forces are synthesized and solved in one or several processors. The performances of two implementations of this divide-and-conquer algorithm in multiple processors are compared with an existing method implemented on a single processor.

Adaptive NN control for discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints.

PubMed

Chen, Weisheng

2009-07-01

This paper focuses on the problem of adaptive neural network tracking control for a class of discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints. Two novel state-feedback and output-feedback dynamic control laws are established where the function tanh(.) is employed to solve the saturation constraint problem. Implicit function theorem and mean value theorem are exploited to deal with non-affine variables that are used as actual control. Radial basis function neural networks are used to approximate the desired input function. Discrete Nussbaum gain is used to estimate the unknown sign of control gain. The uniform boundedness of all closed-loop signals is guaranteed. The tracking error is proved to converge to a small residual set around the origin. A simulation example is provided to illustrate the effectiveness of control schemes proposed in this paper.

Informal Consultations Provided to General Internists by the Gastroenterology Department of an HMO

PubMed Central

Pearson, Steven D; Moreno, Ricardo; Trnka, Yvona

1998-01-01

OBJECTIVE To study the process, outcomes, and time spent on informal consultations provided by gastroenterologists to the primary care general internists of an HMO. DESIGN Observational study. SETTING A large, urban staff-model HMO. PATIENTS/PARTICIPANTS Seven gastroenterologists constituting the total workforce of the gastroenterology department of the HMO. MEASUREMENTS AND MAIN RESULTS Data on 91 informal consultations were obtained, of which 55 (60%) involved the acute management of a patient with new symptoms or test results, and 36 (40%) were for questions related to nonacute diagnostic test selection or medical therapy. Questions regarding patients previously unknown to the gastroenterology department accounted for 74 (81%) of the consultations. Formal referral was recommended in only 16 (22%) of these cases. As judged by the time data gathered on the 91 consultations, the gastroenterologists spent approximately 7.2 hours per week to provide informal consultation for the entire HMO. CONCLUSIONS Gastroenterologists spend a significant amount of time providing informal consultation to their general internist colleagues in this HMO. The role informal consultation plays in the workload of physicians and in the clinical care of populations is an important question for health care system design, policy, and research. PMID:9686708

Operant conditioning: a minimal components requirement in artificial spiking neurons designed for bio-inspired robot's controller

PubMed Central

Cyr, André; Boukadoum, Mounir; Thériault, Frédéric

2014-01-01

In this paper, we investigate the operant conditioning (OC) learning process within a bio-inspired paradigm, using artificial spiking neural networks (ASNN) to act as robot brain controllers. In biological agents, OC results in behavioral changes learned from the consequences of previous actions, based on progressive prediction adjustment from rewarding or punishing signals. In a neurorobotics context, virtual and physical autonomous robots may benefit from a similar learning skill when facing unknown and unsupervised environments. In this work, we demonstrate that a simple invariant micro-circuit can sustain OC in multiple learning scenarios. The motivation for this new OC implementation model stems from the relatively complex alternatives that have been described in the computational literature and recent advances in neurobiology. Our elementary kernel includes only a few crucial neurons, synaptic links and originally from the integration of habituation and spike-timing dependent plasticity as learning rules. Using several tasks of incremental complexity, our results show that a minimal neural component set is sufficient to realize many OC procedures. Hence, with the proposed OC module, designing learning tasks with an ASNN and a bio-inspired robot context leads to simpler neural architectures for achieving complex behaviors. PMID:25120464

Application of discriminant analysis-based model for prediction of risk of low back disorders due to workplace design in industrial jobs.

PubMed

Ganga, G M D; Esposto, K F; Braatz, D

2012-01-01

The occupational exposure limits of different risk factors for development of low back disorders (LBDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors for LBDs interact in causing injury, since the nature and mechanism of these disorders are relatively unknown phenomena. Industrial ergonomists' role becomes further complicated because the potential risk factors that may contribute towards the onset of LBDs interact in a complex manner, which makes it difficult to discriminate in detail among the jobs that place workers at high or low risk of LBDs. The purpose of this paper was to develop a comparative study between predictions based on the neural network-based model proposed by Zurada, Karwowski & Marras (1997) and a linear discriminant analysis model, for making predictions about industrial jobs according to their potential risk of low back disorders due to workplace design. The results obtained through applying the discriminant analysis-based model proved that it is as effective as the neural network-based model. Moreover, the discriminant analysis-based model proved to be more advantageous regarding cost and time savings for future data gathering.

Distribution network design under demand uncertainty using genetic algorithm and Monte Carlo simulation approach: a case study in pharmaceutical industry

NASA Astrophysics Data System (ADS)

Izadi, Arman; Kimiagari, Ali mohammad

2014-01-01

Distribution network design as a strategic decision has long-term effect on tactical and operational supply chain management. In this research, the location-allocation problem is studied under demand uncertainty. The purposes of this study were to specify the optimal number and location of distribution centers and to determine the allocation of customer demands to distribution centers. The main feature of this research is solving the model with unknown demand function which is suitable with the real-world problems. To consider the uncertainty, a set of possible scenarios for customer demands is created based on the Monte Carlo simulation. The coefficient of variation of costs is mentioned as a measure of risk and the most stable structure for firm's distribution network is defined based on the concept of robust optimization. The best structure is identified using genetic algorithms and 14% reduction in total supply chain costs is the outcome. Moreover, it imposes the least cost variation created by fluctuation in customer demands (such as epidemic diseases outbreak in some areas of the country) to the logistical system. It is noteworthy that this research is done in one of the largest pharmaceutical distribution firms in Iran.

Distribution network design under demand uncertainty using genetic algorithm and Monte Carlo simulation approach: a case study in pharmaceutical industry

NASA Astrophysics Data System (ADS)

Izadi, Arman; Kimiagari, Ali Mohammad

2014-05-01

Distribution network design as a strategic decision has long-term effect on tactical and operational supply chain management. In this research, the location-allocation problem is studied under demand uncertainty. The purposes of this study were to specify the optimal number and location of distribution centers and to determine the allocation of customer demands to distribution centers. The main feature of this research is solving the model with unknown demand function which is suitable with the real-world problems. To consider the uncertainty, a set of possible scenarios for customer demands is created based on the Monte Carlo simulation. The coefficient of variation of costs is mentioned as a measure of risk and the most stable structure for firm's distribution network is defined based on the concept of robust optimization. The best structure is identified using genetic algorithms and 14 % reduction in total supply chain costs is the outcome. Moreover, it imposes the least cost variation created by fluctuation in customer demands (such as epidemic diseases outbreak in some areas of the country) to the logistical system. It is noteworthy that this research is done in one of the largest pharmaceutical distribution firms in Iran.

Operant conditioning: a minimal components requirement in artificial spiking neurons designed for bio-inspired robot's controller.

PubMed

Cyr, André; Boukadoum, Mounir; Thériault, Frédéric

2014-01-01

In this paper, we investigate the operant conditioning (OC) learning process within a bio-inspired paradigm, using artificial spiking neural networks (ASNN) to act as robot brain controllers. In biological agents, OC results in behavioral changes learned from the consequences of previous actions, based on progressive prediction adjustment from rewarding or punishing signals. In a neurorobotics context, virtual and physical autonomous robots may benefit from a similar learning skill when facing unknown and unsupervised environments. In this work, we demonstrate that a simple invariant micro-circuit can sustain OC in multiple learning scenarios. The motivation for this new OC implementation model stems from the relatively complex alternatives that have been described in the computational literature and recent advances in neurobiology. Our elementary kernel includes only a few crucial neurons, synaptic links and originally from the integration of habituation and spike-timing dependent plasticity as learning rules. Using several tasks of incremental complexity, our results show that a minimal neural component set is sufficient to realize many OC procedures. Hence, with the proposed OC module, designing learning tasks with an ASNN and a bio-inspired robot context leads to simpler neural architectures for achieving complex behaviors.

On the deterministic and stochastic use of hydrologic models

USGS Publications Warehouse

Farmer, William H.; Vogel, Richard M.

2016-01-01

Environmental simulation models, such as precipitation-runoff watershed models, are increasingly used in a deterministic manner for environmental and water resources design, planning, and management. In operational hydrology, simulated responses are now routinely used to plan, design, and manage a very wide class of water resource systems. However, all such models are calibrated to existing data sets and retain some residual error. This residual, typically unknown in practice, is often ignored, implicitly trusting simulated responses as if they are deterministic quantities. In general, ignoring the residuals will result in simulated responses with distributional properties that do not mimic those of the observed responses. This discrepancy has major implications for the operational use of environmental simulation models as is shown here. Both a simple linear model and a distributed-parameter precipitation-runoff model are used to document the expected bias in the distributional properties of simulated responses when the residuals are ignored. The systematic reintroduction of residuals into simulated responses in a manner that produces stochastic output is shown to improve the distributional properties of the simulated responses. Every effort should be made to understand the distributional behavior of simulation residuals and to use environmental simulation models in a stochastic manner.

Adaptive iterative learning control of a class of nonlinear time-delay systems with unknown backlash-like hysteresis input and control direction.

PubMed

Wei, Jianming; Zhang, Youan; Sun, Meimei; Geng, Baoliang

2017-09-01

This paper presents an adaptive iterative learning control scheme for a class of nonlinear systems with unknown time-varying delays and control direction preceded by unknown nonlinear backlash-like hysteresis. Boundary layer function is introduced to construct an auxiliary error variable, which relaxes the identical initial condition assumption of iterative learning control. For the controller design, integral Lyapunov function candidate is used, which avoids the possible singularity problem by introducing hyperbolic tangent funciton. After compensating for uncertainties with time-varying delays by combining appropriate Lyapunov-Krasovskii function with Young's inequality, an adaptive iterative learning control scheme is designed through neural approximation technique and Nussbaum function method. On the basis of the hyperbolic tangent function's characteristics, the system output is proved to converge to a small neighborhood of the desired trajectory by constructing Lyapunov-like composite energy function (CEF) in two cases, while keeping all the closed-loop signals bounded. Finally, a simulation example is presented to verify the effectiveness of the proposed approach. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

A 'range test' for determining scatterers with unknown physical properties

NASA Astrophysics Data System (ADS)

Potthast, Roland; Sylvester, John; Kusiak, Steven

2003-06-01

We describe a new scheme for determining the convex scattering support of an unknown scatterer when the physical properties of the scatterers are not known. The convex scattering support is a subset of the scatterer and provides information about its location and estimates for its shape. For convex polygonal scatterers the scattering support coincides with the scatterer and we obtain full shape reconstructions. The method will be formulated for the reconstruction of the scatterers from the far field pattern for one or a few incident waves. The method is non-iterative in nature and belongs to the type of recently derived generalized sampling schemes such as the 'no response test' of Luke-Potthast. The range test operates by testing whether it is possible to analytically continue a far field to the exterior of any test domain Omegatest. By intersecting the convex hulls of various test domains we can produce a minimal convex set, the convex scattering support of which must be contained in the convex hull of the support of any scatterer which produces that far field. The convex scattering support is calculated by testing the range of special integral operators for a sampling set of test domains. The numerical results can be used as an approximation for the support of the unknown scatterer. We prove convergence and regularity of the scheme and show numerical examples for sound-soft, sound-hard and medium scatterers. We can apply the range test to non-convex scatterers as well. We can conclude that an Omegatest which passes the range test has a non-empty intersection with the infinity-support (the complement of the unbounded component of the complement of the support) of the true scatterer, but cannot find a minimal set which must be contained therein.

Is CDX2 immunostaining useful for delineating anorectal from penile/vulvar squamous cancer in the setting of squamous cell carcinoma with clinically unknown primary site presenting with histologically confirmed inguinal lymph node metastasis?

PubMed

Gunia, Sven; Koch, Stefan; May, Matthias

2013-02-01

Penile, vulvar and anal squamous cell carcinomas (SCCs) share histomorphological overlap and are prone to lymphatic dissemination into inguinal nodes. Anal SCCs might derive from the anorectal zone (ARZ), anal transitional zone, squamous zone or from perianal skin. These anatomically distinct zones differ in terms of their embryological development. We sought to investigate the role of caudal-related homeobox 2 (CDX2), a homeobox gene implicated in the development and anterior/posterior pattern specification from duodenum to rectum including the ARZ, in terms of narrowing the possible sites of origin to be considered in the setting of SCC with unknown primary presenting with histologically confirmed inguinal lymph node metastasis. By immunohistochemistry (IHC) employing a panel of antibodies directed against CK5/6, CK7, CK20, p63, p16, CEA and CDX2, we compared 89 penile, 11 vulvar and eight anal SCCs with respect to their staining profiles. Moreover, anal SCCs were subjected to in situ hybridisation (ISH) for high-risk human papillomavirus (HPV) subtypes. By IHC, CDX2 expression was observed in 2/8 anal SCCs (25%) while being absent from all penile and vulvar SCCs examined. High-risk HPV subtypes were detected by ISH in all anal SCCs examined, which were uniformly p16-positive by IHC. CDX2 might be valuable in terms of narrowing the possible sites of origin to be considered in the setting of SCC with unknown primary presenting with inguinal lymph node metastasis. However, despite its favourable specificity, the diagnostic benefit achieved by this observation is limited by the low sensitivity.

Designing efficient nitrous oxide sampling strategies in agroecosystems using simulation models

USDA-ARS?s Scientific Manuscript database

Cumulative nitrous oxide (N2O) emissions calculated from discrete chamber-based flux measurements have unknown uncertainty. This study used an agroecosystems simulation model to design sampling strategies that yield accurate cumulative N2O flux estimates with a known uncertainty level. Daily soil N2...

Numerical Schemes for the Hamilton-Jacobi and Level Set Equations on Triangulated Domains

NASA Technical Reports Server (NTRS)

Barth, Timothy J.; Sethian, James A.

2006-01-01

Borrowing from techniques developed for conservation law equations, we have developed both monotone and higher order accurate numerical schemes which discretize the Hamilton-Jacobi and level set equations on triangulated domains. The use of unstructured meshes containing triangles (2D) and tetrahedra (3D) easily accommodates mesh adaptation to resolve disparate level set feature scales with a minimal number of solution unknowns. The minisymposium talk will discuss these algorithmic developments and present sample calculations using our adaptive triangulation algorithm applied to various moving interface problems such as etching, deposition, and curvature flow.

Aspect: A Formal Specification Language for Detecting Bugs

DTIC Science & Technology

1992-06-01

the Aspect state from Chapter 6 and, below it, the definition of the approximating state used by the checker. The additional component Multilocs marks...stages. First, each collection object in Multilocs is expanded into a set of objects whose dependency and value sets are subsets of those of the... Multilocs x Prelocs Env = Var ý7 PLoc x PSource Store = Loc x Aspect F-k Val x PSource Vat = Unknown + PLoc Aspect = PlainAspect + Pointer + Collection

Best strategies to implement clinical pathways in an emergency department setting: study protocol for a cluster randomized controlled trial

PubMed Central

2013-01-01

Background The clinical pathway is a tool that operationalizes best evidence recommendations and clinical practice guidelines in an accessible format for ‘point of care’ management by multidisciplinary health teams in hospital settings. While high-quality, expert-developed clinical pathways have many potential benefits, their impact has been limited by variable implementation strategies and suboptimal research designs. Best strategies for implementing pathways into hospital settings remain unknown. This study will seek to develop and comprehensively evaluate best strategies for effective local implementation of externally developed expert clinical pathways. Design/methods We will develop a theory-based and knowledge user-informed intervention strategy to implement two pediatric clinical pathways: asthma and gastroenteritis. Using a balanced incomplete block design, we will randomize 16 community emergency departments to receive the intervention for one clinical pathway and serve as control for the alternate clinical pathway, thus conducting two cluster randomized controlled trials to evaluate this implementation intervention. A minimization procedure will be used to randomize sites. Intervention sites will receive a tailored strategy to support full clinical pathway implementation. We will evaluate implementation strategy effectiveness through measurement of relevant process and clinical outcomes. The primary process outcome will be the presence of an appropriately completed clinical pathway on the chart for relevant patients. Primary clinical outcomes for each clinical pathway include the following: Asthma—the proportion of asthmatic patients treated appropriately with corticosteroids in the emergency department and at discharge; and Gastroenteritis—the proportion of relevant patients appropriately treated with oral rehydration therapy. Data sources include chart audits, administrative databases, environmental scans, and qualitative interviews. We will also conduct an overall process evaluation to assess the implementation strategy and an economic analysis to evaluate implementation costs and benefits. Discussion This study will contribute to the body of evidence supporting effective strategies for clinical pathway implementation, and ultimately reducing the research to practice gaps by operationalizing best evidence care recommendations through effective use of clinical pathways. Trial registration ClinicalTrials.gov: NCT01815710 PMID:23692634

33. Photocopy of photograph (original print located in LBNL Photo ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

33. Photocopy of photograph (original print located in LBNL Photo Lab Collection). Photographer unknown. April 10, 1958. BEV-1515. ANTI-PROTON SET-UP; BRUCE CORK, GLENN LAMBERTSON. B-51. - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

Marine nitrous oxide emissions: An unknown liability for the international water sector

EPA Science Inventory

Reliable estimates of anthropogenic greenhouse gas (GHG) emissions are essential for setting effective climate policy at both the sector and national level. Current IPCC Guidelines for calculating nitrous oxide (N2O) emissions from sewage management are both highly uncertain and ...

[Parental alienation syndrome (PAS): unknown in medical settings, endemic in courts].

PubMed

Pignotti, Maria Serenella

2013-02-01

A purposed syndrome of so-called parental alienation (PAS), unsupported by any evidence-based data, unknown in medical settings, unquoted in medical books, absent in DSM and ICD, never demonstrated by controlled studies published in high scientific level journals, is rampant in Courts where it can lead to loose parental custody. During a divorce trial, almost always the mothers and the children, become joint in a sort of folie au deux, in a denigration campaign of ex-husband/father. From a review on this issue it seems evident its theoretical roots lie on a theory that justify gender violence and children sexual abuse. The bias that both of them are layers and that he children have not autonomy block their possibility of any defence in front of a Court. In severe cases, PAS becomes a new and efficient tool of intra-familiar violence. The treatment of severe cases is to stop any contact between mother and children. The resort to PAS in Courts must be strongly rejected.

Previously unknown class of metalorganic compounds revealed in meteorites

PubMed Central

Ruf, Alexander; Kanawati, Basem; Hertkorn, Norbert; Yin, Qing-Zhu; Moritz, Franco; Harir, Mourad; Lucio, Marianna; Michalke, Bernhard; Wimpenny, Joshua; Shilobreeva, Svetlana; Bronsky, Basil; Saraykin, Vladimir; Gabelica, Zelimir; Gougeon, Régis D.; Quirico, Eric; Ralew, Stefan; Jakubowski, Tomasz; Haack, Henning; Gonsior, Michael; Jenniskens, Peter; Hinman, Nancy W.; Schmitt-Kopplin, Philippe

2017-01-01

The rich diversity and complexity of organic matter found in meteorites is rapidly expanding our knowledge and understanding of extreme environments from which the early solar system emerged and evolved. Here, we report the discovery of a hitherto unknown chemical class, dihydroxymagnesium carboxylates [(OH)2MgO2CR]−, in meteoritic soluble organic matter. High collision energies, which are required for fragmentation, suggest substantial thermal stability of these Mg-metalorganics (CHOMg compounds). This was corroborated by their higher abundance in thermally processed meteorites. CHOMg compounds were found to be present in a set of 61 meteorites of diverse petrological classes. The appearance of this CHOMg chemical class extends the previously investigated, diverse set of CHNOS molecules. A connection between the evolution of organic compounds and minerals is made, as Mg released from minerals gets trapped into organic compounds. These CHOMg metalorganic compounds and their relation to thermal processing in meteorites might shed new light on our understanding of carbon speciation at a molecular level in meteorite parent bodies. PMID:28242686

Multiple-Instance Regression with Structured Data

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri L.; Lane, Terran; Roper, Alex

2008-01-01

We present a multiple-instance regression algorithm that models internal bag structure to identify the items most relevant to the bag labels. Multiple-instance regression (MIR) operates on a set of bags with real-valued labels, each containing a set of unlabeled items, in which the relevance of each item to its bag label is unknown. The goal is to predict the labels of new bags from their contents. Unlike previous MIR methods, MI-ClusterRegress can operate on bags that are structured in that they contain items drawn from a number of distinct (but unknown) distributions. MI-ClusterRegress simultaneously learns a model of the bag's internal structure, the relevance of each item, and a regression model that accurately predicts labels for new bags. We evaluated this approach on the challenging MIR problem of crop yield prediction from remote sensing data. MI-ClusterRegress provided predictions that were more accurate than those obtained with non-multiple-instance approaches or MIR methods that do not model the bag structure.

Model risk for European-style stock index options.

PubMed

Gençay, Ramazan; Gibson, Rajna

2007-01-01

In empirical modeling, there have been two strands for pricing in the options literature, namely the parametric and nonparametric models. Often, the support for the nonparametric methods is based on a benchmark such as the Black-Scholes (BS) model with constant volatility. In this paper, we study the stochastic volatility (SV) and stochastic volatility random jump (SVJ) models as parametric benchmarks against feedforward neural network (FNN) models, a class of neural network models. Our choice for FNN models is due to their well-studied universal approximation properties of an unknown function and its partial derivatives. Since the partial derivatives of an option pricing formula are risk pricing tools, an accurate estimation of the unknown option pricing function is essential for pricing and hedging. Our findings indicate that FNN models offer themselves as robust option pricing tools, over their sophisticated parametric counterparts in predictive settings. There are two routes to explain the superiority of FNN models over the parametric models in forecast settings. These are nonnormality of return distributions and adaptive learning.

Tasks and premises in quantum state determination

NASA Astrophysics Data System (ADS)

Carmeli, Claudio; Heinosaari, Teiko; Schultz, Jussi; Toigo, Alessandro

2014-02-01

The purpose of quantum tomography is to determine an unknown quantum state from measurement outcome statistics. There are two obvious ways to generalize this setting. First, our task need not be the determination of any possible input state but only some input states, for instance pure states. Second, we may have some prior information, or premise, which guarantees that the input state belongs to some subset of states, for instance the set of states with rank less than half of the dimension of the Hilbert space. We investigate state determination under these two supplemental features, concentrating on the cases where the task and the premise are statements about the rank of the unknown state. We characterize the structure of quantum observables (positive operator valued measures) that are capable of fulfilling these type of determination tasks. After the general treatment we focus on the class of covariant phase space observables, thus providing physically relevant examples of observables both capable and incapable of performing these tasks. In this context, the effect of noise is discussed.

Syntactic Awareness and Arithmetic Word Problem Solving in Children With and Without Learning Disabilities.

PubMed

Peake, Christian; Jiménez, Juan E; Rodríguez, Cristina; Bisschop, Elaine; Villarroel, Rebeca

2015-01-01

Arithmetic word problem (AWP) solving is a highly demanding task for children with learning disabilities (LD) since verbal and mathematical information have to be integrated. This study examines specifically how syntactic awareness (SA), the ability to manage the grammatical structures of language, affects AWP solving. Three groups of children in elementary education were formed: children with arithmetic learning disabilities (ALD), children with reading learning disabilities (RLD), and children with comorbid arithmetic and reading learning disabilities (ARLD). Mediation analysis confirmed that SA was a mediator variable for both groups of children with reading disabilities when solving AWPs, but not for children in the ALD group. All groups performed below the control group in the problem solving task. When SA was controlled for, semantic structure and position of the unknown set were variables that affected both groups with ALD. Specifically, children with ALD only were more affected by the place of the unknown set. © Hammill Institute on Disabilities 2014.

Orbit Determination and Maneuver Detection Using Event Representation with Thrust-Fourier-Coefficients

NASA Astrophysics Data System (ADS)

Lubey, D.; Ko, H.; Scheeres, D.

The classical orbit determination (OD) method of dealing with unknown maneuvers is to restart the OD process with post-maneuver observations. However, it is also possible to continue the OD process through such unknown maneuvers by representing those unknown maneuvers with an appropriate event representation. It has been shown in previous work (Ko & Scheeres, JGCD 2014) that any maneuver performed by a satellite transitioning between two arbitrary orbital states can be represented as an equivalent maneuver connecting those two states using Thrust-Fourier-Coefficients (TFCs). Event representation using TFCs rigorously provides a unique control law that can generate the desired secular behavior for a given unknown maneuver. This paper presents applications of this representation approach to orbit prediction and maneuver detection problem across unknown maneuvers. The TFCs are appended to a sequential filter as an adjoint state to compensate unknown perturbing accelerations and the modified filter estimates the satellite state and thrust coefficients by processing OD across the time of an unknown maneuver. This modified sequential filter with TFCs is capable of fitting tracking data and maintaining an OD solution in the presence of unknown maneuvers. Also, the modified filter is found effective in detecting a sudden change in TFC values which indicates a maneuver. In order to illustrate that the event representation approach with TFCs is robust and sufficiently general to be easily adjustable, different types of measurement data are processed with the filter in a realistic LEO setting. Further, cases with mis-modeling of non-gravitational force are included in our study to verify the versatility and efficiency of our presented algorithm. Simulation results show that the modified sequential filter with TFCs can detect and estimate the orbit and thrust parameters in the presence of unknown maneuvers with or without measurement data during maneuvers. With no measurement data during maneuvers, the modified filter with TFCs uses an existing pre-maneuver orbit solution to compute a post-maneuver orbit solution by forcing TFCs to compensate for an unknown maneuver. With observation data available during maneuvers, maneuver start time and stop time is determined

Big Events in Greece and HIV Infection Among People Who Inject Drugs

PubMed Central

Nikolopoulos, Georgios K.; Sypsa, Vana; Bonovas, Stefanos; Paraskevis, Dimitrios; Malliori-Minerva, Melpomeni; Hatzakis, Angelos; Friedman, Samuel R.

2015-01-01

Big Events are processes like macroeconomic transitions that have lowered social well-being in various settings in the past. Greece has been hit by the global crisis and experienced an HIV outbreak among people who inject drugs. Since the crisis began (2008), Greece has seen population displacement, inter-communal violence, cuts in governmental expenditures, and social movements. These may have affected normative regulation, networks, and behaviors. However, most pathways to risk remain unknown or unmeasured. We use what is known and unknown about the Greek HIV outbreak to suggest modifications in Big Events models and the need for additional research. PMID:25723309

A Unified Approach to Adaptive Neural Control for Nonlinear Discrete-Time Systems With Nonlinear Dead-Zone Input.

PubMed

Liu, Yan-Jun; Gao, Ying; Tong, Shaocheng; Chen, C L Philip

2016-01-01

In this paper, an effective adaptive control approach is constructed to stabilize a class of nonlinear discrete-time systems, which contain unknown functions, unknown dead-zone input, and unknown control direction. Different from linear dead zone, the dead zone, in this paper, is a kind of nonlinear dead zone. To overcome the noncausal problem, which leads to the control scheme infeasible, the systems can be transformed into a m -step-ahead predictor. Due to nonlinear dead-zone appearance, the transformed predictor still contains the nonaffine function. In addition, it is assumed that the gain function of dead-zone input and the control direction are unknown. These conditions bring about the difficulties and the complicacy in the controller design. Thus, the implicit function theorem is applied to deal with nonaffine dead-zone appearance, the problem caused by the unknown control direction can be resolved through applying the discrete Nussbaum gain, and the neural networks are used to approximate the unknown function. Based on the Lyapunov theory, all the signals of the resulting closed-loop system are proved to be semiglobal uniformly ultimately bounded. Moreover, the tracking error is proved to be regulated to a small neighborhood around zero. The feasibility of the proposed approach is demonstrated by a simulation example.

Pattern-Based Inverse Modeling for Characterization of Subsurface Flow Models with Complex Geologic Heterogeneity

NASA Astrophysics Data System (ADS)

Golmohammadi, A.; Jafarpour, B.; M Khaninezhad, M. R.

2017-12-01

Calibration of heterogeneous subsurface flow models leads to ill-posed nonlinear inverse problems, where too many unknown parameters are estimated from limited response measurements. When the underlying parameters form complex (non-Gaussian) structured spatial connectivity patterns, classical variogram-based geostatistical techniques cannot describe the underlying connectivity patterns. Modern pattern-based geostatistical methods that incorporate higher-order spatial statistics are more suitable for describing such complex spatial patterns. Moreover, when the underlying unknown parameters are discrete (geologic facies distribution), conventional model calibration techniques that are designed for continuous parameters cannot be applied directly. In this paper, we introduce a novel pattern-based model calibration method to reconstruct discrete and spatially complex facies distributions from dynamic flow response data. To reproduce complex connectivity patterns during model calibration, we impose a feasibility constraint to ensure that the solution follows the expected higher-order spatial statistics. For model calibration, we adopt a regularized least-squares formulation, involving data mismatch, pattern connectivity, and feasibility constraint terms. Using an alternating directions optimization algorithm, the regularized objective function is divided into a continuous model calibration problem, followed by mapping the solution onto the feasible set. The feasibility constraint to honor the expected spatial statistics is implemented using a supervised machine learning algorithm. The two steps of the model calibration formulation are repeated until the convergence criterion is met. Several numerical examples are used to evaluate the performance of the developed method.

Epidemiology and antimicrobial susceptibility of Gram-negative aerobic bacteria causing intra-abdominal infections during 2010-2011.

PubMed

Hawser, Stephen; Hoban, Daryl J; Badal, Robert E; Bouchillon, Samuel K; Biedenbach, Douglas; Hackel, Meredith; Morrissey, Ian

2015-02-01

The study for monitoring antimicrobial resistance trends (SMART) surveillance program monitors the epidemiology and trends in antibiotic resistance of intra-abdominal pathogens to currently used therapies. The current report describes such trends during 2010-2011. A total of 25,746 Gram-negative clinical isolates from intra-abdominal infections were collected and classified as hospital-associated (HA) if the hospital length of stay (LOS) at the time of specimen collection was ≥48 hours, community-associated (CA) if LOS at the time of specimen collection was <48 hours, or unknown (no designation given by participating centre). A total of 92 different species were collected of which the most common was Escherichia coli: 39% of all isolates in North America to 55% in Africa. Klebsiella pneumoniae was the second most common pathogen: 11% of all isolates from Europe to 19% of all isolates from Asia. Isolates were from multiple intra-abdominal sources of which 32% were peritoneal fluid, 20% were intra-abdominal abscesses, and 16.5% were gall bladder infections. Isolates were further classified as HA (55% of all isolates), CA (39% of all isolates), or unknown (6% of all isolates). The most active antibiotics tested were imipenem, ertapenem, amikacin, and piperacillin-tazobactam. Resistance rates to all other antibiotics tested were high. Considering the current data set and high-level resistance of intra-abdominal pathogens to various antibiotics, further monitoring of the epidemiology of intra-abdominal infections and their susceptibility to antibiotics through SMART is warranted.

Improving Life-Cycle Cost Management of Spacecraft Missions

NASA Technical Reports Server (NTRS)

Clardy, Dennon

2010-01-01

This presentation will explore the results of a recent NASA Life-Cycle Cost study and how project managers can use the findings and recommendations to improve planning and coordination early in the formulation cycle and avoid common pitfalls resulting in cost overruns. The typical NASA space science mission will exceed both the initial estimated and the confirmed life-cycle costs by the end of the mission. In a fixed-budget environment, these overruns translate to delays in starting or launching future missions, or in the worst case can lead to cancelled missions. Some of these overruns are due to issues outside the control of the project; others are due to the unpredictable problems (unknown unknowns) that can affect any development project. However, a recent study of life-cycle cost growth by the Discovery and New Frontiers Program Office identified a number of areas that are within the scope of project management to address. The study also found that the majority of the underlying causes for cost overruns are embedded in the project approach during the formulation and early design phases, but the actual impacts typically are not experienced until late in the project life cycle. Thus, project management focus in key areas such as integrated schedule development, management structure and contractor communications processes, heritage and technology assumptions, and operations planning, can be used to validate initial cost assumptions and set in place management processes to avoid the common pitfalls resulting in cost overruns.

Design and Initial Characterization of the SC-200 Proteomics Standard Mixture

PubMed Central

Bauman, Andrew; Higdon, Roger; Rapson, Sean; Loiue, Brenton; Hogan, Jason; Stacy, Robin; Napuli, Alberto; Guo, Wenjin; van Voorhis, Wesley; Roach, Jared; Lu, Vincent; Landorf, Elizabeth; Stewart, Elizabeth; Kolker, Natali; Collart, Frank; Myler, Peter; van Belle, Gerald

2011-01-01

Abstract High-throughput (HTP) proteomics studies generate large amounts of data. Interpretation of these data requires effective approaches to distinguish noise from biological signal, particularly as instrument and computational capacity increase and studies become more complex. Resolving this issue requires validated and reproducible methods and models, which in turn requires complex experimental and computational standards. The absence of appropriate standards and data sets for validating experimental and computational workflows hinders the development of HTP proteomics methods. Most protein standards are simple mixtures of proteins or peptides, or undercharacterized reference standards in which the identity and concentration of the constituent proteins is unknown. The Seattle Children's 200 (SC-200) proposed proteomics standard mixture is the next step toward developing realistic, fully characterized HTP proteomics standards. The SC-200 exhibits a unique modular design to extend its functionality, and consists of 200 proteins of known identities and molar concentrations from 6 microbial genomes, distributed into 10 molar concentration tiers spanning a 1,000-fold range. We describe the SC-200's design, potential uses, and initial characterization. We identified 84% of SC-200 proteins with an LTQ-Orbitrap and 65% with an LTQ-Velos (false discovery rate = 1% for both). There were obvious trends in success rate, sequence coverage, and spectral counts with protein concentration; however, protein identification, sequence coverage, and spectral counts vary greatly within concentration levels. PMID:21250827

Design and initial characterization of the SC-200 proteomics standard mixture.

PubMed

Bauman, Andrew; Higdon, Roger; Rapson, Sean; Loiue, Brenton; Hogan, Jason; Stacy, Robin; Napuli, Alberto; Guo, Wenjin; van Voorhis, Wesley; Roach, Jared; Lu, Vincent; Landorf, Elizabeth; Stewart, Elizabeth; Kolker, Natali; Collart, Frank; Myler, Peter; van Belle, Gerald; Kolker, Eugene

2011-01-01

High-throughput (HTP) proteomics studies generate large amounts of data. Interpretation of these data requires effective approaches to distinguish noise from biological signal, particularly as instrument and computational capacity increase and studies become more complex. Resolving this issue requires validated and reproducible methods and models, which in turn requires complex experimental and computational standards. The absence of appropriate standards and data sets for validating experimental and computational workflows hinders the development of HTP proteomics methods. Most protein standards are simple mixtures of proteins or peptides, or undercharacterized reference standards in which the identity and concentration of the constituent proteins is unknown. The Seattle Children's 200 (SC-200) proposed proteomics standard mixture is the next step toward developing realistic, fully characterized HTP proteomics standards. The SC-200 exhibits a unique modular design to extend its functionality, and consists of 200 proteins of known identities and molar concentrations from 6 microbial genomes, distributed into 10 molar concentration tiers spanning a 1,000-fold range. We describe the SC-200's design, potential uses, and initial characterization. We identified 84% of SC-200 proteins with an LTQ-Orbitrap and 65% with an LTQ-Velos (false discovery rate = 1% for both). There were obvious trends in success rate, sequence coverage, and spectral counts with protein concentration; however, protein identification, sequence coverage, and spectral counts vary greatly within concentration levels.

Laboratory Practical Exams in the Biochemistry Lab Course.

ERIC Educational Resources Information Center

Robyt, John F.; White, Bernard J.

1990-01-01

Described are the composition, design, administration, and evaluation of practical examinations. A table of the composition of biochemical unknowns for analysis in practical examinations is included. (CW)

13. Photographic copy of original Design For New Sluice Gate ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

13. Photographic copy of original Design For New Sluice Gate drawing, date and engineer unknown (original in possession of United States Department of Agriculture-Forest Service-Allegheny National Forest). - Loleta Recreation Area, Lower Dam, 6 miles Southeast of interesection of State Route 24041 & State Route 66, Loleta, Elk County, PA

Chapter 11: Dinkey north and south project

Treesearch

M North; R. Rojas

2012-01-01

Designing and implementing vegetation treatments that can move a forest landscape toward a desired future condition is often challenging. Faced with diverse stakeholder interests and the unknown effects of changing climate conditions, managers need to engage and build collaborative projects. One such effort is the Dinkey project designed to help restore a healthy,...

Bristol Stool Form Scale reliability and agreement decreases when determining Rome III stool form designations

USDA-ARS?s Scientific Manuscript database

Rater reproducibility of the Bristol Stool Form Scale (BSFS), which categorizes stools into one of seven types, is unknown. We sought to determine reliability and agreement by individual stool type and when responses are categorized by Rome III clinical designation as normal or abnormal (constipatio...

A Measure Approximation for Distributionally Robust PDE-Constrained Optimization Problems

DOE PAGES

Kouri, Drew Philip

2017-12-19

In numerous applications, scientists and engineers acquire varied forms of data that partially characterize the inputs to an underlying physical system. This data is then used to inform decisions such as controls and designs. Consequently, it is critical that the resulting control or design is robust to the inherent uncertainties associated with the unknown probabilistic characterization of the model inputs. Here in this work, we consider optimal control and design problems constrained by partial differential equations with uncertain inputs. We do not assume a known probabilistic model for the inputs, but rather we formulate the problem as a distributionally robustmore » optimization problem where the outer minimization problem determines the control or design, while the inner maximization problem determines the worst-case probability measure that matches desired characteristics of the data. We analyze the inner maximization problem in the space of measures and introduce a novel measure approximation technique, based on the approximation of continuous functions, to discretize the unknown probability measure. Finally, we prove consistency of our approximated min-max problem and conclude with numerical results.« less

Survivorship and functional outcomes of patellofemoral arthroplasty: a systematic review.

PubMed

van der List, J P; Chawla, H; Zuiderbaan, H A; Pearle, A D

2017-08-01

Historically poor results of survivorship and functional outcomes of patellofemoral arthroplasty (PFA) have been reported in the setting of isolated patellofemoral osteoarthritis. More recently, however, fairly good results of PFA were reported, but the current status of PFA outcomes is unknown. Therefore, a systematic review was performed to assess overall PFA survivorship and functional outcomes. A search was performed using PubMed, Embase and Cochrane systems, and the registries were searched. Twenty-three cohort studies and one registry reported survivorship using Kaplan-Meier curve, while 51 cohort studies reported functional outcomes of PFA. Twelve studies were level II studies, while 45 studies were level III or IV studies. Heterogeneity was mainly seen in type of prosthesis and year the cohort started. Nine hundred revisions in 9619 PFAs were reported yielding 5-, 10-, 15- and 20-year PFA survivorships of 91.7, 83.3, 74.9 and 66.6 %, respectively, and an annual revision rate of 2.18. Functional outcomes were reported in 2587 PFAs with an overall score of 82.2 % of the maximum score. KSS and Knee Function Score were 87.5 and 81.6 %, respectively. This systematic review showed that fairly good results of PFA survivorship and functional outcomes were reported at short- and midterm follow-up in the setting of isolated patellofemoral osteoarthritis. Heterogeneity existed mainly in prosthesis design and year the cohort started. These results provide a clear overview of the current status of PFA in the setting of isolated patellofemoral osteoarthritis. IV.

Diversity of wild bees supports pollination services in an urbanized landscape.

PubMed

Lowenstein, David M; Matteson, Kevin C; Minor, Emily S

2015-11-01

Plantings in residential neighborhoods can support wild pollinators. However, it is unknown how effectively wild pollinators maintain pollination services in small, urban gardens with diverse floral resources. We used a 'mobile garden' experimental design, whereby potted plants of cucumber, eggplant, and purple coneflower were brought to 30 residential yards in Chicago, IL, USA, to enable direct assessment of pollination services provided by wild pollinator communities. We measured fruit and seed set and investigated the effect of within-yard characteristics and adjacent floral resources on plant pollination. Increased pollinator visitation and taxonomic richness generally led to increases in fruit and seed set for all focal plants. Furthermore, fruit and seed set were correlated across the three species, suggesting that pollination services vary across the landscape in ways that are consistent among different plant species. Plant species varied in terms of which pollinator groups provided the most visits and benefit for pollination. Cucumber pollination was linked to visitation by small sweat bees (Lasioglossum spp.), whereas eggplant pollination was linked to visits by bumble bees. Purple coneflower was visited by the most diverse group of pollinators and, perhaps due to this phenomenon, was more effectively pollinated in florally-rich gardens. Our results demonstrate how a diversity of wild bees supports pollination of multiple plant species, highlighting the importance of pollinator conservation within cities. Non-crop resources should continue to be planted in urban gardens, as these resources have a neutral and potentially positive effect on crop pollination.

Maximum likelihood estimation of protein kinetic parameters under weak assumptions from unfolding force spectroscopy experiments

NASA Astrophysics Data System (ADS)

Aioanei, Daniel; Samorì, Bruno; Brucale, Marco

2009-12-01

Single molecule force spectroscopy (SMFS) is extensively used to characterize the mechanical unfolding behavior of individual protein domains under applied force by pulling chimeric polyproteins consisting of identical tandem repeats. Constant velocity unfolding SMFS data can be employed to reconstruct the protein unfolding energy landscape and kinetics. The methods applied so far require the specification of a single stretching force increase function, either theoretically derived or experimentally inferred, which must then be assumed to accurately describe the entirety of the experimental data. The very existence of a suitable optimal force model, even in the context of a single experimental data set, is still questioned. Herein, we propose a maximum likelihood (ML) framework for the estimation of protein kinetic parameters which can accommodate all the established theoretical force increase models. Our framework does not presuppose the existence of a single force characteristic function. Rather, it can be used with a heterogeneous set of functions, each describing the protein behavior in the stretching time range leading to one rupture event. We propose a simple way of constructing such a set of functions via piecewise linear approximation of the SMFS force vs time data and we prove the suitability of the approach both with synthetic data and experimentally. Additionally, when the spontaneous unfolding rate is the only unknown parameter, we find a correction factor that eliminates the bias of the ML estimator while also reducing its variance. Finally, we investigate which of several time-constrained experiment designs leads to better estimators.

Gender inequality in predispersal seed predation contributes to female seed set advantage in a gynodioecious species.

PubMed

Clarke, Gretel L; Brody, Alison K

2015-05-01

Most flowering plants are hermaphrodites. However, in gynodioecious species, some members of the population are male-sterile and reproduce only by setting seed, while others gain fitness through both male and female function. How females compensate for the loss of male function remains unresolved for most gynodioecious species. Here, as with many plants, fitness differences may be influenced by interactions with multiple species. However, whether multiple species interactions result in gender-specific fitness differences remains unknown. Using observational data from 2009-2010, we quantified seed set of the two sex morphs of Polemonium foliosissimu and asked how it is affected by pollination, and seed predation from a dipteran predispersal seed predator (Anthomyiidae: Hylemya sp.). We assessed seed production and losses to predation in 27 populations for one year and in six populations for a second year. Females set significantly more seed than did hermaphrodites in both years. Of the fitness components we assessed, including the number of flowers per plant, fruit set, seeds/fruit, and proportion of fruits destroyed by Hylemya, only fruit destruction differed significantly between the sexes. In one year, seeds/fruit and predation had a stronger effect on seed set for hermaphrodites than for females. Because predispersal seed predators do not pollinate flowers, their effects may depend on successful pollination of flowers on which they oviposit. To examine if genders differed in pollen limitation and seed predation and/or their interactive effects, in 2011 we hand-pollinated flowers and removed seed predator eggs in a fully factorial design. Both sexes were pollen limited, but their degree of pollen limitation did not differ. However, predation reduced.seed set more for hermaphrodites than for females. We found no significant interaction between hand pollen and seed predation, and no interaction between hand pollination and gender. Our results suggest that while interactions with both pollinators and seed predators affect reproductive success, floral enemies can cause inequality in seed set between genders. The next step is to understand how the seed set advantage affects long-term fitness and persistence of females in gynodioecious populations.

Photocopy of photograph (from NBPPNSY) photographer unknown, c. 1950's view ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Photocopy of photograph (from NBP-PNSY) photographer unknown, c. 1950's view northwest from 350-ton crane of drydock no. 2 (Haer no. Pa-387-B), 1950's. Pump house for the drydock is the round building below center of the photograph. The large building at the left center is building 546, the Turret Shop where naval gun turrets were assembled at the center rear is the foundry/propeller shop (Haer No. Pa-387-O) built in 1919. The foundry/propeller shop (building no. 20), designed by Warren-Moore and Company, resembles the Contemporaneous Architecture of Albert Kahn, who designed similar buildings for Henry Ford and the Chrysler Corporation in the 1920's and 1930's. - Naval Base Philadelphia-Philadelphia Naval Shipyard, League Island, Philadelphia, Philadelphia County, PA

Cryogenic propellant thermal control system design considerations, analyses, and concepts applied to a Mars human exploration mission

NASA Technical Reports Server (NTRS)

Plachta, David W.; Tucker, Stephen; Hoffman, David J.

1993-01-01

This paper analyzes, defines, and sizes cryogenic storage thermal control systems that meet the requirements of future NASA Mars human exploration missions. The design issues of this system include the projection of the existing Multilayer Insulation data base for cryogenic storage to much thicker (10 cm or more) insulation systems, the unknown heat leak from mechanical interfaces, and the thermal and structural performance effects of the large tank sizes required for a Mars mission. Acknowledging these unknown effects, heat loss projections are made based on extrapolation of the existing data base. The results indicate that hydrogen, methane, and oxygen are feasible propellants, and that the best suited thermal control sytems are 'thick' MLI, thermodynamic vent sytems, cryocoolers, and vacuum jackets.

RatLab: an easy to use tool for place code simulations

PubMed Central

Schönfeld, Fabian; Wiskott, Laurenz

2013-01-01

In this paper we present the RatLab toolkit, a software framework designed to set up and simulate a wide range of studies targeting the encoding of space in rats. It provides open access to our modeling approach to establish place and head direction cells within unknown environments and it offers a set of parameters to allow for the easy construction of a variety of enclosures for a virtual rat as well as controlling its movement pattern over the course of experiments. Once a spatial code is formed RatLab can be used to modify aspects of the enclosure or movement pattern and plot the effect of such modifications on the spatial representation, i.e., place and head direction cell activity. The simulation is based on a hierarchical Slow Feature Analysis (SFA) network that has been shown before to establish a spatial encoding of new environments using visual input data only. RatLab encapsulates such a network, generates the visual training data, and performs all sampling automatically—with each of these stages being further configurable by the user. RatLab was written with the intention to make our SFA model more accessible to the community and to that end features a range of elements to allow for experimentation with the model without the need for specific programming skills. PMID:23908627

Real-time qualitative reasoning for telerobotic systems

NASA Technical Reports Server (NTRS)

Pin, Eancois G.

1993-01-01

This paper discusses the sensor-based telerobotic driving of a car in a-priori unknown environments using 'human-like' reasoning schemes implemented on custom-designed VLSI fuzzy inferencing boards. These boards use the Fuzzy Set theoretic framework to allow very vast (30 kHz) processing of full sets of information that are expressed in qualitative form using membership functions. The sensor-based and fuzzy inferencing system was incorporated on an outdoor test-bed platform to investigate two control modes for driving a car on the basis of very sparse and imprecise range data. In the first mode, the car navigates fully autonomously to a goal specified by the operator, while in the second mode, the system acts as a telerobotic driver's aid providing the driver with linguistic (fuzzy) commands to turn left or right, speed up, slow down, stop, or back up depending on the obstacles perceived by the sensors. Indoor and outdoor experiments with both modes of control are described in which the system uses only three acoustic range (sonar) sensor channels to perceive the environment. Sample results are presented that illustrate the feasibility of developing autonomous navigation modules and robust, safety-enhancing driver's aids for telerobotic systems using the new fuzzy inferencing VLSI hardware and 'human-like' reasoning schemes.

Treatment outcomes after implementation of an adapted WHO protocol for severe sepsis and septic shock in Haiti.

PubMed

Papali, Alfred; Eoin West, T; Verceles, Avelino C; Augustin, Marc E; Nathalie Colas, L; Jean-Francois, Carl H; Patel, Devang M; Todd, Nevins W; McCurdy, Michael T

2017-10-01

The World Health Organization (WHO) has developed a simplified algorithm specific to resource-limited settings for the treatment of severe sepsis emphasizing early fluids and antibiotics. However, this protocol's clinical effectiveness is unknown. We describe patient outcomes before and after implementation of an adapted WHO severe sepsis protocol at a community hospital in Haiti. Using a before-and-after study design, we retrospectively enrolled 99 adult Emergency Department patients with severe sepsis from January through March 2012. After protocol implementation in January 2014, we compared outcomes to 67 patients with severe sepsis retrospectively enrolled from February to April 2014. We defined sepsis according to the WHO's Integrated Management of Adult Illness guidelines and severe sepsis as sepsis plus organ dysfunction. After protocol implementation, quantity of fluid administered increased and the physician's differential diagnoses more often included sepsis. Patients were more likely to have follow-up vital signs taken sooner, a radiograph performed, and a lactic acid tested. There were no improvements in mortality, time to fluids or antimicrobials. Use of a simplified sepsis protocol based primarily on physiologic parameters allows for substantial improvements in process measures in the care of severely septic patients in a resource-constrained setting. Copyright © 2017 Elsevier Inc. All rights reserved.

The Relationship Between and Factors Influencing Staff Nurses' Perceptions of Nurse Manager Caring and Exposure to Workplace Bullying in Multiple Healthcare Settings.

PubMed

Olender, Lynda

2017-10-01

The aim of this study was to examine the relationship between, and factors influencing, staff nurse perceptions of nurse manager caring (NMC) and the perceived exposure to workplace bullying (WPB) in multiple healthcare settings. Workplace bullying is commonplace, increasing, and detrimental to the health and availability of our nursing workforce. Positive relationships between a nurse manager (NM) and staff increase staff satisfaction and reduce turnover. Still unknown, however, is whether a caring relationship between manager and staff can reduce staff nurse perception of exposure to WPB. On the basis of Watson's theory that caring is reciprocal in nature, a descriptive correlational design was used to assess 156 staff nurses' self-report of NMC and their exposure to negative acts using the Caring Factor Survey-Caring of the Manager and the Negative Acts Questionnaire-Revised instruments. There is a significant inverse relationship between NMC and exposure to WPB in the nursing workplace. Gender, work environment, and a high workload influenced these findings. This study highlights the importance of caring leadership to reduce exposure to negative behaviors. The data lend support to the idea of educating NMs regarding the application of caring behaviors to support staff at the point of care.

Structural insights into binding of small molecule inhibitors to Enhancer of Zeste Homolog 2

NASA Astrophysics Data System (ADS)

Kalinić, Marko; Zloh, Mire; Erić, Slavica

2014-11-01

Enhancer of Zeste Homolog 2 (EZH2) is a SET domain protein lysine methyltransferase (PKMT) which has recently emerged as a chemically tractable and therapeutically promising epigenetic target, evidenced by the discovery and characterization of potent and highly selective EZH2 inhibitors. However, no experimental structures of the inhibitors co-crystallized to EZH2 have been resolved, and the structural basis for their activity and selectivity remains unknown. Considering the need to minimize cross-reactivity between prospective PKMT inhibitors, much can be learned from understanding the molecular basis for selective inhibition of EZH2. Thus, to elucidate the binding of small-molecule inhibitors to EZH2, we have developed a model of its fully-formed cofactor binding site and used it to carry out molecular dynamics simulations of protein-ligand complexes, followed by molecular mechanics/generalized born surface area calculations. The obtained results are in good agreement with biochemical inhibition data and reflect the structure-activity relationships of known ligands. Our findings suggest that the variable and flexible post-SET domain plays an important role in inhibitor binding, allowing possibly distinct binding modes of inhibitors with only small variations in their structure. Insights from this study present a good basis for design of novel and optimization of existing compounds targeting the cofactor binding site of EZH2.

Effects of 4-Week Training Intervention with Unknown Loads on Power Output Performance and Throwing Velocity in Junior Team Handball Players

PubMed Central

Sabido, Rafael; Hernández-Davó, Jose Luis; Botella, Javier; Moya, Manuel

2016-01-01

Purpose To compare the effect of 4-week unknown vs known loads strength training intervention on power output performance and throwing velocity in junior team handball players. Methods Twenty-eight junior team-handball players (17.2 ± 0.6 years, 1.79 ± 0.07 m, 75.6 ± 9.4 kg)were divided into two groups (unknown loads: UL; known loads: KL). Both groups performed two sessions weekly consisting of four sets of six repetitions of the bench press throw exercise, using the 30%, 50% and 70% of subjects’ individual 1 repetition maximum (1RM). In each set, two repetitions with each load were performed, but the order of the loads was randomised. In the KL group, researchers told the subjects the load to mobilise prior each repetition, while in the UL group, researchers did not provide any information. Maximal dynamic strength (1RM bench press), power output (with 30, 50 and 70% of 1RM) and throwing velocity (7 m standing throw and 9 m jumping throw) were assessed pre- and post-training intervention. Results Both UL and KL group improved similarly their 1RM bench press as well as mean and peak power with all loads. There were significant improvements in power developed in all the early time intervals measured (150 ms) with the three loads (30, 50, 70% 1RM) in the UL group, while KL only improved with 30% 1RM (all the time intervals) and with 70% 1RM (at certain time intervals). Only the UL group improved throwing velocity in both standing (4.7%) and jumping (5.3%) throw (p > 0.05). Conclusions The use of unknown loads has led to greater gains in power output in the early time intervals as well as to increases in throwing velocity compared with known loads. Therefore unknown loads are of significant practical use to increase both strength and in-field performance in a short period of training. PMID:27310598

Unified quantum no-go theorems and transforming of quantum pure states in a restricted set

NASA Astrophysics Data System (ADS)

Luo, Ming-Xing; Li, Hui-Ran; Lai, Hong; Wang, Xiaojun

2017-12-01

The linear superposition principle in quantum mechanics is essential for several no-go theorems such as the no-cloning theorem, the no-deleting theorem and the no-superposing theorem. In this paper, we investigate general quantum transformations forbidden or permitted by the superposition principle for various goals. First, we prove a no-encoding theorem that forbids linearly superposing of an unknown pure state and a fixed pure state in Hilbert space of a finite dimension. The new theorem is further extended for multiple copies of an unknown state as input states. These generalized results of the no-encoding theorem include the no-cloning theorem, the no-deleting theorem and the no-superposing theorem as special cases. Second, we provide a unified scheme for presenting perfect and imperfect quantum tasks (cloning and deleting) in a one-shot manner. This scheme may lead to fruitful results that are completely characterized with the linear independence of the representative vectors of input pure states. The upper bounds of the efficiency are also proved. Third, we generalize a recent superposing scheme of unknown states with a fixed overlap into new schemes when multiple copies of an unknown state are as input states.

E-health and health care behaviour of parents of young children: a qualitative study

PubMed Central

van der Gugten, Anne C.; de Leeuw, Rob J. R. J.; Verheij, Theo J.M.; van der Ent, Cornelis K.; Kars, Marijke C.

2016-01-01

Objective Internet plays a huge role in providing information about health care problems. However, it is unknown how parents use and perceive the internet as a source of information and how this influences health care utilisation when it comes to common complaints in infants. The objective was to evaluate the perception parents have on the role of internet in providing health care information on common symptoms in infants and its effects on health care utilisation. Design A qualitative design was chosen. Setting and subjects Parents were recruited from a population-based birth-cohort and selected purposefully. Main outcome measures Semi-structured interviews were used to receive information of parentsʼ ideas. Thematic coding and constant comparison were used for interview transcript analysis. Results Ten parents were interviewed. Parents felt anxious and responsible when their child displayed common symptoms, and appeared to be in need of information. They tried to obtain information from relatives, but more so from the internet, because of its accessibility. Nevertheless, information found on the internet had several limitations, evoked new doubts and insecurity and although parents compared information from multiple sources, only the physician was able to take away the insecurity. The internet did not interfere in the decision to consult the physician. Conclusions Parents need information about their childrenʼs symptoms and the internet is a major resource. However, only physicians could take away their symptom-related doubts and insecurities and internet information did not play a role in parental decision making. Information gathered online may complement the information from physicians, rather than replace it. Key pointsInternet plays an increasing role in providing health care information but it is unknown how this influences health care utilisation.Our study suggests that:Parents need information about their children’s symptoms and the internet is a major resource.However, only physicians could take away their symptom-related doubts and insecurities.Internet information did not play a role in parental decision making. PMID:27063729

Best strategies to implement clinical pathways in an emergency department setting: study protocol for a cluster randomized controlled trial.

PubMed

Jabbour, Mona; Curran, Janet; Scott, Shannon D; Guttman, Astrid; Rotter, Thomas; Ducharme, Francine M; Lougheed, M Diane; McNaughton-Filion, M Louise; Newton, Amanda; Shafir, Mark; Paprica, Alison; Klassen, Terry; Taljaard, Monica; Grimshaw, Jeremy; Johnson, David W

2013-05-22

The clinical pathway is a tool that operationalizes best evidence recommendations and clinical practice guidelines in an accessible format for 'point of care' management by multidisciplinary health teams in hospital settings. While high-quality, expert-developed clinical pathways have many potential benefits, their impact has been limited by variable implementation strategies and suboptimal research designs. Best strategies for implementing pathways into hospital settings remain unknown. This study will seek to develop and comprehensively evaluate best strategies for effective local implementation of externally developed expert clinical pathways. We will develop a theory-based and knowledge user-informed intervention strategy to implement two pediatric clinical pathways: asthma and gastroenteritis. Using a balanced incomplete block design, we will randomize 16 community emergency departments to receive the intervention for one clinical pathway and serve as control for the alternate clinical pathway, thus conducting two cluster randomized controlled trials to evaluate this implementation intervention. A minimization procedure will be used to randomize sites. Intervention sites will receive a tailored strategy to support full clinical pathway implementation. We will evaluate implementation strategy effectiveness through measurement of relevant process and clinical outcomes. The primary process outcome will be the presence of an appropriately completed clinical pathway on the chart for relevant patients. Primary clinical outcomes for each clinical pathway include the following: Asthma--the proportion of asthmatic patients treated appropriately with corticosteroids in the emergency department and at discharge; and Gastroenteritis--the proportion of relevant patients appropriately treated with oral rehydration therapy. Data sources include chart audits, administrative databases, environmental scans, and qualitative interviews. We will also conduct an overall process evaluation to assess the implementation strategy and an economic analysis to evaluate implementation costs and benefits. This study will contribute to the body of evidence supporting effective strategies for clinical pathway implementation, and ultimately reducing the research to practice gaps by operationalizing best evidence care recommendations through effective use of clinical pathways. ClinicalTrials.gov: NCT01815710.

Quantum computation with cold bosonic atoms in an optical lattice.

PubMed

García-Ripoll, Juan José; Cirac, Juan Ignacio

2003-07-15

We analyse an implementation of a quantum computer using bosonic atoms in an optical lattice. We show that, even though the number of atoms per site and the tunnelling rate between neighbouring sites is unknown, one may operate a universal set of gates by means of adiabatic passage.

Focus on the Social Aspect of Autism

ERIC Educational Resources Information Center

Kaluzna-Czaplinska, Joanna; Zurawicz, Ewa; Józwik-Pruska, Jagoda

2018-01-01

Autism spectrum disorder (ASD) describes a set of neurodevelopmental disorders. Despite extensive ASD research lasting more than 60 years, its causes are still unknown. Without indicating the etiology, its development cannot be stopped. Over the years, both the definition and diagnostic criteria have developed. The number of ASD incidence is…

The Secret Talents of Fundraisers

ERIC Educational Resources Information Center

Pulley, John

2010-01-01

A significant but unknown number of performing artists have redirected their creativity and passion into development. They are ballet and contemporary dancers, jazz and orchestral musicians, actors and comedians, opera divas and gospel belters. None of them set out to become fundraisers. Yet here they are, and they partly credit their success in…

Toward Diagnostic and Phenotype Markers for Genetically Transmitted Speech Delay

ERIC Educational Resources Information Center

Shriberg, Lawrence D.; Lewis, Barbara A.; Tomblin, J. Bruce; McSweeny, Jane L.; Karlsson, Heather B.; Scheer, Alison R.

2005-01-01

Converging evidence supports the hypothesis that the most common subtype of childhood speech sound disorder (SSD) of currently unknown origin is genetically transmitted. We report the first findings toward a set of diagnostic markers to differentiate this proposed etiological subtype (provisionally termed "speech delay-genetic") from other…

Evaluation of Measurement Instrument Criterion Validity in Finite Mixture Settings

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.; Li, Tenglong

2016-01-01

A method for evaluating the validity of multicomponent measurement instruments in heterogeneous populations is discussed. The procedure can be used for point and interval estimation of criterion validity of linear composites in populations representing mixtures of an unknown number of latent classes. The approach permits also the evaluation of…

Acute esophageal necrosis and liver pathology, a rare combination

PubMed Central

Khan, Amir Maqbul; Hundal, Rangit; Ramaswamy, Vijaya; Korsten, Mark; Dhuper, Sunil

2004-01-01

Acute esophageal necrosis (AEN) or “black esophagus” is a clinical condition found at endoscopy. It is a rare entity the exact etiology of which remains unknown. We describe a case of ‘black esophagus’, first of its kind, in the setting of liver cirrhosis and hepatic encephalopathy. PMID:15285044

ROBUST ESTIMATION OF MEAN AND VARIANCE USING ENVIRONMENTAL DATA SETS WITH BELOW DETECTION LIMIT OBSERVATIONS

EPA Science Inventory

Scientists, especially environmental scientists often encounter trace level concentrations that are typically reported as less than a certain limit of detection, L. Type 1, left-censored data arise when certain low values lying below L are ignored or unknown as they cannot be mea...

Evaluating the impacts of the Panama Canal Expansion on Texas gulf ports.

DOT National Transportation Integrated Search

2013-03-01

This report covers a four-year period after contractors started work on the third set of locks, which in 2015 will effectively double the size of the ship using the Panama Canal. Many of the impacts linked to the new locks remain unknown (like lock f...

Cross-Situational Learning of Minimal Word Pairs

ERIC Educational Resources Information Center

Escudero, Paola; Mulak, Karen E.; Vlach, Haley A.

2016-01-01

"Cross-situational statistical learning" of words involves tracking co-occurrences of auditory words and objects across time to infer word-referent mappings. Previous research has demonstrated that learners can infer referents across sets of very phonologically distinct words (e.g., WUG, DAX), but it remains unknown whether learners can…

A set of GFP organelle marker lines for intracellular localization studies in Medicago truncatula

USDA-ARS?s Scientific Manuscript database

Genomics advances in the model legume Medicago truncatula have led to an increase in the number of identified genes encoding proteins with unknown biological function. Determining the intracellular location of uncharacterized proteins often aids in the elucidation of biological function. To expedite...

Students' Understanding of Dictionary Entries: A Study with Respect to Four Learners' Dictionaries.

ERIC Educational Resources Information Center

Jana, Abhra; Amritavalli, Vijaya; Amritavalli, R.

2003-01-01

Investigates the effects of definitional information in the form of dictionary entries, on second language learners' vocabulary learning in an instructed setting. Indian students (Native Hindi speakers) of English received monolingual English dictionary entries of five previously unknown words from four different learner's dictionaries. Results…

Smooth empirical Bayes estimation of observation error variances in linear systems

NASA Technical Reports Server (NTRS)

Martz, H. F., Jr.; Lian, M. W.

1972-01-01

A smooth empirical Bayes estimator was developed for estimating the unknown random scale component of each of a set of observation error variances. It is shown that the estimator possesses a smaller average squared error loss than other estimators for a discrete time linear system.

Mortality of trees in loblolly pine plantations

Treesearch

Boris Zeide; Yujia Zhang

2006-01-01

The annual probability of mortality for planted loblolly pine (Pinus taeda L.) trees was estimated using a set of permanent plots covering the entire native range of the species. The recorded causes of death were infestation by the southern pine beetle (Dendroctonus frontalis Zimmermann) and other insects, lightning, and unknown...

Listen, Imagine, and Create.

ERIC Educational Resources Information Center

Baumgartel, Marguerite; Lamb, Louise

1979-01-01

Presented is a very short story about a visit to an unknown, imaginary planet. The story is designed to provoke creative artistic responses from elementary level children in an art education class. (KC)

Dynamic modelling and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances

NASA Astrophysics Data System (ADS)

Yang, Xinxin; Ge, Shuzhi Sam; He, Wei

2018-04-01

In this paper, both the closed-form dynamics and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances are developed. The dynamic model of the system is described with assumed modes approach and Lagrangian method. The flexible manipulators are represented as Euler-Bernoulli beams. Based on singular perturbation technique, the displacements/joint angles and flexible modes are modelled as slow and fast variables, respectively. A sliding mode control is designed for trajectories tracking of the slow subsystem under unknown but bounded disturbances, and an adaptive sliding mode control is derived for slow subsystem under unknown slowly time-varying disturbances. An optimal linear quadratic regulator method is proposed for the fast subsystem to damp out the vibrations of the flexible manipulators. Theoretical analysis validates the stability of the proposed composite controller. Numerical simulation results demonstrate the performance of the closed-loop flexible space robot system.

Half-blind remote sensing image restoration with partly unknown degradation

NASA Astrophysics Data System (ADS)

Xie, Meihua; Yan, Fengxia

2017-01-01

The problem of image restoration has been extensively studied for its practical importance and theoretical interest. This paper mainly discusses the problem of image restoration with partly unknown kernel. In this model, the degraded kernel function is known but its parameters are unknown. With this model, we should estimate the parameters in Gaussian kernel and the real image simultaneity. For this new problem, a total variation restoration model is put out and an intersect direction iteration algorithm is designed. Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measurement (SSIM) are used to measure the performance of the method. Numerical results show that we can estimate the parameters in kernel accurately, and the new method has both much higher PSNR and much higher SSIM than the expectation maximization (EM) method in many cases. In addition, the accuracy of estimation is not sensitive to noise. Furthermore, even though the support of the kernel is unknown, we can also use this method to get accurate estimation.

Adaptive Neural Tracking Control for Switched High-Order Stochastic Nonlinear Systems.

PubMed

Zhao, Xudong; Wang, Xinyong; Zong, Guangdeng; Zheng, Xiaolong

2017-10-01

This paper deals with adaptive neural tracking control design for a class of switched high-order stochastic nonlinear systems with unknown uncertainties and arbitrary deterministic switching. The considered issues are: 1) completely unknown uncertainties; 2) stochastic disturbances; and 3) high-order nonstrict-feedback system structure. The considered mathematical models can represent many practical systems in the actual engineering. By adopting the approximation ability of neural networks, common stochastic Lyapunov function method together with adding an improved power integrator technique, an adaptive state feedback controller with multiple adaptive laws is systematically designed for the systems. Subsequently, a controller with only two adaptive laws is proposed to solve the problem of over parameterization. Under the designed controllers, all the signals in the closed-loop system are bounded-input bounded-output stable in probability, and the system output can almost surely track the target trajectory within a specified bounded error. Finally, simulation results are presented to show the effectiveness of the proposed approaches.

Analysis of Soft Drinks Using Nuclear Magnetic Resonance Spectroscopy: A Mentorship

NASA Astrophysics Data System (ADS)

Wilson, Arkim; Myers, Craig; Crull, George; Curtis, Michael; Pasciak Patterson, Pamela

1999-10-01

This mentorship was designed to expose a student to the laboratory routine for a chemist at Bristol Myers Squibb Company (BMS). The student visited BMS, collaborated with BMS scientists, and actually completed a project on site. He was asked to determine the identity of an unknown sample of soft drink retrieved from a fictitious crime scene using NMR spectroscopy. He designed an experiment to test the unknown sample and used samples of purified sugar, purified caffeine, purified citric acid, Coke, Diet Coke, Pepsi, Mountain Dew, Diet 7-Up, and Sam's Diet Cola as controls. The results were analyzed and presented in a final report. The student was able to determine if the unknown contained sugar, caffeine, Nutrasweet, or sodium benzoate. He learned how to compile relevant information, conduct an experiment, collect and analyze data, draw conclusions, and prepare and edit a formal report. In addition to learning the uses of NMR, he also learned some of its limitations. In the final report, he was encouraged to reflect on the difficulties a scientist might encounter when trying to identify NMR peaks without an "ingredient list" like those of the soft drink cans. The experience was rewarding for the student and all scientists involved.

Group sequential designs for stepped-wedge cluster randomised trials

PubMed Central

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.

PubMed

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.

Mean-square state and parameter estimation for stochastic linear systems with Gaussian and Poisson noises

NASA Astrophysics Data System (ADS)

Basin, M.; Maldonado, J. J.; Zendejo, O.

2016-07-01

This paper proposes new mean-square filter and parameter estimator design for linear stochastic systems with unknown parameters over linear observations, where unknown parameters are considered as combinations of Gaussian and Poisson white noises. The problem is treated by reducing the original problem to a filtering problem for an extended state vector that includes parameters as additional states, modelled as combinations of independent Gaussian and Poisson processes. The solution to this filtering problem is based on the mean-square filtering equations for incompletely polynomial states confused with Gaussian and Poisson noises over linear observations. The resulting mean-square filter serves as an identifier for the unknown parameters. Finally, a simulation example shows effectiveness of the proposed mean-square filter and parameter estimator.

Adaptive neural control for a class of nonlinear time-varying delay systems with unknown hysteresis.

PubMed

Liu, Zhi; Lai, Guanyu; Zhang, Yun; Chen, Xin; Chen, Chun Lung Philip

2014-12-01

This paper investigates the fusion of unknown direction hysteresis model with adaptive neural control techniques in face of time-delayed continuous time nonlinear systems without strict-feedback form. Compared with previous works on the hysteresis phenomenon, the direction of the modified Bouc-Wen hysteresis model investigated in the literature is unknown. To reduce the computation burden in adaptation mechanism, an optimized adaptation method is successfully applied to the control design. Based on the Lyapunov-Krasovskii method, two neural-network-based adaptive control algorithms are constructed to guarantee that all the system states and adaptive parameters remain bounded, and the tracking error converges to an adjustable neighborhood of the origin. In final, some numerical examples are provided to validate the effectiveness of the proposed control methods.

An Observational Study of Peer Learning for High School Students at a Cybersecurity Camp

ERIC Educational Resources Information Center

Pittman, Jason M.; Pike, Ronald E.

2016-01-01

This paper reports on the design and implementation of a cybersecurity camp offered as a cybersecurity learning experience to a group of female and male high school students. Students ranged in grade level from freshmen to senior. Student demographics, including any existing pre-requisite knowledge, were unknown to camp designers prior to the…

Teaching letter sounds to kindergarten English language learners using incremental rehearsal.

PubMed

Peterson, Meredith; Brandes, Dana; Kunkel, Amy; Wilson, Jennifer; Rahn, Naomi L; Egan, Andrea; McComas, Jennifer

2014-02-01

Proficiency in letter-sound correspondence is important for decoding connected text. This study examined the effects of an evidence-based intervention, incremental rehearsal (IR), on the letter-sound expression of three kindergarten English language learners (ELLs) performing below the district benchmark for letter-sound fluency. Participants were native speakers of Hmong, Spanish, and Polish. A multiple-baseline design across sets of unknown letter sounds was used to evaluate the effects of IR on letter-sound expression. Visual analysis of the data showed an increase in level and trend when IR was introduced in each phase. Percentage of all non-overlapping data (PAND) ranged from 95% to 100%. All participants exceeded expected growth and reached the spring district benchmark for letter-sound fluency. Results suggest that IR is a promising intervention for increasing letter-sound expression for ELLs who evidence delays in acquiring letter sounds. Copyright © 2013 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

On Bayesian methods of exploring qualitative interactions for targeted treatment.

PubMed

Chen, Wei; Ghosh, Debashis; Raghunathan, Trivellore E; Norkin, Maxim; Sargent, Daniel J; Bepler, Gerold

2012-12-10

Providing personalized treatments designed to maximize benefits and minimizing harms is of tremendous current medical interest. One problem in this area is the evaluation of the interaction between the treatment and other predictor variables. Treatment effects in subgroups having the same direction but different magnitudes are called quantitative interactions, whereas those having opposite directions in subgroups are called qualitative interactions (QIs). Identifying QIs is challenging because they are rare and usually unknown among many potential biomarkers. Meanwhile, subgroup analysis reduces the power of hypothesis testing and multiple subgroup analyses inflate the type I error rate. We propose a new Bayesian approach to search for QI in a multiple regression setting with adaptive decision rules. We consider various regression models for the outcome. We illustrate this method in two examples of phase III clinical trials. The algorithm is straightforward and easy to implement using existing software packages. We provide a sample code in Appendix A. Copyright © 2012 John Wiley & Sons, Ltd.

Data mining: childhood injury control and beyond.

PubMed

Tepas, Joseph J

2009-08-01

Data mining is defined as the automatic extraction of useful, often previously unknown information from large databases or data sets. It has become a major part of modern life and is extensively used in industry, banking, government, and health care delivery. The process requires a data collection system that integrates input from multiple sources containing critical elements that define outcomes of interest. Appropriately designed data mining processes identify and adjust for confounding variables. The statistical modeling used to manipulate accumulated data may involve any number of techniques. As predicted results are periodically analyzed against those observed, the model is consistently refined to optimize precision and accuracy. Whether applying integrated sources of clinical data to inferential probabilistic prediction of risk of ventilator-associated pneumonia or population surveillance for signs of bioterrorism, it is essential that modern health care providers have at least a rudimentary understanding of what the concept means, how it basically works, and what it means to current and future health care.

Identifiability and identification of trace continuous pollutant source.

PubMed

Qu, Hongquan; Liu, Shouwen; Pang, Liping; Hu, Tao

2014-01-01

Accidental pollution events often threaten people's health and lives, and a pollutant source is very necessary so that prompt remedial actions can be taken. In this paper, a trace continuous pollutant source identification method is developed to identify a sudden continuous emission pollutant source in an enclosed space. The location probability model is set up firstly, and then the identification method is realized by searching a global optimal objective value of the location probability. In order to discuss the identifiability performance of the presented method, a conception of a synergy degree of velocity fields is presented in order to quantitatively analyze the impact of velocity field on the identification performance. Based on this conception, some simulation cases were conducted. The application conditions of this method are obtained according to the simulation studies. In order to verify the presented method, we designed an experiment and identified an unknown source appearing in the experimental space. The result showed that the method can identify a sudden trace continuous source when the studied situation satisfies the application conditions.

Accommodating Sensor Bias in MRAC for State Tracking

NASA Technical Reports Server (NTRS)

Patre, Parag; Joshi, Suresh M.

2011-01-01

The problem of accommodating unknown sensor bias is considered in a direct model reference adaptive control (MRAC) setting for state tracking using state feedback. Sensor faults can occur during operation, and if the biased state measurements are directly used with a standard MRAC control law, neither closed-loop signal boundedness, nor asymptotic tracking can be guaranteed and the resulting tracking errors may be unbounded or unacceptably large. A modified MRAC law is proposed, which combines a bias estimator with control gain adaptation, and it is shown that signal boundedness can be accomplished, although the tracking error may not go to zero. Further, for the case wherein an asymptotically stable sensor bias estimator is available, an MRAC control law is proposed to accomplish asymptotic tracking and signal boundedness. Such a sensor bias estimator can be designed if additional sensor measurements are available, as illustrated for the case wherein bias is present in the rate gyro and airspeed measurements. Numerical example results are presented to illustrate each of the schemes.

Neural networks and fault probability evaluation for diagnosis issues.

PubMed

Kourd, Yahia; Lefebvre, Dimitri; Guersi, Noureddine

2014-01-01

This paper presents a new FDI technique for fault detection and isolation in unknown nonlinear systems. The objective of the research is to construct and analyze residuals by means of artificial intelligence and probabilistic methods. Artificial neural networks are first used for modeling issues. Neural networks models are designed for learning the fault-free and the faulty behaviors of the considered systems. Once the residuals generated, an evaluation using probabilistic criteria is applied to them to determine what is the most likely fault among a set of candidate faults. The study also includes a comparison between the contributions of these tools and their limitations, particularly through the establishment of quantitative indicators to assess their performance. According to the computation of a confidence factor, the proposed method is suitable to evaluate the reliability of the FDI decision. The approach is applied to detect and isolate 19 fault candidates in the DAMADICS benchmark. The results obtained with the proposed scheme are compared with the results obtained according to a usual thresholding method.

Secret Sharing of a Quantum State.

PubMed

Lu, He; Zhang, Zhen; Chen, Luo-Kan; Li, Zheng-Da; Liu, Chang; Li, Li; Liu, Nai-Le; Ma, Xiongfeng; Chen, Yu-Ao; Pan, Jian-Wei

2016-07-15

Secret sharing of a quantum state, or quantum secret sharing, in which a dealer wants to share a certain amount of quantum information with a few players, has wide applications in quantum information. The critical criterion in a threshold secret sharing scheme is confidentiality: with less than the designated number of players, no information can be recovered. Furthermore, in a quantum scenario, one additional critical criterion exists: the capability of sharing entangled and unknown quantum information. Here, by employing a six-photon entangled state, we demonstrate a quantum threshold scheme, where the shared quantum secrecy can be efficiently reconstructed with a state fidelity as high as 93%. By observing that any one or two parties cannot recover the secrecy, we show that our scheme meets the confidentiality criterion. Meanwhile, we also demonstrate that entangled quantum information can be shared and recovered via our setting, which shows that our implemented scheme is fully quantum. Moreover, our experimental setup can be treated as a decoding circuit of the five-qubit quantum error-correcting code with two erasure errors.

"Finding the Joy in the Unknown": Implementation of STEAM Teaching Practices in Middle School Science and Math Classrooms

NASA Astrophysics Data System (ADS)

Quigley, Cassie F.; Herro, Dani

2016-06-01

In response to a desire to strengthen the economy, educational settings are emphasizing science, technology, engineering, and mathematics (STEM) curriculum and programs. Yet, because of the narrow approach to STEM, educational leaders continue to call for a more balanced approach to teaching and learning, which includes the arts, design, and humanities. This desire created space for science, technology, engineering, arts, and mathematics (STEAM) education, a transdisciplinary approach that focuses on problem-solving. STEAM-based curricula and STEAM-themed schools are appearing all over the globe. This growing national and global attention to STEAM provides an opportunity for teacher education to explore the ways in which teachers implement STEAM practices, examining the successes and challenges, and how teachers are beginning to make sense of this innovative teaching practice. The purpose of this paper is to examine the implementation of STEAM teaching practices in science and math middle school classrooms, in hopes to provide research-based evidence on this emerging topic to guide teacher educators.

Synthetic biology approaches to biological containment: pre-emptively tackling potential risks

PubMed Central

Krüger, Antje; Csibra, Eszter; Gianni, Edoardo

2016-01-01

Biocontainment comprises any strategy applied to ensure that harmful organisms are confined to controlled laboratory conditions and not allowed to escape into the environment. Genetically engineered microorganisms (GEMs), regardless of the nature of the modification and how it was established, have potential human or ecological impact if accidentally leaked or voluntarily released into a natural setting. Although all evidence to date is that GEMs are unable to compete in the environment, the power of synthetic biology to rewrite life requires a pre-emptive strategy to tackle possible unknown risks. Physical containment barriers have proven effective but a number of strategies have been developed to further strengthen biocontainment. Research on complex genetic circuits, lethal genes, alternative nucleic acids, genome recoding and synthetic auxotrophies aim to design more effective routes towards biocontainment. Here, we describe recent advances in synthetic biology that contribute to the ongoing efforts to develop new and improved genetic, semantic, metabolic and mechanistic plans for the containment of GEMs. PMID:27903826

Development of x-ray imaging technique for liquid screening at airport

NASA Astrophysics Data System (ADS)

Sulaiman, Nurhani binti; Srisatit, Somyot

2016-01-01

X-ray imaging technology is a viable option to recognize flammable liquids for the purposes of aviation security. In this study, an X-ray imaging technology was developed whereby, the image viewing system was built with the use of a digital camera coupled with a gadolinium oxysulfide (GOS) fluorescent screen. The camera was equipped with a software for remote control setting of the camera via a USB cable which allows the images to be captured. The image was analysed to determine the average grey level using a software designed by Microsoft Visual Basic 6.0. The data was obtained for various densities of liquid thickness of 4.5 cm, 6.0 cm and 7.5 cm respectively for X-ray energies ranging from 70 to 200 kVp. In order to verify the reliability of the constructed calibration data, the system was tested with a few types of unknown liquids. The developed system could be conveniently employed for security screening in order to discriminate between a threat and an innocuous liquid.

Sequential Feedback Scheme Outperforms the Parallel Scheme for Hamiltonian Parameter Estimation.

PubMed

Yuan, Haidong

2016-10-14

Measurement and estimation of parameters are essential for science and engineering, where the main quest is to find the highest achievable precision with the given resources and design schemes to attain it. Two schemes, the sequential feedback scheme and the parallel scheme, are usually studied in the quantum parameter estimation. While the sequential feedback scheme represents the most general scheme, it remains unknown whether it can outperform the parallel scheme for any quantum estimation tasks. In this Letter, we show that the sequential feedback scheme has a threefold improvement over the parallel scheme for Hamiltonian parameter estimations on two-dimensional systems, and an order of O(d+1) improvement for Hamiltonian parameter estimation on d-dimensional systems. We also show that, contrary to the conventional belief, it is possible to simultaneously achieve the highest precision for estimating all three components of a magnetic field, which sets a benchmark on the local precision limit for the estimation of a magnetic field.

Synthetic biology approaches to biological containment: pre-emptively tackling potential risks.

PubMed

Torres, Leticia; Krüger, Antje; Csibra, Eszter; Gianni, Edoardo; Pinheiro, Vitor B

2016-11-30

Biocontainment comprises any strategy applied to ensure that harmful organisms are confined to controlled laboratory conditions and not allowed to escape into the environment. Genetically engineered microorganisms (GEMs), regardless of the nature of the modification and how it was established, have potential human or ecological impact if accidentally leaked or voluntarily released into a natural setting. Although all evidence to date is that GEMs are unable to compete in the environment, the power of synthetic biology to rewrite life requires a pre-emptive strategy to tackle possible unknown risks. Physical containment barriers have proven effective but a number of strategies have been developed to further strengthen biocontainment. Research on complex genetic circuits, lethal genes, alternative nucleic acids, genome recoding and synthetic auxotrophies aim to design more effective routes towards biocontainment. Here, we describe recent advances in synthetic biology that contribute to the ongoing efforts to develop new and improved genetic, semantic, metabolic and mechanistic plans for the containment of GEMs. © 2016 The Author(s).

Educating Mental Health Clinicians About Sensory Modulation to Enhance Clinical Practice in a Youth Acute Inpatient Mental Health Unit: A Feasibility Study.

PubMed

Blackburn, Julie; McKenna, Brian; Jackson, Brian; Hitch, Danielle; Benitez, Jessica; McLennan, Cathy; Furness, Trentham

2016-07-01

There is an emergence of literature describing effective sensory modulation (SM) interventions to de-escalate violence and aggression among mental health inpatients. However, the evidence is limited to adult settings, with the effect of SM in youth acute settings unknown. Yet, before SM may be used as a de-escalation intervention in youth acute settings, multidisciplinary staff need to be educated about and supported in the clinical application of SM. In the current study, an online SM education package was developed to assist mental health staff understand SM. This was blended with action learning sets (ALS), small group experiential opportunities consisting staff and consumers to learn about SM resources, and the support of SM trained nurses. The aims of the study were to evaluate the effectiveness of this SM education intervention in (a) transferring knowledge of SM to staff, and (b) translating this knowledge into practice in a youth acute inpatient mental health unit. A mixed methods research design with an 11-item pre- and post-education questionnaire was used along with three-month follow-up focus groups. The SM education improved understanding about SM (all 11-items p ≤ 0.004, r ≥ 0.47). Three-months after SM education, four themes evident in the focus group data emerged about the practice and process of SM; (1) translating of learning into practice, (2) SM in practice, (3) perceptions of SM benefits, and (4) limitations of SM. A blended SM education process enhanced clinical practice in the unit, yet participants were mindful of limitations of SM in situations of distress or escalating agitation.

Graduate-Assistant Athletic Trainers' Perceptions of Professional Socialization in the Collegiate Setting: Part I

PubMed Central

Thrasher, Ashley B.; Walker, Stacy E.; Hankemeier, Dorice A.; Mulvihill, Thalia

2016-01-01

Context: Many newly credentialed athletic trainers (ATs) pursue graduate assistantships, which allow them to gain experience while being supervised by an experienced AT. The graduate-assistant (GA) ATs' perception of their socialization process into the collegiate setting is unknown. Objective: To explore the professional socialization of GAs in the collegiate setting. Design: Qualitative study. Setting: Phone interviews. Patients or Other Participants: A total of 19 collegiate GAs (15 women, 4 men; average age = 23 ± 0.15 years; National Collegiate Athletic Association Division I = 13, II = 3, III = 2; National Association of Intercollegiate Athletics = 2; postprofessional athletic training program = 6) participated. Data Collection and Analysis: Data were collected via phone interviews and transcribed verbatim. Interviews were conducted until data saturation occurred. Data were analyzed through phenomenologic reduction. Trustworthiness was established via member checks and peer review. Results: Four themes emerged: (1) role identity, (2) initial entry into role, (3) maturation, and (4) success. Before beginning their role, participants envisioned the assistantship as a way to gain independent experience while being mentored. They perceived themselves as the primary care providers for their athletic teams. Those who were immediately immersed into clinical practice adapted to their role quickly despite experiencing stress initially. Participants felt that a formal orientation process and a policies and procedures manual would have alleviated some of the initial stress. The GAs matured as they practiced clinically and developed confidence as they gained experience. Personal attributes, experience, and peer and supervisor support contributed to perceived success as GAs. Factors that hindered perceived success were lack of confidence, an unsupportive environment, and long hours. Conclusions: When looking for graduate assistantships, ATs should seek a position that allows them to practice independently and provides didactic educational opportunities while aligning with their athletic training philosophies. PMID:27831745

Desired Accuracy Estimation of Noise Function from ECG Signal by Fuzzy Approach

PubMed Central

Vahabi, Zahra; Kermani, Saeed

2012-01-01

Unknown noise and artifacts present in medical signals with non-linear fuzzy filter will be estimated and then removed. An adaptive neuro-fuzzy interference system which has a non-linear structure presented for the noise function prediction by before Samples. This paper is about a neuro-fuzzy method to estimate unknown noise of Electrocardiogram signal. Adaptive neural combined with Fuzzy System to construct a fuzzy Predictor. For this system setting parameters such as the number of Membership Functions for each input and output, training epochs, type of MFs for each input and output, learning algorithm and etc. is determined by learning data. At the end simulated experimental results are presented for proper validation. PMID:23717810

Groebner Basis Solutions to Satellite Trajectory Control by Pole Placement

NASA Astrophysics Data System (ADS)

Kukelova, Z.; Krsek, P.; Smutny, V.; Pajdla, T.

2013-09-01

Satellites play an important role, e.g., in telecommunication, navigation and weather monitoring. Controlling their trajectories is an important problem. In [1], an approach to the pole placement for the synthesis of a linear controller has been presented. It leads to solving five polynomial equations in nine unknown elements of the state space matrices of a compensator. This is an underconstrained system and therefore four of the unknown elements need to be considered as free parameters and set to some prior values to obtain a system of five equations in five unknowns. In [1], this system was solved for one chosen set of free parameters with the help of Dixon resultants. In this work, we study and present Groebner basis solutions to this problem of computation of a dynamic compensator for the satellite for different combinations of input free parameters. We show that the Groebner basis method for solving systems of polynomial equations leads to very simple solutions for all combinations of free parameters. These solutions require to perform only the Gauss-Jordan elimination of a small matrix and computation of roots of a single variable polynomial. The maximum degree of this polynomial is not greater than six in general but for most combinations of the input free parameters its degree is even lower. [1] B. Palancz. Application of Dixon resultant to satellite trajectory control by pole placement. Journal of Symbolic Computation, Volume 50, March 2013, Pages 79-99, Elsevier.

Improved central confidence intervals for the ratio of Poisson means

NASA Astrophysics Data System (ADS)

Cousins, R. D.

The problem of confidence intervals for the ratio of two unknown Poisson means was "solved" decades ago, but a closer examination reveals that the standard solution is far from optimal from the frequentist point of view. We construct a more powerful set of central confidence intervals, each of which is a (typically proper) subinterval of the corresponding standard interval. They also provide upper and lower confidence limits which are more restrictive than the standard limits. The construction follows Neyman's original prescription, though discreteness of the Poisson distribution and the presence of a nuisance parameter (one of the unknown means) lead to slightly conservative intervals. Philosophically, the issue of the appropriateness of the construction method is similar to the issue of conditioning on the margins in 2×2 contingency tables. From a frequentist point of view, the new set maintains (over) coverage of the unknown true value of the ratio of means at each stated confidence level, even though the new intervals are shorter than the old intervals by any measure (except for two cases where they are identical). As an example, when the number 2 is drawn from each Poisson population, the 90% CL central confidence interval on the ratio of means is (0.169, 5.196), rather than (0.108, 9.245). In the cited literature, such confidence intervals have applications in numerous branches of pure and applied science, including agriculture, wildlife studies, manufacturing, medicine, reliability theory, and elementary particle physics.

Adaptive Control in the Presence of Simultaneous Sensor Bias and Actuator Failures

NASA Technical Reports Server (NTRS)

Joshi, Suresh M.

2012-01-01

The problem of simultaneously accommodating unknown sensor biases and unknown actuator failures in uncertain systems is considered in a direct model reference adaptive control (MRAC) setting for state tracking using state feedback. Sensor biases and actuator faults may be present at the outset or may occur at unknown instants of time during operation. A modified MRAC law is proposed, which combines sensor bias estimation with control gain adaptation for accommodation of sensor biases and actuator failures. This control law is shown to provide signal boundedness in the resulting system. For the case when an external asymptotically stable sensor bias estimator is available, an MRAC law is developed to accomplish asymptotic state tracking and signal boundedness. For a special case wherein biases are only present in the rate measurements and bias-free position measurements are available, an MRAC law is developed using a model-independent bias estimator, and is shown to provide asymptotic state tracking with signal boundedness.

Do educational interventions improve nurses' clinical decision making and judgement? A systematic review.

PubMed

Thompson, Carl; Stapley, Sally

2011-07-01

Despite the growing popularity of decision making in nursing curricula, the effectiveness of educational interventions to improve nursing judgement and decision making is unknown. We sought to synthesise and summarise the comparative evidence for educational interventions to improve nursing judgements and clinical decisions. A systematic review. Electronic databases: Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, CINAHL and PsycINFO, Social Sciences Citation Index, OpenSIGLE conference proceedings and hand searching nursing journals. Studies published since 1960, reporting any educational intervention that aimed to improve nurses' clinical judgements or decision making were included. Studies were assessed for relevance and quality. Data extracted included study design; educational setting; the nature of participants; whether the study was concerned with the clinical application of skills or the application of theory; the type of decision targeted by the intervention (e.g. diagnostic reasoning) and whether the evaluation of the intervention focused on efficacy or effectiveness. A narrative approach to study synthesis was used due to heterogeneity in interventions, study samples, outcomes and settings and incomplete reporting of effect sizes. From 5262 initial citations 24 studies were included in the review. A variety of educational approaches were reported. Study quality and content reporting was generally poor. Pedagogical theories were widely used but use of decision theory (with the exception of subjective expected utility theory implicit in decision analysis) was rare. The effectiveness and efficacy of interventions was mixed. Educational interventions to improve nurses' judgements and decisions are complex and the evidence from comparative studies does little to reduce the uncertainty about 'what works'. Nurse educators need to pay attention to decision, as well as pedagogical, theory in the design of interventions. Study design and reporting requires improvement to maximise the information contained in reports of educational interventions. Copyright © 2011 Elsevier Ltd. All rights reserved.

Use of designed sequences in protein structure recognition.

PubMed

Kumar, Gayatri; Mudgal, Richa; Srinivasan, Narayanaswamy; Sandhya, Sankaran

2018-05-09

Knowledge of the protein structure is a pre-requisite for improved understanding of molecular function. The gap in the sequence-structure space has increased in the post-genomic era. Grouping related protein sequences into families can aid in narrowing the gap. In the Pfam database, structure description is provided for part or full-length proteins of 7726 families. For the remaining 52% of the families, information on 3-D structure is not yet available. We use the computationally designed sequences that are intermediately related to two protein domain families, which are already known to share the same fold. These strategically designed sequences enable detection of distant relationships and here, we have employed them for the purpose of structure recognition of protein families of yet unknown structure. We first measured the success rate of our approach using a dataset of protein families of known fold and achieved a success rate of 88%. Next, for 1392 families of yet unknown structure, we made structural assignments for part/full length of the proteins. Fold association for 423 domains of unknown function (DUFs) are provided as a step towards functional annotation. The results indicate that knowledge-based filling of gaps in protein sequence space is a lucrative approach for structure recognition. Such sequences assist in traversal through protein sequence space and effectively function as 'linkers', where natural linkers between distant proteins are unavailable. This article was reviewed by Oliviero Carugo, Christine Orengo and Srikrishna Subramanian.

34. Photocopy of photograph (original print located in LBNL Photo ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

34. Photocopy of photograph (original print located in LBNL Photo Lab Collection). Photographer unknown. October 6, 1955. BEV-938. ANTI-PROTON SET-UP WITH WORK GROUP; E. SEGRE, C. WIEGAND, E. LOFGREN, O. CHAMBERLAIN, T. YPSILANTIS. B-51. - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

Using transcriptomic tools to evaluate biological effects across effluent gradients at a diverse set of study sites in Minnesota, USA

EPA Science Inventory

The aim of this overall project was to explore the utility of ?‘omics’ approaches in monitoring aquatic environments where complex, often unknown, stressors make chemical-specific risk assessment untenable. This specific component of the effort examined changes in the fathead min...

Private Middle School Parents' Perspectives Regarding School-Located Immunization Programs (SLIPs)

ERIC Educational Resources Information Center

Venkatesh, Sheila R.; Acosta, Amy B.; Middleman, Amy B.

2013-01-01

The perspectives of parents of private middle school students regarding the use of school-located immunization programs (SLIPs) are unknown. Parents of private middle school students in a large, urban setting were surveyed "N" = 1,210) regarding their willingness to use SLIPs. Analyses included frequencies and chi-square analyses. Data…

Metabolomic technologies for improving the quality of food: Practice and promise

USDA-ARS?s Scientific Manuscript database

It is now well documented that the diet has a significant impact on human health and well-being. However, the complete set of small molecule metabolites present in foods that make up the human diet and the role of food production systems in altering this food metabolome are still largely unknown. Me...

Student Engagement in Long-Term Collaborative EFL Storytelling Activities: An Analysis of Learners with English Proficiency Differences

ERIC Educational Resources Information Center

Huang, Yun-Yin; Liu, Chen-Chung; Wang, Yu; Tsai, Chin-Chung; Lin, Hung-Ming

2017-01-01

English proficiency difference among students is a challenging pedagogical issue in EFL classrooms worldwide. Collaborative digital storytelling has been adopted in language learning settings to increase motivation and engagement, especially for young learners. However, it remains unknown whether students of different proficiency levels can…

Modeling Human Performance in Restless Bandits with Particle Filters

ERIC Educational Resources Information Center

Yi, Sheng Kung M.; Steyvers, Mark; Lee, Michael

2009-01-01

Bandit problems provide an interesting and widely-used setting for the study of sequential decision-making. In their most basic form, bandit problems require people to choose repeatedly between a small number of alternatives, each of which has an unknown rate of providing reward. We investigate restless bandit problems, where the distributions of…

Utility of Pamphlets in Promoting Knowledge and Positive Attitudes about Two Early Cancer Detection Procedures.

ERIC Educational Resources Information Center

Marty, Phillip J.; McDermott, Robert J.

Informational pamphlets about breast self-examination (BSE) and testicular self-examination (TSE) are widely distributed in health care settings, but the pamphlets' effectiveness in promoting knowledge and positive attitudes about these early cancer detection procedures is largely unknown. A study compared pamphlets with alternative methods of…

The Positive and Negative Consequences of Multiple-Choice Testing

ERIC Educational Resources Information Center

Roediger, Henry L.; Marsh, Elizabeth J.

2005-01-01

Multiple-choice tests are commonly used in educational settings but with unknown effects on students' knowledge. The authors examined the consequences of taking a multiple-choice test on a later general knowledge test in which students were warned not to guess. A large positive testing effect was obtained: Prior testing of facts aided final…

Known and Unknown Weaknesses in Software Animated Demonstrations (Screencasts): A Study in Self-Paced Learning Settings

ERIC Educational Resources Information Center

Palaigeorgiou, George; Despotakis, Theofanis

2010-01-01

Learning about computers continues to be regarded as a rather informal and complex landscape dominated by individual exploratory and opportunistic approaches, even for students and instructors in Computer Science Departments. During the last two decades, software animated demonstrations (SADs), also known as screencasts, have attracted particular…

The cellular and molecular etiology of the craniofacial defects in the avian ciliopathic mutant talpid2

USDA-ARS?s Scientific Manuscript database

talpid2 is an avian autosomal recessive mutant with a myriad of congenital malformations, including polydactyly and facial clefting. Although phenotypically similar to talpid3, talpid2 has a distinct facial phenotype and an unknown cellular, molecular and genetic basis. We set out to determine the e...

Socialization, Social Support, and Social Cognitive Theory: An Examination of the Graduate Teaching Assistant

ERIC Educational Resources Information Center

Dixon, Kelly Elizabeth

2012-01-01

Graduate teaching assistants (GTAs) face the unknown as they negotiate their multiple roles and identities within the graduate school and classroom setting as teachers, students, and researchers. The purpose of this study is to identify the role that institutionalized socialization, social support, and behavioral observation and modeling play for…

No-Suicide Contracts with Suicidal Youth: Mental Health Professionals' Perceptions and Current Practice

ERIC Educational Resources Information Center

Hansen, Andrea; Heath, Melissa Allen; Williams, Marleen; Fox, Jay; Hudnall, Gregory A.; Bledsoe, Catherine

2012-01-01

Commonly used in clinical and medical settings, no-suicide contracts (NSCs) solicit commitment from suicidal individuals not to attempt suicide. The prevalence of community and school-based Mental Health Professionals' (MHPs) use of NSCs with suicidal youth (SY) is unknown. Additionally, minimal feedback is available regarding MHPs' current…

Empowering Students with Word-Learning Strategies: Teach a Child to Fish

ERIC Educational Resources Information Center

Graves, Michael F.; Schneider, Steven; Ringstaff, Cathy

2018-01-01

This article on word-learning strategies describes a theory- and research-based set of procedures for teaching students to use word-learning strategies--word parts, context clues, the dictionary, and a combined strategy--to infer the meanings of unknown words. The article begins with a rationale for teaching word-learning strategies, particularly…

Bayesian assessment of the expected data impact on prediction confidence in optimal sampling design

NASA Astrophysics Data System (ADS)

Leube, P. C.; Geiges, A.; Nowak, W.

2012-02-01

Incorporating hydro(geo)logical data, such as head and tracer data, into stochastic models of (subsurface) flow and transport helps to reduce prediction uncertainty. Because of financial limitations for investigation campaigns, information needs toward modeling or prediction goals should be satisfied efficiently and rationally. Optimal design techniques find the best one among a set of investigation strategies. They optimize the expected impact of data on prediction confidence or related objectives prior to data collection. We introduce a new optimal design method, called PreDIA(gnosis) (Preposterior Data Impact Assessor). PreDIA derives the relevant probability distributions and measures of data utility within a fully Bayesian, generalized, flexible, and accurate framework. It extends the bootstrap filter (BF) and related frameworks to optimal design by marginalizing utility measures over the yet unknown data values. PreDIA is a strictly formal information-processing scheme free of linearizations. It works with arbitrary simulation tools, provides full flexibility concerning measurement types (linear, nonlinear, direct, indirect), allows for any desired task-driven formulations, and can account for various sources of uncertainty (e.g., heterogeneity, geostatistical assumptions, boundary conditions, measurement values, model structure uncertainty, a large class of model errors) via Bayesian geostatistics and model averaging. Existing methods fail to simultaneously provide these crucial advantages, which our method buys at relatively higher-computational costs. We demonstrate the applicability and advantages of PreDIA over conventional linearized methods in a synthetic example of subsurface transport. In the example, we show that informative data is often invisible for linearized methods that confuse zero correlation with statistical independence. Hence, PreDIA will often lead to substantially better sampling designs. Finally, we extend our example to specifically highlight the consideration of conceptual model uncertainty.

Estimating open population site occupancy from presence-absence data lacking the robust design.

PubMed

Dail, D; Madsen, L

2013-03-01

Many animal monitoring studies seek to estimate the proportion of a study area occupied by a target population. The study area is divided into spatially distinct sites where the detected presence or absence of the population is recorded, and this is repeated in time for multiple seasons. However, when occupied sites are detected with probability p < 1, the lack of a detection does not imply lack of occupancy. MacKenzie et al. (2003, Ecology 84, 2200-2207) developed a multiseason model for estimating seasonal site occupancy (ψt ) while accounting for unknown p. Their model performs well when observations are collected according to the robust design, where multiple sampling occasions occur during each season; the repeated sampling aids in the estimation p. However, their model does not perform as well when the robust design is lacking. In this paper, we propose an alternative likelihood model that yields improved seasonal estimates of p and Ψt in the absence of the robust design. We construct the marginal likelihood of the observed data by conditioning on, and summing out, the latent number of occupied sites during each season. A simulation study shows that in cases without the robust design, the proposed model estimates p with less bias than the MacKenzie et al. model and hence improves the estimates of Ψt . We apply both models to a data set consisting of repeated presence-absence observations of American robins (Turdus migratorius) with yearly survey periods. The two models are compared to a third estimator available when the repeated counts (from the same study) are considered, with the proposed model yielding estimates of Ψt closest to estimates from the point count model. Copyright © 2013, The International Biometric Society.

Sequence Elucidation of an Unknown Cyclic Peptide of High Doping Potential by ETD and CID Tandem Mass Spectrometry

NASA Astrophysics Data System (ADS)

Guan, Fuyu; Uboh, Cornelius E.; Soma, Lawrence R.; Rudy, Jeffrey

2011-04-01

Identification of an unknown substance without any information remains a daunting challenge despite advances in chemistry and mass spectrometry. However, an unknown cyclic peptide in a sample with very limited volume seized at a Pennsylvania racetrack has been successfully identified. The unknown sample was determined by accurate mass measurements to contain a small unknown peptide as the major component. Collision-induced dissociation (CID) of the unknown peptide revealed the presence of Lys (not Gln, by accurate mass), Phe, and Arg residues, and absence of any y-type product ion. The latter, together with the tryptic digestion results of the unusual deamidation and absence of any tryptic cleavage, suggests a cyclic structure for the peptide. Electron-transfer dissociation (ETD) of the unknown peptide indicated the presence of Gln (not Lys, by the unusual deamidation), Phe, and Arg residues and their connectivity. After all the results were pieced together, a cyclic tetrapeptide, cyclo[Arg-Lys-N(C6H9)Gln-Phe], is proposed for the unknown peptide. Observations of different amino acid residues from CID and ETD experiments for the peptide were interpreted by a fragmentation pathway proposed, as was preferential CID loss of a Lys residue from the peptide. ETD was used for the first time in sequencing of a cyclic peptide; product ions resulting from ETD of the peptide identified were categorized into two types and named pseudo-b and pseudo-z ions that are important for sequencing of cyclic peptides. The ETD product ions were interpreted by fragmentation pathways proposed. Additionally, multi-stage CID mass spectrometry cannot provide complete sequence information for cyclic peptides containing adjacent Arg and Lys residues. The identified cyclic peptide has not been documented in the literature, its pharmacological effects are unknown, but it might be a "designer" drug with athletic performance-enhancing effects.

Genetic Variants Identified from Epilepsy of Unknown Etiology in Chinese Children by Targeted Exome Sequencing

PubMed Central

Wang, Yimin; Du, Xiaonan; Bin, Rao; Yu, Shanshan; Xia, Zhezhi; Zheng, Guo; Zhong, Jianmin; Zhang, Yunjian; Jiang, Yong-hui; Wang, Yi

2017-01-01

Genetic factors play a major role in the etiology of epilepsy disorders. Recent genomics studies using next generation sequencing (NGS) technique have identified a large number of genetic variants including copy number (CNV) and single nucleotide variant (SNV) in a small set of genes from individuals with epilepsy. These discoveries have contributed significantly to evaluate the etiology of epilepsy in clinic and lay the foundation to develop molecular specific treatment. However, the molecular basis for a majority of epilepsy patients remains elusive, and furthermore, most of these studies have been conducted in Caucasian children. Here we conducted a targeted exome-sequencing of 63 trios of Chinese epilepsy families using a custom-designed NGS panel that covers 412 known and candidate genes for epilepsy. We identified pathogenic and likely pathogenic variants in 15 of 63 (23.8%) families in known epilepsy genes including SCN1A, CDKL5, STXBP1, CHD2, SCN3A, SCN9A, TSC2, MBD5, POLG and EFHC1. More importantly, we identified likely pathologic variants in several novel candidate genes such as GABRE, MYH1, and CLCN6. Our results provide the evidence supporting the application of custom-designed NGS panel in clinic and indicate a conserved genetic susceptibility for epilepsy between Chinese and Caucasian children. PMID:28074849

Current and new challenges in occupational lung diseases.

PubMed

De Matteis, Sara; Heederik, Dick; Burdorf, Alex; Colosio, Claudio; Cullinan, Paul; Henneberger, Paul K; Olsson, Ann; Raynal, Anne; Rooijackers, Jos; Santonen, Tiina; Sastre, Joaquin; Schlünssen, Vivi; van Tongeren, Martie; Sigsgaard, Torben

2017-12-31

Occupational lung diseases are an important public health issue and are avoidable through preventive interventions in the workplace. Up-to-date knowledge about changes in exposure to occupational hazards as a result of technological and industrial developments is essential to the design and implementation of efficient and effective workplace preventive measures. New occupational agents with unknown respiratory health effects are constantly introduced to the market and require periodic health surveillance among exposed workers to detect early signs of adverse respiratory effects. In addition, the ageing workforce, many of whom have pre-existing respiratory conditions, poses new challenges in terms of the diagnosis and management of occupational lung diseases. Primary preventive interventions aimed to reduce exposure levels in the workplace remain pivotal for elimination of the occupational lung disease burden. To achieve this goal there is still a clear need for setting standard occupational exposure limits based on transparent evidence-based methodology, in particular for carcinogens and sensitising agents that expose large working populations to risk. The present overview, focused on the occupational lung disease burden in Europe, proposes directions for all parties involved in the prevention of occupational lung disease, from researchers and occupational and respiratory health professionals to workers and employers. The content of this work is not subject to copyright. Design and branding are copyright ©ERS 2017.

Recharge beneath low-impact design rain gardens and the influence of El Niño Southern Oscillation on urban, coastal groundwater resources

NASA Astrophysics Data System (ADS)

Newcomer, M. E.; Gurdak, J. J.

2011-12-01

Groundwater resources in urban, coastal environments are highly vulnerable to increased human pressures and climate variability. Impervious surfaces, such as buildings, roads, and parking lots prevent infiltration, reduce recharge to underlying aquifers, and increase contaminants in surface runoff that often overflow sewage systems. To mitigate these effects, cities worldwide are adopting low impact design (LID) approaches that direct runoff into natural vegetated systems, such as rain gardens that reduce, filter, and slow stormwater runoff, and are hypothesized to increase infiltration and recharge rates to aquifers. The effects of LID on recharge rates and quality is unknown, particularly during intense precipitation events for cities along the Pacific coast in response to interannual variability of the El Niño Southern Oscillation (ENSO). Using vadose zone monitoring sensors and instruments, I collected and monitored soil, hydraulic, and geochemical data to quantify the rates and quality of infiltration and recharge to the California Coastal aquifer system beneath a LID rain garden and traditional turf-lawn setting in San Francisco, CA. The data were used to calibrate a HYDRUS-3D model to simulate recharge rates under historical and future variability of ENSO. Understanding these processes has important implications for managing groundwater resources in urban, coastal environments.

Identifying chemicals that are planetary boundary threats.

PubMed

MacLeod, Matthew; Breitholtz, Magnus; Cousins, Ian T; de Wit, Cynthia A; Persson, Linn M; Rudén, Christina; McLachlan, Michael S

2014-10-07

Rockström et al. proposed a set of planetary boundaries that delimit a "safe operating space for humanity". Many of the planetary boundaries that have so far been identified are determined by chemical agents. Other chemical pollution-related planetary boundaries likely exist, but are currently unknown. A chemical poses an unknown planetary boundary threat if it simultaneously fulfills three conditions: (1) it has an unknown disruptive effect on a vital Earth system process; (2) the disruptive effect is not discovered until it is a problem at the global scale, and (3) the effect is not readily reversible. In this paper, we outline scenarios in which chemicals could fulfill each of the three conditions, then use the scenarios as the basis to define chemical profiles that fit each scenario. The chemical profiles are defined in terms of the nature of the effect of the chemical and the nature of exposure of the environment to the chemical. Prioritization of chemicals in commerce against some of the profiles appears feasible, but there are considerable uncertainties and scientific challenges that must be addressed. Most challenging is prioritizing chemicals for their potential to have a currently unknown effect on a vital Earth system process. We conclude that the most effective strategy currently available to identify chemicals that are planetary boundary threats is prioritization against profiles defined in terms of environmental exposure combined with monitoring and study of the biogeochemical processes that underlie vital Earth system processes to identify currently unknown disruptive effects.

The e-health implementation toolkit: qualitative evaluation across four European countries

PubMed Central

2011-01-01

Background Implementation researchers have attempted to overcome the research-practice gap in e-health by developing tools that summarize and synthesize research evidence of factors that impede or facilitate implementation of innovation in healthcare settings. The e-Health Implementation Toolkit (e-HIT) is an example of such a tool that was designed within the context of the United Kingdom National Health Service to promote implementation of e-health services. Its utility in international settings is unknown. Methods We conducted a qualitative evaluation of the e-HIT in use across four countries--Finland, Norway, Scotland, and Sweden. Data were generated using a combination of interview approaches (n = 22) to document e-HIT users' experiences of the tool to guide decision making about the selection of e-health pilot services and to monitor their progress over time. Results e-HIT users evaluated the tool positively in terms of its scope to organize and enhance their critical thinking about their implementation work and, importantly, to facilitate discussion between those involved in that work. It was easy to use in either its paper- or web-based format, and its visual elements were positively received. There were some minor criticisms of the e-HIT with some suggestions for content changes and comments about its design as a generic tool (rather than specific to sites and e-health services). However, overall, e-HIT users considered it to be a highly workable tool that they found useful, which they would use again, and which they would recommend to other e-health implementers. Conclusion The use of the e-HIT is feasible and acceptable in a range of international contexts by a range of professionals for a range of different e-health systems. PMID:22098945

The e-Health Implementation Toolkit: qualitative evaluation across four European countries.

PubMed

MacFarlane, Anne; Clerkin, Pauline; Murray, Elizabeth; Heaney, David J; Wakeling, Mary; Pesola, Ulla-Maija; Waterworth, Eva Lindh; Larsen, Frank; Makiniemi, Minna; Winblad, Ilkka

2011-11-19

Implementation researchers have attempted to overcome the research-practice gap in e-health by developing tools that summarize and synthesize research evidence of factors that impede or facilitate implementation of innovation in healthcare settings. The e-Health Implementation Toolkit (e-HIT) is an example of such a tool that was designed within the context of the United Kingdom National Health Service to promote implementation of e-health services. Its utility in international settings is unknown. We conducted a qualitative evaluation of the e-HIT in use across four countries--Finland, Norway, Scotland, and Sweden. Data were generated using a combination of interview approaches (n = 22) to document e-HIT users' experiences of the tool to guide decision making about the selection of e-health pilot services and to monitor their progress over time. e-HIT users evaluated the tool positively in terms of its scope to organize and enhance their critical thinking about their implementation work and, importantly, to facilitate discussion between those involved in that work. It was easy to use in either its paper- or web-based format, and its visual elements were positively received. There were some minor criticisms of the e-HIT with some suggestions for content changes and comments about its design as a generic tool (rather than specific to sites and e-health services). However, overall, e-HIT users considered it to be a highly workable tool that they found useful, which they would use again, and which they would recommend to other e-health implementers. The use of the e-HIT is feasible and acceptable in a range of international contexts by a range of professionals for a range of different e-health systems.

Physical activity as a preventive measure against overweight, obesity, infections, allergies and cardiovascular disease risk factors in adolescents: AFINOS Study protocol

PubMed Central

2009-01-01

Background Prior studies addressing the impacts of regular physical activity or sedentary habits on the immune system have been conducted in adults and laboratory settings. Thus, it is practically unknown how a healthy active lifestyle could affect low-grade inflammation processes, infections or allergies in young persons. The AFINOS Study was designed to determine the relationship between the regular physical activity levels of adolescents and overweight, infection, and allergies along with the presence of metabolic and immunological biomarkers of a deteriorated health status. A further objective of the AFINOS Study is to assess the health status and lifestyle habits of an adolescent population in an effort to identify any protective factors that could be used as preventive measures, since many chronic diseases and their associated co-morbidities often persist from adolescence into adulthood. Methods/Design This study was conducted as three separate sub-studies in three different populations as follows: (a) Study 1 was performed on a population sample of adolescents; (b) Study 2 on the adolescents' parents; and (c) Study 3 on a subset of the adolescents from Study 1. Study 1 assessed health and lifestyle indicators through a questionnaire administered to a representative sample of adolescents from the Madrid Region (n = 2400) aged 13 to 16 years. In Study 2, the parents of the teenagers participating in Study 1 were required to fill out a questionnaire. Finally in Study 3, body composition, physical activity, health-related physical fitness, and blood measurements were determined in a subset (n = 200) of the individuals included in Study 1. Discussion This paper describes the rationale, design, and methodologies used in the AFINOS Study. This multidisciplinary, multicenter study seeks to evaluate several aspects of existing relationships between routine physical activity/sedentary behaviour and several health status markers, specifically those related to the immune system. The results of this cross-sectional study will serve for comparisons with the available data obtained in laboratory settings and in adults. In addition, knowledge regarding the health status and lifestyle habits of Spanish adolescents and their parents will be useful for designing preventive measures. PMID:20021690

Biological differences between the evolutionary lineages within Phytophthora ramorum and Phytophthora lateralis: Should the lineages be formally taxonomically designated?

Treesearch

Clive Brasier

2017-01-01

It is now generally accepted that the four evolutionary lineages of Phytophthora ramorum (informally designated NA1, NA2, EU1, and EU2) are relatively anciently divergent populations, recently introduced into Europe and North America from different, unknown geographic locations; that recombinants between them are genetically unstable and probably...

Food Microbiology--Design and Testing of a Virtual Laboratory Exercise

ERIC Educational Resources Information Center

Flint, Steve; Stewart, Terry

2010-01-01

A web-based virtual laboratory exercise in identifying an unknown microorganism was designed for use with a cohort of 3rd-year university food-technology students. They were presented with a food-contamination case, and then walked through a number of diagnostic steps to identify the microorganism. At each step, the students were asked to select 1…

Designing efficient nitrous oxide sampling strategies in agroecosystems using simulation models

Treesearch

Debasish Saha; Armen R. Kemanian; Benjamin M. Rau; Paul R. Adler; Felipe Montes

2017-01-01

Annual cumulative soil nitrous oxide (N2O) emissions calculated from discrete chamber-based flux measurements have unknown uncertainty. We used outputs from simulations obtained with an agroecosystem model to design sampling strategies that yield accurate cumulative N2O flux estimates with a known uncertainty level. Daily soil N2O fluxes were simulated for Ames, IA (...

The Design of Video-Based Professional Development: An Exploratory Experiment Intended to Identify Effective Features

ERIC Educational Resources Information Center

Beisiegel, Mary; Mitchell, Rebecca; Hill, Heather C.

2018-01-01

Although video cases and video clubs have become popular forms of teacher professional development, there have been few systematic investigations of designs for such programs. Programs may vary according to (a) whether teachers watch videos of their own/their peers' instruction, or whether teachers watch stock video of unknown teachers; and (b)…

L∞-gain adaptive fuzzy fault accommodation control design for nonlinear time-delay systems.

PubMed

Wu, Huai-Ning; Qiang, Xiao-Hong; Guo, Lei

2011-06-01

In this paper, an adaptive fuzzy fault accommodation (FA) control design with a guaranteed L(∞)-gain performance is developed for a class of nonlinear time-delay systems with persistent bounded disturbances. Using the Lyapunov technique and the Razumikhin-type lemma, the existence condition of the L(∞) -gain adaptive fuzzy FA controllers is provided in terms of linear matrix inequalities (LMIs). In the proposed FA scheme, a fuzzy logic system is employed to approximate the unknown term in the derivative of the Lyapunov function due to the unknown fault function; a continuous-state feedback control strategy is adopted for the control design to avoid the undesirable chattering phenomenon. The resulting FA controllers can ensure that every response of the closed-loop system is uniformly ultimately bounded with a guaranteed L(∞)-gain performance in the presence of a fault. Moreover, by the existing LMI optimization technique, a suboptimal controller is obtained in the sense of minimizing an upper bound of the L(∞)-gain. Finally, the achieved simulation results on the FA control of a continuous stirred tank reactor (CSTR) show the effectiveness of the proposed design procedure.

Global tracking for a class of uncertain nonlinear systems with unknown sign-switching control direction by output feedback

NASA Astrophysics Data System (ADS)

Roux Oliveira, Tiago; Jacoud Peixoto, Alessandro; Hsu, Liu

2015-09-01

This paper addresses the design of a sliding mode controller for a class of high-order uncertain nonlinear plants with unmatched state-dependent nonlinearities and unknown sign of the high frequency gain, i.e., the control direction is assumed unknown. Differently from most previous studies, the control direction is allowed to switch its sign. We show that it is possible to obtain global exact tracking using only output-feedback by coupling a relay periodic switching function with a norm state observer. One significant advantage of the new scheme is its robustness and improved transient response under arbitrary changes of the control direction which have been theoretically demonstrated for jump variations and successfully tested by simulations. The proposed controller is also evaluated with a DC motor control experiment.

Recommendations for the inclusion of Fabry disease as a rare febrile condition in existing algorithms for fever of unknown origin.

PubMed

Manna, Raffaele; Cauda, Roberto; Feriozzi, Sandro; Gambaro, Giovanni; Gasbarrini, Antonio; Lacombe, Didier; Livneh, Avi; Martini, Alberto; Ozdogan, Huri; Pisani, Antonio; Riccio, Eleonora; Verrecchia, Elena; Dagna, Lorenzo

2017-10-01

Fever of unknown origin (FUO) is a rather rare clinical syndrome representing a major diagnostic challenge. The occurrence of more than three febrile attacks with fever-free intervals of variable duration during 6 months of observation has recently been proposed as a subcategory of FUO, Recurrent FUO (RFUO). A substantial number of patients with RFUO have auto-inflammatory genetic fevers, but many patients remain undiagnosed. We hypothesize that this undiagnosed subgroup may be comprised of, at least in part, a number of rare genetic febrile diseases such as Fabry disease. We aimed to identify key features or potential diagnostic clues for Fabry disease as a model of rare genetic febrile diseases causing RFUO, and to develop diagnostic guidelines for RFUO, using Fabry disease as an example of inserting other rare diseases in the existing FUO algorithms. An international panel of specialists in recurrent fevers and rare diseases, including internists, infectious disease specialists, rheumatologists, gastroenterologists, nephrologists, and medical geneticists convened to review the existing diagnostic algorithms, and to suggest recommendations for arriving at accurate diagnoses on the basis of available literature and clinical experience. By combining specific features of rare diseases with other diagnostic considerations, guidelines have been designed to raise awareness and identify rare diseases among other causes of FUO. The proposed guidelines may be useful for the inclusion of rare diseases in the diagnostic algorithms for FUO. A wide spectrum of patients will be needed to validate the algorithm in different clinical settings.

After-school setting, physical activity, and sedentary behavior in 5th grade boys and girls.

PubMed

Taverno Ross, S E; Dowda, M; Colabianchi, N; Saunders, R; Pate, R R

2012-09-01

After-school hours are considered critical for children's physical activity (PA) and sedentary behaviors (SB); however, whether the after-school setting influences children's activity patterns is unknown. This study examined the influence of after-school setting (i.e., parent report of the child's usual after-school setting) on 5th grade children's PA and SB, and differences by race/ethnicity. Boys whose parents reported they usually attended an after-school program had higher PA than boys who usually went home after school. A significant interaction between race/ethnicity and after-school setting showed that minority girls whose parents reported they usually attended an after-school program had higher PA and engaged in less SB compared with those who usually went home, whereas the activity patterns of white girls did not differ by after-school setting. Children's usual after-school setting affects their activity patterns; after-school programs may potentially increase PA in boys and minority girls. Copyright © 2012 Elsevier Ltd. All rights reserved.

Uncovering the unknown: A grounded theory study exploring the impact of self-awareness on the culture of feedback in residency education.

PubMed

Ramani, Subha; Könings, Karen; Mann, Karen V; van der Vleuten, Cees

2017-10-01

Self-assessment and reflection are essential for meaningful feedback. We aimed to explore whether the well-known Johari window model of self-awareness could guide feedback conversations between faculty and residents and enhance the institutional feedback culture. We had previously explored perceptions of residents and faculty regarding sociocultural factors impacting feedback. We re-analyzed data targeting themes related to self-assessment, reflection, feedback seeking and acceptance, aiming to generate individual and institutional feedback strategies applicable to each quadrant of the window. We identified the following themes for each quadrant: (1) Behaviors known to self and others - Validating the known; (2) Behaviors unknown to self but known to others - Accepting the blind; (3) Behaviors known to self and unknown to others - Disclosure of hidden; and (4) Behaviors unknown to self and others - Uncovering the unknown. Normalizing self-disclosure of limitations, encouraging feedback seeking, training in nonjudgmental feedback and providing opportunities for longitudinal relationships could promote self-awareness, ultimately expanding the "open" quadrant of the Johari window. The Johari window, a model of self-awareness in interpersonal communications, could provide a robust framework for individuals to improve their feedback conversations and institutions to design feedback initiatives that enhance its quality and impact.

Custom oligonucleotide array-based CGH: a reliable diagnostic tool for detection of exonic copy-number changes in multiple targeted genes

PubMed Central

Vasson, Aurélie; Leroux, Céline; Orhant, Lucie; Boimard, Mathieu; Toussaint, Aurélie; Leroy, Chrystel; Commere, Virginie; Ghiotti, Tiffany; Deburgrave, Nathalie; Saillour, Yoann; Atlan, Isabelle; Fouveaut, Corinne; Beldjord, Cherif; Valleix, Sophie; Leturcq, France; Dodé, Catherine; Bienvenu, Thierry; Chelly, Jamel; Cossée, Mireille

2013-01-01

The frequency of disease-related large rearrangements (referred to as copy-number mutations, CNMs) varies among genes, and search for these mutations has an important place in diagnostic strategies. In recent years, CGH method using custom-designed high-density oligonucleotide-based arrays allowed the development of a powerful tool for detection of alterations at the level of exons and made it possible to provide flexibility through the possibility of modeling chips. The aim of our study was to test custom-designed oligonucleotide CGH array in a diagnostic laboratory setting that analyses several genes involved in various genetic diseases, and to compare it with conventional strategies. To this end, we designed a 12-plex CGH array (135k; 135 000 probes/subarray) (Roche Nimblegen) with exonic and intronic oligonucleotide probes covering 26 genes routinely analyzed in the laboratory. We tested control samples with known CNMs and patients for whom genetic causes underlying their disorders were unknown. The contribution of this technique is undeniable. Indeed, it appeared reproducible, reliable and sensitive enough to detect heterozygous single-exon deletions or duplications, complex rearrangements and somatic mosaicism. In addition, it improves reliability of CNM detection and allows determination of boundaries precisely enough to direct targeted sequencing of breakpoints. All of these points, associated with the possibility of a simultaneous analysis of several genes and scalability ‘homemade' make it a valuable tool as a new diagnostic approach of CNMs. PMID:23340513

Fusing Range Measurements from Ultrasonic Beacons and a Laser Range Finder for Localization of a Mobile Robot

PubMed Central

Ko, Nak Yong; Kuc, Tae-Yong

2015-01-01

This paper proposes a method for mobile robot localization in a partially unknown indoor environment. The method fuses two types of range measurements: the range from the robot to the beacons measured by ultrasonic sensors and the range from the robot to the walls surrounding the robot measured by a laser range finder (LRF). For the fusion, the unscented Kalman filter (UKF) is utilized. Because finding the Jacobian matrix is not feasible for range measurement using an LRF, UKF has an advantage in this situation over the extended KF. The locations of the beacons and range data from the beacons are available, whereas the correspondence of the range data to the beacon is not given. Therefore, the proposed method also deals with the problem of data association to determine which beacon corresponds to the given range data. The proposed approach is evaluated using different sets of design parameter values and is compared with the method that uses only an LRF or ultrasonic beacons. Comparative analysis shows that even though ultrasonic beacons are sparsely populated, have a large error and have a slow update rate, they improve the localization performance when fused with the LRF measurement. In addition, proper adjustment of the UKF design parameters is crucial for full utilization of the UKF approach for sensor fusion. This study contributes to the derivation of a UKF-based design methodology to fuse two exteroceptive measurements that are complementary to each other in localization. PMID:25970259

LinkImpute: Fast and Accurate Genotype Imputation for Nonmodel Organisms

PubMed Central

Money, Daniel; Gardner, Kyle; Migicovsky, Zoë; Schwaninger, Heidi; Zhong, Gan-Yuan; Myles, Sean

2015-01-01

Obtaining genome-wide genotype data from a set of individuals is the first step in many genomic studies, including genome-wide association and genomic selection. All genotyping methods suffer from some level of missing data, and genotype imputation can be used to fill in the missing data and improve the power of downstream analyses. Model organisms like human and cattle benefit from high-quality reference genomes and panels of reference genotypes that aid in imputation accuracy. In nonmodel organisms, however, genetic and physical maps often are either of poor quality or are completely absent, and there are no panels of reference genotypes available. There is therefore a need for imputation methods designed specifically for nonmodel organisms in which genomic resources are poorly developed and marker order is unreliable or unknown. Here we introduce LinkImpute, a software package based on a k-nearest neighbor genotype imputation method, LD-kNNi, which is designed for unordered markers. No physical or genetic maps are required, and it is designed to work on unphased genotype data from heterozygous species. It exploits the fact that markers useful for imputation often are not physically close to the missing genotype but rather distributed throughout the genome. Using genotyping-by-sequencing data from diverse and heterozygous accessions of apples, grapes, and maize, we compare LD-kNNi with several genotype imputation methods and show that LD-kNNi is fast, comparable in accuracy to the best-existing methods, and exhibits the least bias in allele frequency estimates. PMID:26377960

Computing and Applying Atomic Regulons to Understand Gene Expression and Regulation

PubMed Central

Faria, José P.; Davis, James J.; Edirisinghe, Janaka N.; Taylor, Ronald C.; Weisenhorn, Pamela; Olson, Robert D.; Stevens, Rick L.; Rocha, Miguel; Rocha, Isabel; Best, Aaron A.; DeJongh, Matthew; Tintle, Nathan L.; Parrello, Bruce; Overbeek, Ross; Henry, Christopher S.

2016-01-01

Understanding gene function and regulation is essential for the interpretation, prediction, and ultimate design of cell responses to changes in the environment. An important step toward meeting the challenge of understanding gene function and regulation is the identification of sets of genes that are always co-expressed. These gene sets, Atomic Regulons (ARs), represent fundamental units of function within a cell and could be used to associate genes of unknown function with cellular processes and to enable rational genetic engineering of cellular systems. Here, we describe an approach for inferring ARs that leverages large-scale expression data sets, gene context, and functional relationships among genes. We computed ARs for Escherichia coli based on 907 gene expression experiments and compared our results with gene clusters produced by two prevalent data-driven methods: Hierarchical clustering and k-means clustering. We compared ARs and purely data-driven gene clusters to the curated set of regulatory interactions for E. coli found in RegulonDB, showing that ARs are more consistent with gold standard regulons than are data-driven gene clusters. We further examined the consistency of ARs and data-driven gene clusters in the context of gene interactions predicted by Context Likelihood of Relatedness (CLR) analysis, finding that the ARs show better agreement with CLR predicted interactions. We determined the impact of increasing amounts of expression data on AR construction and find that while more data improve ARs, it is not necessary to use the full set of gene expression experiments available for E. coli to produce high quality ARs. In order to explore the conservation of co-regulated gene sets across different organisms, we computed ARs for Shewanella oneidensis, Pseudomonas aeruginosa, Thermus thermophilus, and Staphylococcus aureus, each of which represents increasing degrees of phylogenetic distance from E. coli. Comparison of the organism-specific ARs showed that the consistency of AR gene membership correlates with phylogenetic distance, but there is clear variability in the regulatory networks of closely related organisms. As large scale expression data sets become increasingly common for model and non-model organisms, comparative analyses of atomic regulons will provide valuable insights into fundamental regulatory modules used across the bacterial domain. PMID:27933038

Discrete-time online learning control for a class of unknown nonaffine nonlinear systems using reinforcement learning.

PubMed

Yang, Xiong; Liu, Derong; Wang, Ding; Wei, Qinglai

2014-07-01

In this paper, a reinforcement-learning-based direct adaptive control is developed to deliver a desired tracking performance for a class of discrete-time (DT) nonlinear systems with unknown bounded disturbances. We investigate multi-input-multi-output unknown nonaffine nonlinear DT systems and employ two neural networks (NNs). By using Implicit Function Theorem, an action NN is used to generate the control signal and it is also designed to cancel the nonlinearity of unknown DT systems, for purpose of utilizing feedback linearization methods. On the other hand, a critic NN is applied to estimate the cost function, which satisfies the recursive equations derived from heuristic dynamic programming. The weights of both the action NN and the critic NN are directly updated online instead of offline training. By utilizing Lyapunov's direct method, the closed-loop tracking errors and the NN estimated weights are demonstrated to be uniformly ultimately bounded. Two numerical examples are provided to show the effectiveness of the present approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

SNP-associations and phenotype predictions from hundreds of microbial genomes without genome alignments.

PubMed

Hall, Barry G

2014-01-01

SNP-association studies are a starting point for identifying genes that may be responsible for specific phenotypes, such as disease traits. The vast bulk of tools for SNP-association studies are directed toward SNPs in the human genome, and I am unaware of any tools designed specifically for such studies in bacterial or viral genomes. The PPFS (Predict Phenotypes From SNPs) package described here is an add-on to kSNP , a program that can identify SNPs in a data set of hundreds of microbial genomes. PPFS identifies those SNPs that are non-randomly associated with a phenotype based on the χ² probability, then uses those diagnostic SNPs for two distinct, but related, purposes: (1) to predict the phenotypes of strains whose phenotypes are unknown, and (2) to identify those diagnostic SNPs that are most likely to be causally related to the phenotype. In the example illustrated here, from a set of 68 E. coli genomes, for 67 of which the pathogenicity phenotype was known, there were 418,500 SNPs. Using the phenotypes of 36 of those strains, PPFS identified 207 diagnostic SNPs. The diagnostic SNPs predicted the phenotypes of all of the genomes with 97% accuracy. It then identified 97 SNPs whose probability of being causally related to the pathogenic phenotype was >0.999. In a second example, from a set of 116 E. coli genome sequences, using the phenotypes of 65 strains PPFS identified 101 SNPs that predicted the source host (human or non-human) with 90% accuracy.

Comparison of attitudes of guilt and forgiveness in cancer patients without evidence of disease and advanced cancer patients in a palliative care setting.

PubMed

van Laarhoven, Hanneke W M; Schilderman, Johannes; Verhagen, Constans A H H V M; Prins, Judith B

2012-01-01

: Attitudes toward guilt and forgiveness may be important factors determining distress in cancer patients. Direct comparative studies in patients with different life expectancies exploring attitudes toward guilt and forgiveness are lacking. Also, sociodemographic and religious characteristics determining the attitudes toward guilt and forgiveness are unknown. : The objective of this study was to compare attitudes toward guilt and forgiveness in cancer patients without evidence of disease and advanced cancer patients. : A descriptive research design was used. Ninety-seven patients without evidence of disease and 55 advanced cancer patients filled out the Dutch Guilt Measurement Instrument and the Forgiveness of Others Scale. : Both groups had an attitude of nonreligious guilt and forgiveness, but not of religious guilt. No significant differences in attitudes toward guilt and forgiveness were observed between the 2 groups. In contrast to sociodemographic characteristics, religious characteristics were relevant predictors for guilt and forgiveness. Significant differences in relations between images of God and attitudes toward guilt were observed between the 2 patient groups. : An attitude of nonreligious guilt and forgiveness was found in cancer patients, irrespective of the stage of disease. Religious characteristics were significantly associated with attitudes of guilt and forgiveness. This correlation differed in the early and the advanced setting of disease. : The observed relations between religious characteristics and attitudes of guilt and forgiveness suggest that a careful examination of the role of religious beliefs and values is relevant in the clinical care of patients with cancer, both in the setting of early and advanced disease.

Therapeutic exercise for rotator cuff tendinopathy: a systematic review of contextual factors and prescription parameters.

PubMed

Littlewood, Chris; Malliaras, Peter; Chance-Larsen, Ken

2015-06-01

Exercise is widely regarded as an effective intervention for symptomatic rotator cuff tendinopathy but the prescription is diverse and the important components of such programmes are not well understood. The objective of this study was to systematically review the contextual factors and prescription parameters of published exercise programmes for rotator cuff tendinopathy, to generate recommendations based on current evidence. An electronic search of AMED, CiNAHL, CENTRAL, MEDLINE, PEDro and SPORTDiscus was undertaken from their inception to June 2014 and supplemented by hand searching. Eligible studies included randomized controlled trials evaluating the effectiveness of exercise in participants with rotator cuff tendinopathy. Included studies were appraised using the Cochrane risk of bias tool and synthesized narratively. Fourteen studies were included, and suggested that exercise programmes are widely applicable and can be successfully designed by physiotherapists with varying experience; whether the exercise is completed at home or within a clinic setting does not appear to matter and neither does pain production or pain avoidance during exercise; inclusion of some level of resistance does seem to matter although the optimal level is unclear, the optimal number of repetitions is also unclear but higher repetitions might confer superior outcomes; three sets of exercise are preferable to two or one set but the optimal frequency is unknown; most programmes should demonstrate clinically significant outcomes by 12 weeks. This systematic review has offered preliminary guidance in relation to contextual factors and prescription parameters to aid development and application of exercise programmes for rotator cuff tendinopathy.

Efficient design of cluster randomized trials with treatment-dependent costs and treatment-dependent unknown variances.

PubMed

van Breukelen, Gerard J P; Candel, Math J J M

2018-06-10

Cluster randomized trials evaluate the effect of a treatment on persons nested within clusters, where treatment is randomly assigned to clusters. Current equations for the optimal sample size at the cluster and person level assume that the outcome variances and/or the study costs are known and homogeneous between treatment arms. This paper presents efficient yet robust designs for cluster randomized trials with treatment-dependent costs and treatment-dependent unknown variances, and compares these with 2 practical designs. First, the maximin design (MMD) is derived, which maximizes the minimum efficiency (minimizes the maximum sampling variance) of the treatment effect estimator over a range of treatment-to-control variance ratios. The MMD is then compared with the optimal design for homogeneous variances and costs (balanced design), and with that for homogeneous variances and treatment-dependent costs (cost-considered design). The results show that the balanced design is the MMD if the treatment-to control cost ratio is the same at both design levels (cluster, person) and within the range for the treatment-to-control variance ratio. It still is highly efficient and better than the cost-considered design if the cost ratio is within the range for the squared variance ratio. Outside that range, the cost-considered design is better and highly efficient, but it is not the MMD. An example shows sample size calculation for the MMD, and the computer code (SPSS and R) is provided as supplementary material. The MMD is recommended for trial planning if the study costs are treatment-dependent and homogeneity of variances cannot be assumed. © 2018 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Study unique artistic lopburi province for design brass tea set of bantahkrayang community

NASA Astrophysics Data System (ADS)

Pliansiri, V.; Seviset, S.

2017-07-01

The objectives of this study were as follows: 1) to study the production process of handcrafted Brass Tea Set; and 2) to design and develop the handcrafted of Brass Tea Set. The process of design was started by mutual analytical processes and conceptual framework for product design, Quality Function Deployment, Theory of Inventive Problem Solving, Principles of Craft Design, and Principle of Reverse Engineering. The experts in field of both Industrial Product Design and Brass Handicraft Product, have evaluated the Brass Tea Set design and created prototype of Brass tea set by the sample of consumers who have ever bought the Brass Tea Set of Bantahkrayang Community on this research. The statistics methods used were percentage, mean ({{{\\overline X}} = }) and standard deviation (S.D.) 3. To assess consumer satisfaction toward of handcrafted Brass tea set was at the high level.

Orthology and paralogy constraints: satisfiability and consistency.

PubMed

Lafond, Manuel; El-Mabrouk, Nadia

2014-01-01

A variety of methods based on sequence similarity, reconciliation, synteny or functional characteristics, can be used to infer orthology and paralogy relations between genes of a given gene family  G. But is a given set  C of orthology/paralogy constraints possible, i.e., can they simultaneously co-exist in an evolutionary history for  G? While previous studies have focused on full sets of constraints, here we consider the general case where  C does not necessarily involve a constraint for each pair of genes. The problem is subdivided in two parts: (1) Is  C satisfiable, i.e. can we find an event-labeled gene tree G inducing  C? (2) Is there such a G which is consistent, i.e., such that all displayed triplet phylogenies are included in a species tree? Previous results on the Graph sandwich problem can be used to answer to (1), and we provide polynomial-time algorithms for satisfiability and consistency with a given species tree. We also describe a new polynomial-time algorithm for the case of consistency with an unknown species tree and full knowledge of pairwise orthology/paralogy relationships, as well as a branch-and-bound algorithm in the case when unknown relations are present. We show that our algorithms can be used in combination with ProteinOrtho, a sequence similarity-based orthology detection tool, to extract a set of robust orthology/paralogy relationships.

Orthology and paralogy constraints: satisfiability and consistency

PubMed Central

2014-01-01

Background A variety of methods based on sequence similarity, reconciliation, synteny or functional characteristics, can be used to infer orthology and paralogy relations between genes of a given gene family  G. But is a given set  C of orthology/paralogy constraints possible, i.e., can they simultaneously co-exist in an evolutionary history for  G? While previous studies have focused on full sets of constraints, here we consider the general case where  C does not necessarily involve a constraint for each pair of genes. The problem is subdivided in two parts: (1) Is  C satisfiable, i.e. can we find an event-labeled gene tree G inducing  C? (2) Is there such a G which is consistent, i.e., such that all displayed triplet phylogenies are included in a species tree? Results Previous results on the Graph sandwich problem can be used to answer to (1), and we provide polynomial-time algorithms for satisfiability and consistency with a given species tree. We also describe a new polynomial-time algorithm for the case of consistency with an unknown species tree and full knowledge of pairwise orthology/paralogy relationships, as well as a branch-and-bound algorithm in the case when unknown relations are present. We show that our algorithms can be used in combination with ProteinOrtho, a sequence similarity-based orthology detection tool, to extract a set of robust orthology/paralogy relationships. PMID:25572629

Accurate prediction of severe allergic reactions by a small set of environmental parameters (NDVI, temperature).

PubMed

Notas, George; Bariotakis, Michail; Kalogrias, Vaios; Andrianaki, Maria; Azariadis, Kalliopi; Kampouri, Errika; Theodoropoulou, Katerina; Lavrentaki, Katerina; Kastrinakis, Stelios; Kampa, Marilena; Agouridakis, Panagiotis; Pirintsos, Stergios; Castanas, Elias

2015-01-01

Severe allergic reactions of unknown etiology,necessitating a hospital visit, have an important impact in the life of affected individuals and impose a major economic burden to societies. The prediction of clinically severe allergic reactions would be of great importance, but current attempts have been limited by the lack of a well-founded applicable methodology and the wide spatiotemporal distribution of allergic reactions. The valid prediction of severe allergies (and especially those needing hospital treatment) in a region, could alert health authorities and implicated individuals to take appropriate preemptive measures. In the present report we have collecterd visits for serious allergic reactions of unknown etiology from two major hospitals in the island of Crete, for two distinct time periods (validation and test sets). We have used the Normalized Difference Vegetation Index (NDVI), a satellite-based, freely available measurement, which is an indicator of live green vegetation at a given geographic area, and a set of meteorological data to develop a model capable of describing and predicting severe allergic reaction frequency. Our analysis has retained NDVI and temperature as accurate identifiers and predictors of increased hospital severe allergic reactions visits. Our approach may contribute towards the development of satellite-based modules, for the prediction of severe allergic reactions in specific, well-defined geographical areas. It could also probably be used for the prediction of other environment related diseases and conditions.

Accurate Prediction of Severe Allergic Reactions by a Small Set of Environmental Parameters (NDVI, Temperature)

PubMed Central

Andrianaki, Maria; Azariadis, Kalliopi; Kampouri, Errika; Theodoropoulou, Katerina; Lavrentaki, Katerina; Kastrinakis, Stelios; Kampa, Marilena; Agouridakis, Panagiotis; Pirintsos, Stergios; Castanas, Elias

2015-01-01

Severe allergic reactions of unknown etiology,necessitating a hospital visit, have an important impact in the life of affected individuals and impose a major economic burden to societies. The prediction of clinically severe allergic reactions would be of great importance, but current attempts have been limited by the lack of a well-founded applicable methodology and the wide spatiotemporal distribution of allergic reactions. The valid prediction of severe allergies (and especially those needing hospital treatment) in a region, could alert health authorities and implicated individuals to take appropriate preemptive measures. In the present report we have collecterd visits for serious allergic reactions of unknown etiology from two major hospitals in the island of Crete, for two distinct time periods (validation and test sets). We have used the Normalized Difference Vegetation Index (NDVI), a satellite-based, freely available measurement, which is an indicator of live green vegetation at a given geographic area, and a set of meteorological data to develop a model capable of describing and predicting severe allergic reaction frequency. Our analysis has retained NDVI and temperature as accurate identifiers and predictors of increased hospital severe allergic reactions visits. Our approach may contribute towards the development of satellite-based modules, for the prediction of severe allergic reactions in specific, well-defined geographical areas. It could also probably be used for the prediction of other environment related diseases and conditions. PMID:25794106

The Association of Multiple Interacting Genes with Specific Phenotypes in Rice Using Gene Coexpression Networks1[C][W][OA

PubMed Central

Ficklin, Stephen P.; Luo, Feng; Feltus, F. Alex

2010-01-01

Discovering gene sets underlying the expression of a given phenotype is of great importance, as many phenotypes are the result of complex gene-gene interactions. Gene coexpression networks, built using a set of microarray samples as input, can help elucidate tightly coexpressed gene sets (modules) that are mixed with genes of known and unknown function. Functional enrichment analysis of modules further subdivides the coexpressed gene set into cofunctional gene clusters that may coexist in the module with other functionally related gene clusters. In this study, 45 coexpressed gene modules and 76 cofunctional gene clusters were discovered for rice (Oryza sativa) using a global, knowledge-independent paradigm and the combination of two network construction methodologies. Some clusters were enriched for previously characterized mutant phenotypes, providing evidence for specific gene sets (and their annotated molecular functions) that underlie specific phenotypes. PMID:20668062

The association of multiple interacting genes with specific phenotypes in rice using gene coexpression networks.

PubMed

Ficklin, Stephen P; Luo, Feng; Feltus, F Alex

2010-09-01

Discovering gene sets underlying the expression of a given phenotype is of great importance, as many phenotypes are the result of complex gene-gene interactions. Gene coexpression networks, built using a set of microarray samples as input, can help elucidate tightly coexpressed gene sets (modules) that are mixed with genes of known and unknown function. Functional enrichment analysis of modules further subdivides the coexpressed gene set into cofunctional gene clusters that may coexist in the module with other functionally related gene clusters. In this study, 45 coexpressed gene modules and 76 cofunctional gene clusters were discovered for rice (Oryza sativa) using a global, knowledge-independent paradigm and the combination of two network construction methodologies. Some clusters were enriched for previously characterized mutant phenotypes, providing evidence for specific gene sets (and their annotated molecular functions) that underlie specific phenotypes.

Involvement of astrocyte metabolic coupling in Tourette syndrome pathogenesis.

PubMed

de Leeuw, Christiaan; Goudriaan, Andrea; Smit, August B; Yu, Dongmei; Mathews, Carol A; Scharf, Jeremiah M; Verheijen, Mark H G; Posthuma, Danielle

2015-11-01

Tourette syndrome is a heritable neurodevelopmental disorder whose pathophysiology remains unknown. Recent genome-wide association studies suggest that it is a polygenic disorder influenced by many genes of small effect. We tested whether these genes cluster in cellular function by applying gene-set analysis using expert curated sets of brain-expressed genes in the current largest available Tourette syndrome genome-wide association data set, involving 1285 cases and 4964 controls. The gene sets included specific synaptic, astrocytic, oligodendrocyte and microglial functions. We report association of Tourette syndrome with a set of genes involved in astrocyte function, specifically in astrocyte carbohydrate metabolism. This association is driven primarily by a subset of 33 genes involved in glycolysis and glutamate metabolism through which astrocytes support synaptic function. Our results indicate for the first time that the process of astrocyte-neuron metabolic coupling may be an important contributor to Tourette syndrome pathogenesis.

Involvement of astrocyte metabolic coupling in Tourette syndrome pathogenesis

PubMed Central

de Leeuw, Christiaan; Goudriaan, Andrea; Smit, August B; Yu, Dongmei; Mathews, Carol A; Scharf, Jeremiah M; Scharf, J M; Pauls, D L; Yu, D; Illmann, C; Osiecki, L; Neale, B M; Mathews, C A; Reus, V I; Lowe, T L; Freimer, N B; Cox, N J; Davis, L K; Rouleau, G A; Chouinard, S; Dion, Y; Girard, S; Cath, D C; Posthuma, D; Smit, J H; Heutink, P; King, R A; Fernandez, T; Leckman, J F; Sandor, P; Barr, C L; McMahon, W; Lyon, G; Leppert, M; Morgan, J; Weiss, R; Grados, M A; Singer, H; Jankovic, J; Tischfield, J A; Heiman, G A; Verheijen, Mark H G; Posthuma, Danielle

2015-01-01

Tourette syndrome is a heritable neurodevelopmental disorder whose pathophysiology remains unknown. Recent genome-wide association studies suggest that it is a polygenic disorder influenced by many genes of small effect. We tested whether these genes cluster in cellular function by applying gene-set analysis using expert curated sets of brain-expressed genes in the current largest available Tourette syndrome genome-wide association data set, involving 1285 cases and 4964 controls. The gene sets included specific synaptic, astrocytic, oligodendrocyte and microglial functions. We report association of Tourette syndrome with a set of genes involved in astrocyte function, specifically in astrocyte carbohydrate metabolism. This association is driven primarily by a subset of 33 genes involved in glycolysis and glutamate metabolism through which astrocytes support synaptic function. Our results indicate for the first time that the process of astrocyte-neuron metabolic coupling may be an important contributor to Tourette syndrome pathogenesis. PMID:25735483

Industrialized timber structures.

DOT National Transportation Integrated Search

1974-01-01

It was recently learned that a number of innovations in structural timber components are available to the construction industry, but that they were largely unknown to bridge designers. The purpose of this study was to develop for the Department a fea...

Effects of errors and gaps in spatial data sets on assessment of conservation progress.

PubMed

Visconti, P; Di Marco, M; Álvarez-Romero, J G; Januchowski-Hartley, S R; Pressey, R L; Weeks, R; Rondinini, C

2013-10-01

Data on the location and extent of protected areas, ecosystems, and species' distributions are essential for determining gaps in biodiversity protection and identifying future conservation priorities. However, these data sets always come with errors in the maps and associated metadata. Errors are often overlooked in conservation studies, despite their potential negative effects on the reported extent of protection of species and ecosystems. We used 3 case studies to illustrate the implications of 3 sources of errors in reporting progress toward conservation objectives: protected areas with unknown boundaries that are replaced by buffered centroids, propagation of multiple errors in spatial data, and incomplete protected-area data sets. As of 2010, the frequency of protected areas with unknown boundaries in the World Database on Protected Areas (WDPA) caused the estimated extent of protection of 37.1% of the terrestrial Neotropical mammals to be overestimated by an average 402.8% and of 62.6% of species to be underestimated by an average 10.9%. Estimated level of protection of the world's coral reefs was 25% higher when using recent finer-resolution data on coral reefs as opposed to globally available coarse-resolution data. Accounting for additional data sets not yet incorporated into WDPA contributed up to 6.7% of additional protection to marine ecosystems in the Philippines. We suggest ways for data providers to reduce the errors in spatial and ancillary data and ways for data users to mitigate the effects of these errors on biodiversity assessments. © 2013 Society for Conservation Biology.

Customer loads of two-wheeled vehicles

NASA Astrophysics Data System (ADS)

Gorges, C.; Öztürk, K.; Liebich, R.

2017-12-01

Customer usage profiles are the most unknown influences in vehicle design targets and they play an important role in durability analysis. This publication presents a customer load acquisition system for two-wheeled vehicles that utilises the vehicle's onboard signals. A road slope estimator was developed to reveal the unknown slope resistance force with the help of a linear Kalman filter. Furthermore, an automated mass estimator was developed to consider the correct vehicle loading. The mass estimation is performed by an extended Kalman filter. Finally, a model-based wheel force calculation was derived, which is based on the superposition of forces calculated from measured onboard signals. The calculated wheel forces were validated by measurements with wheel-load transducers through the comparison of rainflow matrices. The calculated wheel forces correspond with the measured wheel forces in terms of both quality and quantity. The proposed methods can be used to gather field data for improved vehicle design loads.

Neural-network-observer-based optimal control for unknown nonlinear systems using adaptive dynamic programming

NASA Astrophysics Data System (ADS)

Liu, Derong; Huang, Yuzhu; Wang, Ding; Wei, Qinglai

2013-09-01

In this paper, an observer-based optimal control scheme is developed for unknown nonlinear systems using adaptive dynamic programming (ADP) algorithm. First, a neural-network (NN) observer is designed to estimate system states. Then, based on the observed states, a neuro-controller is constructed via ADP method to obtain the optimal control. In this design, two NN structures are used: a three-layer NN is used to construct the observer which can be applied to systems with higher degrees of nonlinearity and without a priori knowledge of system dynamics, and a critic NN is employed to approximate the value function. The optimal control law is computed using the critic NN and the observer NN. Uniform ultimate boundedness of the closed-loop system is guaranteed. The actor, critic, and observer structures are all implemented in real-time, continuously and simultaneously. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control scheme.

Observed-Based Adaptive Fuzzy Tracking Control for Switched Nonlinear Systems With Dead-Zone.

PubMed

Tong, Shaocheng; Sui, Shuai; Li, Yongming

2015-12-01

In this paper, the problem of adaptive fuzzy output-feedback control is investigated for a class of uncertain switched nonlinear systems in strict-feedback form. The considered switched systems contain unknown nonlinearities, dead-zone, and immeasurable states. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, a switched fuzzy state observer is designed and thus the immeasurable states are obtained by it. By applying the adaptive backstepping design principle and the average dwell time method, an adaptive fuzzy output-feedback tracking control approach is developed. It is proved that the proposed control approach can guarantee that all the variables in the closed-loop system are bounded under a class of switching signals with average dwell time, and also that the system output can track a given reference signal as closely as possible. The simulation results are given to check the effectiveness of the proposed approach.

On position/force tracking control problem of cooperative robot manipulators using adaptive fuzzy backstepping approach.

PubMed

Baigzadehnoe, Barmak; Rahmani, Zahra; Khosravi, Alireza; Rezaie, Behrooz

2017-09-01

In this paper, the position and force tracking control problem of cooperative robot manipulator system handling a common rigid object with unknown dynamical models and unknown external disturbances is investigated. The universal approximation properties of fuzzy logic systems are employed to estimate the unknown system dynamics. On the other hand, by defining new state variables based on the integral and differential of position and orientation errors of the grasped object, the error system of coordinated robot manipulators is constructed. Subsequently by defining the appropriate change of coordinates and using the backstepping design strategy, an adaptive fuzzy backstepping position tracking control scheme is proposed for multi-robot manipulator systems. By utilizing the properties of internal forces, extra terms are also added to the control signals to consider the force tracking problem. Moreover, it is shown that the proposed adaptive fuzzy backstepping position/force control approach ensures all the signals of the closed loop system uniformly ultimately bounded and tracking errors of both positions and forces can converge to small desired values by proper selection of the design parameters. Finally, the theoretic achievements are tested on the two three-link planar robot manipulators cooperatively handling a common object to illustrate the effectiveness of the proposed approach. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive Robust Output Feedback Control for a Marine Dynamic Positioning System Based on a High-Gain Observer.

PubMed

Du, Jialu; Hu, Xin; Liu, Hongbo; Chen, C L Philip

2015-11-01

This paper develops an adaptive robust output feedback control scheme for dynamically positioned ships with unavailable velocities and unknown dynamic parameters in an unknown time-variant disturbance environment. The controller is designed by incorporating the high-gain observer and radial basis function (RBF) neural networks in vectorial backstepping method. The high-gain observer provides the estimations of the ship position and heading as well as velocities. The RBF neural networks are employed to compensate for the uncertainties of ship dynamics. The adaptive laws incorporating a leakage term are designed to estimate the weights of RBF neural networks and the bounds of unknown time-variant environmental disturbances. In contrast to the existing results of dynamic positioning (DP) controllers, the proposed control scheme relies only on the ship position and heading measurements and does not require a priori knowledge of the ship dynamics and external disturbances. By means of Lyapunov functions, it is theoretically proved that our output feedback controller can control a ship's position and heading to the arbitrarily small neighborhood of the desired target values while guaranteeing that all signals in the closed-loop DP control system are uniformly ultimately bounded. Finally, simulations involving two ships are carried out, and simulation results demonstrate the effectiveness of the proposed control scheme.

Finite-time sliding surface constrained control for a robot manipulator with an unknown deadzone and disturbance.

PubMed

Ik Han, Seong; Lee, Jangmyung

2016-11-01

This paper presents finite-time sliding mode control (FSMC) with predefined constraints for the tracking error and sliding surface in order to obtain robust positioning of a robot manipulator with input nonlinearity due to an unknown deadzone and external disturbance. An assumed model feedforward FSMC was designed to avoid tedious identification procedures for the manipulator parameters and to obtain a fast response time. Two constraint switching control functions based on the tracking error and finite-time sliding surface were added to the FSMC to guarantee the predefined tracking performance despite the presence of an unknown deadzone and disturbance. The tracking error due to the deadzone and disturbance can be suppressed within the predefined error boundary simply by tuning the gain value of the constraint switching function and without the addition of an extra compensator. Therefore, the designed constraint controller has a simpler structure than conventional transformed error constraint methods and the sliding surface constraint scheme can also indirectly guarantee the tracking error constraint while being more stable than the tracking error constraint control. A simulation and experiment were performed on an articulated robot manipulator to validate the proposed control schemes. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Data-driven robust approximate optimal tracking control for unknown general nonlinear systems using adaptive dynamic programming method.

PubMed

Zhang, Huaguang; Cui, Lili; Zhang, Xin; Luo, Yanhong

2011-12-01

In this paper, a novel data-driven robust approximate optimal tracking control scheme is proposed for unknown general nonlinear systems by using the adaptive dynamic programming (ADP) method. In the design of the controller, only available input-output data is required instead of known system dynamics. A data-driven model is established by a recurrent neural network (NN) to reconstruct the unknown system dynamics using available input-output data. By adding a novel adjustable term related to the modeling error, the resultant modeling error is first guaranteed to converge to zero. Then, based on the obtained data-driven model, the ADP method is utilized to design the approximate optimal tracking controller, which consists of the steady-state controller and the optimal feedback controller. Further, a robustifying term is developed to compensate for the NN approximation errors introduced by implementing the ADP method. Based on Lyapunov approach, stability analysis of the closed-loop system is performed to show that the proposed controller guarantees the system state asymptotically tracking the desired trajectory. Additionally, the obtained control input is proven to be close to the optimal control input within a small bound. Finally, two numerical examples are used to demonstrate the effectiveness of the proposed control scheme.

Sampling in ecology and evolution - bridging the gap between theory and practice

USGS Publications Warehouse

Albert, C.H.; Yoccoz, N.G.; Edwards, T.C.; Graham, C.H.; Zimmermann, N.E.; Thuiller, W.

2010-01-01

Sampling is a key issue for answering most ecological and evolutionary questions. The importance of developing a rigorous sampling design tailored to specific questions has already been discussed in the ecological and sampling literature and has provided useful tools and recommendations to sample and analyse ecological data. However, sampling issues are often difficult to overcome in ecological studies due to apparent inconsistencies between theory and practice, often leading to the implementation of simplified sampling designs that suffer from unknown biases. Moreover, we believe that classical sampling principles which are based on estimation of means and variances are insufficient to fully address many ecological questions that rely on estimating relationships between a response and a set of predictor variables over time and space. Our objective is thus to highlight the importance of selecting an appropriate sampling space and an appropriate sampling design. We also emphasize the importance of using prior knowledge of the study system to estimate models or complex parameters and thus better understand ecological patterns and processes generating these patterns. Using a semi-virtual simulation study as an illustration we reveal how the selection of the space (e.g. geographic, climatic), in which the sampling is designed, influences the patterns that can be ultimately detected. We also demonstrate the inefficiency of common sampling designs to reveal response curves between ecological variables and climatic gradients. Further, we show that response-surface methodology, which has rarely been used in ecology, is much more efficient than more traditional methods. Finally, we discuss the use of prior knowledge, simulation studies and model-based designs in defining appropriate sampling designs. We conclude by a call for development of methods to unbiasedly estimate nonlinear ecologically relevant parameters, in order to make inferences while fulfilling requirements of both sampling theory and field work logistics. ?? 2010 The Authors.

Cued Speech Transliteration: Effects of Speaking Rate and Lag Time on Production Accuracy

ERIC Educational Resources Information Center

Krause, Jean C.; Tessler, Morgan P.

2016-01-01

Many deaf and hard-of-hearing children rely on interpreters to access classroom communication. Although the exact level of access provided by interpreters in these settings is unknown, it is likely to depend heavily on interpreter accuracy (portion of message correctly produced by the interpreter) and the factors that govern interpreter accuracy.…

Leaping into the Unknown: Developing Thinking in the Primary Science Classroom

ERIC Educational Resources Information Center

Serret, Natasha

2004-01-01

The original project, the foundation for all subsequent work, was set up in 1981 by Michael Shayer, with Philip Adey and Carolyn Yates, and became known as CASE @ KS3 (Adey and Shayer, 1994). CASE stands for Cognitive Acceleration through Science Education. The original CASE project drew on Piaget's work on the stage theory of cognitive…

Examining the Educational Benefits of and Attitudes toward Closed Captioning among Undergraduate Students

ERIC Educational Resources Information Center

Dallas, Bryan K.; McCarthy, Amanda K.; Long, Greg

2016-01-01

Closed-captioning technology has been available for decades and is often used by individuals with disabilities to access video-based information. Videos are routinely used by educators in higher education settings throughout the United States. It is unknown, however, if closed captions are educationally beneficial for all students. The purpose of…

Field evaluation of potential weed-suppressive traits in an indica x tropical japonica mapping population

USDA-ARS?s Scientific Manuscript database

The indica rice accession, PI 312777 (a.k.a. WC 4644), is highly productive and can suppress barnyardgrass (Echinochloa crus-galli) in reduced-input systems, but the genetic control of this weed suppression is unknown. A set of 330 recombinant inbred lines (RILs) was developed using single seed desc...

Challenges and Visions for Higher Education in a Complex World: Commentary on Barnett and Barrie

ERIC Educational Resources Information Center

Austin, Ann E.

2012-01-01

In this commentary, the author considers two articles: Simon C. Barrie's "A research-based approach to generic graduate attributes policy" (2004) and Ronald Barnett's "Learning for an unknown future" (2004). Taken as a set, these two articles raise several questions about higher education that transcend national boundaries and institutional type.…

Exploitation of children and young people through prostitution.

PubMed

Walker, Karen Elizabeth

2002-09-01

The numbers of children in contemporary society involved in prostitution is still largely unknown. However, there are multiple factors which leave children vulnerable and involved in prostitution. This article aims to explore the historical context of child prostitution, factors which may predispose an adolescent engaging in prostitution, and the role that professionals within the healthcare settings can offer.

Can the "Best Practice" Trend Leave Room for the Unknown?

ERIC Educational Resources Information Center

Nicoll, Jessica; Oreck, Barry

2013-01-01

As teachers of the arts we are committed to nurturing the creative potential of all our students. We value process and want to inspire young artists to find their unique voices. But do we? Habitual models of teaching, along with external pressures in the settings in which we teach--including pursuing models and language of "best…

Psychometric Inferences from a Meta-Analysis of Reliability and Internal Consistency Coefficients

ERIC Educational Resources Information Center

Botella, Juan; Suero, Manuel; Gambara, Hilda

2010-01-01

A meta-analysis of the reliability of the scores from a specific test, also called reliability generalization, allows the quantitative synthesis of its properties from a set of studies. It is usually assumed that part of the variation in the reliability coefficients is due to some unknown and implicit mechanism that restricts and biases the…

The Accuracy of the ADOS-2 in Identifying Autism among Adults with Complex Psychiatric Conditions

ERIC Educational Resources Information Center

Maddox, Brenna B.; Brodkin, Edward S.; Calkins, Monica E.; Shea, Kathleen; Mullan, Katherine; Hostager, Jack; Mandell, David S.; Miller, Judith S.

2017-01-01

The Autism Diagnostic Observation Schedule, Second Edition (ADOS-2), Module 4 is considered a "gold-standard" instrument for diagnosing autism spectrum disorder (ASD) in adults. Although the ADOS-2 shows good sensitivity and specificity in lab-based settings, it is unknown whether these results hold in community clinics that serve a more…

The Freedom to Set Research Agendas--Illusion and Reality of the Research Units in the Dutch Universities

ERIC Educational Resources Information Center

Leisyte, Liudvika; Enders, Jurgen; De Boer, Harry

2008-01-01

The Dutch higher education and research system has incrementally changed during the last decade. Several reforms, initiated by the government, have hinted towards influencing the basic processes within universities, such as research programming. However, it is largely unknown how these reforms have been implemented at the university shop floor…

Vehicle longitudinal velocity estimation during the braking process using unknown input Kalman filter

NASA Astrophysics Data System (ADS)

Moaveni, Bijan; Khosravi Roqaye Abad, Mahdi; Nasiri, Sayyad

2015-10-01

In this paper, vehicle longitudinal velocity during the braking process is estimated by measuring the wheels speed. Here, a new algorithm based on the unknown input Kalman filter is developed to estimate the vehicle longitudinal velocity with a minimum mean square error and without using the value of braking torque in the estimation procedure. The stability and convergence of the filter are analysed and proved. Effectiveness of the method is shown by designing a real experiment and comparing the estimation result with actual longitudinal velocity computing from a three-axis accelerometer output.

An Alternative Approach to "Identification of Unknowns": Designing a Protocol to Verify the Identities of Nitrogen Fixing Bacteria.

PubMed

Martinez-Vaz, Betsy M; Denny, Roxanne; Young, Nevin D; Sadowsky, Michael J

2015-12-01

Microbiology courses often include a laboratory activity on the identification of unknown microbes. This activity consists of providing students with microbial cultures and running biochemical assays to identify the organisms. This approach lacks molecular techniques such as sequencing of genes encoding 16S rRNA, which is currently the method of choice for identification of unknown bacteria. A laboratory activity was developed to teach students how to identify microorganisms using 16S rRNA polymerase chain reaction (PCR) and validate microbial identities using biochemical techniques. We hypothesized that designing an experimental protocol to confirm the identity of a bacterium would improve students' knowledge of microbial identification techniques and the physiological characteristics of bacterial species. Nitrogen-fixing bacteria were isolated from the root nodules of Medicago truncatula and prepared for 16S rRNA PCR analysis. Once DNA sequencing revealed the identity of the organisms, the students designed experimental protocols to verify the identity of rhizobia. An assessment was conducted by analyzing pre- and posttest scores and by grading students' verification protocols and presentations. Posttest scores were higher than pretest scores at or below p = 0.001. Normalized learning gains (G) showed an improvement of students' knowledge of microbial identification methods (LO4, G = 0.46), biochemical properties of nitrogen-fixing bacteria (LO3, G = 0.45), and the events leading to the establishment of nitrogen-fixing symbioses (LO1&2, G = 0.51, G = 0.37). An evaluation of verification protocols also showed significant improvement with a p value of less than 0.001.

A forward genetic screen reveals essential and non-essential RNAi factors in Paramecium tetraurelia

PubMed Central

Marker, Simone; Carradec, Quentin; Tanty, Véronique; Arnaiz, Olivier; Meyer, Eric

2014-01-01

In most eukaryotes, small RNA-mediated gene silencing pathways form complex interacting networks. In the ciliate Paramecium tetraurelia, at least two RNA interference (RNAi) mechanisms coexist, involving distinct but overlapping sets of protein factors and producing different types of short interfering RNAs (siRNAs). One is specifically triggered by high-copy transgenes, and the other by feeding cells with double-stranded RNA (dsRNA)-producing bacteria. In this study, we designed a forward genetic screen for mutants deficient in dsRNA-induced silencing, and a powerful method to identify the relevant mutations by whole-genome sequencing. We present a set of 47 mutant alleles for five genes, revealing two previously unknown RNAi factors: a novel Paramecium-specific protein (Pds1) and a Cid1-like nucleotidyl transferase. Analyses of allelic diversity distinguish non-essential and essential genes and suggest that the screen is saturated for non-essential, single-copy genes. We show that non-essential genes are specifically involved in dsRNA-induced RNAi while essential ones are also involved in transgene-induced RNAi. One of the latter, the RNA-dependent RNA polymerase RDR2, is further shown to be required for all known types of siRNAs, as well as for sexual reproduction. These results open the way for the dissection of the genetic complexity, interconnection, mechanisms and natural functions of RNAi pathways in P. tetraurelia. PMID:24860163

The current state of funded NIH grants in implementation science in genomic medicine: a portfolio analysis.

PubMed

Roberts, Megan C; Clyne, Mindy; Kennedy, Amy E; Chambers, David A; Khoury, Muin J

2017-10-26

PurposeImplementation science offers methods to evaluate the translation of genomic medicine research into practice. The extent to which the National Institutes of Health (NIH) human genomics grant portfolio includes implementation science is unknown. This brief report's objective is to describe recently funded implementation science studies in genomic medicine in the NIH grant portfolio, and identify remaining gaps.MethodsWe identified investigator-initiated NIH research grants on implementation science in genomic medicine (funding initiated 2012-2016). A codebook was adapted from the literature, three authors coded grants, and descriptive statistics were calculated for each code.ResultsForty-two grants fit the inclusion criteria (~1.75% of investigator-initiated genomics grants). The majority of included grants proposed qualitative and/or quantitative methods with cross-sectional study designs, and described clinical settings and primarily white, non-Hispanic study populations. Most grants were in oncology and examined genetic testing for risk assessment. Finally, grants lacked the use of implementation science frameworks, and most examined uptake of genomic medicine and/or assessed patient-centeredness.ConclusionWe identified large gaps in implementation science studies in genomic medicine in the funded NIH portfolio over the past 5 years. To move the genomics field forward, investigator-initiated research grants should employ rigorous implementation science methods within diverse settings and populations.Genetics in Medicine advance online publication, 26 October 2017; doi:10.1038/gim.2017.180.

On synchronisation of a class of complex chaotic systems with complex unknown parameters via integral sliding mode control

NASA Astrophysics Data System (ADS)

Tirandaz, Hamed; Karami-Mollaee, Ali

2018-06-01

Chaotic systems demonstrate complex behaviour in their state variables and their parameters, which generate some challenges and consequences. This paper presents a new synchronisation scheme based on integral sliding mode control (ISMC) method on a class of complex chaotic systems with complex unknown parameters. Synchronisation between corresponding states of a class of complex chaotic systems and also convergence of the errors of the system parameters to zero point are studied. The designed feedback control vector and complex unknown parameter vector are analytically achieved based on the Lyapunov stability theory. Moreover, the effectiveness of the proposed methodology is verified by synchronisation of the Chen complex system and the Lorenz complex systems as the leader and the follower chaotic systems, respectively. In conclusion, some numerical simulations related to the synchronisation methodology is given to illustrate the effectiveness of the theoretical discussions.

Indirect adaptive fuzzy fault-tolerant tracking control for MIMO nonlinear systems with actuator and sensor failures.

PubMed

Bounemeur, Abdelhamid; Chemachema, Mohamed; Essounbouli, Najib

2018-05-10

In this paper, an active fuzzy fault tolerant tracking control (AFFTTC) scheme is developed for a class of multi-input multi-output (MIMO) unknown nonlinear systems in the presence of unknown actuator faults, sensor failures and external disturbance. The developed control scheme deals with four kinds of faults for both sensors and actuators. The bias, drift, and loss of accuracy additive faults are considered along with the loss of effectiveness multiplicative fault. A fuzzy adaptive controller based on back-stepping design is developed to deal with actuator failures and unknown system dynamics. However, an additional robust control term is added to deal with sensor faults, approximation errors, and external disturbances. Lyapunov theory is used to prove the stability of the closed loop system. Numerical simulations on a quadrotor are presented to show the effectiveness of the proposed approach. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Development of autonomous grasping and navigating robot

NASA Astrophysics Data System (ADS)

Kudoh, Hiroyuki; Fujimoto, Keisuke; Nakayama, Yasuichi

2015-01-01

The ability to find and grasp target items in an unknown environment is important for working robots. We developed an autonomous navigating and grasping robot. The operations are locating a requested item, moving to where the item is placed, finding the item on a shelf or table, and picking the item up from the shelf or the table. To achieve these operations, we designed the robot with three functions: an autonomous navigating function that generates a map and a route in an unknown environment, an item position recognizing function, and a grasping function. We tested this robot in an unknown environment. It achieved a series of operations: moving to a destination, recognizing the positions of items on a shelf, picking up an item, placing it on a cart with its hand, and returning to the starting location. The results of this experiment show the applicability of reducing the workforce with robots.

Adaptive neural control for dual-arm coordination of humanoid robot with unknown nonlinearities in output mechanism.

PubMed

Liu, Zhi; Chen, Ci; Zhang, Yun; Chen, C L P

2015-03-01

To achieve an excellent dual-arm coordination of the humanoid robot, it is essential to deal with the nonlinearities existing in the system dynamics. The literatures so far on the humanoid robot control have a common assumption that the problem of output hysteresis could be ignored. However, in the practical applications, the output hysteresis is widely spread; and its existing limits the motion/force performances of the robotic system. In this paper, an adaptive neural control scheme, which takes the unknown output hysteresis and computational efficiency into account, is presented and investigated. In the controller design, the prior knowledge of system dynamics is assumed to be unknown. The motion error is guaranteed to converge to a small neighborhood of the origin by Lyapunov's stability theory. Simultaneously, the internal force is kept bounded and its error can be made arbitrarily small.

Adaptive output feedback NN control of a class of discrete-time MIMO nonlinear systems with unknown control directions.

PubMed

Li, Yanan; Yang, Chenguang; Ge, Shuzhi Sam; Lee, Tong Heng

2011-04-01

In this paper, adaptive neural network (NN) control is investigated for a class of block triangular multiinput-multioutput nonlinear discrete-time systems with each subsystem in pure-feedback form with unknown control directions. These systems are of couplings in every equation of each subsystem, and different subsystems may have different orders. To avoid the noncausal problem in the control design, the system is transformed into a predictor form by rigorous derivation. By exploring the properties of the block triangular form, implicit controls are developed for each subsystem such that the couplings of inputs and states among subsystems have been completely decoupled. The radial basis function NN is employed to approximate the unknown control. Each subsystem achieves a semiglobal uniformly ultimately bounded stability with the proposed control, and simulation results are presented to demonstrate its efficiency.

Off-Policy Integral Reinforcement Learning Method to Solve Nonlinear Continuous-Time Multiplayer Nonzero-Sum Games.

PubMed

Song, Ruizhuo; Lewis, Frank L; Wei, Qinglai

2017-03-01

This paper establishes an off-policy integral reinforcement learning (IRL) method to solve nonlinear continuous-time (CT) nonzero-sum (NZS) games with unknown system dynamics. The IRL algorithm is presented to obtain the iterative control and off-policy learning is used to allow the dynamics to be completely unknown. Off-policy IRL is designed to do policy evaluation and policy improvement in the policy iteration algorithm. Critic and action networks are used to obtain the performance index and control for each player. The gradient descent algorithm makes the update of critic and action weights simultaneously. The convergence analysis of the weights is given. The asymptotic stability of the closed-loop system and the existence of Nash equilibrium are proved. The simulation study demonstrates the effectiveness of the developed method for nonlinear CT NZS games with unknown system dynamics.

Quadrotor Control in the Presence of Unknown Mass Properties

NASA Astrophysics Data System (ADS)

Duivenvoorden, Rikky Ricardo Petrus Rufino

Quadrotor UAVs are popular due to their mechanical simplicity, as well as their capability to hover and vertically take-off and land. As applications diversify, quadrotors are increasingly required to operate under unknown mass properties, for example as a multirole sensor platform or for package delivery operations. The work presented here consists of the derivation of a generalized quadrotor dynamic model without the typical simplifying assumptions on the first and second moments of mass. The maximum payload capacity of a quadrotor in hover, and the observability of the unknown mass properties are discussed. A brief introduction of L1 adaptive control is provided, and three different L 1 adaptive controllers were designed for the Parrot AR.Drone quadrotor. Their tracking and disturbance rejection performance was compared to the baseline nonlinear controller in experiments. Finally, the results of the combination of L1 adaptive control with iterative learning control are presented, showing high performance trajectory tracking under uncertainty.

Neuro-adaptive backstepping control of SISO non-affine systems with unknown gain sign.

PubMed

Ramezani, Zahra; Arefi, Mohammad Mehdi; Zargarzadeh, Hassan; Jahed-Motlagh, Mohammad Reza

2016-11-01

This paper presents two neuro-adaptive controllers for a class of uncertain single-input, single-output (SISO) nonlinear non-affine systems with unknown gain sign. The first approach is state feedback controller, so that a neuro-adaptive state-feedback controller is constructed based on the backstepping technique. The second approach is an observer-based controller and K-filters are designed to estimate the system states. The proposed method relaxes a priori knowledge of control gain sign and therefore by utilizing the Nussbaum-type functions this problem is addressed. In these methods, neural networks are employed to approximate the unknown nonlinear functions. The proposed adaptive control schemes guarantee that all the closed-loop signals are semi-globally uniformly ultimately bounded (SGUUB). Finally, the theoretical results are numerically verified through simulation examples. Simulation results show the effectiveness of the proposed methods. Copyright © 2016 ISA. All rights reserved.

Illumination estimation via thin-plate spline interpolation.

PubMed

Shi, Lilong; Xiong, Weihua; Funt, Brian

2011-05-01

Thin-plate spline interpolation is used to interpolate the chromaticity of the color of the incident scene illumination across a training set of images. Given the image of a scene under unknown illumination, the chromaticity of the scene illumination can be found from the interpolated function. The resulting illumination-estimation method can be used to provide color constancy under changing illumination conditions and automatic white balancing for digital cameras. A thin-plate spline interpolates over a nonuniformly sampled input space, which in this case is a training set of image thumbnails and associated illumination chromaticities. To reduce the size of the training set, incremental k medians are applied. Tests on real images demonstrate that the thin-plate spline method can estimate the color of the incident illumination quite accurately, and the proposed training set pruning significantly decreases the computation.

Structural control and health monitoring of building structures with unknown ground excitations: Experimental investigation

NASA Astrophysics Data System (ADS)

He, Jia; Xu, You-Lin; Zhan, Sheng; Huang, Qin

2017-03-01

When health monitoring system and vibration control system both are required for a building structure, it will be beneficial and cost-effective to integrate these two systems together for creating a smart building structure. Recently, on the basis of extended Kalman filter (EKF), a time-domain integrated approach was proposed for the identification of structural parameters of the controlled buildings with unknown ground excitations. The identified physical parameters and structural state vectors were then utilized to determine the control force for vibration suppression. In this paper, the possibility of establishing such a smart building structure with the function of simultaneous damage detection and vibration suppression was explored experimentally. A five-story shear building structure equipped with three magneto-rheological (MR) dampers was built. Four additional columns were added to the building model, and several damage scenarios were then simulated by symmetrically cutting off these columns in certain stories. Two sets of earthquakes, i.e. Kobe earthquake and Northridge earthquake, were considered as seismic input and assumed to be unknown during the tests. The structural parameters and the unknown ground excitations were identified during the tests by using the proposed identification method with the measured control forces. Based on the identified structural parameters and system states, a switching control law was employed to adjust the current applied to the MR dampers for the purpose of vibration attenuation. The experimental results show that the presented approach is capable of satisfactorily identifying structural damages and unknown excitations on one hand and significantly mitigating the structural vibration on the other hand.

A least squares approach to estimating the probability distribution of unobserved data in multiphoton microscopy

NASA Astrophysics Data System (ADS)

Salama, Paul

2008-02-01

Multi-photon microscopy has provided biologists with unprecedented opportunities for high resolution imaging deep into tissues. Unfortunately deep tissue multi-photon microscopy images are in general noisy since they are acquired at low photon counts. To aid in the analysis and segmentation of such images it is sometimes necessary to initially enhance the acquired images. One way to enhance an image is to find the maximum a posteriori (MAP) estimate of each pixel comprising an image, which is achieved by finding a constrained least squares estimate of the unknown distribution. In arriving at the distribution it is assumed that the noise is Poisson distributed, the true but unknown pixel values assume a probability mass function over a finite set of non-negative values, and since the observed data also assumes finite values because of low photon counts, the sum of the probabilities of the observed pixel values (obtained from the histogram of the acquired pixel values) is less than one. Experimental results demonstrate that it is possible to closely estimate the unknown probability mass function with these assumptions.

Carcinoma of unknown primary: key radiological issues from the recent National Institute for Health and Clinical Excellence guidelines

PubMed Central

Taylor, M B; Bromham, N R; Arnold, S E

2012-01-01

Carcinoma of unknown primary origin (CUP) accounts for 3–5% of cancer cases and is the fourth most common cause of cancer death in the UK. CUP management is challenging, partly owing to the heterogeneity of the condition and its presentation, but also owing to the lack of dedicated clinical services for these patients. The recent National Institute for Health and Clinical Excellence (NICE) guidelines on metastatic malignancy of unknown primary origin were developed to improve the co-ordination of diagnostic and clinical services at hospitals treating cancer patients in England and Wales, in particular by the setting up of CUP teams to manage these patients. Radiologists have a vital role in the diagnosis of these patients and should work closely with the CUP team to streamline the diagnostic pathway. This article summarises areas of the NICE guidelines relevant to radiology and discusses the radiological management of patients with CUP, including initial investigation, the importance of biopsy, the management of specific presentations, special investigations and organisational issues. PMID:22374278

Analysis of sensorless control of brushless DC motor using unknown input observer with different gains

NASA Astrophysics Data System (ADS)

Astik, Mitesh B.; Bhatt, Praghnesh; Bhalja, Bhavesh R.

2017-03-01

A sensorless control scheme based on an unknown input observer is presented in this paper in which back EMF of the Brushless DC Motor (BLDC) is continuously estimated from available line voltages and currents. During negative rotation of motor, actual and estimated speed fail to track the reference speed and if the corrective action is not taken by the observer, the motor goes into saturation. To overcome this problem, the speed estimation algorithm has been implemented in this paper to control the dynamic behavior of the motor during negative rotation. The Ackermans method was used to calculate the gains of an unknown input observer which is based on the appropriate choice of the eigenvalues in advance. The criteria to choose eigenvalue is to obtain a balance between faster convergence rate and the least noise level. Simulations have been carried out for different disturbances such as step changes in motor reference speed and load torque. The comparative simulation results clearly depict that the disturbance effects in actual and estimated responses minimizes as observer gain setting increases.

Group prioritisation with unknown expert weights in incomplete linguistic context

NASA Astrophysics Data System (ADS)

Cheng, Dong; Cheng, Faxin; Zhou, Zhili; Wang, Juan

2017-09-01

In this paper, we study a group prioritisation problem in situations when the expert weights are completely unknown and their judgement preferences are linguistic and incomplete. Starting from the theory of relative entropy (RE) and multiplicative consistency, an optimisation model is provided for deriving an individual priority vector without estimating the missing value(s) of an incomplete linguistic preference relation. In order to address the unknown expert weights in the group aggregating process, we define two new kinds of expert weight indicators based on RE: proximity entropy weight and similarity entropy weight. Furthermore, a dynamic-adjusting algorithm (DAA) is proposed to obtain an objective expert weight vector and capture the dynamic properties involved in it. Unlike the extant literature of group prioritisation, the proposed RE approach does not require pre-allocation of expert weights and can solve incomplete preference relations. An interesting finding is that once all the experts express their preference relations, the final expert weight vector derived from the DAA is fixed irrespective of the initial settings of expert weights. Finally, an application example is conducted to validate the effectiveness and robustness of the RE approach.

Should nevirapine be used to prevent mother-to-child transmission of HIV among women of unknown serostatus?

PubMed Central

Sint, Tin Tin; Dabis, François; Kamenga, Claude; Shaffer, Nathan; de Zoysa, Isabelle F.

2005-01-01

At present, HIV testing and counselling during pregnancy represent the key entry point for women to learn their serostatus and for them to access, if they are HIV-positive, specific interventions to reduce mother-to-child transmission (MTCT) of HIV. However, the provision and uptake of testing and counselling services are inadequate, and many pregnant women in countries most affected by the HIV/AIDS epidemic remain unaware of their HIV status. The offer of single-dose nevirapine prophylaxis to women whose HIV status is unknown at the time of delivery has been proposed to circumvent these problems in high-prevalence settings. The potential advantages and disadvantages of three different programme approaches are considered: targeted programmes in which antiretroviral drugs are offered only to women who are known to be HIV-positive; combined programmes in which nevirapine prophylaxis is offered to women whose serostatus remains unknown at the time of delivery despite targeted programme inputs; and universal nevirapine prophylaxis programmes in which HIV testing and counselling are not available and all pregnant women, regardless of their serostatus, are offered nevirapine prophylaxis. PMID:15798847

Rough Set Approach to Incomplete Multiscale Information System

PubMed Central

Yang, Xibei; Qi, Yong; Yu, Dongjun; Yu, Hualong; Song, Xiaoning; Yang, Jingyu

2014-01-01

Multiscale information system is a new knowledge representation system for expressing the knowledge with different levels of granulations. In this paper, by considering the unknown values, which can be seen everywhere in real world applications, the incomplete multiscale information system is firstly investigated. The descriptor technique is employed to construct rough sets at different scales for analyzing the hierarchically structured data. The problem of unravelling decision rules at different scales is also addressed. Finally, the reduct descriptors are formulated to simplify decision rules, which can be derived from different scales. Some numerical examples are employed to substantiate the conceptual arguments. PMID:25276852

Quantum Hamiltonian identification from measurement time traces.

PubMed

Zhang, Jun; Sarovar, Mohan

2014-08-22

Precise identification of parameters governing quantum processes is a critical task for quantum information and communication technologies. In this Letter, we consider a setting where system evolution is determined by a parametrized Hamiltonian, and the task is to estimate these parameters from temporal records of a restricted set of system observables (time traces). Based on the notion of system realization from linear systems theory, we develop a constructive algorithm that provides estimates of the unknown parameters directly from these time traces. We illustrate the algorithm and its robustness to measurement noise by applying it to a one-dimensional spin chain model with variable couplings.

Solidification of a binary mixture

NASA Technical Reports Server (NTRS)

Antar, B. N.

1982-01-01

The time dependent concentration and temperature profiles of a finite layer of a binary mixture are investigated during solidification. The coupled time dependent Stefan problem is solved numerically using an implicit finite differencing algorithm with the method of lines. Specifically, the temporal operator is approximated via an implicit finite difference operator resulting in a coupled set of ordinary differential equations for the spatial distribution of the temperature and concentration for each time. Since the resulting differential equations set form a boundary value problem with matching conditions at an unknown spatial point, the method of invariant imbedding is used for its solution.

An ``Openable,'' High-Strength Gradient Set for Orthopedic MRI

NASA Astrophysics Data System (ADS)

Crozier, Stuart; Roffmann, Wolfgang U.; Luescher, Kurt; Snape-Jenkinson, Christopher; Forbes, Lawrence K.; Doddrell, David M.

1999-07-01

A novel three-axis gradient set and RF resonator for orthopedic MRI has been designed and constructed. The set is openable and may be wrapped around injured joints. The design methodology used was the minimization of magnetic field spherical harmonics by simulated annealing. Splitting of the longitudinal coil presents the major design challenge to a fully openable gradient set and in order to efficiently design such coils, we have developed a new fast algorithm for determining the magnetic field spherical harmonics generated by an arc of multiturn wire. The algorithm allows a realistic impression of the effect of split longitudinal designs. A prototype set was constructed based on the new designs and tested in a 2-T clinical research system. The set generated 12 mT/m/A with a linear region of 12 cm and a switching time of 100 μs, conforming closely with theoretical predictions. Preliminary images from the set are presented.

Sub-Audible Speech Recognition Based upon Electromyographic Signals

NASA Technical Reports Server (NTRS)

Jorgensen, Charles C. (Inventor); Agabon, Shane T. (Inventor); Lee, Diana D. (Inventor)

2012-01-01

Method and system for processing and identifying a sub-audible signal formed by a source of sub-audible sounds. Sequences of samples of sub-audible sound patterns ("SASPs") for known words/phrases in a selected database are received for overlapping time intervals, and Signal Processing Transforms ("SPTs") are formed for each sample, as part of a matrix of entry values. The matrix is decomposed into contiguous, non-overlapping two-dimensional cells of entries, and neural net analysis is applied to estimate reference sets of weight coefficients that provide sums with optimal matches to reference sets of values. The reference sets of weight coefficients are used to determine a correspondence between a new (unknown) word/phrase and a word/phrase in the database.

Prediction of binding hot spot residues by using structural and evolutionary parameters.

PubMed

Higa, Roberto Hiroshi; Tozzi, Clésio Luis

2009-07-01

In this work, we present a method for predicting hot spot residues by using a set of structural and evolutionary parameters. Unlike previous studies, we use a set of parameters which do not depend on the structure of the protein in complex, so that the predictor can also be used when the interface region is unknown. Despite the fact that no information concerning proteins in complex is used for prediction, the application of the method to a compiled dataset described in the literature achieved a performance of 60.4%, as measured by F-Measure, corresponding to a recall of 78.1% and a precision of 49.5%. This result is higher than those reported by previous studies using the same data set.

New control concepts for uncertain water resources systems: 1. Theory

NASA Astrophysics Data System (ADS)

Georgakakos, Aris P.; Yao, Huaming

1993-06-01

A major complicating factor in water resources systems management is handling unknown inputs. Stochastic optimization provides a sound mathematical framework but requires that enough data exist to develop statistical input representations. In cases where data records are insufficient (e.g., extreme events) or atypical of future input realizations, stochastic methods are inadequate. This article presents a control approach where input variables are only expected to belong in certain sets. The objective is to determine sets of admissible control actions guaranteeing that the system will remain within desirable bounds. The solution is based on dynamic programming and derived for the case where all sets are convex polyhedra. A companion paper (Yao and Georgakakos, this issue) addresses specific applications and problems in relation to reservoir system management.

Designing clinical trials for amblyopia

PubMed Central

Holmes, Jonathan M.

2015-01-01

Randomized clinical trial (RCT) study design leads to one of the highest levels of evidence, and is a preferred study design over cohort studies, because randomization reduces bias and maximizes the chance that even unknown confounding factors will be balanced between treatment groups. Recent randomized clinical trials and observational studies in amblyopia can be taken together to formulate an evidence-based approach to amblyopia treatment, which is presented in this review. When designing future clinical studies of amblyopia treatment, issues such as regression to the mean, sample size and trial duration must be considered, since each may impact study results and conclusions. PMID:25752747

Infrasound Assessment of Infrastructure Report 6: Scour Detection and Riverine Health Assessment Using Infrasound

DTIC Science & Technology

2016-05-01

construed as an official Department of the Army position unless so designated by other authorized documents. DESTROY THIS REPORT WHEN NO LONGER NEEDED...20 Figure 14. Seismic and infrasound detection of a barge strike on the I-20 bridge pier during the...foundations meaning that no plans, either design or as-built, existed for the structure. Initially, bridges classified as having unknown foundations

Synthetic Molecular Evolution of Membrane-Active Peptides

NASA Astrophysics Data System (ADS)

Wimley, William

The physical chemistry of membrane partitioning largely determines the function of membrane active peptides. Membrane-active peptides have potential utility in many areas, including in the cellular delivery of polar compounds, cancer therapy, biosensor design, and in antibacterial, antiviral and antifungal therapies. Yet, despite decades of research on thousands of known examples, useful sequence-structure-function relationships are essentially unknown. Because peptide-membrane interactions within the highly fluid bilayer are dynamic and heterogeneous, accounts of mechanism are necessarily vague and descriptive, and have little predictive power. This creates a significant roadblock to advances in the field. We are bypassing that roadblock with synthetic molecular evolution: iterative peptide library design and orthogonal high-throughput screening. We start with template sequences that have at least some useful activity, and create small, focused libraries using structural and biophysical principles to design the sequence space around the template. Orthogonal high-throughput screening is used to identify gain-of-function peptides by simultaneously selecting for several different properties (e.g. solubility, activity and toxicity). Multiple generations of iterative library design and screening have enabled the identification of membrane-active sequences with heretofore unknown properties, including clinically relevant, broad-spectrum activity against drug-resistant bacteria and enveloped viruses as well as pH-triggered macromolecular poration.

SET8 promotes epithelial–mesenchymal transition and confers TWIST dual transcriptional activities

PubMed Central

Yang, Fen; Sun, Luyang; Li, Qian; Han, Xiao; Lei, Liandi; Zhang, Hua; Shang, Yongfeng

2012-01-01

SET8 is implicated in transcriptional regulation, heterochromatin formation, genomic stability, cell-cycle progression, and development. As such, it is predicted that SET8 might be involved in the development and progression of tumour. However, whether and how SET8 might be implicated in tumourigenesis is currently unknown. Here, we report that SET8 is physically associated with TWIST, a master regulator of epithelial–mesenchymal transition (EMT). We demonstrated that SET8 and TWIST are functionally interdependent in promoting EMT and enhancing the invasive potential of breast cancer cells in vitro and in vivo. We showed that SET8 acts as a dual epigenetic modifier on the promoters of the TWIST target genes E-cadherin and N-cadherin via its H4K20 monomethylation activity. Significantly, in breast carcinoma samples, SET8 expression is positively correlated with metastasis and the expression of TWIST and N-cadherin and negatively correlated with E-cadherin. Together, our experiments revealed a novel role for SET8 in tumour invasion and metastasis and provide a molecular mechanism underlying TWIST-promoted EMT, suggesting SET8 as a potential target for intervention of the metastasis of breast cancer. PMID:21983900

Quantitative real-time imaging of glutathione

USDA-ARS?s Scientific Manuscript database

Glutathione plays many important roles in biological processes; however, the dynamic changes of glutathione concentrations in living cells remain largely unknown. Here, we report a reversible reaction-based fluorescent probe—designated as RealThiol (RT)—that can quantitatively monitor the real-time ...

13. Photocopy of photograph (original in Documents Collection, College of ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

13. Photocopy of photograph (original in Documents Collection, College of Environmental Design, University of California, Berkeley, CA) Circa 1910, photographer unknown VIEW LOOKING NORTHEAST - Howard B. Gates House, 62 South Thirteenth Street, San Jose, Santa Clara County, CA

Task Engagement in Young Adults with High-Functioning Autism Spectrum Disorders: Generalization Effects of Behavioral Skills Training

ERIC Educational Resources Information Center

Palmen, Annemiek; Didden, Robert

2012-01-01

This study evaluated the effectiveness of a behavioral skills training package on task engagement in six young adults with high-functioning ASD who worked in a regular job-training setting. Experimental sessions were implemented in a small-group training format in a therapy room using unknown tasks. Data were collected on participant's off-task…

Quantitative Analysis in the General Chemistry Laboratory: Training Students to Analyze Individual Results in the Context of Collective Data

ERIC Educational Resources Information Center

Ling, Chris D.; Bridgeman, Adam J.

2011-01-01

Titration experiments are ideal for generating large data sets for use in quantitative-analysis activities that are meaningful and transparent to general chemistry students. We report the successful implementation of a sophisticated quantitative exercise in which the students identify a series of unknown acids by determining their molar masses…

Case study 6.1: DNA survey for fisher in northern Idaho

Treesearch

Samuel Cushman; Kevin McKelvey; Michael Schwartz

2008-01-01

Unique haplotypes indicating the presence of a residual native population of fisher were found in central Idaho (Vinkey et al. 2006). Fishers had been detected previously using camera sets in the Selkirk Mountains just south of the Canadian border, but their population status and genetic composition were unknown. The purpose of the study was to provide a comprehensive...

Motives for Risk-Taking in Adolescence: A Cross-Cultural Study

ERIC Educational Resources Information Center

Kloep, M.; Guney, N.; Cok, F.; Simsek, O. F.

2009-01-01

Most research on adolescent risk-taking has been conducted in Western societies, but it is as yet unknown whether motives to engage in risk behaviours show cultural variety. This study sets out to investigate differences in perceived motives to engage in perceived risks in Turkish and Welsh samples of young people (N = 922) between 14 and 20 years…

Dissociation between Small and Large Numerosities in Newborn Infants

ERIC Educational Resources Information Center

Coubart, Aurélie; Izard, Véronique; Spelke, Elizabeth S.; Marie, Julien; Streri, Arlette

2014-01-01

In the first year of life, infants possess two cognitive systems encoding numerical information: one for processing the numerosity of sets of 4 or more items, and the second for tracking up to 3 objects in parallel. While a previous study showed the former system to be already present a few hours after birth, it is unknown whether the latter…

Adult and Adolescent Social Reciprocity: Experimental Data from the Trust Game

ERIC Educational Resources Information Center

Belli, Stefano R.; Rogers, Robert D.; Lau, Jennifer Y. F.

2012-01-01

Twenty-four adults (aged 19-35) and 27 adolescents (aged 13-14) played as "Trustee" in an iterated Trust Game against a pre-programmed set of "Investor" moves, said to belong to an unknown co-player. Trustee behaviour was examined first in response to normative Investor cooperation, and then in response to a period of social rupture caused by…

Perceptions of the Benefits to Using a Secondary Admissions Process in Professional Bachelor's Athletic Training Programs

ERIC Educational Resources Information Center

Bowman, Thomas G.; Mazerolle, Stephanie M.; Dodge, Thomas M.

2016-01-01

Context: Some athletic training program (ATP) directors use direct admit, where students are admitted into the ATP directly out of high school. Other ATP directors admit students into the program after a set time period on campus through a secondary admissions process. It remains unknown why ATP directors use various admissions practices.…

Chapter 06: Identification key

Treesearch

Alex Wiedenhoeft

2011-01-01

The key is written to guide you through the identification process in the most efficient and accurate way possible. It presents you with a numbered series of questions and asks you to answer them. The answers you provide will be based on your interpretations of the anatomical characters in your unknown specimen and will lead you to a new set of questions. Each time you...

Inherited Disorders as a Risk Factor and Predictor of Neurodevelopmental Outcome in Pediatric Cancer

ERIC Educational Resources Information Center

Ullrich, Nicole J.

2008-01-01

Each year in the United States, an average of one to two children per 10,000 develop cancer. The etiology of most childhood cancer remains largely unknown but is likely attributable to random or induced genetic aberrations in somatic tissue. However, a subset of children develops cancer in the setting of an underlying inheritable condition…

Knowledge Management in Acquisition and Program Management (KM in the AM and PM)

DTIC Science & Technology

2002-01-01

a clumping of clusters.16 If all the planets in a solar system had moons, the moons would be the people, each planet would be a discipline or cluster...exploration, one looks for non-obvious, unknown relation- ships in a data set. The discovery that cus- tomers frequently buy beer and diapers to- gether from