Advanced development of atmospheric models. [SEASAT Program support

NASA Technical Reports Server (NTRS)

Kesel, P. G.; Langland, R. A.; Stephens, P. L.; Welleck, R. E.; Wolff, P. M.

1979-01-01

A set of atmospheric analysis and prediction models was developed in support of the SEASAT Program existing objective analysis models which utilize a 125x125 polar stereographic grid of the Northern Hemisphere, which were modified in order to incorporate and assess the impact of (real or simulated) satellite data in the analysis of a two-day meteorological scenario in January 1979. Program/procedural changes included: (1) a provision to utilize winds in the sea level pressure and multi-level height analyses (1000-100 MBS); (2) The capability to perform a pre-analysis at two control levels (1000 MBS and 250 MBS); (3) a greater degree of wind- and mass-field coupling, especially at these controls levels; (4) an improved facility to bogus the analyses based on results of the preanalysis; and (5) a provision to utilize (SIRS) satellite thickness values and cloud motion vectors in the multi-level height analysis.

Accounting for correlation in network meta-analysis with multi-arm trials.

PubMed

Franchini, A J; Dias, S; Ades, A E; Jansen, J P; Welton, N J

2012-06-01

Multi-arm trials (trials with more than two arms) are particularly valuable forms of evidence for network meta-analysis (NMA). Trial results are available either as arm-level summaries, where effect measures are reported for each arm, or as contrast-level summaries, where the differences in effect between arms compare with the control arm chosen for the trial. We show that likelihood-based inference in both contrast-level and arm-level formats is identical if there are only two-arm trials, but that if there are multi-arm trials, results from the contrast-level format will be incorrect unless correlations are accounted for in the likelihood. We review Bayesian and frequentist software for NMA with multi-arm trials that can account for this correlation and give an illustrative example of the difference in estimates that can be introduced if the correlations are not incorporated. We discuss methods of imputing correlations when they cannot be derived from the reported results and urge trialists to report the standard error for the control arm even if only contrast-level summaries are reported. Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.

[Research Progress of Multi-Model Medical Image Fusion at Feature Level].

PubMed

Zhang, Junjie; Zhou, Tao; Lu, Huiling; Wang, Huiqun

2016-04-01

Medical image fusion realizes advantage integration of functional images and anatomical images.This article discusses the research progress of multi-model medical image fusion at feature level.We firstly describe the principle of medical image fusion at feature level.Then we analyze and summarize fuzzy sets,rough sets,D-S evidence theory,artificial neural network,principal component analysis and other fusion methods’ applications in medical image fusion and get summery.Lastly,we in this article indicate present problems and the research direction of multi-model medical images in the future.

Multi-Unit Considerations for Human Reliability Analysis

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

St. Germain, S.; Boring, R.; Banaseanu, G.

This paper uses the insights from the Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) methodology to help identify human actions currently modeled in the single unit PSA that may need to be modified to account for additional challenges imposed by a multi-unit accident as well as identify possible new human actions that might be modeled to more accurately characterize multi-unit risk. In identifying these potential human action impacts, the use of the SPAR-H strategy to include both errors in diagnosis and errors in action is considered as well as identifying characteristics of a multi-unit accident scenario that may impact themore » selection of the performance shaping factors (PSFs) used in SPAR-H. The lessons learned from the Fukushima Daiichi reactor accident will be addressed to further help identify areas where improved modeling may be required. While these multi-unit impacts may require modifications to a Level 1 PSA model, it is expected to have much more importance for Level 2 modeling. There is little currently written specifically about multi-unit HRA issues. A review of related published research will be presented. While this paper cannot answer all issues related to multi-unit HRA, it will hopefully serve as a starting point to generate discussion and spark additional ideas towards the proper treatment of HRA in a multi-unit PSA.« less

Group-level spatio-temporal pattern recovery in MEG decoding using multi-task joint feature learning.

PubMed

Kia, Seyed Mostafa; Pedregosa, Fabian; Blumenthal, Anna; Passerini, Andrea

2017-06-15

The use of machine learning models to discriminate between patterns of neural activity has become in recent years a standard analysis approach in neuroimaging studies. Whenever these models are linear, the estimated parameters can be visualized in the form of brain maps which can aid in understanding how brain activity in space and time underlies a cognitive function. However, the recovered brain maps often suffer from lack of interpretability, especially in group analysis of multi-subject data. To facilitate the application of brain decoding in group-level analysis, we present an application of multi-task joint feature learning for group-level multivariate pattern recovery in single-trial magnetoencephalography (MEG) decoding. The proposed method allows for recovering sparse yet consistent patterns across different subjects, and therefore enhances the interpretability of the decoding model. Our experimental results demonstrate that the mutli-task joint feature learning framework is capable of recovering more meaningful patterns of varying spatio-temporally distributed brain activity across individuals while still maintaining excellent generalization performance. We compare the performance of the multi-task joint feature learning in terms of generalization, reproducibility, and quality of pattern recovery against traditional single-subject and pooling approaches on both simulated and real MEG datasets. These results can facilitate the usage of brain decoding for the characterization of fine-level distinctive patterns in group-level inference. Considering the importance of group-level analysis, the proposed approach can provide a methodological shift towards more interpretable brain decoding models. Copyright © 2017 Elsevier B.V. All rights reserved.

Advancing Ecological Models to Compare Scale in Multi-Level Educational Change

ERIC Educational Resources Information Center

Woo, David James

2016-01-01

Education systems as units of analysis have been metaphorically likened to ecologies to model change. However, ecological models to date have been ineffective in modelling educational change that is multi-scale and occurs across multiple levels of an education system. Thus, this paper advances two innovative, ecological frameworks that improve on…

The Dubious Benefits of Multi-Level Modeling

ERIC Educational Resources Information Center

Gorard, Stephen

2007-01-01

This paper presents an argument against the wider adoption of complex forms of data analysis, using multi-level modeling (MLM) as an extended case study. MLM was devised to overcome some deficiencies in existing datasets, such as the bias caused by clustering. The paper suggests that MLM has an unclear theoretical and empirical basis, has not led…

Multi-Morbidity in Hospitalised Older Patients: Who Are the Complex Elderly?

PubMed Central

Ruiz, Milagros; Bottle, Alex; Long, Susannah; Aylin, Paul

2015-01-01

Background No formal definition for the “complex elderly” exists; moreover, these older patients with high levels of multi-morbidity are not readily identified as such at point of hospitalisation, thus missing a valuable opportunity to manage the older patient appropriately within the hospital setting. Objectives To empirically identify the complex elderly patient based on degree of multi-morbidity. Design Retrospective observational study using administrative data. Setting English hospitals during the financial year 2012–13. Subjects All admitted patients aged 65 years and over. Methods By using exploratory analysis (correspondence analysis) we identify multi-morbidity groups based on 20 target conditions whose hospital prevalence was ≥ 1%. Results We examined a total of 2788900 hospital admissions. Multi-morbidity was highly prevalent, 62.8% had 2 or more of the targeted conditions while 4.7% had six or more. Multi-morbidity increased with age from 56% (65-69yr age-groups) up to 67% (80-84yr age-group). The average multi-morbidity was 3.2±1.2 (SD). Correspondence analysis revealed 3 distinct groups of older patients. Group 1 (multi-morbidity ≤2), associated with cancer and/or metastasis; Group 2 (multi-morbidity of 3, 4 or 5), associated with chronic pulmonary disease, lung disease, rheumatism and osteoporosis; finally Group 3 with the highest level of multi-morbidity (≥6) and associated with heart failure, cerebrovascular accident, diabetes, hypertension and myocardial infarction. Conclusions By using widely available hospital administrative data, we propose patients in Groups 2 and 3 to be identified as the complex elderly. Identification of multi-morbidity patterns can help to predict the needs of the older patient and improve resource provision. PMID:26716440

A new rational-based optimal design strategy of ship structure based on multi-level analysis and super-element modeling method

NASA Astrophysics Data System (ADS)

Sun, Li; Wang, Deyu

2011-09-01

A new multi-level analysis method of introducing the super-element modeling method, derived from the multi-level analysis method first proposed by O. F. Hughes, has been proposed in this paper to solve the problem of high time cost in adopting a rational-based optimal design method for ship structural design. Furthermore, the method was verified by its effective application in optimization of the mid-ship section of a container ship. A full 3-D FEM model of a ship, suffering static and quasi-static loads, was used as the analyzing object for evaluating the structural performance of the mid-ship module, including static strength and buckling performance. Research results reveal that this new method could substantially reduce the computational cost of the rational-based optimization problem without decreasing its accuracy, which increases the feasibility and economic efficiency of using a rational-based optimal design method in ship structural design.

VLBI-resolution radio-map algorithms: Performance analysis of different levels of data-sharing on multi-socket, multi-core architectures

NASA Astrophysics Data System (ADS)

Tabik, S.; Romero, L. F.; Mimica, P.; Plata, O.; Zapata, E. L.

2012-09-01

A broad area in astronomy focuses on simulating extragalactic objects based on Very Long Baseline Interferometry (VLBI) radio-maps. Several algorithms in this scope simulate what would be the observed radio-maps if emitted from a predefined extragalactic object. This work analyzes the performance and scaling of this kind of algorithms on multi-socket, multi-core architectures. In particular, we evaluate a sharing approach, a privatizing approach and a hybrid approach on systems with complex memory hierarchy that includes shared Last Level Cache (LLC). In addition, we investigate which manual processes can be systematized and then automated in future works. The experiments show that the data-privatizing model scales efficiently on medium scale multi-socket, multi-core systems (up to 48 cores) while regardless of algorithmic and scheduling optimizations, the sharing approach is unable to reach acceptable scalability on more than one socket. However, the hybrid model with a specific level of data-sharing provides the best scalability over all used multi-socket, multi-core systems.

Multi-level optimization of a beam-like space truss utilizing a continuum model

NASA Technical Reports Server (NTRS)

Yates, K.; Gurdal, Z.; Thangjitham, S.

1992-01-01

A continuous beam model is developed for approximate analysis of a large, slender, beam-like truss. The model is incorporated in a multi-level optimization scheme for the weight minimization of such trusses. This scheme is tested against traditional optimization procedures for savings in computational cost. Results from both optimization methods are presented for comparison.

Using Evaluation Research as a Means for Policy Analysis in a "New" Mission-Oriented Policy Context

ERIC Educational Resources Information Center

Amanatidou, Effie; Cunningham, Paul; Gök, Abdullah; Garefi, Ioanna

2014-01-01

Grand challenges stress the importance of multi-disciplinary research, a multi-actor approach in examining the current state of affairs and exploring possible solutions, multi-level governance and policy coordination across geographical boundaries and policy areas, and a policy environment for enabling change both in science and technology and in…

Multi-level of Fidelity Multi-Disciplinary Design Optimization of Small, Solid-Propellant Launch Vehicles

NASA Astrophysics Data System (ADS)

Roshanian, Jafar; Jodei, Jahangir; Mirshams, Mehran; Ebrahimi, Reza; Mirzaee, Masood

A new automated multi-level of fidelity Multi-Disciplinary Design Optimization (MDO) methodology has been developed at the MDO Laboratory of K.N. Toosi University of Technology. This paper explains a new design approach by formulation of developed disciplinary modules. A conceptual design for a small, solid-propellant launch vehicle was considered at two levels of fidelity structure. Low and medium level of fidelity disciplinary codes were developed and linked. Appropriate design and analysis codes were defined according to their effect on the conceptual design process. Simultaneous optimization of the launch vehicle was performed at the discipline level and system level. Propulsion, aerodynamics, structure and trajectory disciplinary codes were used. To reach the minimum launch weight, the Low LoF code first searches the whole design space to achieve the mission requirements. Then the medium LoF code receives the output of the low LoF and gives a value near the optimum launch weight with more details and higher fidelity.

Multi-level Discourse Analysis in a Physics Teaching Methods Course from the Psychological Perspective of Activity Theory

NASA Astrophysics Data System (ADS)

Vieira, Rodrigo Drumond; Kelly, Gregory J.

2014-11-01

In this paper, we present and apply a multi-level method for discourse analysis in science classrooms. This method is based on the structure of human activity (activity, actions, and operations) and it was applied to study a pre-service physics teacher methods course. We argue that such an approach, based on a cultural psychological perspective, affords opportunities for analysts to perform a theoretically based detailed analysis of discourse events. Along with the presentation of analysis, we show and discuss how the articulation of different levels offers interpretative criteria for analyzing instructional conversations. We synthesize the results into a model for a teacher's practice and discuss the implications and possibilities of this approach for the field of discourse analysis in science classrooms. Finally, we reflect on how the development of teachers' understanding of their activity structures can contribute to forms of progressive discourse of science education.

A multimodal image sensor system for identifying water stress in grapevines

NASA Astrophysics Data System (ADS)

Zhao, Yong; Zhang, Qin; Li, Minzan; Shao, Yongni; Zhou, Jianfeng; Sun, Hong

2012-11-01

Water stress is one of the most common limitations of fruit growth. Water is the most limiting resource for crop growth. In grapevines, as well as in other fruit crops, fruit quality benefits from a certain level of water deficit which facilitates to balance vegetative and reproductive growth and the flow of carbohydrates to reproductive structures. A multi-modal sensor system was designed to measure the reflectance signature of grape plant surfaces and identify different water stress levels in this paper. The multi-modal sensor system was equipped with one 3CCD camera (three channels in R, G, and IR). The multi-modal sensor can capture and analyze grape canopy from its reflectance features, and identify the different water stress levels. This research aims at solving the aforementioned problems. The core technology of this multi-modal sensor system could further be used as a decision support system that combines multi-modal sensory data to improve plant stress detection and identify the causes of stress. The images were taken by multi-modal sensor which could output images in spectral bands of near-infrared, green and red channel. Based on the analysis of the acquired images, color features based on color space and reflectance features based on image process method were calculated. The results showed that these parameters had the potential as water stress indicators. More experiments and analysis are needed to validate the conclusion.

Mobile, Multi-modal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia

DTIC Science & Technology

2015-10-01

eyes and image choroidal vessels/capillaries using CARS intravital microscopy Subtask 3: Measure oxy-hemoglobin levels in PBI test and control eyes...AWARD NUMBER: W81XWH-14-1-0537 TITLE: Mobile, Multi-modal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia...4. TITLE AND SUBTITLE Mobile, Multimodal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia 5a. CONTRACT NUMBER W81XWH

Multi-scale statistical analysis of coronal solar activity

DOE PAGES

Gamborino, Diana; del-Castillo-Negrete, Diego; Martinell, Julio J.

2016-07-08

Multi-filter images from the solar corona are used to obtain temperature maps that are analyzed using techniques based on proper orthogonal decomposition (POD) in order to extract dynamical and structural information at various scales. Exploring active regions before and after a solar flare and comparing them with quiet regions, we show that the multi-scale behavior presents distinct statistical properties for each case that can be used to characterize the level of activity in a region. Information about the nature of heat transport is also to be extracted from the analysis.

Dynamic analysis of space structures including elastic, multibody, and control behavior

NASA Technical Reports Server (NTRS)

Pinson, Larry; Soosaar, Keto

1989-01-01

The problem is to develop analysis methods, modeling stategies, and simulation tools to predict with assurance the on-orbit performance and integrity of large complex space structures that cannot be verified on the ground. The problem must incorporate large reliable structural models, multi-body flexible dynamics, multi-tier controller interaction, environmental models including 1g and atmosphere, various on-board disturbances, and linkage to mission-level performance codes. All areas are in serious need of work, but the weakest link is multi-body flexible dynamics.

Users matter : multi-agent systems model of high performance computing cluster users.

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

North, M. J.; Hood, C. S.; Decision and Information Sciences

2005-01-01

High performance computing clusters have been a critical resource for computational science for over a decade and have more recently become integral to large-scale industrial analysis. Despite their well-specified components, the aggregate behavior of clusters is poorly understood. The difficulties arise from complicated interactions between cluster components during operation. These interactions have been studied by many researchers, some of whom have identified the need for holistic multi-scale modeling that simultaneously includes network level, operating system level, process level, and user level behaviors. Each of these levels presents its own modeling challenges, but the user level is the most complex duemore » to the adaptability of human beings. In this vein, there are several major user modeling goals, namely descriptive modeling, predictive modeling and automated weakness discovery. This study shows how multi-agent techniques were used to simulate a large-scale computing cluster at each of these levels.« less

Regional variations in mortality rates in England and Wales: an analysis using multi-level modelling.

PubMed

Langford, I H; Bentham, G

1996-03-01

Mortality rates in England and Wales display a persistent regional pattern indicating generally poorer health in the North and West. Some of this is simply a reflection of regional differences in the extent of social deprivation which is known to exert a profound influence on health. Part of the pattern may also be the result of regional differences in urbanization which also affect mortality rates. However, there may be important regional differences over and above these compositional effects. This study attempts to establish the magnitude of such independent regional differences in mortality rates by using the techniques of multi-level modelling. Standardized mortality rates (SMRs) for males and females under 65 for 1989-91 in local authority districts are grouped into categories using the ACORN classification scheme. The Townsend Index is included as a measure of social deprivation. Using a cross-classified multi-level model, it is shown that region accounts for approximately four times more variation in SMRs than is explained by the ACORN classification. Analysis of diagnostic residuals show a clear North-South divide in excess mortality when both regional and socio-economic classification of districts are modelled simultaneously, a possibility allowed for by the use of a multi-level model.

A dynamic multi-level optimal design method with embedded finite-element modeling for power transformers

NASA Astrophysics Data System (ADS)

Zhang, Yunpeng; Ho, Siu-lau; Fu, Weinong

2018-05-01

This paper proposes a dynamic multi-level optimal design method for power transformer design optimization (TDO) problems. A response surface generated by second-order polynomial regression analysis is updated dynamically by adding more design points, which are selected by Shifted Hammersley Method (SHM) and calculated by finite-element method (FEM). The updating stops when the accuracy requirement is satisfied, and optimized solutions of the preliminary design are derived simultaneously. The optimal design level is modulated through changing the level of error tolerance. Based on the response surface of the preliminary design, a refined optimal design is added using multi-objective genetic algorithm (MOGA). The effectiveness of the proposed optimal design method is validated through a classic three-phase power TDO problem.

Analysis of a four lamp flash system for calibrating multi-junction solar cells under concentrated light

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

Schachtner, Michael, E-mail: michael.schachtner@ise.fraunhofer.de; Prado, Marcelo Loyo; Reichmuth, S. Kasimir

2015-09-28

It has been known for a long time that the precise characterization of multi-junction solar cells demands spectrally tunable solar simulators. The calibration of innovative multi-junction solar cells for CPV applications now requires tunable solar simulators which provide high irradiation levels. This paper describes the commissioning and calibration of a flash-based four-lamp simulator to be used for the measurement of multi-junction solar cells with up to four subcells under concentrated light.

Distributed Multi-Cell Resource Allocation with Price Based ICI Coordination in Downlink OFDMA Networks

NASA Astrophysics Data System (ADS)

Lv, Gangming; Zhu, Shihua; Hui, Hui

Multi-cell resource allocation under minimum rate request for each user in OFDMA networks is addressed in this paper. Based on Lagrange dual decomposition theory, the joint multi-cell resource allocation problem is decomposed and modeled as a limited-cooperative game, and a distributed multi-cell resource allocation algorithm is thus proposed. Analysis and simulation results show that, compared with non-cooperative iterative water-filling algorithm, the proposed algorithm can remarkably reduce the ICI level and improve overall system performances.

Institutional Disparities in the Cost Effectiveness of GCE A-Level Provision: A Multi-Level Approach.

ERIC Educational Resources Information Center

Fielding, A.

1995-01-01

Reanalyzes H. Thomas's 1980s data, which used teaching group as the unit of analysis and illuminated some institutional disparities in provision of General Certificate of Education (GCE) A-levels. Uses multilevel analysis to focus on individual students in a hierarchical framework. Among the study institutions, school sixth forms appear less…

A multi-level model accounting for the effects of JAK2-STAT5 signal modulation in erythropoiesis.

PubMed

Lai, Xin; Nikolov, Svetoslav; Wolkenhauer, Olaf; Vera, Julio

2009-08-01

We develop a multi-level model, using ordinary differential equations, based on quantitative experimental data, accounting for murine erythropoiesis. At the sub-cellular level, the model includes a description of the regulation of red blood cell differentiation through Epo-stimulated JAK2-STAT5 signalling activation, while at the cell population level the model describes the dynamics of (STAT5-mediated) red blood cell differentiation from their progenitors. Furthermore, the model includes equations depicting the hypoxia-mediated regulation of hormone erythropoietin blood levels. Take all together, the model constitutes a multi-level, feedback loop-regulated biological system, involving processes in different organs and at different organisational levels. We use our model to investigate the effect of deregulation in the proteins involved in the JAK2-STAT5 signalling pathway in red blood cells. Our analysis results suggest that down-regulation in any of the three signalling system components affects the hematocrit level in an individual considerably. In addition, our analysis predicts that exogenous Epo injection (an already existing treatment for several blood diseases) may compensate the effects of single down-regulation of Epo hormone level, STAT5 or EpoR/JAK2 expression level, and that it may be insufficient to counterpart a combined down-regulation of all the elements in the JAK2-STAT5 signalling cascade.

Concurrent Probabilistic Simulation of High Temperature Composite Structural Response

NASA Technical Reports Server (NTRS)

Abdi, Frank

1996-01-01

A computational structural/material analysis and design tool which would meet industry's future demand for expedience and reduced cost is presented. This unique software 'GENOA' is dedicated to parallel and high speed analysis to perform probabilistic evaluation of high temperature composite response of aerospace systems. The development is based on detailed integration and modification of diverse fields of specialized analysis techniques and mathematical models to combine their latest innovative capabilities into a commercially viable software package. The technique is specifically designed to exploit the availability of processors to perform computationally intense probabilistic analysis assessing uncertainties in structural reliability analysis and composite micromechanics. The primary objectives which were achieved in performing the development were: (1) Utilization of the power of parallel processing and static/dynamic load balancing optimization to make the complex simulation of structure, material and processing of high temperature composite affordable; (2) Computational integration and synchronization of probabilistic mathematics, structural/material mechanics and parallel computing; (3) Implementation of an innovative multi-level domain decomposition technique to identify the inherent parallelism, and increasing convergence rates through high- and low-level processor assignment; (4) Creating the framework for Portable Paralleled architecture for the machine independent Multi Instruction Multi Data, (MIMD), Single Instruction Multi Data (SIMD), hybrid and distributed workstation type of computers; and (5) Market evaluation. The results of Phase-2 effort provides a good basis for continuation and warrants Phase-3 government, and industry partnership.

Two-bit multi-level phase change random access memory with a triple phase change material stack structure

NASA Astrophysics Data System (ADS)

Gyanathan, Ashvini; Yeo, Yee-Chia

2012-11-01

This work demonstrates a novel two-bit multi-level device structure comprising three phase change material (PCM) layers, separated by SiN thermal barrier layers. This triple PCM stack consisted of (from bottom to top), Ge2Sb2Te5 (GST), an ultrathin SiN barrier, nitrogen-doped GST, another ultrathin SiN barrier, and Ag0.5In0.5Sb3Te6. The PCM layers can selectively amorphize to form 4 different resistance levels ("00," "01," "10," and "11") using respective voltage pulses. Electrical characterization was extensively performed on these devices. Thermal analysis was also done to understand the physics behind the phase changing characteristics of the two-bit memory devices. The melting and crystallization temperatures of the PCMs play important roles in the power consumption of the multi-level devices. The electrical resistivities and thermal conductivities of the PCMs and the SiN thermal barrier are also crucial factors contributing to the phase changing behaviour of the PCMs in the two-bit multi-level PCRAM device.

Multi-level characterization of balanced inhibitory-excitatory cortical neuron network derived from human pluripotent stem cells.

PubMed

Nadadhur, Aishwarya G; Emperador Melero, Javier; Meijer, Marieke; Schut, Desiree; Jacobs, Gerbren; Li, Ka Wan; Hjorth, J J Johannes; Meredith, Rhiannon M; Toonen, Ruud F; Van Kesteren, Ronald E; Smit, August B; Verhage, Matthijs; Heine, Vivi M

2017-01-01

Generation of neuronal cultures from induced pluripotent stem cells (hiPSCs) serve the studies of human brain disorders. However we lack neuronal networks with balanced excitatory-inhibitory activities, which are suitable for single cell analysis. We generated low-density networks of hPSC-derived GABAergic and glutamatergic cortical neurons. We used two different co-culture models with astrocytes. We show that these cultures have balanced excitatory-inhibitory synaptic identities using confocal microscopy, electrophysiological recordings, calcium imaging and mRNA analysis. These simple and robust protocols offer the opportunity for single-cell to multi-level analysis of patient hiPSC-derived cortical excitatory-inhibitory networks; thereby creating advanced tools to study disease mechanisms underlying neurodevelopmental disorders.

CubeSat mechanical design: creating low mass and durable structures

NASA Astrophysics Data System (ADS)

Fiedler, Gilbert; Straub, Jeremy

2017-05-01

This paper considers the mechanical design of a low-mass, low-cost spacecraft for use in a multi-satellite sensing constellation. For a multi-spacecraft mission, aggregated small mass and cost reductions can have significant impact. One approach to mass reduction is to make cuts into the structure, removing material. Stress analysis is used to determine the level of material reduction possible. Focus areas for this paper include determining areas to make cuts to ensure that a strong shape remains, while considering the comparative cost and skill level of each type of cut. Real-world results for a CubeSat and universally applicable analysis are presented.

FPGA-based multi-channel fluorescence lifetime analysis of Fourier multiplexed frequency-sweeping lifetime imaging

PubMed Central

Zhao, Ming; Li, Yu; Peng, Leilei

2014-01-01

We report a fast non-iterative lifetime data analysis method for the Fourier multiplexed frequency-sweeping confocal FLIM (Fm-FLIM) system [ Opt. Express22, 10221 ( 2014)24921725]. The new method, named R-method, allows fast multi-channel lifetime image analysis in the system’s FPGA data processing board. Experimental tests proved that the performance of the R-method is equivalent to that of single-exponential iterative fitting, and its sensitivity is well suited for time-lapse FLIM-FRET imaging of live cells, for example cyclic adenosine monophosphate (cAMP) level imaging with GFP-Epac-mCherry sensors. With the R-method and its FPGA implementation, multi-channel lifetime images can now be generated in real time on the multi-channel frequency-sweeping FLIM system, and live readout of FRET sensors can be performed during time-lapse imaging. PMID:25321778

Overweight and obesity in India: policy issues from an exploratory multi-level analysis.

PubMed

Siddiqui, Md Zakaria; Donato, Ronald

2016-06-01

This article analyses a nationally representative household dataset-the National Family Health Survey (NFHS-3) conducted in 2005 to 2006-to examine factors influencing the prevalence of overweight/obesity in India. The dataset was disaggregated into four sub-population groups-urban and rural females and males-and multi-level logit regression models were used to estimate the impact of particular covariates on the likelihood of overweight/obesity. The multi-level modelling approach aimed to identify individual and macro-level contextual factors influencing this health outcome. In contrast to most studies on low-income developing countries, the findings reveal that education for females beyond a particular level of educational attainment exhibits a negative relationship with the likelihood of overweight/obesity. This relationship was not observed for males. Muslim females and all Sikh sub-populations have a higher likelihood of overweight/obesity suggesting the importance of socio-cultural influences. The results also show that the relationship between wealth and the probability of overweight/obesity is stronger for males than females highlighting the differential impact of increasing socio-economic status on gender. Multi-level analysis reveals that states exerted an independent influence on the likelihood of overweight/obesity beyond individual-level covariates, reflecting the importance of spatially related contextual factors on overweight/obesity. While this study does not disentangle macro-level 'obesogenic' environmental factors from socio-cultural network influences, the results highlight the need to refrain from adopting a 'one size fits all' policy approach in addressing the overweight/obesity epidemic facing India. Instead, policy implementation requires a more nuanced and targeted approach to incorporate the growing recognition of socio-cultural and spatial contextual factors impacting on healthy behaviours. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Multi-level Bayesian safety analysis with unprocessed Automatic Vehicle Identification data for an urban expressway.

PubMed

Shi, Qi; Abdel-Aty, Mohamed; Yu, Rongjie

2016-03-01

In traffic safety studies, crash frequency modeling of total crashes is the cornerstone before proceeding to more detailed safety evaluation. The relationship between crash occurrence and factors such as traffic flow and roadway geometric characteristics has been extensively explored for a better understanding of crash mechanisms. In this study, a multi-level Bayesian framework has been developed in an effort to identify the crash contributing factors on an urban expressway in the Central Florida area. Two types of traffic data from the Automatic Vehicle Identification system, which are the processed data capped at speed limit and the unprocessed data retaining the original speed were incorporated in the analysis along with road geometric information. The model framework was proposed to account for the hierarchical data structure and the heterogeneity among the traffic and roadway geometric data. Multi-level and random parameters models were constructed and compared with the Negative Binomial model under the Bayesian inference framework. Results showed that the unprocessed traffic data was superior. Both multi-level models and random parameters models outperformed the Negative Binomial model and the models with random parameters achieved the best model fitting. The contributing factors identified imply that on the urban expressway lower speed and higher speed variation could significantly increase the crash likelihood. Other geometric factors were significant including auxiliary lanes and horizontal curvature. Copyright © 2015 Elsevier Ltd. All rights reserved.

Development of a Multi-Disciplinary Computing Environment (MDICE)

NASA Technical Reports Server (NTRS)

Kingsley, Gerry; Siegel, John M., Jr.; Harrand, Vincent J.; Lawrence, Charles; Luker, Joel J.

1999-01-01

The growing need for and importance of multi-component and multi-disciplinary engineering analysis has been understood for many years. For many applications, loose (or semi-implicit) coupling is optimal, and allows the use of various legacy codes without requiring major modifications. For this purpose, CFDRC and NASA LeRC have developed a computational environment to enable coupling between various flow analysis codes at several levels of fidelity. This has been referred to as the Visual Computing Environment (VCE), and is being successfully applied to the analysis of several aircraft engine components. Recently, CFDRC and AFRL/VAAC (WL) have extended the framework and scope of VCE to enable complex multi-disciplinary simulations. The chosen initial focus is on aeroelastic aircraft applications. The developed software is referred to as MDICE-AE, an extensible system suitable for integration of several engineering analysis disciplines. This paper describes the methodology, basic architecture, chosen software technologies, salient library modules, and the current status of and plans for MDICE. A fluid-structure interaction application is described in a separate companion paper.

A new multi-spectral feature level image fusion method for human interpretation

NASA Astrophysics Data System (ADS)

Leviner, Marom; Maltz, Masha

2009-03-01

Various different methods to perform multi-spectral image fusion have been suggested, mostly on the pixel level. However, the jury is still out on the benefits of a fused image compared to its source images. We present here a new multi-spectral image fusion method, multi-spectral segmentation fusion (MSSF), which uses a feature level processing paradigm. To test our method, we compared human observer performance in a three-task experiment using MSSF against two established methods: averaging and principle components analysis (PCA), and against its two source bands, visible and infrared. The three tasks that we studied were: (1) simple target detection, (2) spatial orientation, and (3) camouflaged target detection. MSSF proved superior to the other fusion methods in all three tests; MSSF also outperformed the source images in the spatial orientation and camouflaged target detection tasks. Based on these findings, current speculation about the circumstances in which multi-spectral image fusion in general and specific fusion methods in particular would be superior to using the original image sources can be further addressed.

Navigating a Divided Society: Educational Research Strategies for Post-Conflict Bosnia and Herzegovina

ERIC Educational Resources Information Center

Komatsu, Taro

2012-01-01

This article discusses methodological issues associated with education research in Bosnia and Herzegovina (BiH) and describes strategies taken to address them. Within a case study, mixed methods allowed the author to examine school leaders' perceptions multi-dimensionally. Multi-level analysis was essential to the understanding of policy-making…

A theoretical framework for negotiating the path of emergency management multi-agency coordination.

PubMed

Curnin, Steven; Owen, Christine; Paton, Douglas; Brooks, Benjamin

2015-03-01

Multi-agency coordination represents a significant challenge in emergency management. The need for liaison officers working in strategic level emergency operations centres to play organizational boundary spanning roles within multi-agency coordination arrangements that are enacted in complex and dynamic emergency response scenarios creates significant research and practical challenges. The aim of the paper is to address a gap in the literature regarding the concept of multi-agency coordination from a human-environment interaction perspective. We present a theoretical framework for facilitating multi-agency coordination in emergency management that is grounded in human factors and ergonomics using the methodology of core-task analysis. As a result we believe the framework will enable liaison officers to cope more efficiently within the work domain. In addition, we provide suggestions for extending the theory of core-task analysis to an alternate high reliability environment. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Implementation of Finite Volume based Navier Stokes Algorithm Within General Purpose Flow Network Code

NASA Technical Reports Server (NTRS)

Schallhorn, Paul; Majumdar, Alok

2012-01-01

This paper describes a finite volume based numerical algorithm that allows multi-dimensional computation of fluid flow within a system level network flow analysis. There are several thermo-fluid engineering problems where higher fidelity solutions are needed that are not within the capacity of system level codes. The proposed algorithm will allow NASA's Generalized Fluid System Simulation Program (GFSSP) to perform multi-dimensional flow calculation within the framework of GFSSP s typical system level flow network consisting of fluid nodes and branches. The paper presents several classical two-dimensional fluid dynamics problems that have been solved by GFSSP's multi-dimensional flow solver. The numerical solutions are compared with the analytical and benchmark solution of Poiseulle, Couette and flow in a driven cavity.

The Role of Thermodynamic Processes in the Evolution of Single and Multi-banding within Winter Storms

NASA Astrophysics Data System (ADS)

Ganetis, Sara Anne

Mesoscale precipitation bands within Northeast U.S. (NEUS) winter storms result in heterogeneous spatial and temporal snowfall. Several studies have provided analysis of snowbands focusing on larger, meso-beta scale bands with lengths (L) > 200 km known as single bands. NEUS winter storms can also exhibit multiple bands with meso-beta scale (L < 200 km) and similar spatial orientation and when ≥ 3 occur are termed multi-bands; however, the genesis and evolution of multi-bands is less well understood. Unlike single bands, there is no multi-bands climatological study. In addition, there has been little detailed thermodynamic analysis of snowbands. This dissertation utilizes radar observations, reanalyses, and high-resolution model simulations to explore the thermodynamic evolution of single and multi-bands. Bands are identified within 20 cool season (October-April) NEUS storms. The 110-case dataset was classified using a combination of automated and manual methods into: single band only (SINGLE), multi-bands only (MULTI), both single and multi-bands (BOTH), and non-banded (NONE). Multi-bands occur with the presence of a single band in 55.4% of times used in this study, without the presence of a single band 18.1% of the time, and precipitation exhibits no banded characteristics 23.8% of the time. Most MULTI events occur in the northeast quadrant of a developing cyclone poleward of weak-midlevel forcing along a warm front, whereas multi-bands associated with BOTH events mostly occur in the northwest quadrant of mature cyclones associated with strong mid-level frontogenesis and conditional symmetric instability. The non-banded precipitation associated with NONE events occur in the eastern quadrants of developing and mature cyclones lacking mid-level forcing to concentrate the precipitation into bands. A high-resolution mesoscale model is used to explore the evolution of single and multi-bands based on two case studies, one of a single band and one of multi-bands. The multi-bands form in response to intermittent mid-level frontogenetical forcing in a conditionally unstable environment. The bands within their genesis location southeast of the single band move northwest towards the single band by 700-hPa steering flow. This allows for the formation of new multi-bands within the genesis region, unlike the single band that remains fixed to a 700-hPa frontogenesis maximum. Latent heating within the band is shown to increase the intensity and duration of single and multi-bands through decreased geopotential height below the heating maximum that leads to increased convergence within the band.

Impact of copula directional specification on multi-trial evaluation of surrogate endpoints

PubMed Central

Renfro, Lindsay A.; Shang, Hongwei; Sargent, Daniel J.

2014-01-01

Evaluation of surrogate endpoints using patient-level data from multiple trials is the gold standard, where multi-trial copula models are used to quantify both patient-level and trial-level surrogacy. While limited consideration has been given in the literature to copula choice (e.g., Clayton), no prior consideration has been given to direction of implementation (via survival versus distribution functions). We demonstrate that evenwith the “correct” copula family, directional misspecification leads to biased estimates of patient-level and trial-level surrogacy. We illustrate with a simulation study and a re-analysis of disease-free survival as a surrogate for overall survival in early stage colon cancer. PMID:24905465

Automated daily quality control analysis for mammography in a multi-unit imaging center.

PubMed

Sundell, Veli-Matti; Mäkelä, Teemu; Meaney, Alexander; Kaasalainen, Touko; Savolainen, Sauli

2018-01-01

Background The high requirements for mammography image quality necessitate a systematic quality assurance process. Digital imaging allows automation of the image quality analysis, which can potentially improve repeatability and objectivity compared to a visual evaluation made by the users. Purpose To develop an automatic image quality analysis software for daily mammography quality control in a multi-unit imaging center. Material and Methods An automated image quality analysis software using the discrete wavelet transform and multiresolution analysis was developed for the American College of Radiology accreditation phantom. The software was validated by analyzing 60 randomly selected phantom images from six mammography systems and 20 phantom images with different dose levels from one mammography system. The results were compared to a visual analysis made by four reviewers. Additionally, long-term image quality trends of a full-field digital mammography system and a computed radiography mammography system were investigated. Results The automated software produced feature detection levels comparable to visual analysis. The agreement was good in the case of fibers, while the software detected somewhat more microcalcifications and characteristic masses. Long-term follow-up via a quality assurance web portal demonstrated the feasibility of using the software for monitoring the performance of mammography systems in a multi-unit imaging center. Conclusion Automated image quality analysis enables monitoring the performance of digital mammography systems in an efficient, centralized manner.

Multi-objective optimization in systematic conservation planning and the representation of genetic variability among populations.

PubMed

Schlottfeldt, S; Walter, M E M T; Carvalho, A C P L F; Soares, T N; Telles, M P C; Loyola, R D; Diniz-Filho, J A F

2015-06-18

Biodiversity crises have led scientists to develop strategies for achieving conservation goals. The underlying principle of these strategies lies in systematic conservation planning (SCP), in which there are at least 2 conflicting objectives, making it a good candidate for multi-objective optimization. Although SCP is typically applied at the species level (or hierarchically higher), it can be used at lower hierarchical levels, such as using alleles as basic units for analysis, for conservation genetics. Here, we propose a method of SCP using a multi-objective approach. We used non-dominated sorting genetic algorithm II in order to identify the smallest set of local populations of Dipteryx alata (baru) (a Brazilian Cerrado species) for conservation, representing the known genetic diversity and using allele frequency information associated with heterozygosity and Hardy-Weinberg equilibrium. We worked in 3 variations for the problem. First, we reproduced a previous experiment, but using a multi-objective approach. We found that the smallest set of populations needed to represent all alleles under study was 7, corroborating the results of the previous study, but with more distinct solutions. In the 2nd and 3rd variations, we performed simultaneous optimization of 4 and 5 objectives, respectively. We found similar but refined results for 7 populations, and a larger portfolio considering intra-specific diversity and persistence with populations ranging from 8-22. This is the first study to apply multi-objective algorithms to an SCP problem using alleles at the population level as basic units for analysis.

Priority setting for the prevention and control of cardiovascular diseases: multi-criteria decision analysis in four eastern Mediterranean countries.

PubMed

Ghandour, Rula; Shoaibi, Azza; Khatib, Rana; Abu Rmeileh, Niveen; Unal, Belgin; Sözmen, Kaan; Kılıç, Bülent; Fouad, Fouad; Al Ali, Radwan; Ben Romdhane, Habiba; Aissi, Wafa; Ahmad, Balsam; Capewell, Simon; Critchley, Julia; Husseini, Abdullatif

2015-01-01

To explore the feasibility of using a simple multi-criteria decision analysis method with policy makers/key stakeholders to prioritize cardiovascular disease (CVD) policies in four Mediterranean countries: Palestine, Syria, Tunisia and Turkey. A simple multi-criteria decision analysis (MCDA) method was piloted. A mixed methods study was used to identify a preliminary list of policy options in each country. These policies were rated by different policymakers/stakeholders against pre-identified criteria to generate a priority score for each policy and then rank the policies. Twenty-five different policies were rated in the four countries to create a country-specific list of CVD prevention and control policies. The response rate was 100% in each country. The top policies were mostly population level interventions and health systems' level policies. Successful collaboration between policy makers/stakeholders and researchers was established in this small pilot study. MCDA appeared to be feasible and effective. Future applications should aim to engage a larger, representative sample of policy makers, especially from outside the health sector. Weighting the selected criteria might also be assessed.

Multi-Disciplinary, Multi-Fidelity Discrete Data Transfer Using Degenerate Geometry Forms

NASA Technical Reports Server (NTRS)

Olson, Erik D.

2016-01-01

In a typical multi-fidelity design process, different levels of geometric abstraction are used for different analysis methods, and transitioning from one phase of design to the next often requires a complete re-creation of the geometry. To maintain consistency between lower-order and higher-order analysis results, Vehicle Sketch Pad (OpenVSP) recently introduced the ability to generate and export several degenerate forms of the geometry, representing the type of abstraction required to perform low- to medium-order analysis for a range of aeronautical disciplines. In this research, the functionality of these degenerate models was extended, so that in addition to serving as repositories for the geometric information that is required as input to an analysis, the degenerate models can also store the results of that analysis mapped back onto the geometric nodes. At the same time, the results are also mapped indirectly onto the nodes of lower-order degenerate models using a process called aggregation, and onto higher-order models using a process called disaggregation. The mapped analysis results are available for use by any subsequent analysis in an integrated design and analysis process. A simple multi-fidelity analysis process for a single-aisle subsonic transport aircraft is used as an example case to demonstrate the value of the approach.

Grounding a new information technology implementation framework in behavioral science: a systematic analysis of the literature on IT use.

PubMed

Kukafka, Rita; Johnson, Stephen B; Linfante, Allison; Allegrante, John P

2003-06-01

Many interventions to improve the success of information technology (IT) implementations are grounded in behavioral science, using theories, and models to identify conditions and determinants of successful use. However, each model in the IT literature has evolved to address specific theoretical problems of particular disciplinary concerns, and each model has been tested and has evolved using, in most cases, a more or less restricted set of IT implementation procedures. Functionally, this limits the perspective for taking into account the multiple factors at the individual, group, and organizational levels that influence use behavior. While a rich body of literature has emerged, employing prominent models such as the Technology Adoption Model, Social-Cognitive Theory, and Diffusion of Innovation Theory, the complexity of defining a suitable multi-level intervention has largely been overlooked. A gap exists between the implementation of IT and the integration of theories and models that can be utilized to develop multi-level approaches to identify factors that impede usage behavior. We present a novel framework that is intended to guide synthesis of more than one theoretical perspective for the purpose of planning multi-level interventions to enhance IT use. This integrative framework is adapted from PRECEDE/PROCEDE, a conceptual framework used by health planners in hundreds of published studies to direct interventions that account for the multiple determinants of behavior. Since we claim that the literature on IT use behavior does not now include a multi-level approach, we undertook a systematic literature analysis to confirm this assertion. Our framework facilitated organizing this literature synthesis and our analysis was aimed at determining if the IT implementation approaches in the published literature were characterized by an approach that considered at least two levels of IT usage determinants. We found that while 61% of studies mentioned or referred to theory, none considered two or more levels. In other words, although the researchers employ behavioral theory, they omit two fundamental propositions: (1) IT usage is influenced by multiple factors and (2) interventions must be multi-dimensional. Our literature synthesis may provide additional insight into the reason for high failure rates associated with underutilized systems, and underscores the need to move beyond the current dominant approach that employs a single model to guide IT implementation plans that aim to address factors associated with IT acceptance and subsequent positive use behavior.

Trans-Ethnic Meta-Analysis Identifies Common and Rare Variants Associated with Hepatocyte Growth Factor Levels in the Multi-Ethnic Study of Atherosclerosis (MESA)

PubMed Central

Larson, Nicholas B.; Berardi, Cecilia; Decker, Paul A.; Wassel, Christina L.; Kirsch, Phillip S.; Pankow, James S.; Sale, Michele M.; de Andrade, Mariza; Sicotte, Hugues; Tang, Weihong; Hanson, Naomi Q.; Tsai, Michael Y.; Taylor, Kent D.; Bielinski, Suzette J.

2015-01-01

Summary Hepatocyte growth factor (HGF) is a mesenchyme-derived pleiotropic factor that regulates cell growth, motility, mitogenesis, and morphogenesis in a variety of cells, and increased serum levels of HGF have been linked to a number of clinical and subclinical cardiovascular disease phenotypes. However, little is currently known regarding what genetic factors influence HGF levels, despite evidence of substantial genetic contributions to HGF variation. Based upon ethnicity-stratified single-variant association analysis and trans-ethnic meta-analysis of 6201 participants of the Multi-Ethnic Study of Atherosclerosis (MESA), we discovered five statistically significant common and low-frequency variants: HGF missense polymorphism rs5745687 (p.E299K) as well as four variants (rs16844364, rs4690098, rs114303452, rs3748034) within or in proximity to HGFAC. We also identified two significant ethnicity-specific gene-level associations (A1BG in African Americans; FASN in Chinese Americans) based upon low-frequency/rare variants, while meta-analysis of gene-level results identified a significant association for HGFAC. However, identified single-variant associations explained modest proportions of the total trait variation and were not significantly associated with coronary artery calcium or coronary heart disease. Our findings indicate genetic factors influencing circulating HGF levels may be complex and ethnically diverse. PMID:25998175

Comparative Genomics Study of Multi-Drug-Resistance Mechanisms in the Antibiotic-Resistant Streptococcus suis R61 Strain

PubMed Central

Zhang, Anding; Wu, Jiayan; Chen, Bo; Hua, Yafeng; Yu, Jun; Chen, Huanchun; Xiao, Jingfa; Jin, Meilin

2011-01-01

Background Streptococcus suis infections are a serious problem for both humans and pigs worldwide. The emergence and increasing prevalence of antibiotic-resistant S. suis strains pose significant clinical and societal challenges. Results In our study, we sequenced one multi-drug-resistant S. suis strain, R61, and one S. suis strain, A7, which is fully sensitive to all tested antibiotics. Comparative genomic analysis revealed that the R61 strain is phylogenetically distinct from other S. suis strains, and the genome of R61 exhibits extreme levels of evolutionary plasticity with high levels of gene gain and loss. Our results indicate that the multi-drug-resistant strain R61 has evolved three main categories of resistance. Conclusions Comparative genomic analysis of S. suis strains with diverse drug-resistant phenotypes provided evidence that horizontal gene transfer is an important evolutionary force in shaping the genome of multi-drug-resistant strain R61. In this study, we discovered novel and previously unexamined mutations that are strong candidates for conferring drug resistance. We believe that these mutations will provide crucial clues for designing new drugs against this pathogen. In addition, our work provides a clear demonstration that the use of drugs has driven the emergence of the multi-drug-resistant strain R61. PMID:21966396

Comparative genomics study of multi-drug-resistance mechanisms in the antibiotic-resistant Streptococcus suis R61 strain.

PubMed

Hu, Pan; Yang, Ming; Zhang, Anding; Wu, Jiayan; Chen, Bo; Hua, Yafeng; Yu, Jun; Chen, Huanchun; Xiao, Jingfa; Jin, Meilin

2011-01-01

Streptococcus suis infections are a serious problem for both humans and pigs worldwide. The emergence and increasing prevalence of antibiotic-resistant S. suis strains pose significant clinical and societal challenges. In our study, we sequenced one multi-drug-resistant S. suis strain, R61, and one S. suis strain, A7, which is fully sensitive to all tested antibiotics. Comparative genomic analysis revealed that the R61 strain is phylogenetically distinct from other S. suis strains, and the genome of R61 exhibits extreme levels of evolutionary plasticity with high levels of gene gain and loss. Our results indicate that the multi-drug-resistant strain R61 has evolved three main categories of resistance. Comparative genomic analysis of S. suis strains with diverse drug-resistant phenotypes provided evidence that horizontal gene transfer is an important evolutionary force in shaping the genome of multi-drug-resistant strain R61. In this study, we discovered novel and previously unexamined mutations that are strong candidates for conferring drug resistance. We believe that these mutations will provide crucial clues for designing new drugs against this pathogen. In addition, our work provides a clear demonstration that the use of drugs has driven the emergence of the multi-drug-resistant strain R61.

Multi-scale modelling of elastic moduli of trabecular bone

PubMed Central

Hamed, Elham; Jasiuk, Iwona; Yoo, Andrew; Lee, YikHan; Liszka, Tadeusz

2012-01-01

We model trabecular bone as a nanocomposite material with hierarchical structure and predict its elastic properties at different structural scales. The analysis involves a bottom-up multi-scale approach, starting with nanoscale (mineralized collagen fibril) and moving up the scales to sub-microscale (single lamella), microscale (single trabecula) and mesoscale (trabecular bone) levels. Continuum micromechanics methods, composite materials laminate theory and finite-element methods are used in the analysis. Good agreement is found between theoretical and experimental results. PMID:22279160

Control electronics for a multi-laser/multi-detector scanning system

NASA Technical Reports Server (NTRS)

Kennedy, W.

1980-01-01

The Mars Rover Laser Scanning system uses a precision laser pointing mechanism, a photodetector array, and the concept of triangulation to perform three dimensional scene analysis. The system is used for real time terrain sensing and vision. The Multi-Laser/Multi-Detector laser scanning system is controlled by a digital device called the ML/MD controller. A next generation laser scanning system, based on the Level 2 controller, is microprocessor based. The new controller capabilities far exceed those of the ML/MD device. The first draft circuit details and general software structure are presented.

Center-Within-Trial Versus Trial-Level Evaluation of Surrogate Endpoints.

PubMed

Renfro, Lindsay A; Shi, Qian; Xue, Yuan; Li, Junlong; Shang, Hongwei; Sargent, Daniel J

2014-10-01

Evaluation of candidate surrogate endpoints using individual patient data from multiple clinical trials is considered the gold standard approach to validate surrogates at both patient and trial levels. However, this approach assumes the availability of patient-level data from a relatively large collection of similar trials, which may not be possible to achieve for a given disease application. One common solution to the problem of too few similar trials involves performing trial-level surrogacy analyses on trial sub-units (e.g., centers within trials), thereby artificially increasing the trial-level sample size for feasibility of the multi-trial analysis. To date, the practical impact of treating trial sub-units (centers) identically to trials in multi-trial surrogacy analyses remains unexplored, and conditions under which this ad hoc solution may in fact be reasonable have not been identified. We perform a simulation study to identify such conditions, and demonstrate practical implications using a multi-trial dataset of patients with early stage colon cancer.

Center-Within-Trial Versus Trial-Level Evaluation of Surrogate Endpoints

PubMed Central

Renfro, Lindsay A.; Shi, Qian; Xue, Yuan; Li, Junlong; Shang, Hongwei; Sargent, Daniel J.

2014-01-01

Evaluation of candidate surrogate endpoints using individual patient data from multiple clinical trials is considered the gold standard approach to validate surrogates at both patient and trial levels. However, this approach assumes the availability of patient-level data from a relatively large collection of similar trials, which may not be possible to achieve for a given disease application. One common solution to the problem of too few similar trials involves performing trial-level surrogacy analyses on trial sub-units (e.g., centers within trials), thereby artificially increasing the trial-level sample size for feasibility of the multi-trial analysis. To date, the practical impact of treating trial sub-units (centers) identically to trials in multi-trial surrogacy analyses remains unexplored, and conditions under which this ad hoc solution may in fact be reasonable have not been identified. We perform a simulation study to identify such conditions, and demonstrate practical implications using a multi-trial dataset of patients with early stage colon cancer. PMID:25061255

mlCAF: Multi-Level Cross-Domain Semantic Context Fusioning for Behavior Identification.

PubMed

Razzaq, Muhammad Asif; Villalonga, Claudia; Lee, Sungyoung; Akhtar, Usman; Ali, Maqbool; Kim, Eun-Soo; Khattak, Asad Masood; Seung, Hyonwoo; Hur, Taeho; Bang, Jaehun; Kim, Dohyeong; Ali Khan, Wajahat

2017-10-24

The emerging research on automatic identification of user's contexts from the cross-domain environment in ubiquitous and pervasive computing systems has proved to be successful. Monitoring the diversified user's contexts and behaviors can help in controlling lifestyle associated to chronic diseases using context-aware applications. However, availability of cross-domain heterogeneous contexts provides a challenging opportunity for their fusion to obtain abstract information for further analysis. This work demonstrates extension of our previous work from a single domain (i.e., physical activity) to multiple domains (physical activity, nutrition and clinical) for context-awareness. We propose multi-level Context-aware Framework (mlCAF), which fuses the multi-level cross-domain contexts in order to arbitrate richer behavioral contexts. This work explicitly focuses on key challenges linked to multi-level context modeling, reasoning and fusioning based on the mlCAF open-source ontology. More specifically, it addresses the interpretation of contexts from three different domains, their fusioning conforming to richer contextual information. This paper contributes in terms of ontology evolution with additional domains, context definitions, rules and inclusion of semantic queries. For the framework evaluation, multi-level cross-domain contexts collected from 20 users were used to ascertain abstract contexts, which served as basis for behavior modeling and lifestyle identification. The experimental results indicate a context recognition average accuracy of around 92.65% for the collected cross-domain contexts.

mlCAF: Multi-Level Cross-Domain Semantic Context Fusioning for Behavior Identification

PubMed Central

Villalonga, Claudia; Lee, Sungyoung; Akhtar, Usman; Ali, Maqbool; Kim, Eun-Soo; Khattak, Asad Masood; Seung, Hyonwoo; Hur, Taeho; Kim, Dohyeong; Ali Khan, Wajahat

2017-01-01

The emerging research on automatic identification of user’s contexts from the cross-domain environment in ubiquitous and pervasive computing systems has proved to be successful. Monitoring the diversified user’s contexts and behaviors can help in controlling lifestyle associated to chronic diseases using context-aware applications. However, availability of cross-domain heterogeneous contexts provides a challenging opportunity for their fusion to obtain abstract information for further analysis. This work demonstrates extension of our previous work from a single domain (i.e., physical activity) to multiple domains (physical activity, nutrition and clinical) for context-awareness. We propose multi-level Context-aware Framework (mlCAF), which fuses the multi-level cross-domain contexts in order to arbitrate richer behavioral contexts. This work explicitly focuses on key challenges linked to multi-level context modeling, reasoning and fusioning based on the mlCAF open-source ontology. More specifically, it addresses the interpretation of contexts from three different domains, their fusioning conforming to richer contextual information. This paper contributes in terms of ontology evolution with additional domains, context definitions, rules and inclusion of semantic queries. For the framework evaluation, multi-level cross-domain contexts collected from 20 users were used to ascertain abstract contexts, which served as basis for behavior modeling and lifestyle identification. The experimental results indicate a context recognition average accuracy of around 92.65% for the collected cross-domain contexts. PMID:29064459

Multi-resolutional shape features via non-Euclidean wavelets: Applications to statistical analysis of cortical thickness

PubMed Central

Kim, Won Hwa; Singh, Vikas; Chung, Moo K.; Hinrichs, Chris; Pachauri, Deepti; Okonkwo, Ozioma C.; Johnson, Sterling C.

2014-01-01

Statistical analysis on arbitrary surface meshes such as the cortical surface is an important approach to understanding brain diseases such as Alzheimer’s disease (AD). Surface analysis may be able to identify specific cortical patterns that relate to certain disease characteristics or exhibit differences between groups. Our goal in this paper is to make group analysis of signals on surfaces more sensitive. To do this, we derive multi-scale shape descriptors that characterize the signal around each mesh vertex, i.e., its local context, at varying levels of resolution. In order to define such a shape descriptor, we make use of recent results from harmonic analysis that extend traditional continuous wavelet theory from the Euclidean to a non-Euclidean setting (i.e., a graph, mesh or network). Using this descriptor, we conduct experiments on two different datasets, the Alzheimer’s Disease NeuroImaging Initiative (ADNI) data and images acquired at the Wisconsin Alzheimer’s Disease Research Center (W-ADRC), focusing on individuals labeled as having Alzheimer’s disease (AD), mild cognitive impairment (MCI) and healthy controls. In particular, we contrast traditional univariate methods with our multi-resolution approach which show increased sensitivity and improved statistical power to detect a group-level effects. We also provide an open source implementation. PMID:24614060

Analysis Commons, A Team Approach to Discovery in a Big-Data Environment for Genetic Epidemiology

PubMed Central

Brody, Jennifer A.; Morrison, Alanna C.; Bis, Joshua C.; O'Connell, Jeffrey R.; Brown, Michael R.; Huffman, Jennifer E.; Ames, Darren C.; Carroll, Andrew; Conomos, Matthew P.; Gabriel, Stacey; Gibbs, Richard A.; Gogarten, Stephanie M.; Gupta, Namrata; Jaquish, Cashell E.; Johnson, Andrew D.; Lewis, Joshua P.; Liu, Xiaoming; Manning, Alisa K.; Papanicolaou, George J.; Pitsillides, Achilleas N.; Rice, Kenneth M.; Salerno, William; Sitlani, Colleen M.; Smith, Nicholas L.; Heckbert, Susan R.; Laurie, Cathy C.; Mitchell, Braxton D.; Vasan, Ramachandran S.; Rich, Stephen S.; Rotter, Jerome I.; Wilson, James G.; Boerwinkle, Eric; Psaty, Bruce M.; Cupples, L. Adrienne

2017-01-01

Summary paragraph The exploding volume of whole-genome sequence (WGS) and multi-omics data requires new approaches for analysis. As one solution, we have created a cloud-based Analysis Commons, which brings together genotype and phenotype data from multiple studies in a setting that is accessible by multiple investigators. This framework addresses many of the challenges of multi-center WGS analyses, including data sharing mechanisms, phenotype harmonization, integrated multi-omics analyses, annotation, and computational flexibility. In this setting, the computational pipeline facilitates a sequence-to-discovery analysis workflow illustrated here by an analysis of plasma fibrinogen levels in 3996 individuals from the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) WGS program. The Analysis Commons represents a novel model for transforming WGS resources from a massive quantity of phenotypic and genomic data into knowledge of the determinants of health and disease risk in diverse human populations. PMID:29074945

Multi-level assessment protocol (MAP) for adoption in multi-site clinical trials

PubMed Central

Guydish, J.; Manser, S.T.; Jessup, M.; Tajima, B.; Sears, C.; Montini, T.

2010-01-01

The National Institute on Drug Abuse (NIDA) Clinical Trials Network (CTN) is intended to test promising drug abuse treatment models in multi-site clinical trials, and to support adoption of new interventions into clinical practice. Using qualitative research methods we asked: How might the technology of multi-site clinical trials be modified to better support adoption of tested interventions? A total of 42 participants, representing 8 organizational levels ranging from clinic staff to clinical trial leaders, were interviewed about their role in the clinical trial, its interactions with clinics, and intervention adoption. Among eight clinics participating in the clinical trial, we found adoption of the tested intervention in one clinic only. In analysis of interview data we identified four conceptual themes which are likely to affect adoption and may be informative in future multi-site clinical trials. We offer the conclusion that planning for adoption in the early stages of protocol development will better serve the aim of integrating new interventions into practice. PMID:20890376

An empirical study of statistical properties of variance partition coefficients for multi-level logistic regression models

USGS Publications Warehouse

Li, Ji; Gray, B.R.; Bates, D.M.

2008-01-01

Partitioning the variance of a response by design levels is challenging for binomial and other discrete outcomes. Goldstein (2003) proposed four definitions for variance partitioning coefficients (VPC) under a two-level logistic regression model. In this study, we explicitly derived formulae for multi-level logistic regression model and subsequently studied the distributional properties of the calculated VPCs. Using simulations and a vegetation dataset, we demonstrated associations between different VPC definitions, the importance of methods for estimating VPCs (by comparing VPC obtained using Laplace and penalized quasilikehood methods), and bivariate dependence between VPCs calculated at different levels. Such an empirical study lends an immediate support to wider applications of VPC in scientific data analysis.

Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study

PubMed Central

2010-01-01

Background Gene silencing using exogenous small interfering RNAs (siRNAs) is now a widespread molecular tool for gene functional study and new-drug target identification. The key mechanism in this technique is to design efficient siRNAs that incorporated into the RNA-induced silencing complexes (RISC) to bind and interact with the mRNA targets to repress their translations to proteins. Although considerable progress has been made in the computational analysis of siRNA binding efficacy, few joint analysis of different RNAi experiments conducted under different experimental scenarios has been done in research so far, while the joint analysis is an important issue in cross-platform siRNA efficacy prediction. A collective analysis of RNAi mechanisms for different datasets and experimental conditions can often provide new clues on the design of potent siRNAs. Results An elegant multi-task learning paradigm for cross-platform siRNA efficacy prediction is proposed. Experimental studies were performed on a large dataset of siRNA sequences which encompass several RNAi experiments recently conducted by different research groups. By using our multi-task learning method, the synergy among different experiments is exploited and an efficient multi-task predictor for siRNA efficacy prediction is obtained. The 19 most popular biological features for siRNA according to their jointly importance in multi-task learning were ranked. Furthermore, the hypothesis is validated out that the siRNA binding efficacy on different messenger RNAs(mRNAs) have different conditional distribution, thus the multi-task learning can be conducted by viewing tasks at an "mRNA"-level rather than at the "experiment"-level. Such distribution diversity derived from siRNAs bound to different mRNAs help indicate that the properties of target mRNA have important implications on the siRNA binding efficacy. Conclusions The knowledge gained from our study provides useful insights on how to analyze various cross-platform RNAi data for uncovering of their complex mechanism. PMID:20380733

Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study.

PubMed

Liu, Qi; Xu, Qian; Zheng, Vincent W; Xue, Hong; Cao, Zhiwei; Yang, Qiang

2010-04-10

Gene silencing using exogenous small interfering RNAs (siRNAs) is now a widespread molecular tool for gene functional study and new-drug target identification. The key mechanism in this technique is to design efficient siRNAs that incorporated into the RNA-induced silencing complexes (RISC) to bind and interact with the mRNA targets to repress their translations to proteins. Although considerable progress has been made in the computational analysis of siRNA binding efficacy, few joint analysis of different RNAi experiments conducted under different experimental scenarios has been done in research so far, while the joint analysis is an important issue in cross-platform siRNA efficacy prediction. A collective analysis of RNAi mechanisms for different datasets and experimental conditions can often provide new clues on the design of potent siRNAs. An elegant multi-task learning paradigm for cross-platform siRNA efficacy prediction is proposed. Experimental studies were performed on a large dataset of siRNA sequences which encompass several RNAi experiments recently conducted by different research groups. By using our multi-task learning method, the synergy among different experiments is exploited and an efficient multi-task predictor for siRNA efficacy prediction is obtained. The 19 most popular biological features for siRNA according to their jointly importance in multi-task learning were ranked. Furthermore, the hypothesis is validated out that the siRNA binding efficacy on different messenger RNAs(mRNAs) have different conditional distribution, thus the multi-task learning can be conducted by viewing tasks at an "mRNA"-level rather than at the "experiment"-level. Such distribution diversity derived from siRNAs bound to different mRNAs help indicate that the properties of target mRNA have important implications on the siRNA binding efficacy. The knowledge gained from our study provides useful insights on how to analyze various cross-platform RNAi data for uncovering of their complex mechanism.

The Influence of Game Design on the Collaborative Problem Solving Process: A Cross-Case Study of Multi-Player Collaborative Gameplay Analysis

ERIC Educational Resources Information Center

Yildirim, Nilay

2013-01-01

This cross-case study examines the relationships between game design attributes and collaborative problem solving process in the context of multi-player video games. The following game design attributes: sensory stimuli elements, level of challenge, and presentation of game goals and rules were examined to determine their influence on game…

Animal movement data: GPS telemetry, autocorrelation and the need for path-level analysis [chapter 7

Treesearch

Samuel A. Cushman

2010-01-01

In the previous chapter we presented the idea of a multi-layer, multi-scale, spatially referenced data-cube as the foundation for monitoring and for implementing flexible modeling of ecological pattern-process relationships in particulate, in context and to integrate these across large spatial extents at the grain of the strongest linkage between response and driving...

Measuring sustainable development using a multi-criteria model: a case study.

PubMed

Boggia, Antonio; Cortina, Carla

2010-11-01

This paper shows how Multi-criteria Decision Analysis (MCDA) can help in a complex process such as the assessment of the level of sustainability of a certain area. The paper presents the results of a study in which a model for measuring sustainability was implemented to better aid public policy decisions regarding sustainability. In order to assess sustainability in specific areas, a methodological approach based on multi-criteria analysis has been developed. The aim is to rank areas in order to understand the specific technical and/or financial support that they need to develop sustainable growth. The case study presented is an assessment of the level of sustainability in different areas of an Italian Region using the MCDA approach. Our results show that MCDA is a proper approach for sustainability assessment. The results are easy to understand and the evaluation path is clear and transparent. This is what decision makers need for having support to their decisions. The multi-criteria model for evaluation has been developed respecting the sustainable development economic theory, so that final results can have a clear meaning in terms of sustainability. Copyright 2010 Elsevier Ltd. All rights reserved.

Multispectral image fusion for target detection

NASA Astrophysics Data System (ADS)

Leviner, Marom; Maltz, Masha

2009-09-01

Various different methods to perform multi-spectral image fusion have been suggested, mostly on the pixel level. However, the jury is still out on the benefits of a fused image compared to its source images. We present here a new multi-spectral image fusion method, multi-spectral segmentation fusion (MSSF), which uses a feature level processing paradigm. To test our method, we compared human observer performance in an experiment using MSSF against two established methods: Averaging and Principle Components Analysis (PCA), and against its two source bands, visible and infrared. The task that we studied was: target detection in the cluttered environment. MSSF proved superior to the other fusion methods. Based on these findings, current speculation about the circumstances in which multi-spectral image fusion in general and specific fusion methods in particular would be superior to using the original image sources can be further addressed.

Using Course-Level Factors as Predictors of Online Course Outcomes: A Multi-Level Analysis at a US Urban Community College

ERIC Educational Resources Information Center

Wladis, Claire; Conway, Katherine; Hachey, Alyse C.

2017-01-01

Research has documented lower retention rates in online versus face-to-face courses. However, little research has focused on the impact of course-level characteristics (e.g. elective versus distributional versus major requirements; difficulty level; STEM status) on online course outcomes. Yet, focusing interventions at the course level versus the…

Multi-segmental movement patterns reflect juggling complexity and skill level.

PubMed

Zago, Matteo; Pacifici, Ilaria; Lovecchio, Nicola; Galli, Manuela; Federolf, Peter Andreas; Sforza, Chiarella

2017-08-01

The juggling action of six experts and six intermediates jugglers was recorded with a motion capture system and decomposed into its fundamental components through Principal Component Analysis. The aim was to quantify trends in movement dimensionality, multi-segmental patterns and rhythmicity as a function of proficiency level and task complexity. Dimensionality was quantified in terms of Residual Variance, while the Relative Amplitude was introduced to account for individual differences in movement components. We observed that: experience-related modifications in multi-segmental actions exist, such as the progressive reduction of error-correction movements, especially in complex task condition. The systematic identification of motor patterns sensitive to the acquisition of specific experience could accelerate the learning process. Copyright © 2017 Elsevier B.V. All rights reserved.

Hollow optical-fiber based infrared spectroscopy for measurement of blood glucose level by using multi-reflection prism.

PubMed

Kino, Saiko; Omori, Suguru; Katagiri, Takashi; Matsuura, Yuji

2016-02-01

A mid-infrared attenuated total reflection (ATR) spectroscopy system employing hollow optical fibers and a trapezoidal multi-reflection ATR prism has been developed to measure blood glucose levels. Using a multi-reflection prism brought about higher sensitivity, and the flat and wide contact surface of the prism resulted in higher measurement reproducibility. An analysis of in vivo measurements of human inner lip mucosa revealed clear signatures of glucose in the difference spectra between ones taken during the fasting state and ones taken after ingestion of glucose solutions. A calibration plot based on the absorption peak at 1155 cm(-1) that originates from the pyranose ring structure of glucose gave measurement errors less than 20%.

4D-CT Lung registration using anatomy-based multi-level multi-resolution optical flow analysis and thin-plate splines.

PubMed

Min, Yugang; Neylon, John; Shah, Amish; Meeks, Sanford; Lee, Percy; Kupelian, Patrick; Santhanam, Anand P

2014-09-01

The accuracy of 4D-CT registration is limited by inconsistent Hounsfield unit (HU) values in the 4D-CT data from one respiratory phase to another and lower image contrast for lung substructures. This paper presents an optical flow and thin-plate spline (TPS)-based 4D-CT registration method to account for these limitations. The use of unified HU values on multiple anatomy levels (e.g., the lung contour, blood vessels, and parenchyma) accounts for registration errors by inconsistent landmark HU value. While 3D multi-resolution optical flow analysis registers each anatomical level, TPS is employed for propagating the results from one anatomical level to another ultimately leading to the 4D-CT registration. 4D-CT registration was validated using target registration error (TRE), inverse consistency error (ICE) metrics, and a statistical image comparison using Gamma criteria of 1 % intensity difference in 2 mm(3) window range. Validation results showed that the proposed method was able to register CT lung datasets with TRE and ICE values <3 mm. In addition, the average number of voxel that failed the Gamma criteria was <3 %, which supports the clinical applicability of the propose registration mechanism. The proposed 4D-CT registration computes the volumetric lung deformations within clinically viable accuracy.

Towards Simpler Custom and OpenSearch Services for Voluminous NEWS Merged A-Train Data (Invited)

NASA Astrophysics Data System (ADS)

Hua, H.; Fetzer, E.; Braverman, A. J.; Lewis, S.; Henderson, M. L.; Guillaume, A.; Lee, S.; de La Torre Juarez, M.; Dang, H. T.

2010-12-01

To simplify access to large and complex satellite data sets for climate analysis and model verification, we developed web services that is used to study long-term and global-scale trends in climate, water and energy cycle, and weather variability. A related NASA Energy and Water Cycle Study (NEWS) task has created a merged NEWS Level 2 data from multiple instruments in NASA’s A-Train constellation of satellites. We used this data to enable creation of climatologies that include correlation between observed temperature, water vapor and cloud properties from the A-Train sensors. Instead of imposing on the user an often rigid and limiting web-based analysis environment, we recognize the need for simple and well-designed services so that users can perform analysis in their own familiar computing environments. Custom on-demand services were developed to improve data accessibility of voluminous multi-sensor data. Services enabling geospatial, geographical, and multi-sensor parameter subsets of the data, as well a custom time-averaged Level 3 service will be presented. We will also show how a Level 3Q data reduction approach can be used to help “browse” the voluminous multi-sensor Level 2 data. An OpenSearch capability with full text + space + time search of data products will also be presented as an approach to facilitated interoperability with other data systems. We will present our experiences for improving user usability as well as strategies for facilitating interoperability with other data systems.

Multi-level structure in the large scale distribution of optically luminous galaxies

NASA Astrophysics Data System (ADS)

Deng, Xin-fa; Deng, Zu-gan; Liu, Yong-zhen

1992-04-01

Fractal dimensions in the large scale distribution of galaxies have been calculated with the method given by Wen et al. [1] Samples are taken from CfA redshift survey in northern and southern galactic [2] hemisphere in our analysis respectively. Results from these two regions are compared with each other. There are significant differences between the distributions in these two regions. However, our analyses do show some common features of the distributions in these two regions. All subsamples show multi-level fractal character distinctly. Combining it with the results from analyses of samples given by IRAS galaxies and results from samples given by redshift survey in pencil-beam fields, [3,4] we suggest that multi-level fractal structure is most likely to be a general and important character in the large scale distribution of galaxies. The possible implications of this character are discussed.

[Location selection for Shenyang urban parks based on GIS and multi-objective location allocation model].

PubMed

Zhou, Yuan; Shi, Tie-Mao; Hu, Yuan-Man; Gao, Chang; Liu, Miao; Song, Lin-Qi

2011-12-01

Based on geographic information system (GIS) technology and multi-objective location-allocation (LA) model, and in considering of four relatively independent objective factors (population density level, air pollution level, urban heat island effect level, and urban land use pattern), an optimized location selection for the urban parks within the Third Ring of Shenyang was conducted, and the selection results were compared with the spatial distribution of existing parks, aimed to evaluate the rationality of the spatial distribution of urban green spaces. In the location selection of urban green spaces in the study area, the factor air pollution was most important, and, compared with single objective factor, the weighted analysis results of multi-objective factors could provide optimized spatial location selection of new urban green spaces. The combination of GIS technology with LA model would be a new approach for the spatial optimizing of urban green spaces.

Multiframe video coding for improved performance over wireless channels.

PubMed

Budagavi, M; Gibson, J D

2001-01-01

We propose and evaluate a multi-frame extension to block motion compensation (BMC) coding of videoconferencing-type video signals for wireless channels. The multi-frame BMC (MF-BMC) coder makes use of the redundancy that exists across multiple frames in typical videoconferencing sequences to achieve additional compression over that obtained by using the single frame BMC (SF-BMC) approach, such as in the base-level H.263 codec. The MF-BMC approach also has an inherent ability of overcoming some transmission errors and is thus more robust when compared to the SF-BMC approach. We model the error propagation process in MF-BMC coding as a multiple Markov chain and use Markov chain analysis to infer that the use of multiple frames in motion compensation increases robustness. The Markov chain analysis is also used to devise a simple scheme which randomizes the selection of the frame (amongst the multiple previous frames) used in BMC to achieve additional robustness. The MF-BMC coders proposed are a multi-frame extension of the base level H.263 coder and are found to be more robust than the base level H.263 coder when subjected to simulated errors commonly encountered on wireless channels.

Multiple-function multi-input/multi-output digital control and on-line analysis

NASA Technical Reports Server (NTRS)

Hoadley, Sherwood T.; Wieseman, Carol D.; Mcgraw, Sandra M.

1992-01-01

The design and capabilities of two digital controller systems for aeroelastic wind-tunnel models are described. The first allowed control of flutter while performing roll maneuvers with wing load control as well as coordinating the acquisition, storage, and transfer of data for on-line analysis. This system, which employs several digital signal multi-processor (DSP) boards programmed in high-level software languages, is housed in a SUN Workstation environment. A second DCS provides a measure of wind-tunnel safety by functioning as a trip system during testing in the case of high model dynamic response or in case the first DCS fails. The second DCS uses National Instruments LabVIEW Software and Hardware within a Macintosh environment.

A Multi-Level Simultaneous Analysis of How Student and School Characteristics Are Related to Students' English Language Achievement

ERIC Educational Resources Information Center

Güvendir, Emre

2015-01-01

This study examines how student and school characteristics are related to Turkish students' English language achievement in Evaluation of Student Achievement Test (ÖBBS) of 2009. The participants of the study involve 43707 ninth year students who were required to take ÖBBS in 2009. For data analysis two level hierarchical linear modeling was…

Multi-level significance of vulnerability indicators. Case study: Eastern Romania

NASA Astrophysics Data System (ADS)

Stanga, I. C.; Grozavu, A.

2012-04-01

Vulnerability assessment aims, most frequently, to emphasize internal fragility of a system comparing to a reference standard, to similar systems or in relation to a given hazard. Internal fragility, either biophysical or structural, may affect the capacity to predict, to prepare for, to cope with or to recover from a disaster. Thus, vulnerability is linked to resilience and adaptive capacity. From local level to global one, vulnerability factors and corresponding indicators are different and their significance must be tested and validated in a well-structured conceptual and methodological framework. In this paper, the authors aim to show the real vulnerability of rural settlements in Eastern Romania in a multi-level approach. The research area, Tutova Hills, counts about 3421 sq.km and more than 200.000 inhabitants in 421 villages characterized by deficient accessibility, lack of endowments, subsistential agriculture, high pressure on natural environment (especially on forest and soil resources), poverty and aging process of population. Factors that could influence the vulnerability of these rural settlements have been inventoried and assigned into groups through a cluster analysis: habitat and technical urban facilities, infrastructure, economical, social and demographical indicators, environment quality, management of emergency situations etc. Firstly, the main difficulty was to convert qualitative variable in quantitative indicators and to standardize all values to make possible mathematical and statistical processing of data. Secondly, the great variability of vulnerability factors, their different measuring units and their high amplitude of variation require different method of standardization in order to obtain values between zero (minimum vulnerability) and one (maximum vulnerability). Final vulnerability indicators were selected and integrated in a general scheme, according to their significance resulted from an appropriate factor analysis: linear and logistic regression, varimax rotation, multiple-criteria decision analysis, weight of evidence, multi-criteria evaluation method etc. The approach started from the local level which allows a functional and structural analysis and was progressively translated to an upper level and to a spatial analysis. The model shows that changing the level of analysis diminishes the functional significance of some indicators and increases the capacity of discretization in the case of others, highlighting the spatial and functional complexity of vulnerability.

Using Multi-Core Systems for Rover Autonomy

NASA Technical Reports Server (NTRS)

Clement, Brad; Estlin, Tara; Bornstein, Benjamin; Springer, Paul; Anderson, Robert C.

2010-01-01

Task Objectives are: (1) Develop and demonstrate key capabilities for rover long-range science operations using multi-core computing, (a) Adapt three rover technologies to execute on SOA multi-core processor (b) Illustrate performance improvements achieved (c) Demonstrate adapted capabilities with rover hardware, (2) Targeting three high-level autonomy technologies (a) Two for onboard data analysis (b) One for onboard command sequencing/planning, (3) Technologies identified as enabling for future missions, (4)Benefits will be measured along several metrics: (a) Execution time / Power requirements (b) Number of data products processed per unit time (c) Solution quality

Associations between state minimum wage policy and health care access: a multi-level analysis of the 2004 Behavioral Risk Factor survey.

PubMed

McCarrier, Kelly P; Martin, Diane P; Ralston, James D; Zimmerman, Frederick J

2010-05-01

Minimum wage policies have been advanced as mechanisms to improve the economic conditions of the working poor. Both positive and negative effects of such policies on health care access have been hypothesized, but associations have yet to be thoroughly tested. To examine whether the presence of minimum wage policies in excess of the federal standard of $5.15 per hour was associated with health care access indicators among low-skilled adults of working age, a cross-sectional analysis of 2004 Behavioral Risk Factor Surveillance System data was conducted. Self-reported health insurance status and experience with cost-related barriers to needed medical care were adjusted in multi-level logistic regression models to control for potential confounding at the state, county, and individual levels. State-level wage policy was not found to be associated with insurance status or unmet medical need in the models, providing early evidence that increased minimum wage rates may neither strengthen nor weaken access to care as previously predicted.

Multi-Locus Candidate Gene Analyses of Lipid Levels in a Pediatric Turkish Cohort: Lessons Learned on LPL, CETP, LIPC, ABCA1, and SHBG

PubMed Central

Eren, Fatih; Agirbasli, Deniz; White, Marquitta J.; Williams, Scott M

2013-01-01

Abstract Cardiovascular risk factors and atherosclerosis precursors were examined in 365 Turkish children and adolescents. Study participants were recruited at five different state schools. We tested single and multi-locus effects of six polymorphisms from five candidate genes, chosen based on prior known association with lipid levels in adults, for association with low (≤10th percentile) high density lipoprotein cholesterol (HDL-C) and high (≥90th percentile) triglycerides (TG), and the related continuous outcomes. We observed an association between CETP variant rs708272 and low HDL-C (allelic p=0.020, genotypic p=0.046), which was supported by an independent analysis, PRAT (PRAT control p=0.027). Sex-stratified logistic regression analysis showed that the B2 allele of rs708272 decreased odds of being in the lower tenth percentile of HDL-C measurements (OR=0.36, p=0.02) in girls; this direction of effect was also seen in boys but was not significant (OR=0.64, p=0.21). Logistic regression analysis also revealed that the T allele of rs6257 (SHBG) decreased odds of being in the top tenth percentile of TG measurements in boys (OR=0.43, p=0.03). Analysis of lipid levels as a continuous trait revealed a significant association between rs708272 (CETP) and LDL-C levels in males (p=0.02) with the B2B2 genotype group having the lowest mean LDL-C; the same direction of effect was also seen in females (p=0.05). An effect was also seen between rs708272 and HDL-C levels in girls (p=0.01), with the B2B2 genotype having the highest mean HDL-C levels. Multi-locus analysis, using quantitative multifactor dimensionality reduction (qMDR) identified the previously mentioned CETP variant as the best single locus model, and overall model, for predicting HDL-C levels in children. This study provides evidence for association between CETP and low HDL-C phenotype in children, but the results appear to be weaker in children than previous results in adults and may also be subject to gender effects. PMID:23988150

MultiSpec—a tool for multispectral hyperspectral image data analysis

NASA Astrophysics Data System (ADS)

Biehl, Larry; Landgrebe, David

2002-12-01

MultiSpec is a multispectral image data analysis software application. It is intended to provide a fast, easy-to-use means for analysis of multispectral image data, such as that from the Landsat, SPOT, MODIS or IKONOS series of Earth observational satellites, hyperspectral data such as that from the Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) and EO-1 Hyperion satellite system or the data that will be produced by the next generation of Earth observational sensors. The primary purpose for the system was to make new, otherwise complex analysis tools available to the general Earth science community. It has also found use in displaying and analyzing many other types of non-space related digital imagery, such as medical image data and in K-12 and university level educational activities. MultiSpec has been implemented for both the Apple Macintosh ® and Microsoft Windows ® operating systems (OS). The effort was first begun on the Macintosh OS in 1988. The GLOBE ( http://www.globe.gov) program supported the development of a subset of MultiSpec for the Windows OS in 1995. Since then most (but not all) of the features in the Macintosh OS version have been ported to the Windows OS version. Although copyrighted, MultiSpec with its documentation is distributed without charge. The Macintosh and Windows versions and documentation on its use are available from the World Wide Web at URL: http://dynamo.ecn.purdue.edu/˜biehl/MultiSpec/ MultiSpec is copyrighted (1991-2001) by Purdue Research Foundation, West Lafayette, Indiana 47907.

Discovering the Past through Data: Promoting the Design and Analysis of Original Data-Sets in History Undergraduate Courses in Hong Kong

ERIC Educational Resources Information Center

Kim, Loretta; Wong, Shun Han Rebekah

2015-01-01

This article discusses the objectives and outcomes of a project to enhance digital humanities training at the undergraduate level in a Hong Kong university. The co-investigators re-designed a multi-source data-set as an example and then taught a multi-step curriculum about gathering, organizing, and presenting original data to an introductory…

Reducing fatalities and severe injuries on Florida's high-speed multi-lane arterial corridors : part III, county level and roadway level GIS safety analysis of state multilane corridors in Florida, final report, April 2009

DOT National Transportation Integrated Search

2009-04-28

This part of the study examines the locations of high trends of severe crashes (incapacitating and fatal crashes) on multilane corridors in the state of Florida at two levels, county level and roadway level. The Geographic Information System (GIS) to...

Community economic status and intimate partner violence against women in bangladesh: compositional or contextual effects?

PubMed

VanderEnde, Kristin E; Sibley, Lynn M; Cheong, Yuk Fai; Naved, Ruchira Tabassum; Yount, Kathryn M

2015-06-01

In this research, we used a multi-level contextual-effects analysis to disentangle the household- and community-level associations between income and intimate partner violence (IPV) against women in Bangladesh. Our analyses of data from 2,668 women interviewed as part of the World Health Organization (WHO) multi-country study on women's health and domestic violence against women showed that household income was negatively associated with women's risk of experiencing IPV. Controlling for residence in a low-income household, living in a low-income community was not associated with women's risk of experiencing IPV. These results support a household-level, not community-level, relationship between income and IPV in Bangladesh. © The Author(s) 2015.

Analytic hierarchy process-based approach for selecting a Pareto-optimal solution of a multi-objective, multi-site supply-chain planning problem

NASA Astrophysics Data System (ADS)

Ayadi, Omar; Felfel, Houssem; Masmoudi, Faouzi

2017-07-01

The current manufacturing environment has changed from traditional single-plant to multi-site supply chain where multiple plants are serving customer demands. In this article, a tactical multi-objective, multi-period, multi-product, multi-site supply-chain planning problem is proposed. A corresponding optimization model aiming to simultaneously minimize the total cost, maximize product quality and maximize the customer satisfaction demand level is developed. The proposed solution approach yields to a front of Pareto-optimal solutions that represents the trade-offs among the different objectives. Subsequently, the analytic hierarchy process method is applied to select the best Pareto-optimal solution according to the preferences of the decision maker. The robustness of the solutions and the proposed approach are discussed based on a sensitivity analysis and an application to a real case from the textile and apparel industry.

GELATIO: a general framework for modular digital analysis of high-purity Ge detector signals

NASA Astrophysics Data System (ADS)

Agostini, M.; Pandola, L.; Zavarise, P.; Volynets, O.

2011-08-01

GELATIO is a new software framework for advanced data analysis and digital signal processing developed for the GERDA neutrinoless double beta decay experiment. The framework is tailored to handle the full analysis flow of signals recorded by high purity Ge detectors and photo-multipliers from the veto counters. It is designed to support a multi-channel modular and flexible analysis, widely customizable by the user either via human-readable initialization files or via a graphical interface. The framework organizes the data into a multi-level structure, from the raw data up to the condensed analysis parameters, and includes tools and utilities to handle the data stream between the different levels. GELATIO is implemented in C++. It relies upon ROOT and its extension TAM, which provides compatibility with PROOF, enabling the software to run in parallel on clusters of computers or many-core machines. It was tested on different platforms and benchmarked in several GERDA-related applications. A stable version is presently available for the GERDA Collaboration and it is used to provide the reference analysis of the experiment data.

Satellite Imagery Analysis for Automated Global Food Security Forecasting

NASA Astrophysics Data System (ADS)

Moody, D.; Brumby, S. P.; Chartrand, R.; Keisler, R.; Mathis, M.; Beneke, C. M.; Nicholaeff, D.; Skillman, S.; Warren, M. S.; Poehnelt, J.

2017-12-01

The recent computing performance revolution has driven improvements in sensor, communication, and storage technology. Multi-decadal remote sensing datasets at the petabyte scale are now available in commercial clouds, with new satellite constellations generating petabytes/year of daily high-resolution global coverage imagery. Cloud computing and storage, combined with recent advances in machine learning, are enabling understanding of the world at a scale and at a level of detail never before feasible. We present results from an ongoing effort to develop satellite imagery analysis tools that aggregate temporal, spatial, and spectral information and that can scale with the high-rate and dimensionality of imagery being collected. We focus on the problem of monitoring food crop productivity across the Middle East and North Africa, and show how an analysis-ready, multi-sensor data platform enables quick prototyping of satellite imagery analysis algorithms, from land use/land cover classification and natural resource mapping, to yearly and monthly vegetative health change trends at the structural field level.

Comparison of multi-subject ICA methods for analysis of fMRI data

PubMed Central

Erhardt, Erik Barry; Rachakonda, Srinivas; Bedrick, Edward; Allen, Elena; Adali, Tülay; Calhoun, Vince D.

2010-01-01

Spatial independent component analysis (ICA) applied to functional magnetic resonance imaging (fMRI) data identifies functionally connected networks by estimating spatially independent patterns from their linearly mixed fMRI signals. Several multi-subject ICA approaches estimating subject-specific time courses (TCs) and spatial maps (SMs) have been developed, however there has not yet been a full comparison of the implications of their use. Here, we provide extensive comparisons of four multi-subject ICA approaches in combination with data reduction methods for simulated and fMRI task data. For multi-subject ICA, the data first undergo reduction at the subject and group levels using principal component analysis (PCA). Comparisons of subject-specific, spatial concatenation, and group data mean subject-level reduction strategies using PCA and probabilistic PCA (PPCA) show that computationally intensive PPCA is equivalent to PCA, and that subject-specific and group data mean subject-level PCA are preferred because of well-estimated TCs and SMs. Second, aggregate independent components are estimated using either noise free ICA or probabilistic ICA (PICA). Third, subject-specific SMs and TCs are estimated using back-reconstruction. We compare several direct group ICA (GICA) back-reconstruction approaches (GICA1-GICA3) and an indirect back-reconstruction approach, spatio-temporal regression (STR, or dual regression). Results show the earlier group ICA (GICA1) approximates STR, however STR has contradictory assumptions and may show mixed-component artifacts in estimated SMs. Our evidence-based recommendation is to use GICA3, introduced here, with subject-specific PCA and noise-free ICA, providing the most robust and accurate estimated SMs and TCs in addition to offering an intuitive interpretation. PMID:21162045

STRUCTURING EDUCATION FOR BUSINESS MANAGEMENT.

ERIC Educational Resources Information Center

WHITT, ROBERT L.

IN TERMS OF SERVICES RECEIVED, LOCAL SCHOOLS BENEFIT SUBSTANTIALLY FROM EDUCATIONAL BUSINESS MANAGEMENT. IN ORDER TO ISOLATE BUSINESS ADMINISTRATIVE PROBLEMS OF THE SCHOOL SYSTEM, AN ANALYSIS WAS CONDUCTED AT EACH OF 6 ADMINISTRATIVE SERVICE LEVELS--LOCAL (ATTENDANCE LEVEL), DISTRICT, AREA, REGIONAL, STATE, AND MULTI-STATE. AS A RESULT OF MERGED…

Risk analysis based on hazards interactions

NASA Astrophysics Data System (ADS)

Rossi, Lauro; Rudari, Roberto; Trasforini, Eva; De Angeli, Silvia; Becker, Joost

2017-04-01

Despite an increasing need for open, transparent, and credible multi-hazard risk assessment methods, models, and tools, the availability of comprehensive risk information needed to inform disaster risk reduction is limited, and the level of interaction across hazards is not systematically analysed. Risk assessment methodologies for different hazards often produce risk metrics that are not comparable. Hazard interactions (consecutive occurrence two or more different events) are generally neglected, resulting in strongly underestimated risk assessment in the most exposed areas. This study presents cases of interaction between different hazards, showing how subsidence can affect coastal and river flood risk (Jakarta and Bandung, Indonesia) or how flood risk is modified after a seismic event (Italy). The analysis of well documented real study cases, based on a combination between Earth Observation and in-situ data, would serve as basis the formalisation of a multi-hazard methodology, identifying gaps and research frontiers. Multi-hazard risk analysis is performed through the RASOR platform (Rapid Analysis and Spatialisation Of Risk). A scenario-driven query system allow users to simulate future scenarios based on existing and assumed conditions, to compare with historical scenarios, and to model multi-hazard risk both before and during an event (www.rasor.eu).

Multi-intelligence critical rating assessment of fusion techniques (MiCRAFT)

NASA Astrophysics Data System (ADS)

Blasch, Erik

2015-06-01

Assessment of multi-intelligence fusion techniques includes credibility of algorithm performance, quality of results against mission needs, and usability in a work-domain context. Situation awareness (SAW) brings together low-level information fusion (tracking and identification), high-level information fusion (threat and scenario-based assessment), and information fusion level 5 user refinement (physical, cognitive, and information tasks). To measure SAW, we discuss the SAGAT (Situational Awareness Global Assessment Technique) technique for a multi-intelligence fusion (MIF) system assessment that focuses on the advantages of MIF against single intelligence sources. Building on the NASA TLX (Task Load Index), SAGAT probes, SART (Situational Awareness Rating Technique) questionnaires, and CDM (Critical Decision Method) decision points; we highlight these tools for use in a Multi-Intelligence Critical Rating Assessment of Fusion Techniques (MiCRAFT). The focus is to measure user refinement of a situation over the information fusion quality of service (QoS) metrics: timeliness, accuracy, confidence, workload (cost), and attention (throughput). A key component of any user analysis includes correlation, association, and summarization of data; so we also seek measures of product quality and QuEST of information. Building a notion of product quality from multi-intelligence tools is typically subjective which needs to be aligned with objective machine metrics.

Risk Evaluation of Railway Coal Transportation Network Based on Multi Level Grey Evaluation Model

NASA Astrophysics Data System (ADS)

Niu, Wei; Wang, Xifu

2018-01-01

The railway transport mode is currently the most important way of coal transportation, and now China’s railway coal transportation network has become increasingly perfect, but there is still insufficient capacity, some lines close to saturation and other issues. In this paper, the theory and method of risk assessment, analytic hierarchy process and multi-level gray evaluation model are applied to the risk evaluation of coal railway transportation network in China. Based on the example analysis of Shanxi railway coal transportation network, to improve the internal structure and the competitiveness of the market.

Neighborhood-Level Correlates of Consistent Condom Use among Men Who have Sex with Men: A Multi-Level Analysis

PubMed Central

Koblin, Beryl; Chin, John; Beard, John; Blaney, Shannon; Halkitis, Perry; Vlahov, David; Galea, Sandro

2014-01-01

There is growing evidence that the neighborhood environment influences sexual behavior and related outcomes, but little work has focused specifically on men who have sex with men (MSM). Using interview data from a probability sample of 385 young MSM living in New York City, recruited at public venues in 1999 and 2000 as part of the Young Men’s Survey-New York City, and data on neighborhood characteristics obtained from the U.S. Census 2000, we conducted multi-level analyses of the associations between neighborhood-level characteristics and consistent condom use during anal intercourse, while controlling for individual-level sociodemographic and other factors. After adjusting for individual-level factors, neighborhood-level gay presence remained significantly and positively associated with consistent condom use during anal intercourse. This finding suggests that neighborhoods with a significant gay presence may have norms that act to discourage high risk sexual activity. PMID:18712593

Working together versus working autonomously: a new power-dependence perspective on the individual-level of analysis.

PubMed

de Jong, Simon B

2014-01-01

Recent studies have indicated that it is important to investigate the interaction between task interdependence and task autonomy because this interaction can affect team effectiveness. However, only a limited number of studies have been conducted and those studies focused solely on the team level of analysis. Moreover, there has also been a dearth of theoretical development. Therefore, this study develops and tests an alternative theoretical perspective in an attempt to understand if, and if so why, this interaction is important at the individual level of analysis. Based on interdependence theory and power-dependence theory, we expected that highly task-interdependent individuals who reported high task autonomy would be more powerful and better performers. In contrast, we expected that similarly high task-interdependent individuals who reported less task autonomy would be less powerful and would be weaker performers. These expectations were supported by multi-level and bootstrapping analyses performed on a multi-source dataset (self-, peer-, manager-ratings) comprised of 182 employees drawn from 37 teams. More specifically, the interaction between task interdependence and task autonomy was γ =.128, p <.05 for power and γ =.166, p <.05 for individual performance. The 95% bootstrap interval ranged from .0038 to .0686.

The automated multi-stage substructuring system for NASTRAN

NASA Technical Reports Server (NTRS)

Field, E. I.; Herting, D. N.; Herendeen, D. L.; Hoesly, R. L.

1975-01-01

The substructuring capability developed for eventual installation in Level 16 is now operational in a test version of NASTRAN. Its features are summarized. These include the user-oriented, Case Control type control language, the automated multi-stage matrix processing, the independent direct access data storage facilities, and the static and normal modes solution capabilities. A complete problem analysis sequence is presented with card-by-card description of the user input.

Analysis of Multi-Vane Radiometers in High-Altitude Propulsion

DTIC Science & Technology

2010-06-17

m] I. Introduction EAR space is generally defined as the altitude region above where jet aircraft can produce enough lift to maintain level...temperature gradient [5]. To maximize the gradient, the hot surface and cold surface are separated by thermal insulator, in this case aerogel . The hot...of the multi-vanes are vehicle specific base on altitude. Each individual vane consists of silicone aerogel sandwiched between two thin aluminum

An Exploration of the Interaction between Global Education Policy Orthodoxies and National Education Practices in Cambodia, Illuminated through the Voices of Local Teacher Educators

ERIC Educational Resources Information Center

Courtney, Jane

2017-01-01

This research is based on a multi-disciplinary and multi-levelled analysis of evidence to present the case that education reform needs to be contextualised far more widely than is currently practised. It focuses on the voices of Cambodian local teacher trainers through interviews over a five-year period. Interview data is triangulated against…

Systematic review and meta-analysis: Multi-strain probiotics as adjunct therapy for Helicobacter pylori eradication and prevention of adverse events

PubMed Central

Huang, Ying; Wang, Lin; Malfertheiner, Peter

2015-01-01

Background Eradication rates with triple therapy for Helicobacter pylori infections have currently declined to unacceptable levels worldwide. Newer quadruple therapies are burdened with a high rate of adverse events. Whether multi-strain probiotics can improve eradication rates or diminish adverse events remains uncertain. Methods Relevant publications in which patients with H. pylori infections were randomized to a multi-strain probiotic or control were identified in PubMed, Cochrane Databases, and other sources from 1 January 1960–3 June 2015. Primary outcomes included eradication rates, incidence of any adverse event and the incidence of antibiotic-associated diarrhea. As probiotic efficacy is strain-specific, pooled relative risks and 95% confidence intervals were calculated using meta-analysis stratified by similar multi-strain probiotic mixtures. Results A total of 19 randomized controlled trials (20 treatment arms, n = 2730) assessing one of six mixtures of strains of probiotics were included. Four multi-strain probiotics significantly improved H. pylori eradication rates, five significantly prevented any adverse reactions and three significantly reduced antibiotic-associated diarrhea. Only two probiotic mixtures (Lactobacillus acidophilus/Bifidobacterium animalis and an eight-strain mixture) had significant efficacy for all three outcomes. Conclusions Our meta-analysis found adjunctive use of some multi-strain probiotics may improve H. pylori eradication rates and prevent the development of adverse events and antibiotic-associated diarrhea, but not all mixtures were effective. PMID:27536365

Species-level assessment of secondary metabolite diversity among Hamigera species and a taxonomic note on the genus

USDA-ARS?s Scientific Manuscript database

Secondary metabolite phenotypes in nine species of the Hamigera clade were analysed to assess their correlations to a multi-gene species-level phylogeny. High-pressure-liquid-chromatography-based chemical analysis revealed three distinctive patterns of secondary metabolite production: (1) the nine s...

A Liver-centric Multiscale Modeling Framework for Xenobiotics ...

EPA Pesticide Factsheets

We describe a multi-scale framework for modeling acetaminophen-induced liver toxicity. Acetaminophen is a widely used analgesic. Overdose of acetaminophen can result in liver injury via its biotransformation into toxic product, which further induce massive necrosis. Our study focuses on developing a multi-scale computational model to characterize both phase I and phase II metabolism of acetaminophen, by bridging Physiologically Based Pharmacokinetic (PBPK) modeling at the whole body level, cell movement and blood flow at the tissue level and cell signaling and drug metabolism at the sub-cellular level. To validate the model, we estimated our model parameters by fi?tting serum concentrations of acetaminophen and its glucuronide and sulfate metabolites to experiments, and carried out sensitivity analysis on 35 parameters selected from three modules. Our study focuses on developing a multi-scale computational model to characterize both phase I and phase II metabolism of acetaminophen, by bridging Physiologically Based Pharmacokinetic (PBPK) modeling at the whole body level, cell movement and blood flow at the tissue level and cell signaling and drug metabolism at the sub-cellular level. This multiscale model bridges the CompuCell3D tool used by the Virtual Tissue project with the httk tool developed by the Rapid Exposure and Dosimetry project.

A morphologically preserved multi-resolution TIN surface modeling and visualization method for virtual globes

NASA Astrophysics Data System (ADS)

Zheng, Xianwei; Xiong, Hanjiang; Gong, Jianya; Yue, Linwei

2017-07-01

Virtual globes play an important role in representing three-dimensional models of the Earth. To extend the functioning of a virtual globe beyond that of a "geobrowser", the accuracy of the geospatial data in the processing and representation should be of special concern for the scientific analysis and evaluation. In this study, we propose a method for the processing of large-scale terrain data for virtual globe visualization and analysis. The proposed method aims to construct a morphologically preserved multi-resolution triangulated irregular network (TIN) pyramid for virtual globes to accurately represent the landscape surface and simultaneously satisfy the demands of applications at different scales. By introducing cartographic principles, the TIN model in each layer is controlled with a data quality standard to formulize its level of detail generation. A point-additive algorithm is used to iteratively construct the multi-resolution TIN pyramid. The extracted landscape features are also incorporated to constrain the TIN structure, thus preserving the basic morphological shapes of the terrain surface at different levels. During the iterative construction process, the TIN in each layer is seamlessly partitioned based on a virtual node structure, and tiled with a global quadtree structure. Finally, an adaptive tessellation approach is adopted to eliminate terrain cracks in the real-time out-of-core spherical terrain rendering. The experiments undertaken in this study confirmed that the proposed method performs well in multi-resolution terrain representation, and produces high-quality underlying data that satisfy the demands of scientific analysis and evaluation.

Poly-Pattern Compressive Segmentation of ASTER Data for GIS

NASA Technical Reports Server (NTRS)

Myers, Wayne; Warner, Eric; Tutwiler, Richard

2007-01-01

Pattern-based segmentation of multi-band image data, such as ASTER, produces one-byte and two-byte approximate compressions. This is a dual segmentation consisting of nested coarser and finer level pattern mappings called poly-patterns. The coarser A-level version is structured for direct incorporation into geographic information systems in the manner of a raster map. GIs renderings of this A-level approximation are called pattern pictures which have the appearance of color enhanced images. The two-byte version consisting of thousands of B-level segments provides a capability for approximate restoration of the multi-band data in selected areas or entire scenes. Poly-patterns are especially useful for purposes of change detection and landscape analysis at multiple scales. The primary author has implemented the segmentation methodology in a public domain software suite.

Automated multi-plug filtration cleanup for liquid chromatographic-tandem mass spectrometric pesticide multi-residue analysis in representative crop commodities.

PubMed

Qin, Yuhong; Zhang, Jingru; Zhang, Yuan; Li, Fangbing; Han, Yongtao; Zou, Nan; Xu, Haowei; Qian, Meiyuan; Pan, Canping

2016-09-02

An automated multi-plug filtration cleanup (m-PFC) method on modified QuEChERS (quick, easy, cheap, effective, rugged, and safe) extracts was developed. The automatic device was aimed to reduce labor-consuming manual operation workload in the cleanup steps. It could control the volume and the speed of pulling and pushing cycles accurately. In this work, m-PFC was based on multi-walled carbon nanotubes (MWCNTs) mixed with other sorbents and anhydrous magnesium sulfate (MgSO4) in a packed tip for analysis of pesticide multi-residues in crop commodities followed by liquid chromatography with tandem mass spectrometric (LC-MS/MS) detection. It was validated by analyzing 25 pesticides in six representative matrices spiked at two concentration levels of 10 and 100μg/kg. Salts, sorbents, m-PFC procedure, automated pulling and pushing volume, automated pulling speed, and pushing speed for each matrix were optimized. After optimization, two general automated m-PFC methods were introduced to relatively simple (apple, citrus fruit, peanut) and relatively complex (spinach, leek, green tea) matrices. Spike recoveries were within 83 and 108% and 1-14% RSD for most analytes in the tested matrices. Matrix-matched calibrations were performed with the coefficients of determination >0.997 between concentration levels of 10 and 1000μg/kg. The developed method was successfully applied to the determination of pesticide residues in market samples. Copyright © 2016 Elsevier B.V. All rights reserved.

Learning Natural Selection in 4th Grade with Multi-Agent-Based Computational Models

NASA Astrophysics Data System (ADS)

Dickes, Amanda Catherine; Sengupta, Pratim

2013-06-01

In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term "agent" in an MABM indicates individual computational objects or actors (e.g., cars), and these agents obey simple rules assigned or manipulated by the user (e.g., speeding up, slowing down, etc.). It is the interactions between these agents, based on the rules assigned by the user, that give rise to emergent, aggregate-level behavior (e.g., formation and movement of the traffic jam). Natural selection is such an emergent phenomenon, which has been shown to be challenging for novices (K16 students) to understand. Whereas prior research on learning evolutionary phenomena with MABMs has typically focused on high school students and beyond, we investigate how elementary students (4th graders) develop multi-level explanations of some introductory aspects of natural selection—species differentiation and population change—through scaffolded interactions with an MABM that simulates predator-prey dynamics in a simple birds-butterflies ecosystem. We conducted a semi-clinical interview based study with ten participants, in which we focused on the following: a) identifying the nature of learners' initial interpretations of salient events or elements of the represented phenomena, b) identifying the roles these interpretations play in the development of their multi-level explanations, and c) how attending to different levels of the relevant phenomena can make explicit different mechanisms to the learners. In addition, our analysis also shows that although there were differences between high- and low-performing students (in terms of being able to explain population-level behaviors) in the pre-test, these differences disappeared in the post-test.

Analytical transmissibility based transfer path analysis for multi-energy-domain systems using four-pole parameter theory

NASA Astrophysics Data System (ADS)

Mashayekhi, Mohammad Jalali; Behdinan, Kamran

2017-10-01

The increasing demand to minimize undesired vibration and noise levels in several high-tech industries has generated a renewed interest in vibration transfer path analysis. Analyzing vibration transfer paths within a system is of crucial importance in designing an effective vibration isolation strategy. Most of the existing vibration transfer path analysis techniques are empirical which are suitable for diagnosis and troubleshooting purpose. The lack of an analytical transfer path analysis to be used in the design stage is the main motivation behind this research. In this paper an analytical transfer path analysis based on the four-pole theory is proposed for multi-energy-domain systems. Bond graph modeling technique which is an effective approach to model multi-energy-domain systems is used to develop the system model. In this paper an electro-mechanical system is used as a benchmark example to elucidate the effectiveness of the proposed technique. An algorithm to obtain the equivalent four-pole representation of a dynamical systems based on the corresponding bond graph model is also presented in this paper.

Automated diagnosis of interstitial lung diseases and emphysema in MDCT imaging

NASA Astrophysics Data System (ADS)

Fetita, Catalin; Chang Chien, Kuang-Che; Brillet, Pierre-Yves; Prêteux, Françoise

2007-09-01

Diffuse lung diseases (DLD) include a heterogeneous group of non-neoplasic disease resulting from damage to the lung parenchyma by varying patterns of inflammation. Characterization and quantification of DLD severity using MDCT, mainly in interstitial lung diseases and emphysema, is an important issue in clinical research for the evaluation of new therapies. This paper develops a 3D automated approach for detection and diagnosis of diffuse lung diseases such as fibrosis/honeycombing, ground glass and emphysema. The proposed methodology combines multi-resolution 3D morphological filtering (exploiting the sup-constrained connection cost operator) and graph-based classification for a full characterization of the parenchymal tissue. The morphological filtering performs a multi-level segmentation of the low- and medium-attenuated lung regions as well as their classification with respect to a granularity criterion (multi-resolution analysis). The original intensity range of the CT data volume is thus reduced in the segmented data to a number of levels equal to the resolution depth used (generally ten levels). The specificity of such morphological filtering is to extract tissue patterns locally contrasting with their neighborhood and of size inferior to the resolution depth, while preserving their original shape. A multi-valued hierarchical graph describing the segmentation result is built-up according to the resolution level and the adjacency of the different segmented components. The graph nodes are then enriched with the textural information carried out by their associated components. A graph analysis-reorganization based on the nodes attributes delivers the final classification of the lung parenchyma in normal and ILD/emphysematous regions. It also makes possible to discriminate between different types, or development stages, among the same class of diseases.

Reducing fatalities and severe injuries on Florida's high-speed multi-lane arterial corridors : part II, analysis of the crash level data, final report, April 2009

DOT National Transportation Integrated Search

2009-04-28

This report presents the analysis conducted to identify the factors that contribute to severe and fatal crash occurrence on multilane corridors. The authors preliminary investigation using simultaneous ordered probit model provided enough evidence...

Predictors of Self-Directed Learning for Low-Qualified Employees: A Multi-Level Analysis

ERIC Educational Resources Information Center

Raemdonck, Isabel; van der Leeden, Rien; Valcke, Martin; Segers, Mien; Thijssen, Jo

2012-01-01

Purpose: This study aims to examine which variables at the level of the individual employee and at the company level are predictors of self-directed learning in low-qualified employees. Methodology: Results were obtained from a sample of 408 low-qualified employees from 35 different companies. The companies were selected from the energy sector,…

Addressing data privacy in matched studies via virtual pooling.

PubMed

Saha-Chaudhuri, P; Weinberg, C R

2017-09-07

Data confidentiality and shared use of research data are two desirable but sometimes conflicting goals in research with multi-center studies and distributed data. While ideal for straightforward analysis, confidentiality restrictions forbid creation of a single dataset that includes covariate information of all participants. Current approaches such as aggregate data sharing, distributed regression, meta-analysis and score-based methods can have important limitations. We propose a novel application of an existing epidemiologic tool, specimen pooling, to enable confidentiality-preserving analysis of data arising from a matched case-control, multi-center design. Instead of pooling specimens prior to assay, we apply the methodology to virtually pool (aggregate) covariates within nodes. Such virtual pooling retains most of the information used in an analysis with individual data and since individual participant data is not shared externally, within-node virtual pooling preserves data confidentiality. We show that aggregated covariate levels can be used in a conditional logistic regression model to estimate individual-level odds ratios of interest. The parameter estimates from the standard conditional logistic regression are compared to the estimates based on a conditional logistic regression model with aggregated data. The parameter estimates are shown to be similar to those without pooling and to have comparable standard errors and confidence interval coverage. Virtual data pooling can be used to maintain confidentiality of data from multi-center study and can be particularly useful in research with large-scale distributed data.

Skilful prediction of Sahel summer rainfall on inter-annual and multi-year timescales

PubMed Central

Sheen, K. L.; Smith, D. M.; Dunstone, N. J.; Eade, R.; Rowell, D. P.; Vellinga, M.

2017-01-01

Summer rainfall in the Sahel region of Africa exhibits one of the largest signals of climatic variability and with a population reliant on agricultural productivity, the Sahel is particularly vulnerable to major droughts such as occurred in the 1970s and 1980s. Rainfall levels have subsequently recovered, but future projections remain uncertain. Here we show that Sahel rainfall is skilfully predicted on inter-annual and multi-year (that is, >5 years) timescales and use these predictions to better understand the driving mechanisms. Moisture budget analysis indicates that on multi-year timescales, a warmer north Atlantic and Mediterranean enhance Sahel rainfall through increased meridional convergence of low-level, externally sourced moisture. In contrast, year-to-year rainfall levels are largely determined by the recycling rate of local moisture, regulated by planetary circulation patterns associated with the El Niño-Southern Oscillation. Our findings aid improved understanding and forecasting of Sahel drought, paramount for successful adaptation strategies in a changing climate. PMID:28541288

Variable cycle control model for intersection based on multi-source information

NASA Astrophysics Data System (ADS)

Sun, Zhi-Yuan; Li, Yue; Qu, Wen-Cong; Chen, Yan-Yan

2018-05-01

In order to improve the efficiency of traffic control system in the era of big data, a new variable cycle control model based on multi-source information is presented for intersection in this paper. Firstly, with consideration of multi-source information, a unified framework based on cyber-physical system is proposed. Secondly, taking into account the variable length of cell, hysteresis phenomenon of traffic flow and the characteristics of lane group, a Lane group-based Cell Transmission Model is established to describe the physical properties of traffic flow under different traffic signal control schemes. Thirdly, the variable cycle control problem is abstracted into a bi-level programming model. The upper level model is put forward for cycle length optimization considering traffic capacity and delay. The lower level model is a dynamic signal control decision model based on fairness analysis. Then, a Hybrid Intelligent Optimization Algorithm is raised to solve the proposed model. Finally, a case study shows the efficiency and applicability of the proposed model and algorithm.

Operational considerations for the application of remotely sensed forest data from LANDSAT or other airborne platforms

NASA Technical Reports Server (NTRS)

Baker, G. R.; Fethe, T. P.

1975-01-01

Research in the application of remotely sensed data from LANDSAT or other airborne platforms to the efficient management of a large timber based forest industry was divided into three phases: (1) establishment of a photo/ground sample correlation, (2) investigation of techniques for multi-spectral digital analysis, and (3) development of a semi-automated multi-level sampling system. To properly verify results, three distinct test areas were selected: (1) Jacksonville Mill Region, Lower Coastal Plain, Flatwoods, (2) Pensacola Mill Region, Middle Coastal Plain, and (3) Mississippi Mill Region, Middle Coastal Plain. The following conclusions were reached: (1) the probability of establishing an information base suitable for management requirements through a photo/ground double sampling procedure, alleviating the ground sampling effort, is encouraging, (2) known classification techniques must be investigated to ascertain the level of precision possible in separating the many densities involved, and (3) the multi-level approach must be related to an information system that is executable and feasible.

Modeling the Multi-Body System Dynamics of a Flexible Solar Sail Spacecraft

NASA Technical Reports Server (NTRS)

Kim, Young; Stough, Robert; Whorton, Mark

2005-01-01

Solar sail propulsion systems enable a wide range of space missions that are not feasible with current propulsion technology. Hardware concepts and analytical methods have matured through ground development to the point that a flight validation mission is now realizable. Much attention has been given to modeling the structural dynamics of the constituent elements, but to date an integrated system level dynamics analysis has been lacking. Using a multi-body dynamics and control analysis tool called TREETOPS, the coupled dynamics of the sailcraft bus, sail membranes, flexible booms, and control system sensors and actuators of a representative solar sail spacecraft are investigated to assess system level dynamics and control issues. With this tool, scaling issues and parametric trade studies can be performed to study achievable performance, control authority requirements, and control/structure interaction assessments.

Multiscale Analysis of Delamination of Carbon Fiber-Epoxy Laminates with Carbon Nanotubes

NASA Technical Reports Server (NTRS)

Riddick, Jaret C.; Frankland, SJV; Gates, TS

2006-01-01

A multi-scale analysis is presented to parametrically describe the Mode I delamination of a carbon fiber/epoxy laminate. In the midplane of the laminate, carbon nanotubes are included for the purposes of selectively enhancing the fracture toughness of the laminate. To analyze carbon fiber epoxy carbon nanotube laminate, the multi-scale methodology presented here links a series of parameterizations taken at various length scales ranging from the atomistic through the micromechanical to the structural level. At the atomistic scale molecular dynamics simulations are performed in conjunction with an equivalent continuum approach to develop constitutive properties for representative volume elements of the molecular structure of components of the laminate. The molecular-level constitutive results are then used in the Mori-Tanaka micromechanics to develop bulk properties for the epoxy-carbon nanotube matrix system. In order to demonstrate a possible application of this multi-scale methodology, a double cantilever beam specimen is modeled. An existing analysis is employed which uses discrete springs to model the fiber bridging affect during delamination propagation. In the absence of empirical data or a damage mechanics model describing the effect of CNTs on fracture toughness, several tractions laws are postulated, linking CNT volume fraction to fiber bridging in a DCB specimen. Results from this demonstration are presented in terms of DCB specimen load-displacement responses.

Probabilistic Approaches for Multi-Hazard Risk Assessment of Structures and Systems

NASA Astrophysics Data System (ADS)

Kwag, Shinyoung

Performance assessment of structures, systems, and components for multi-hazard scenarios has received significant attention in recent years. However, the concept of multi-hazard analysis is quite broad in nature and the focus of existing literature varies across a wide range of problems. In some cases, such studies focus on hazards that either occur simultaneously or are closely correlated with each other. For example, seismically induced flooding or seismically induced fires. In other cases, multi-hazard studies relate to hazards that are not dependent or correlated but have strong likelihood of occurrence at different times during the lifetime of a structure. The current approaches for risk assessment need enhancement to account for multi-hazard risks. It must be able to account for uncertainty propagation in a systems-level analysis, consider correlation among events or failure modes, and allow integration of newly available information from continually evolving simulation models, experimental observations, and field measurements. This dissertation presents a detailed study that proposes enhancements by incorporating Bayesian networks and Bayesian updating within a performance-based probabilistic framework. The performance-based framework allows propagation of risk as well as uncertainties in the risk estimates within a systems analysis. Unlike conventional risk assessment techniques such as a fault-tree analysis, a Bayesian network can account for statistical dependencies and correlations among events/hazards. The proposed approach is extended to develop a risk-informed framework for quantitative validation and verification of high fidelity system-level simulation tools. Validation of such simulations can be quite formidable within the context of a multi-hazard risk assessment in nuclear power plants. The efficiency of this approach lies in identification of critical events, components, and systems that contribute to the overall risk. Validation of any event or component on the critical path is relatively more important in a risk-informed environment. Significance of multi-hazard risk is also illustrated for uncorrelated hazards of earthquakes and high winds which may result in competing design objectives. It is also illustrated that the number of computationally intensive nonlinear simulations needed in performance-based risk assessment for external hazards can be significantly reduced by using the power of Bayesian updating in conjunction with the concept of equivalent limit-state.

Does regional disadvantage affect health-related sport and physical activity level? A multi-level analysis of individual behaviour.

PubMed

Wicker, Pamela; Downward, Paul; Lera-López, Fernando

2017-11-01

This study examines the role of regional government quality in health-related participation in sport and physical activity among adults (18-64 years) in 28 European countries. The importance of the analysis rests in the relative autonomy that regional and local governments have over policy decisions connected with sport and physical activity. While existing studies have focussed on economic and infrastructural investment and expenditure, this research investigates the quality of regional governments across 208 regions within 28 European countries. The individual-level data stem from the 2013 Eurobarometer 80.2 (n = 18,675) and were combined with regional-level data from Eurostat. An individual's level of participation in sport and physical activity was measured by three variables reflecting whether an individual's activity level is below, meets, or exceeds the recommendations of the World Health Organization. The results of multi-level analyses reveal that regional government quality has a significant and positive association with individual participation in sport and physical activity at a level meeting or exceeding the guidelines. The impact is much larger than that of regional gross domestic product per capita, indicating that regional disadvantage in terms of political quality is more relevant than being disadvantaged in terms of economic wealth.

Multi-level stressor analysis from the DNA/biochemical level to community levels in an urban stream and integrative health response (IHR) assessments.

PubMed

Lee, Jae Hoon; Kim, Joon Ha; Oh, Hee-Mock; An, Kwang-Guk

2013-01-01

The objectives of this study were to identify multi-level stressors at the DNA/biochemical level to the community level in fish in an urban stream and to develop an integrative health response (IHR) model for ecological health diagnosis. A pristine control site (S (c) ) and an impacted site (S (i) ) were selected from among seven pre-screened sites studied over seven years. Various chemical analyses indicated that nutrient enrichment (Nitrogen, Phosphorus) and organic pollution were significantly greater (t > 8.783, p < 0.01) at the S (i) site compared to the S (c) site. Single-cell gel electrophoresis (comet assays) of DNA-level impairment indicated significantly (t = 5.678, p < 0.01) greater tail intensity, expressed as % tail-DNA, at the S (i) site and genotoxic responses were detected in the downstream reach. Ethoxyresorufin-O-deethylase (EROD) assays, as a physiological bioindicator, were 2.8-fold higher (p < 0.05, NK-test after ANOVA) at the S (i) site. Tissue analysis using a necropsy-based health assessment index (NHAI) showed distinct internal organ disorders in three tissues, i.e., liver, kidney, and gill, at the S (i) site. Population-level analysis using the sentinel species Zacco platypus showed that the regression coefficient (b) was 3.012 for the S (i) site and 2.915 for the S (c) site, indicating population skewness in the downstream reach. Community-level health was impaired at the S (i) site based on an index of biological integrity (IBI), and physical habitat modifications were identified by a qualitative habitat evaluation index (QHEI). Overall, the model values for the integrative health response (IHR), developed using the star plot approach, were 3.22 (80.5%) at the S (c) site and 0.74 (18.5%) at the S (i) site, indicating that, overall, ecological health impairments were evident in the urban reach. Our study was based on multi-level approaches using biological organization and the results suggest that there is a pivotal point of linkage between mechanistic understanding and real ecological consequences of environmental stressors.

A multi-level simulation platform of natural gas internal reforming solid oxide fuel cell-gas turbine hybrid generation system - Part II. Balancing units model library and system simulation

NASA Astrophysics Data System (ADS)

Bao, Cheng; Cai, Ningsheng; Croiset, Eric

2011-10-01

Following our integrated hierarchical modeling framework of natural gas internal reforming solid oxide fuel cell (IRSOFC), this paper firstly introduces the model libraries of main balancing units, including some state-of-the-art achievements and our specific work. Based on gPROMS programming code, flexible configuration and modular design are fully realized by specifying graphically all unit models in each level. Via comparison with the steady-state experimental data of Siemens-Westinghouse demonstration system, the in-house multi-level SOFC-gas turbine (GT) simulation platform is validated to be more accurate than the advanced power system analysis tool (APSAT). Moreover, some units of the demonstration system are designed reversely for analysis of a typically part-load transient process. The framework of distributed and dynamic modeling in most of units is significant for the development of control strategies in the future.

Multi-ethnic analysis reveals soluble L-selectin may be post-transcriptionally regulated by 3′UTR polymorphism: the Multi-Ethnic Study of Atherosclerosis (MESA)

PubMed Central

Berardi, Cecilia; Larson, Nicholas B.; Decker, Paul A.; Wassel, Christina L.; Kirsch, Phillip S.; Pankow, James S.; Sale, Michele M.; de Andrade, Mariza; Sicotte, Hugues; Tang, Weihong; Hanson, Naomi Q.; Tsai, Michael Y.; da Chen, Yii-Der I; Bielinski, Suzette J.

2015-01-01

L-selectin is constitutively expressed on leukocytes and mediates their interaction with endothelial cells during inflammation. Previous studies on the association of soluble L-selectin (sL-selectin) with cardiovascular disease (CVD) are inconsistent. Genetic variants associated with sL-selectin levels may be a better surrogate of levels over a lifetime. We explored the association of genetic variants and sL-selectin levels in a race/ethnicity stratified random sample of 2,403 participants in the Multi-Ethnic Study of Atherosclerosis (MESA). Through a genome-wide analysis with additive linear regression models, we found that rs12938 on the SELL gene accounted for a significant portion of the protein level variance across all four races/ethnicities. To evaluate potential additional associations, elastic net models were used for variants located in the SELL/SELP/SELE genetic region and an additional two SNPs, rs3917768 and rs4987361, were associated with sL-selectin levels in African Americans. These variants accounted for a portion of protein variance that ranged from 4% in Hispanic to 14% in African Americans. To investigate the relationship of these variants with CVD, 6,317 subjects were used. No significant association was found between any of the identified SNPs and carotid intima-media thickness or presence of carotid plaque using linear and logistic regression, respectively. Similarly no significant results were found for coronary artery calcium or coronary heart disease events. In conclusion, we found that variants within the SELL gene are associated with sL-selectin levels. Despite accounting for a significant portion of the protein level variance, none of the variants was associated with clinical or subclinical CVD. PMID:25576479

Automated Geo/Co-Registration of Multi-Temporal Very-High-Resolution Imagery.

PubMed

Han, Youkyung; Oh, Jaehong

2018-05-17

For time-series analysis using very-high-resolution (VHR) multi-temporal satellite images, both accurate georegistration to the map coordinates and subpixel-level co-registration among the images should be conducted. However, applying well-known matching methods, such as scale-invariant feature transform and speeded up robust features for VHR multi-temporal images, has limitations. First, they cannot be used for matching an optical image to heterogeneous non-optical data for georegistration. Second, they produce a local misalignment induced by differences in acquisition conditions, such as acquisition platform stability, the sensor's off-nadir angle, and relief displacement of the considered scene. Therefore, this study addresses the problem by proposing an automated geo/co-registration framework for full-scene multi-temporal images acquired from a VHR optical satellite sensor. The proposed method comprises two primary steps: (1) a global georegistration process, followed by (2) a fine co-registration process. During the first step, two-dimensional multi-temporal satellite images are matched to three-dimensional topographic maps to assign the map coordinates. During the second step, a local analysis of registration noise pixels extracted between the multi-temporal images that have been mapped to the map coordinates is conducted to extract a large number of well-distributed corresponding points (CPs). The CPs are finally used to construct a non-rigid transformation function that enables minimization of the local misalignment existing among the images. Experiments conducted on five Kompsat-3 full scenes confirmed the effectiveness of the proposed framework, showing that the georegistration performance resulted in an approximately pixel-level accuracy for most of the scenes, and the co-registration performance further improved the results among all combinations of the georegistered Kompsat-3 image pairs by increasing the calculated cross-correlation values.

The Partition of Multi-Resolution LOD Based on Qtm

NASA Astrophysics Data System (ADS)

Hou, M.-L.; Xing, H.-Q.; Zhao, X.-S.; Chen, J.

2011-08-01

The partition hierarch of Quaternary Triangular Mesh (QTM) determine the accuracy of spatial analysis and application based on QTM. In order to resolve the problem that the partition hierarch of QTM is limited by the level of the computer hardware, the new method that Multi- Resolution LOD (Level of Details) based on QTM will be discussed in this paper. This method can make the resolution of the cells varying with the viewpoint position by partitioning the cells of QTM, selecting the particular area according to the viewpoint; dealing with the cracks caused by different subdivisions, it satisfies the request of unlimited partition in part.

Assortativity Patterns in Multi-dimensional Inter-organizational Networks: A Case Study of the Humanitarian Relief Sector

NASA Astrophysics Data System (ADS)

Zhao, Kang; Ngamassi, Louis-Marie; Yen, John; Maitland, Carleen; Tapia, Andrea

We use computational tools to study assortativity patterns in multi-dimensional inter-organizational networks on the basis of different node attributes. In the case study of an inter-organizational network in the humanitarian relief sector, we consider not only macro-level topological patterns, but also assortativity on the basis of micro-level organizational attributes. Unlike assortative social networks, this inter-organizational network exhibits disassortative or random patterns on three node attributes. We believe organizations' seek of complementarity is one of the main reasons for the special patterns. Our analysis also provides insights on how to promote collaborations among the humanitarian relief organizations.

Genre Analysis of Personal Statements: Analysis of Moves in Application Essays to Medical and Dental Schools

ERIC Educational Resources Information Center

Ding, Huiling

2007-01-01

Despite the important role the personal statement plays in the graduate school application processes, little research has been done on its functional features and little instruction has been given about it in academic writing courses. The author conducted a multi-level discourse analysis on a corpus of 30 medical/dental school application letters,…

Multi-level, multi-scale resource selection functions and resistance surfaces for conservation planning: Pumas as a case study

PubMed Central

Vickers, T. Winston; Ernest, Holly B.; Boyce, Walter M.

2017-01-01

The importance of examining multiple hierarchical levels when modeling resource use for wildlife has been acknowledged for decades. Multi-level resource selection functions have recently been promoted as a method to synthesize resource use across nested organizational levels into a single predictive surface. Analyzing multiple scales of selection within each hierarchical level further strengthens multi-level resource selection functions. We extend this multi-level, multi-scale framework to modeling resistance for wildlife by combining multi-scale resistance surfaces from two data types, genetic and movement. Resistance estimation has typically been conducted with one of these data types, or compared between the two. However, we contend it is not an either/or issue and that resistance may be better-modeled using a combination of resistance surfaces that represent processes at different hierarchical levels. Resistance surfaces estimated from genetic data characterize temporally broad-scale dispersal and successful breeding over generations, whereas resistance surfaces estimated from movement data represent fine-scale travel and contextualized movement decisions. We used telemetry and genetic data from a long-term study on pumas (Puma concolor) in a highly developed landscape in southern California to develop a multi-level, multi-scale resource selection function and a multi-level, multi-scale resistance surface. We used these multi-level, multi-scale surfaces to identify resource use patches and resistant kernel corridors. Across levels, we found puma avoided urban, agricultural areas, and roads and preferred riparian areas and more rugged terrain. For other landscape features, selection differed among levels, as did the scales of selection for each feature. With these results, we developed a conservation plan for one of the most isolated puma populations in the U.S. Our approach captured a wide spectrum of ecological relationships for a population, resulted in effective conservation planning, and can be readily applied to other wildlife species. PMID:28609466

Multi-level, multi-scale resource selection functions and resistance surfaces for conservation planning: Pumas as a case study.

PubMed

Zeller, Katherine A; Vickers, T Winston; Ernest, Holly B; Boyce, Walter M

2017-01-01

The importance of examining multiple hierarchical levels when modeling resource use for wildlife has been acknowledged for decades. Multi-level resource selection functions have recently been promoted as a method to synthesize resource use across nested organizational levels into a single predictive surface. Analyzing multiple scales of selection within each hierarchical level further strengthens multi-level resource selection functions. We extend this multi-level, multi-scale framework to modeling resistance for wildlife by combining multi-scale resistance surfaces from two data types, genetic and movement. Resistance estimation has typically been conducted with one of these data types, or compared between the two. However, we contend it is not an either/or issue and that resistance may be better-modeled using a combination of resistance surfaces that represent processes at different hierarchical levels. Resistance surfaces estimated from genetic data characterize temporally broad-scale dispersal and successful breeding over generations, whereas resistance surfaces estimated from movement data represent fine-scale travel and contextualized movement decisions. We used telemetry and genetic data from a long-term study on pumas (Puma concolor) in a highly developed landscape in southern California to develop a multi-level, multi-scale resource selection function and a multi-level, multi-scale resistance surface. We used these multi-level, multi-scale surfaces to identify resource use patches and resistant kernel corridors. Across levels, we found puma avoided urban, agricultural areas, and roads and preferred riparian areas and more rugged terrain. For other landscape features, selection differed among levels, as did the scales of selection for each feature. With these results, we developed a conservation plan for one of the most isolated puma populations in the U.S. Our approach captured a wide spectrum of ecological relationships for a population, resulted in effective conservation planning, and can be readily applied to other wildlife species.

Application of Ontology Technology in Health Statistic Data Analysis.

PubMed

Guo, Minjiang; Hu, Hongpu; Lei, Xingyun

2017-01-01

Research Purpose: establish health management ontology for analysis of health statistic data. Proposed Methods: this paper established health management ontology based on the analysis of the concepts in China Health Statistics Yearbook, and used protégé to define the syntactic and semantic structure of health statistical data. six classes of top-level ontology concepts and their subclasses had been extracted and the object properties and data properties were defined to establish the construction of these classes. By ontology instantiation, we can integrate multi-source heterogeneous data and enable administrators to have an overall understanding and analysis of the health statistic data. ontology technology provides a comprehensive and unified information integration structure of the health management domain and lays a foundation for the efficient analysis of multi-source and heterogeneous health system management data and enhancement of the management efficiency.

Decreased levels of sRAGE in follicular fluid from patients with PCOS.

PubMed

Wang, BiJun; Li, Jing; Yang, QingLing; Zhang, FuLi; Hao, MengMeng; Guo, YiHong

2017-03-01

This study aimed to explore the association between soluble receptor for advanced glycation end products (sRAGE) levels in follicular fluid and the number of oocytes retrieved and to evaluate the effect of sRAGE on vascular endothelial growth factor (VEGF) in granulosa cells in patients with polycystic ovarian syndrome (PCOS). Two sets of experiments were performed in this study. In part one, sRAGE and VEGF protein levels in follicular fluid samples from 39 patients with PCOS and 35 non-PCOS patients were measured by ELISA. In part two, ovarian granulosa cells were isolated from an additional 10 patients with PCOS and cultured. VEGF and SP1 mRNA and protein levels, as well as pAKT levels, were detected by real-time PCR and Western blotting after cultured cells were treated with different concentrations of sRAGE. Compared with the non-PCOS patients, patients with PCOS had lower sRAGE levels in follicular fluid. Multi-adjusted regression analysis showed that high sRAGE levels in follicular fluid predicted a lower Gn dose, more oocytes retrieved, and a better IVF outcome in the non-PCOS group. Logistic regression analysis showed that higher sRAGE levels predicted favorably IVF outcomes in the non-PCOS group. Multi-adjusted regression analysis also showed that high sRAGE levels in follicular fluid predicted a lower Gn dose in the PCOS group. Treating granulosa cells isolated from patients with PCOS with recombinant sRAGE decreased VEGF and SP1 mRNA and protein expression and pAKT levels in a dose-dependent manner. © 2017 Society for Reproduction and Fertility.

Extension of a System Level Tool for Component Level Analysis

NASA Technical Reports Server (NTRS)

Majumdar, Alok; Schallhorn, Paul

2002-01-01

This paper presents an extension of a numerical algorithm for network flow analysis code to perform multi-dimensional flow calculation. The one dimensional momentum equation in network flow analysis code has been extended to include momentum transport due to shear stress and transverse component of velocity. Both laminar and turbulent flows are considered. Turbulence is represented by Prandtl's mixing length hypothesis. Three classical examples (Poiseuille flow, Couette flow and shear driven flow in a rectangular cavity) are presented as benchmark for the verification of the numerical scheme.

Extension of a System Level Tool for Component Level Analysis

NASA Technical Reports Server (NTRS)

Majumdar, Alok; Schallhorn, Paul; McConnaughey, Paul K. (Technical Monitor)

2001-01-01

This paper presents an extension of a numerical algorithm for network flow analysis code to perform multi-dimensional flow calculation. The one dimensional momentum equation in network flow analysis code has been extended to include momentum transport due to shear stress and transverse component of velocity. Both laminar and turbulent flows are considered. Turbulence is represented by Prandtl's mixing length hypothesis. Three classical examples (Poiseuille flow, Couette flow, and shear driven flow in a rectangular cavity) are presented as benchmark for the verification of the numerical scheme.

Medical image classification based on multi-scale non-negative sparse coding.

PubMed

Zhang, Ruijie; Shen, Jian; Wei, Fushan; Li, Xiong; Sangaiah, Arun Kumar

2017-11-01

With the rapid development of modern medical imaging technology, medical image classification has become more and more important in medical diagnosis and clinical practice. Conventional medical image classification algorithms usually neglect the semantic gap problem between low-level features and high-level image semantic, which will largely degrade the classification performance. To solve this problem, we propose a multi-scale non-negative sparse coding based medical image classification algorithm. Firstly, Medical images are decomposed into multiple scale layers, thus diverse visual details can be extracted from different scale layers. Secondly, for each scale layer, the non-negative sparse coding model with fisher discriminative analysis is constructed to obtain the discriminative sparse representation of medical images. Then, the obtained multi-scale non-negative sparse coding features are combined to form a multi-scale feature histogram as the final representation for a medical image. Finally, SVM classifier is combined to conduct medical image classification. The experimental results demonstrate that our proposed algorithm can effectively utilize multi-scale and contextual spatial information of medical images, reduce the semantic gap in a large degree and improve medical image classification performance. Copyright © 2017 Elsevier B.V. All rights reserved.

Uncovering Hidden Layers of Cell Cycle Regulation through Integrative Multi-omic Analysis

PubMed Central

Aviner, Ranen; Shenoy, Anjana; Elroy-Stein, Orna; Geiger, Tamar

2015-01-01

Studying the complex relationship between transcription, translation and protein degradation is essential to our understanding of biological processes in health and disease. The limited correlations observed between mRNA and protein abundance suggest pervasive regulation of post-transcriptional steps and support the importance of profiling mRNA levels in parallel to protein synthesis and degradation rates. In this work, we applied an integrative multi-omic approach to study gene expression along the mammalian cell cycle through side-by-side analysis of mRNA, translation and protein levels. Our analysis sheds new light on the significant contribution of both protein synthesis and degradation to the variance in protein expression. Furthermore, we find that translation regulation plays an important role at S-phase, while progression through mitosis is predominantly controlled by changes in either mRNA levels or protein stability. Specific molecular functions are found to be co-regulated and share similar patterns of mRNA, translation and protein expression along the cell cycle. Notably, these include genes and entire pathways not previously implicated in cell cycle progression, demonstrating the potential of this approach to identify novel regulatory mechanisms beyond those revealed by traditional expression profiling. Through this three-level analysis, we characterize different mechanisms of gene expression, discover new cycling gene products and highlight the importance and utility of combining datasets generated using different techniques that monitor distinct steps of gene expression. PMID:26439921

G14A-06- Analysis of the DORIS, GNSS, SLR, VLBI and Gravimetric Time Series at the GGOS Core Sites

NASA Technical Reports Server (NTRS)

Moreaux, G.; Lemoine, F.; Luceri, V.; Pavlis, E.; MacMillan, D.; Bonvalot, S.; Saunier, J.

2017-01-01

Analysis of the time series at the 3-4 multi-technique GGOS sites to analyze and compare the spectral content of the space geodetic and gravity time series. Evaluate the level of agreement between the space geodesy measurements and the physical tie vectors.

Bottom-Up Analysis of Single-Case Research Designs

ERIC Educational Resources Information Center

Parker, Richard I.; Vannest, Kimberly J.

2012-01-01

This paper defines and promotes the qualities of a "bottom-up" approach to single-case research (SCR) data analysis. Although "top-down" models, for example, multi-level or hierarchical linear models, are gaining momentum and have much to offer, interventionists should be cautious about analyses that are not easily understood, are not governed by…

Multi-criteria analysis of potential recovery facilities in a reverse supply chain

NASA Astrophysics Data System (ADS)

Nukala, Satish; Gupta, Surendra M.

2005-11-01

Analytic Hierarchy Process (AHP) has been employed by researchers for solving multi-criteria analysis problems. However, AHP is often criticized for its unbalanced scale of judgments and failure to precisely handle the inherent uncertainty and vagueness in carrying out the pair-wise comparisons. With an objective to address these drawbacks, in this paper, we employ a fuzzy approach in selecting potential recovery facilities in the strategic planning of a reverse supply chain network that addresses the decision maker's level of confidence in the fuzzy assessments and his/her attitude towards risk. A numerical example is considered to illustrate the methodology.

A Multi-Objective Decision-Making Model for Resources Allocation in Humanitarian Relief

DTIC Science & Technology

2007-03-01

Applied Mathematics and Computation 163, 2005, pp756 19. Malczewski, J., GIS and Multicriteria Decision Analysis , John Wiley and Sons, New York... used when interpreting the results of the analysis . (Raimo et al. 2002) (7) Sensitivity analysis Sensitivity analysis in a DA process answers...Budget Scenario Analysis The MILP is solved ( using LINDO 6.1) for high, medium and low budget scenarios in both damage degree levels. Tables 17 and

SPICODYN: A Toolbox for the Analysis of Neuronal Network Dynamics and Connectivity from Multi-Site Spike Signal Recordings.

PubMed

Pastore, Vito Paolo; Godjoski, Aleksandar; Martinoia, Sergio; Massobrio, Paolo

2018-01-01

We implemented an automated and efficient open-source software for the analysis of multi-site neuronal spike signals. The software package, named SPICODYN, has been developed as a standalone windows GUI application, using C# programming language with Microsoft Visual Studio based on .NET framework 4.5 development environment. Accepted input data formats are HDF5, level 5 MAT and text files, containing recorded or generated time series spike signals data. SPICODYN processes such electrophysiological signals focusing on: spiking and bursting dynamics and functional-effective connectivity analysis. In particular, for inferring network connectivity, a new implementation of the transfer entropy method is presented dealing with multiple time delays (temporal extension) and with multiple binary patterns (high order extension). SPICODYN is specifically tailored to process data coming from different Multi-Electrode Arrays setups, guarantying, in those specific cases, automated processing. The optimized implementation of the Delayed Transfer Entropy and the High-Order Transfer Entropy algorithms, allows performing accurate and rapid analysis on multiple spike trains from thousands of electrodes.

Multi-objective calibration and uncertainty analysis of hydrologic models; A comparative study between formal and informal methods

NASA Astrophysics Data System (ADS)

Shafii, M.; Tolson, B.; Matott, L. S.

2012-04-01

Hydrologic modeling has benefited from significant developments over the past two decades. This has resulted in building of higher levels of complexity into hydrologic models, which eventually makes the model evaluation process (parameter estimation via calibration and uncertainty analysis) more challenging. In order to avoid unreasonable parameter estimates, many researchers have suggested implementation of multi-criteria calibration schemes. Furthermore, for predictive hydrologic models to be useful, proper consideration of uncertainty is essential. Consequently, recent research has emphasized comprehensive model assessment procedures in which multi-criteria parameter estimation is combined with statistically-based uncertainty analysis routines such as Bayesian inference using Markov Chain Monte Carlo (MCMC) sampling. Such a procedure relies on the use of formal likelihood functions based on statistical assumptions, and moreover, the Bayesian inference structured on MCMC samplers requires a considerably large number of simulations. Due to these issues, especially in complex non-linear hydrological models, a variety of alternative informal approaches have been proposed for uncertainty analysis in the multi-criteria context. This study aims at exploring a number of such informal uncertainty analysis techniques in multi-criteria calibration of hydrological models. The informal methods addressed in this study are (i) Pareto optimality which quantifies the parameter uncertainty using the Pareto solutions, (ii) DDS-AU which uses the weighted sum of objective functions to derive the prediction limits, and (iii) GLUE which describes the total uncertainty through identification of behavioral solutions. The main objective is to compare such methods with MCMC-based Bayesian inference with respect to factors such as computational burden, and predictive capacity, which are evaluated based on multiple comparative measures. The measures for comparison are calculated both for calibration and evaluation periods. The uncertainty analysis methodologies are applied to a simple 5-parameter rainfall-runoff model, called HYMOD.

Earth Science Data Fusion with Event Building Approach

NASA Technical Reports Server (NTRS)

Lukashin, C.; Bartle, Ar.; Callaway, E.; Gyurjyan, V.; Mancilla, S.; Oyarzun, R.; Vakhnin, A.

2015-01-01

Objectives of the NASA Information And Data System (NAIADS) project are to develop a prototype of a conceptually new middleware framework to modernize and significantly improve efficiency of the Earth Science data fusion, big data processing and analytics. The key components of the NAIADS include: Service Oriented Architecture (SOA) multi-lingual framework, multi-sensor coincident data Predictor, fast into-memory data Staging, multi-sensor data-Event Builder, complete data-Event streaming (a work flow with minimized IO), on-line data processing control and analytics services. The NAIADS project is leveraging CLARA framework, developed in Jefferson Lab, and integrated with the ZeroMQ messaging library. The science services are prototyped and incorporated into the system. Merging the SCIAMACHY Level-1 observations and MODIS/Terra Level-2 (Clouds and Aerosols) data products, and ECMWF re- analysis will be used for NAIADS demonstration and performance tests in compute Cloud and Cluster environments.

X-framework: Space system failure analysis framework

NASA Astrophysics Data System (ADS)

Newman, John Steven

Space program and space systems failures result in financial losses in the multi-hundred million dollar range every year. In addition to financial loss, space system failures may also represent the loss of opportunity, loss of critical scientific, commercial and/or national defense capabilities, as well as loss of public confidence. The need exists to improve learning and expand the scope of lessons documented and offered to the space industry project team. One of the barriers to incorporating lessons learned include the way in which space system failures are documented. Multiple classes of space system failure information are identified, ranging from "sound bite" summaries in space insurance compendia, to articles in journals, lengthy data-oriented (what happened) reports, and in some rare cases, reports that treat not only the what, but also the why. In addition there are periodically published "corporate crisis" reports, typically issued after multiple or highly visible failures that explore management roles in the failure, often within a politically oriented context. Given the general lack of consistency, it is clear that a good multi-level space system/program failure framework with analytical and predictive capability is needed. This research effort set out to develop such a model. The X-Framework (x-fw) is proposed as an innovative forensic failure analysis approach, providing a multi-level understanding of the space system failure event beginning with the proximate cause, extending to the directly related work or operational processes and upward through successive management layers. The x-fw focus is on capability and control at the process level and examines: (1) management accountability and control, (2) resource and requirement allocation, and (3) planning, analysis, and risk management at each level of management. The x-fw model provides an innovative failure analysis approach for acquiring a multi-level perspective, direct and indirect causation of failures, and generating better and more consistent reports. Through this approach failures can be more fully understood, existing programs can be evaluated and future failures avoided. The x-fw development involved a review of the historical failure analysis and prevention literature, coupled with examination of numerous failure case studies. Analytical approaches included use of a relational failure "knowledge base" for classification and sorting of x-fw elements and attributes for each case. In addition a novel "management mapping" technique was developed as a means of displaying an integrated snapshot of indirect causes within the management chain. Further research opportunities will extend the depth of knowledge available for many of the component level cases. In addition, the x-fw has the potential to expand the scope of space sector lessons learned, and contribute to knowledge management and organizational learning.

Serum reference interval of ARCHITECT alpha-fetoprotein in healthy Chinese Han adults: Sub-analysis of a prospective multi-center study.

PubMed

Yan, Cunling; Yang, Jia; Wei, Lianhua; Hu, Jian; Song, Jiaqi; Wang, Xiaoqin; Han, Ruilin; Huang, Ying; Zhang, Wei; Soh, Andrew; Beshiri, Agim; Fan, Zhuping; Zheng, Yijie; Chen, Wei

2018-02-01

Alpha-fetoprotein (AFP) has been widely used in clinical practice for decades. However, large-scale survey of serum reference interval for ARCHITECT AFP is still absent in Chinese population. This study aimed to measure serum AFP levels in healthy Chinese Han subjects, which is a sub-analysis of an ongoing prospective, cross-sectional, multi-center study (ClinicalTrials.gov Identifier: NCT03047603). This analysis included a total of 530 participants (41.43±12.14years of age on average, 48.49% males), enrolled from 5 regional centers. Serum AFP level was measured by ARCHITECT immunoassay. Statistical analysis was performed using SAS 9.4 and R software. AFP distribution did not show significant correlation with age or sex. The overall median and interquartile range of AFP was 2.87 (2.09, 3.83) ng/mL. AFP level did not show a trend of increasing with age. The new reference interval was 2.0-7.07ng/mL (LOQ- 97.5th percentiles). The reference interval for ARCHITECT AFP is updated with the data of adequate number of healthy Han adults. This new reference interval is more practical and applicable in Chinese adults. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Multi-Tissue Computational Modeling Analyzes Pathophysiology of Type 2 Diabetes in MKR Mice

PubMed Central

Kumar, Amit; Harrelson, Thomas; Lewis, Nathan E.; Gallagher, Emily J.; LeRoith, Derek; Shiloach, Joseph; Betenbaugh, Michael J.

2014-01-01

Computational models using metabolic reconstructions for in silico simulation of metabolic disorders such as type 2 diabetes mellitus (T2DM) can provide a better understanding of disease pathophysiology and avoid high experimentation costs. There is a limited amount of computational work, using metabolic reconstructions, performed in this field for the better understanding of T2DM. In this study, a new algorithm for generating tissue-specific metabolic models is presented, along with the resulting multi-confidence level (MCL) multi-tissue model. The effect of T2DM on liver, muscle, and fat in MKR mice was first studied by microarray analysis and subsequently the changes in gene expression of frank T2DM MKR mice versus healthy mice were applied to the multi-tissue model to test the effect. Using the first multi-tissue genome-scale model of all metabolic pathways in T2DM, we found out that branched-chain amino acids' degradation and fatty acids oxidation pathway is downregulated in T2DM MKR mice. Microarray data showed low expression of genes in MKR mice versus healthy mice in the degradation of branched-chain amino acids and fatty-acid oxidation pathways. In addition, the flux balance analysis using the MCL multi-tissue model showed that the degradation pathways of branched-chain amino acid and fatty acid oxidation were significantly downregulated in MKR mice versus healthy mice. Validation of the model was performed using data derived from the literature regarding T2DM. Microarray data was used in conjunction with the model to predict fluxes of various other metabolic pathways in the T2DM mouse model and alterations in a number of pathways were detected. The Type 2 Diabetes MCL multi-tissue model may explain the high level of branched-chain amino acids and free fatty acids in plasma of Type 2 Diabetic subjects from a metabolic fluxes perspective. PMID:25029527

Expected frontiers: Incorporating weather uncertainty into a policy analysis using an integrated bi-level multi-objective optimization framework

EPA Science Inventory

Weather is the main driver in both plant use of nutrients and fate and transport of nutrients in the environment. In previous work, we evaluated a green tax for control of agricultural nutrients in a bi-level optimization framework that linked deterministic models. In this study,...

A Multi-Level Analysis of the Teacher Education Internship in Terms of Its Collaborative Dimension in Northern Cyprus

ERIC Educational Resources Information Center

Kuter, Sitkiye; Koc, Sabri

2009-01-01

Partnership is a two-way enterprise which becomes meaningful when the partners at different levels are fully engaged in mutual cooperation, aiming at promoting both trainees' and educators' professional growth. This case study, qualitative in nature, was conducted with administrators, educators, and trainees to examine the collaboration dimension…

Multi-country health surveys: are the analyses misleading?

PubMed

Masood, Mohd; Reidpath, Daniel D

2014-05-01

The aim of this paper was to review the types of approaches currently utilized in the analysis of multi-country survey data, specifically focusing on design and modeling issues with a focus on analyses of significant multi-country surveys published in 2010. A systematic search strategy was used to identify the 10 multi-country surveys and the articles published from them in 2010. The surveys were selected to reflect diverse topics and foci; and provide an insight into analytic approaches across research themes. The search identified 159 articles appropriate for full text review and data extraction. The analyses adopted in the multi-country surveys can be broadly classified as: univariate/bivariate analyses, and multivariate/multivariable analyses. Multivariate/multivariable analyses may be further divided into design- and model-based analyses. Of the 159 articles reviewed, 129 articles used model-based analysis, 30 articles used design-based analyses. Similar patterns could be seen in all the individual surveys. While there is general agreement among survey statisticians that complex surveys are most appropriately analyzed using design-based analyses, most researchers continued to use the more common model-based approaches. Recent developments in design-based multi-level analysis may be one approach to include all the survey design characteristics. This is a relatively new area, however, and there remains statistical, as well as applied analytic research required. An important limitation of this study relates to the selection of the surveys used and the choice of year for the analysis, i.e., year 2010 only. There is, however, no strong reason to believe that analytic strategies have changed radically in the past few years, and 2010 provides a credible snapshot of current practice.

Detailed Analysis of the Interoccurrence Time Statistics in Seismic Activity

NASA Astrophysics Data System (ADS)

Tanaka, Hiroki; Aizawa, Yoji

2017-02-01

The interoccurrence time statistics of seismiciry is studied theoretically as well as numerically by taking into account the conditional probability and the correlations among many earthquakes in different magnitude levels. It is known so far that the interoccurrence time statistics is well approximated by the Weibull distribution, but the more detailed information about the interoccurrence times can be obtained from the analysis of the conditional probability. Firstly, we propose the Embedding Equation Theory (EET), where the conditional probability is described by two kinds of correlation coefficients; one is the magnitude correlation and the other is the inter-event time correlation. Furthermore, the scaling law of each correlation coefficient is clearly determined from the numerical data-analysis carrying out with the Preliminary Determination of Epicenter (PDE) Catalog and the Japan Meteorological Agency (JMA) Catalog. Secondly, the EET is examined to derive the magnitude dependence of the interoccurrence time statistics and the multi-fractal relation is successfully formulated. Theoretically we cannot prove the universality of the multi-fractal relation in seismic activity; nevertheless, the theoretical results well reproduce all numerical data in our analysis, where several common features or the invariant aspects are clearly observed. Especially in the case of stationary ensembles the multi-fractal relation seems to obey an invariant curve, furthermore in the case of non-stationary (moving time) ensembles for the aftershock regime the multi-fractal relation seems to satisfy a certain invariant curve at any moving times. It is emphasized that the multi-fractal relation plays an important role to unify the statistical laws of seismicity: actually the Gutenberg-Richter law and the Weibull distribution are unified in the multi-fractal relation, and some universality conjectures regarding the seismicity are briefly discussed.

Multi-Level, Multi Time-Scale Fluorescence Intermittency of Photosynthetic LH2 Complexes: A Precursor of Non-Photochemical Quenching?

PubMed

Schörner, Mario; Beyer, Sebastian Reinhardt; Southall, June; Cogdell, Richard J; Köhler, Jürgen

2015-11-05

The light harvesting complex LH2 is a chromoprotein that is an ideal system for studying protein dynamics via the spectral fluctuations of the emission of its intrinsic chromophores. We have immobilized these complexes in a polymer film and studied the fluctuations of the fluorescence intensity from individual complexes over 9 orders of magnitude in time. Combining time-tagged detection of single photons with a change-point analysis has allowed the unambigeous identification of the various intensity levels due to the huge statistical basis of the data set. We propose that the observed intensity level fluctuations reflect conformational changes of the protein backbone that might be a precursor of the mechanism from which nonphotochemical quenching of higher plants has evolved.

Kinetic analysis of non-isothermal solid-state reactions: multi-stage modeling without assumptions in the reaction mechanism.

PubMed

Pomerantsev, Alexey L; Kutsenova, Alla V; Rodionova, Oxana Ye

2017-02-01

A novel non-linear regression method for modeling non-isothermal thermogravimetric data is proposed. Experiments for several heating rates are analyzed simultaneously. The method is applicable to complex multi-stage processes when the number of stages is unknown. Prior knowledge of the type of kinetics is not required. The main idea is a consequent estimation of parameters when the overall model is successively changed from one level of modeling to another. At the first level, the Avrami-Erofeev functions are used. At the second level, the Sestak-Berggren functions are employed with the goal to broaden the overall model. The method is tested using both simulated and real-world data. A comparison of the proposed method with a recently published 'model-free' deconvolution method is presented.

Acta Aeronautica et Astronautica Sinica,

DTIC Science & Technology

1983-07-28

substructural analysis in modal synthesis - two improved substructural assembling techniques 49 9-node quadrilateral isoparametric element 64 Application of laser...Time from Service Data, J. Aircraft, Vol. 15, No. 11, 1978. 48 MULTI-LEVEL SUBSTRUCTURAL ANALYSIS IN MODAL SYNTHESIS -- TWO IMPROVED SUBSTRUCTURAL...34 Modal Synthesis in Structural Dynamic Analysis ," Naching Institute of Aeronautics and Astronautics, 1979. 62a 8. Chang Te-wen, "Free-Interface Modal

Multi-Scale Impact and Compression-After-Impact Modeling of Reinforced Benzoxazine/Epoxy Composites using Micromechanics Approach

NASA Astrophysics Data System (ADS)

Montero, Marc Villa; Barjasteh, Ehsan; Baid, Harsh K.; Godines, Cody; Abdi, Frank; Nikbin, Kamran

A multi-scale micromechanics approach along with finite element (FE) model predictive tool is developed to analyze low-energy-impact damage footprint and compression-after-impact (CAI) of composite laminates which is also tested and verified with experimental data. Effective fiber and matrix properties were reverse-engineered from lamina properties using an optimization algorithm and used to assess damage at the micro-level during impact and post-impact FE simulations. Progressive failure dynamic analysis (PFDA) was performed for a two step-process simulation. Damage mechanisms at the micro-level were continuously evaluated during the analyses. Contribution of each failure mode was tracked during the simulations and damage and delamination footprint size and shape were predicted to understand when, where and why failure occurred during both impact and CAI events. The composite laminate was manufactured by the vacuum infusion of the aero-grade toughened Benzoxazine system into the fabric preform. Delamination footprint was measured using C-scan data from the impacted panels and compared with the predicated values obtained from proposed multi-scale micromechanics coupled with FE analysis. Furthermore, the residual strength was predicted from the load-displacement curve and compared with the experimental values as well.

Review on Graph Clustering and Subgraph Similarity Based Analysis of Neurological Disorders

PubMed Central

Thomas, Jaya; Seo, Dongmin; Sael, Lee

2016-01-01

How can complex relationships among molecular or clinico-pathological entities of neurological disorders be represented and analyzed? Graphs seem to be the current answer to the question no matter the type of information: molecular data, brain images or neural signals. We review a wide spectrum of graph representation and graph analysis methods and their application in the study of both the genomic level and the phenotypic level of the neurological disorder. We find numerous research works that create, process and analyze graphs formed from one or a few data types to gain an understanding of specific aspects of the neurological disorders. Furthermore, with the increasing number of data of various types becoming available for neurological disorders, we find that integrative analysis approaches that combine several types of data are being recognized as a way to gain a global understanding of the diseases. Although there are still not many integrative analyses of graphs due to the complexity in analysis, multi-layer graph analysis is a promising framework that can incorporate various data types. We describe and discuss the benefits of the multi-layer graph framework for studies of neurological disease. PMID:27258269

Review on Graph Clustering and Subgraph Similarity Based Analysis of Neurological Disorders.

PubMed

Thomas, Jaya; Seo, Dongmin; Sael, Lee

2016-06-01

How can complex relationships among molecular or clinico-pathological entities of neurological disorders be represented and analyzed? Graphs seem to be the current answer to the question no matter the type of information: molecular data, brain images or neural signals. We review a wide spectrum of graph representation and graph analysis methods and their application in the study of both the genomic level and the phenotypic level of the neurological disorder. We find numerous research works that create, process and analyze graphs formed from one or a few data types to gain an understanding of specific aspects of the neurological disorders. Furthermore, with the increasing number of data of various types becoming available for neurological disorders, we find that integrative analysis approaches that combine several types of data are being recognized as a way to gain a global understanding of the diseases. Although there are still not many integrative analyses of graphs due to the complexity in analysis, multi-layer graph analysis is a promising framework that can incorporate various data types. We describe and discuss the benefits of the multi-layer graph framework for studies of neurological disease.

Reliability Analysis of the MSC System

NASA Astrophysics Data System (ADS)

Kim, Young-Soo; Lee, Do-Kyoung; Lee, Chang-Ho; Woo, Sun-Hee

2003-09-01

MSC (Multi-Spectral Camera) is the payload of KOMPSAT-2, which is being developed for earth imaging in optical and near-infrared region. The design of the MSC is completed and its reliability has been assessed from part level to the MSC system level. The reliability was analyzed in worst case and the analysis results showed that the value complies the required value of 0.9. In this paper, a calculation method of reliability for the MSC system is described, and assessment result is presented and discussed.

A Hierarchical Model for Simultaneous Detection and Estimation in Multi-subject fMRI Studies

PubMed Central

Degras, David; Lindquist, Martin A.

2014-01-01

In this paper we introduce a new hierarchical model for the simultaneous detection of brain activation and estimation of the shape of the hemodynamic response in multi-subject fMRI studies. The proposed approach circumvents a major stumbling block in standard multi-subject fMRI data analysis, in that it both allows the shape of the hemodynamic response function to vary across region and subjects, while still providing a straightforward way to estimate population-level activation. An e cient estimation algorithm is presented, as is an inferential framework that not only allows for tests of activation, but also for tests for deviations from some canonical shape. The model is validated through simulations and application to a multi-subject fMRI study of thermal pain. PMID:24793829

What Do Differences Between Multi-voxel and Univariate Analysis Mean? How Subject-, Voxel-, and Trial-level Variance Impact fMRI Analysis

PubMed Central

Davis, Tyler; LaRocque, Karen F.; Mumford, Jeanette; Norman, Kenneth A.; Wagner, Anthony D.; Poldrack, Russell A.

2014-01-01

Multi-voxel pattern analysis (MVPA) has led to major changes in how fMRI data are analyzed and interpreted. Many studies now report both MVPA results and results from standard univariate voxel-wise analysis, often with the goal of drawing different conclusions from each. Because MVPA results can be sensitive to latent multidimensional representations and processes whereas univariate voxel-wise analysis cannot, one conclusion that is often drawn when MVPA and univariate results differ is that the activation patterns underlying MVPA results contain a multidimensional code. In the current study, we conducted simulations to formally test this assumption. Our findings reveal that MVPA tests are sensitive to the magnitude of voxel-level variability in the effect of a condition within subjects, even when the same linear relationship is coded in all voxels. We also find that MVPA is insensitive to subject-level variability in mean activation across an ROI, which is the primary variance component of interest in many standard univariate tests. Together, these results illustrate that differences between MVPA and univariate tests do not afford conclusions about the nature or dimensionality of the neural code. Instead, targeted tests of the informational content and/or dimensionality of activation patterns are critical for drawing strong conclusions about the representational codes that are indicated by significant MVPA results. PMID:24768930

Multi-coated spheres: recommended electrorheological particles

NASA Astrophysics Data System (ADS)

Wu, C. W.; Conrad, H.

1998-11-01

This paper considers the design of electrorheological (ER) particles. Multi-coated particles suspended in insulating (very weakly conducting) oil are recommended for obtaining high-performance ER suspensions. Only the outer two coatings determine the ER strength. The outermost coating should be a material with high dielectric constant, high electrical breakdown strength and a reasonable level of conductivity. The coating immediately below should be a highly conducting material. The inner coatings, including the core (which can be void), can be of any material having such a density that the composite particle has substantially the same density as the host liquid. Our analysis gives that multi-coated particles can have an ER shear strength as high as 29 kPa when the volume fraction of particles is 0.4 and the applied field is 5 kV 0022-3727/31/22/021/img5. Results in the literature provide support for the concept and analysis.

Public data and open source tools for multi-assay genomic investigation of disease.

PubMed

Kannan, Lavanya; Ramos, Marcel; Re, Angela; El-Hachem, Nehme; Safikhani, Zhaleh; Gendoo, Deena M A; Davis, Sean; Gomez-Cabrero, David; Castelo, Robert; Hansen, Kasper D; Carey, Vincent J; Morgan, Martin; Culhane, Aedín C; Haibe-Kains, Benjamin; Waldron, Levi

2016-07-01

Molecular interrogation of a biological sample through DNA sequencing, RNA and microRNA profiling, proteomics and other assays, has the potential to provide a systems level approach to predicting treatment response and disease progression, and to developing precision therapies. Large publicly funded projects have generated extensive and freely available multi-assay data resources; however, bioinformatic and statistical methods for the analysis of such experiments are still nascent. We review multi-assay genomic data resources in the areas of clinical oncology, pharmacogenomics and other perturbation experiments, population genomics and regulatory genomics and other areas, and tools for data acquisition. Finally, we review bioinformatic tools that are explicitly geared toward integrative genomic data visualization and analysis. This review provides starting points for accessing publicly available data and tools to support development of needed integrative methods. © The Author 2015. Published by Oxford University Press.

Multi-Level Anomaly Detection on Time-Varying Graph Data

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

Bridges, Robert A; Collins, John P; Ferragut, Erik M

This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labelled, streaming graph data. We introduce a generalization of the BTER model of Seshadhri et al. by adding flexibility to community structure, and use this model to perform multi-scale graph anomaly detection. Specifically, probability models describing coarse subgraphs are built by aggregating probabilities at finer levels, and these closely related hierarchical models simultaneously detect deviations from expectation. This technique provides insight into a graph's structure and internal context that may shed light on a detected event. Additionally, thismore » multi-scale analysis facilitates intuitive visualizations by allowing users to narrow focus from an anomalous graph to particular subgraphs or nodes causing the anomaly. For evaluation, two hierarchical anomaly detectors are tested against a baseline Gaussian method on a series of sampled graphs. We demonstrate that our graph statistics-based approach outperforms both a distribution-based detector and the baseline in a labeled setting with community structure, and it accurately detects anomalies in synthetic and real-world datasets at the node, subgraph, and graph levels. To illustrate the accessibility of information made possible via this technique, the anomaly detector and an associated interactive visualization tool are tested on NCAA football data, where teams and conferences that moved within the league are identified with perfect recall, and precision greater than 0.786.« less

Brief analysis of Jiangsu grid security and stability based on multi-infeed DC index in power system

NASA Astrophysics Data System (ADS)

Zhang, Wenjia; Wang, Quanquan; Ge, Yi; Huang, Junhui; Chen, Zhengfang

2018-02-01

The impact of Multi-infeed HVDC has gradually increased to security and stability operating in Jiangsu power grid. In this paper, an appraisal method of Multi-infeed HVDC power grid security and stability is raised with Multi-Infeed Effective Short Circuit Ratio, Multi-Infeed Interaction Factor and Commutation Failure Immunity Index. These indices are adopted in security and stability simulating calculation of Jiangsu Multi-infeed HVDC system. The simulation results indicate that Jiangsu power grid is operating with a strong DC system. It has high level of power grid security and stability, and meet the safety running requirements. Jinpin-Suzhou DC system is located in the receiving end with huge capacity, which is easily leading to commutation failure of the transmission line. In order to resolve this problem, dynamic reactive power compensation can be applied in power grid near Jinpin-Suzhou DC system. Simulation result shows this method is feasible to commutation failure.

Adaptive spatio-temporal filtering of disturbed ECGs: a multi-channel approach to heartbeat detection in smart clothing.

PubMed

Wiklund, Urban; Karlsson, Marcus; Ostlund, Nils; Berglin, Lena; Lindecrantz, Kaj; Karlsson, Stefan; Sandsjö, Leif

2007-06-01

Intermittent disturbances are common in ECG signals recorded with smart clothing: this is mainly because of displacement of the electrodes over the skin. We evaluated a novel adaptive method for spatio-temporal filtering for heartbeat detection in noisy multi-channel ECGs including short signal interruptions in single channels. Using multi-channel database recordings (12-channel ECGs from 10 healthy subjects), the results showed that multi-channel spatio-temporal filtering outperformed regular independent component analysis. We also recorded seven channels of ECG using a T-shirt with textile electrodes. Ten healthy subjects performed different sequences during a 10-min recording: resting, standing, flexing breast muscles, walking and pushups. Using adaptive multi-channel filtering, the sensitivity and precision was above 97% in nine subjects. Adaptive multi-channel spatio-temporal filtering can be used to detect heartbeats in ECGs with high noise levels. One application is heartbeat detection in noisy ECG recordings obtained by integrated textile electrodes in smart clothing.

Classification of the European Union member states according to the relative level of sustainable development.

PubMed

Anna, Bluszcz

Nowadays methods of measurement and assessment of the level of sustained development at the international, national and regional level are a current research problem, which requires multi-dimensional analysis. The relative assessment of the sustainability level of the European Union member states and the comparative analysis of the position of Poland relative to other countries was the aim of the conducted studies in the article. EU member states were treated as objects in the multi-dimensional space. Dimensions of space were specified by ten diagnostic variables describing the sustainability level of UE countries in three dimensions, i.e., social, economic and environmental. Because the compiled statistical data were expressed in different units of measure, taxonomic methods were used for building an aggregated measure to assess the level of sustainable development of EU member states, which through normalisation of variables enabled the comparative analysis between countries. Methodology of studies consisted of eight stages, which included, among others: defining data matrices, calculating the variability coefficient for all variables, which variability coefficient was under 10 %, division of variables into stimulants and destimulants, selection of the method of variable normalisation, developing matrices of normalised data, selection of the formula and calculating the aggregated indicator of the relative level of sustainable development of the EU countries, calculating partial development indicators for three studies dimensions: social, economic and environmental and the classification of the EU countries according to the relative level of sustainable development. Statistical date were collected based on the Polish Central Statistical Office publication.

Construction of Covariance Functions with Variable Length Fields

NASA Technical Reports Server (NTRS)

Gaspari, Gregory; Cohn, Stephen E.; Guo, Jing; Pawson, Steven

2005-01-01

This article focuses on construction, directly in physical space, of three-dimensional covariance functions parametrized by a tunable length field, and on an application of this theory to reproduce the Quasi-Biennial Oscillation (QBO) in the Goddard Earth Observing System, Version 4 (GEOS-4) data assimilation system. These Covariance models are referred to as multi-level or nonseparable, to associate them with the application where a multi-level covariance with a large troposphere to stratosphere length field gradient is used to reproduce the QBO from sparse radiosonde observations in the tropical lower stratosphere. The multi-level covariance functions extend well-known single level covariance functions depending only on a length scale. Generalizations of the first- and third-order autoregressive covariances in three dimensions are given, providing multi-level covariances with zero and three derivatives at zero separation, respectively. Multi-level piecewise rational covariances with two continuous derivatives at zero separation are also provided. Multi-level powerlaw covariances are constructed with continuous derivatives of all orders. Additional multi-level covariance functions are constructed using the Schur product of single and multi-level covariance functions. A multi-level powerlaw covariance used to reproduce the QBO in GEOS-4 is described along with details of the assimilation experiments. The new covariance model is shown to represent the vertical wind shear associated with the QBO much more effectively than in the baseline GEOS-4 system.

Multi-level discriminative dictionary learning with application to large scale image classification.

PubMed

Shen, Li; Sun, Gang; Huang, Qingming; Wang, Shuhui; Lin, Zhouchen; Wu, Enhua

2015-10-01

The sparse coding technique has shown flexibility and capability in image representation and analysis. It is a powerful tool in many visual applications. Some recent work has shown that incorporating the properties of task (such as discrimination for classification task) into dictionary learning is effective for improving the accuracy. However, the traditional supervised dictionary learning methods suffer from high computation complexity when dealing with large number of categories, making them less satisfactory in large scale applications. In this paper, we propose a novel multi-level discriminative dictionary learning method and apply it to large scale image classification. Our method takes advantage of hierarchical category correlation to encode multi-level discriminative information. Each internal node of the category hierarchy is associated with a discriminative dictionary and a classification model. The dictionaries at different layers are learnt to capture the information of different scales. Moreover, each node at lower layers also inherits the dictionary of its parent, so that the categories at lower layers can be described with multi-scale information. The learning of dictionaries and associated classification models is jointly conducted by minimizing an overall tree loss. The experimental results on challenging data sets demonstrate that our approach achieves excellent accuracy and competitive computation cost compared with other sparse coding methods for large scale image classification.

Ground water level, Water storage, Soil moisture, Precipitation Variability Using Multi Satellite Data during 2003-2016 Associated with California Drought

NASA Astrophysics Data System (ADS)

Li, J. W.; Singh, R. P.

2017-12-01

The agricultural market of California is a multi-billion-dollar industry, however in the recent years, the state is facing severe drought. It is important to have a deeper understanding of how the agriculture is affected by the amount of rainfall as well as the ground conditions in California. We have considered 5 regions (each 2 degree by 2 degree) covering whole of California. Multi satellite (MODIS Terra, GRACE, GLDAS) data through NASA Giovanni portal were used to study long period variability 2003 - 2016 of ground water level and storage, soil moisture, root zone moisture level, precipitation and normalized vegetation index (NDVI) in these 5 regions. Our detailed analysis of these parameters show a strong correlation between the NDVI and some of these parameters. NDVI represents greenness showing strong drought conditions during the period 2011-2016 due to poor rainfall and recharge of ground water in the mid and southern parts of California. Effect of ground water level and underground storage will be also discussed on the frequency of earthquakes in five regions of California. The mid and southern parts of California show increasing frequency of small earthquakes during drought periods.

[INDENA SPA company's patent portfolio of Ginkgo biloba preparation].

PubMed

Wang, Nan; Guo, Kai; Cheng, Xin-min; Liu, Wei

2015-10-01

INDENA SPA Company in Italy is a multi-national company that produces and sells plant extracts. Based on its own re- search advantages in the field of Ginkgo biloba preparation, the company protects its own products market effectively through building patent portfolio around the patents of its opponent. Based on the multi-angle analysis for patent portfolio of G. biloba preparation from the aspects of application time, legal status, technical development route, and patent portfolio layout, this article provides technical reference on research and development of G. biloba preparation, and the author suggest that Chinese applicants learn techniques and layout experiences of other patents fully to enhance the level of research and patent protection level.

Multi-scale visual analysis of time-varying electrocorticography data via clustering of brain regions

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward; ...

2017-06-06

There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our systemmore » detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.« less

Abnormal functional specialization within medial prefrontal cortex in high-functioning autism: a multi-voxel similarity analysis

PubMed Central

Meuwese, Julia D.I.; Towgood, Karren J.; Frith, Christopher D.; Burgess, Paul W.

2009-01-01

Multi-voxel pattern analyses have proved successful in ‘decoding’ mental states from fMRI data, but have not been used to examine brain differences associated with atypical populations. We investigated a group of 16 (14 males) high-functioning participants with autism spectrum disorder (ASD) and 16 non-autistic control participants (12 males) performing two tasks (spatial/verbal) previously shown to activate medial rostral prefrontal cortex (mrPFC). Each task manipulated: (i) attention towards perceptual versus self-generated information and (ii) reflection on another person's mental state (‘mentalizing'versus ‘non-mentalizing’) in a 2 × 2 design. Behavioral performance and group-level fMRI results were similar between groups. However, multi-voxel similarity analyses revealed strong differences. In control participants, the spatial distribution of activity generalized significantly between task contexts (spatial/verbal) when examining the same function (attention/mentalizing) but not when comparing different functions. This pattern was disrupted in the ASD group, indicating abnormal functional specialization within mrPFC, and demonstrating the applicability of multi-voxel pattern analysis to investigations of atypical populations. PMID:19174370

Multi-template tensor-based morphometry: Application to analysis of Alzheimer's disease

PubMed Central

Koikkalainen, Juha; Lötjönen, Jyrki; Thurfjell, Lennart; Rueckert, Daniel; Waldemar, Gunhild; Soininen, Hilkka

2012-01-01

In this paper methods for using multiple templates in tensor-based morphometry (TBM) are presented and comparedtothe conventional single-template approach. TBM analysis requires non-rigid registrations which are often subject to registration errors. When using multiple templates and, therefore, multiple registrations, it can be assumed that the registration errors are averaged and eventually compensated. Four different methods are proposed for multi-template TBM. The methods were evaluated using magnetic resonance (MR) images of healthy controls, patients with stable or progressive mild cognitive impairment (MCI), and patients with Alzheimer's disease (AD) from the ADNI database (N=772). The performance of TBM features in classifying images was evaluated both quantitatively and qualitatively. Classification results show that the multi-template methods are statistically significantly better than the single-template method. The overall classification accuracy was 86.0% for the classification of control and AD subjects, and 72.1%for the classification of stable and progressive MCI subjects. The statistical group-level difference maps produced using multi-template TBM were smoother, formed larger continuous regions, and had larger t-values than the maps obtained with single-template TBM. PMID:21419228

A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

PubMed

Budinich, Marko; Bourdon, Jérémie; Larhlimi, Abdelhalim; Eveillard, Damien

2017-01-01

Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs) for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA) and multi-objective flux variability analysis (MO-FVA). Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity) that take place at the ecosystem scale.

Zero-internal fields in nonpolar InGaN/GaN multi-quantum wells grown by the multi-buffer layer technique.

PubMed

Song, Hooyoung; Kim, Jin Soak; Kim, Eun Kyu; Seo, Yong Gon; Hwang, Sung-Min

2010-04-02

The potential of nonpolar a-plane InGaN/GaN multi-quantum wells (MQWs), which are free from a strong piezoelectric field, was demonstrated. An a-GaN template grown on an r-plane sapphire substrate by the multi-buffer layer technique showed high structural quality with an omega full width at half maximum value along the c-axis of 418 arcsec obtained from high-resolution x-ray diffraction analysis. From barrier analysis by deep level transient spectroscopy, it appeared that a-plane InGaN/GaN MQWs can solve the efficiency droop problem as they have a lower electron capture barrier than the c-plane sample. The peak shift of the temperature-dependent photoluminescence signal for the nonpolar InGaN/GaN MQWs was well fitted by Varshni's empirical equation with zero-internal fields. A high photoluminescence efficiency of 0.27 from this sample also showed that nonpolar MQWs can be the key factor to solve the efficiency limitation in conventional c-plane GaN based light emitting diodes.

Implications of multi-scale sea level and climate variability for coastal resources

USGS Publications Warehouse

Karamperidou, Christina; Engel, Victor; Lall, Upmanu; Stabenau, Erik; Smith, Thomas J.

2013-01-01

While secular changes in regional sea levels and their implications for coastal zone management have been studied extensively, less attention is being paid to natural fluctuations in sea levels, whose interaction with a higher mean level could have significant impacts on low-lying areas, such as wetlands. Here, the long record of sea level at Key West, FL is studied in terms of both the secular trend and the multi-scale sea level variations. This analysis is then used to explore implications for the Everglades National Park (ENP), which is recognized internationally for its ecological significance, and is the site of the largest wetland restoration project in the world. Very shallow topographic gradients (3–6 cm per km) make the region susceptible to small changes in sea level. Observations of surface water levels from a monitoring network within ENP exhibit both the long-term trends and the interannual-to-(multi)decadal variability that are observed in the Key West record. Water levels recorded at four long-term monitoring stations within ENP exhibit increasing trends approximately equal to or larger than the long-term trend at Key West. Time- and frequency-domain analyses highlight the potential influence of climate mechanisms, such as the El Niño/Southern Oscillation and the North Atlantic Oscillation (NAO), on Key West sea levels and marsh water levels, and the potential modulation of their influence by the background state of the North Atlantic Sea Surface Temperatures. In particular, the Key West sea levels are found to be positively correlated with the NAO index, while the two series exhibit high spectral power during the transition to a cold Atlantic Multidecadal Oscillation (AMO). The correlation between the Key West sea levels and the NINO3 Index reverses its sign in coincidence with a reversal of the AMO phase. Water levels in ENP are also influenced by precipitation and freshwater releases from the northern boundary of the Park. The analysis of both climate variability and climate change in such wetlands is needed to inform management practices in coastal wetland zones around the world.

Assessing intervention fidelity in a multi-level, multi-component, multi-site program: the Children's Healthy Living (CHL) program.

PubMed

Butel, Jean; Braun, Kathryn L; Novotny, Rachel; Acosta, Mark; Castro, Rose; Fleming, Travis; Powers, Julianne; Nigg, Claudio R

2015-12-01

Addressing complex chronic disease prevention, like childhood obesity, requires a multi-level, multi-component culturally relevant approach with broad reach. Models are lacking to guide fidelity monitoring across multiple levels, components, and sites engaged in such interventions. The aim of this study is to describe the fidelity-monitoring approach of The Children's Healthy Living (CHL) Program, a multi-level multi-component intervention in five Pacific jurisdictions. A fidelity-monitoring rubric was developed. About halfway during the intervention, community partners were randomly selected and interviewed independently by local CHL staff and by Coordinating Center representatives to assess treatment fidelity. Ratings were compared and discussed by local and Coordinating Center staff. There was good agreement between the teams (Kappa = 0.50, p < 0.001), and intervention improvement opportunities were identified through data review and group discussion. Fidelity for the multi-level, multi-component, multi-site CHL intervention was successfully assessed, identifying adaptations as well as ways to improve intervention delivery prior to the end of the intervention.

Multi-level trellis coded modulation and multi-stage decoding

NASA Technical Reports Server (NTRS)

Costello, Daniel J., Jr.; Wu, Jiantian; Lin, Shu

1990-01-01

Several constructions for multi-level trellis codes are presented and many codes with better performance than previously known codes are found. These codes provide a flexible trade-off between coding gain, decoding complexity, and decoding delay. New multi-level trellis coded modulation schemes using generalized set partitioning methods are developed for Quadrature Amplitude Modulation (QAM) and Phase Shift Keying (PSK) signal sets. New rotationally invariant multi-level trellis codes which can be combined with differential encoding to resolve phase ambiguity are presented.

Barriers to Uptake of Conservation Agriculture in southern Africa: Multi-level Analyses from Malawi

NASA Astrophysics Data System (ADS)

Dougill, Andrew; Stringer, Lindsay; Whitfield, Stephen; Wood, Ben; Chinseu, Edna

2015-04-01

Conservation agriculture is a key set of actions within the growing body of climate-smart agriculture activities being advocated and rolled out across much of the developing world. Conservation agriculture has purported benefits for environmental quality, food security and the sustained delivery of ecosystem services. In this paper, new multi-level analyses are presented, assessing the current barriers to adoption of conservation agriculture practices in Malawi. Despite significant donor initiatives that have targeted conservation agriculture projects, uptake rates remain low. This paper synthesises studies from across 3 levels in Malawi: i.) national level- drawing on policy analysis, interviews and a multi-stakeholder workshop; ii.) district level - via assessments of development plans and District Office and extension service support, and; iii) local level - through data gained during community / household level studies in Dedza District that have gained significant donor support for conservation agriculture as a component of climate smart agriculture initiatives. The national level multi-stakeholder Conservation Agriculture workshop identified three areas requiring collaborative research and outlined routes for the empowerment of the National Conservation Agriculture Task Force to advance uptake of conservation agriculture and deliver associated benefits in terms of agricultural development, climate adaptation and mitigation. District level analyses highlight that whilst District Development Plans are now checked against climate change adaptation and mitigation criteria, capacity and knowledge limitations exist at the District level, preventing project interventions from being successfully up-scaled. Community level assessments highlight the need for increased community participation at the project-design phase and identify a pressing requirement for conservation agriculture planning processes (in particular those driven by investments in climate-smart agriculture) to better accommodate, and respond to, the differentiated needs of marginalised groups (e.g. poor, elderly, carers). We identify good practices that can be used to design, plan and implement conservation agriculture projects such that the multiple benefits can be realised. We further outline changes to multi-level policy and institutional arrangements to facilitate greater adoption of conservation agriculture in Malawi, noting the vital importance of District-level institutions and amendments and capacity building required within agricultural extension services. We highlight the need for capacity building and support to ensure conservation agriculture's multiple benefits are realised more widely as a route towards sustainable land management.

Evaluating the Impacts of ICT Use: A Multi-Level Analysis with Hierarchical Linear Modeling

ERIC Educational Resources Information Center

Song, Hae-Deok; Kang, Taehoon

2012-01-01

The purpose of this study is to evaluate the impacts of ICT use on achievements by considering not only ICT use, but also the process and background variables that influence ICT use at both the student- and school-level. This study was conducted using data from the 2010 Survey of Seoul Education Longitudinal Research. A Hierarchical Linear…

Assessing the Primary Schools--A Multi-Dimensional Approach: A School Level Analysis Based on Indian Data

ERIC Educational Resources Information Center

Sengupta, Atanu; Pal, Naibedya Prasun

2012-01-01

Primary education is essential for the economic development in any country. Most studies give more emphasis to the final output (such as literacy, enrolment etc.) rather than the delivery of the entire primary education system. In this paper, we study the school level data from an Indian district, collected under the official DISE statistics. We…

An Analysis of Turkey's PISA 2015 Results Using Two-Level Hierarchical Linear Modelling

ERIC Educational Resources Information Center

Atas, Dogu; Karadag, Özge

2017-01-01

In the field of education, most of the data collected are multi-level structured. Cities, city based schools, school based classes and finally students in the classrooms constitute a hierarchical structure. Hierarchical linear models give more accurate results compared to standard models when the data set has a structure going far as individuals,…

Rationalization and the Individuals with Disabilities Education Act: Exploring the Characteristics of Multi-Level Performance Monitoring and Improvement

ERIC Educational Resources Information Center

Mahu, Robert J.

2017-01-01

Performance measurement has emerged as a management tool that, accompanied by advances in technology and data analysis, has allowed public officials to control public policy at multiple levels of government. In the United States, the federal government has used performance measurement as part of an accountability strategy that enables Congress and…

Evidencing Learning Outcomes: A Multi-Level, Multi-Dimensional Course Alignment Model

ERIC Educational Resources Information Center

Sridharan, Bhavani; Leitch, Shona; Watty, Kim

2015-01-01

This conceptual framework proposes a multi-level, multi-dimensional course alignment model to implement a contextualised constructive alignment of rubric design that authentically evidences and assesses learning outcomes. By embedding quality control mechanisms at each level for each dimension, this model facilitates the development of an aligned…

Developing the Coach Analysis and Intervention System (CAIS): establishing validity and reliability of a computerised systematic observation instrument.

PubMed

Cushion, Christopher; Harvey, Stephen; Muir, Bob; Nelson, Lee

2012-01-01

We outline the evolution of a computerised systematic observation tool and describe the process for establishing the validity and reliability of this new instrument. The Coach Analysis and Interventions System (CAIS) has 23 primary behaviours related to physical behaviour, feedback/reinforcement, instruction, verbal/non-verbal, questioning and management. The instrument also analyses secondary coach behaviour related to performance states, recipient, timing, content and questioning/silence. The CAIS is a multi-dimensional and multi-level mechanism able to provide detailed and contextualised data about specific coaching behaviours occurring in complex and nuanced coaching interventions and environments that can be applied to both practice sessions and competition.

Multi-criteria Analysis of Air Pollution with SO(2) and PM(10) in Urban Area Around the Copper Smelter in Bor, Serbia.

PubMed

Nikolić, Djordje; Milošević, Novica; Mihajlović, Ivan; Zivković, Zivan; Tasić, Viša; Kovačević, Renata; Petrović, Nevenka

2010-02-01

This work presents the results of 4 years long monitoring of concentrations of SO(2) gas and PM(10) in the urban area around the copper smelter in Bor. The contents of heavy metals Pb, Cd, Cu, Ni, and As in PM(10) were determined and obtained values were compared to the limit values provided in EU Directives. Manifold excess concentrations of all the components in the atmosphere of the urban area of the townsite Bor were registered. Through application of a multi-criteria analysis by using PROMETHEE/GAIA method, the zones were ranked according to the level of pollution.

Using multi-level data to estimate the effect of an 'alcogenic' environment on hazardous alcohol consumption in the former Soviet Union.

PubMed

Murphy, Adrianna; Roberts, Bayard; Ploubidis, George B; Stickley, Andrew; McKee, Martin

2014-05-01

The purpose of this study was to assess whether alcohol-related community characteristics act collectively to influence individual-level alcohol consumption in the former Soviet Union (fSU). Using multi-level data from nine countries in the fSU we conducted a factor analysis of seven alcohol-related community characteristics. The association between any latent factors underlying these characteristics and two measures of hazardous alcohol consumption was then analysed using a population average regression modelling approach. Our factor analysis produced one factor with an eigenvalue >1 (EV=1.28), which explained 94% of the variance. This factor was statistically significantly associated with increased odds of CAGE problem drinking (OR=1.40 (1.08-1.82)). The estimated association with EHD was not statistically significant (OR=1.10 (0.85-1.44)). Our findings suggest that a high number of beer, wine and spirit advertisements and high alcohol outlet density may work together to create an 'alcogenic' environment that encourages hazardous alcohol consumption in the fSU. Copyright © 2014 Elsevier Ltd. All rights reserved.

Knowledge-Driven Analysis Identifies a Gene–Gene Interaction Affecting High-Density Lipoprotein Cholesterol Levels in Multi-Ethnic Populations

PubMed Central

Ma, Li; Brautbar, Ariel; Boerwinkle, Eric; Sing, Charles F.

2012-01-01

Total cholesterol, low-density lipoprotein cholesterol, triglyceride, and high-density lipoprotein cholesterol (HDL-C) levels are among the most important risk factors for coronary artery disease. We tested for gene–gene interactions affecting the level of these four lipids based on prior knowledge of established genome-wide association study (GWAS) hits, protein–protein interactions, and pathway information. Using genotype data from 9,713 European Americans from the Atherosclerosis Risk in Communities (ARIC) study, we identified an interaction between HMGCR and a locus near LIPC in their effect on HDL-C levels (Bonferroni corrected P c = 0.002). Using an adaptive locus-based validation procedure, we successfully validated this gene–gene interaction in the European American cohorts from the Framingham Heart Study (P c = 0.002) and the Multi-Ethnic Study of Atherosclerosis (MESA; P c = 0.006). The interaction between these two loci is also significant in the African American sample from ARIC (P c = 0.004) and in the Hispanic American sample from MESA (P c = 0.04). Both HMGCR and LIPC are involved in the metabolism of lipids, and genome-wide association studies have previously identified LIPC as associated with levels of HDL-C. However, the effect on HDL-C of the novel gene–gene interaction reported here is twice as pronounced as that predicted by the sum of the marginal effects of the two loci. In conclusion, based on a knowledge-driven analysis of epistasis, together with a new locus-based validation method, we successfully identified and validated an interaction affecting a complex trait in multi-ethnic populations. PMID:22654671

Non-targeted metabolomic biomarkers and metabotypes of type 2 diabetes: A cross-sectional study of PREDIMED trial participants.

PubMed

Urpi-Sarda, M; Almanza-Aguilera, E; Llorach, R; Vázquez-Fresno, R; Estruch, R; Corella, D; Sorli, J V; Carmona, F; Sanchez-Pla, A; Salas-Salvadó, J; Andres-Lacueva, C

2018-02-20

To characterize the urinary metabolomic fingerprint and multi-metabolite signature associated with type 2 diabetes (T2D), and to classify the population into metabotypes related to T2D. A metabolomics analysis using the 1 H-NMR-based, non-targeted metabolomic approach was conducted to determine the urinary metabolomic fingerprint of T2D compared with non-T2D participants in the PREDIMED trial. The discriminant metabolite fingerprint was subjected to logistic regression analysis and ROC analyses to establish and to assess the multi-metabolite signature of T2D prevalence, respectively. Metabotypes associated with T2D were identified using the k-means algorithm. A total of 33 metabolites were significantly different (P<0.05) between T2D and non-T2D participants. The multi-metabolite signature of T2D comprised high levels of methylsuccinate, alanine, dimethylglycine and guanidoacetate, and reduced levels of glutamine, methylguanidine, 3-hydroxymandelate and hippurate, and had a 96.4% AUC, which was higher than the metabolites on their own and glucose. Amino-acid and carbohydrate metabolism were the main metabolic alterations in T2D, and various metabotypes were identified in the studied population. Among T2D participants, those with a metabotype of higher levels of phenylalanine, phenylacetylglutamine, p-cresol and acetoacetate had significantly higher levels of plasma glucose. The multi-metabolite signature of T2D highlights the altered metabolic fingerprint associated mainly with amino-acid, carbohydrate and microbiota metabolism. Metabotypes identified in this patient population could be related to higher risk of long-term cardiovascular events and therefore require further studies. Metabolomics is a useful tool for elucidating the metabolic complexity and interindividual variation in T2D towards the development of stratified precision nutrition and medicine. Trial registration at www.controlled-trials.com: ISRCTN35739639. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Evaluating flow cytometer performance with weighted quadratic least squares analysis of LED and multi-level bead data

PubMed Central

Parks, David R.; Khettabi, Faysal El; Chase, Eric; Hoffman, Robert A.; Perfetto, Stephen P.; Spidlen, Josef; Wood, James C.S.; Moore, Wayne A.; Brinkman, Ryan R.

2017-01-01

We developed a fully automated procedure for analyzing data from LED pulses and multi-level bead sets to evaluate backgrounds and photoelectron scales of cytometer fluorescence channels. The method improves on previous formulations by fitting a full quadratic model with appropriate weighting and by providing standard errors and peak residuals as well as the fitted parameters themselves. Here we describe the details of the methods and procedures involved and present a set of illustrations and test cases that demonstrate the consistency and reliability of the results. The automated analysis and fitting procedure is generally quite successful in providing good estimates of the Spe (statistical photoelectron) scales and backgrounds for all of the fluorescence channels on instruments with good linearity. The precision of the results obtained from LED data is almost always better than for multi-level bead data, but the bead procedure is easy to carry out and provides results good enough for most purposes. Including standard errors on the fitted parameters is important for understanding the uncertainty in the values of interest. The weighted residuals give information about how well the data fits the model, and particularly high residuals indicate bad data points. Known photoelectron scales and measurement channel backgrounds make it possible to estimate the precision of measurements at different signal levels and the effects of compensated spectral overlap on measurement quality. Combining this information with measurements of standard samples carrying dyes of biological interest, we can make accurate comparisons of dye sensitivity among different instruments. Our method is freely available through the R/Bioconductor package flowQB. PMID:28160404

Trace analysis of multi-class pesticide residues in Chinese medicinal health wines using gas chromatography with electron capture detection

PubMed Central

Kong, Wei-Jun; Liu, Qiu-Tao; Kong, Dan-Dan; Liu, Qian-Zhen; Ma, Xin-Ping; Yang, Mei-Hua

2016-01-01

A method is described for multi-residue, high-throughput determination of trace levels of 22 organochlorine pesticides (OCPs) and 5 pyrethroid pesticides (PYPs) in Chinese medicinal (CM) health wines using a QuEChERS (quick, easy, cheap, effective, rugged, and safe) based extraction method and gas chromatography-electron capture detection (GC-ECD). Several parameters were optimized to improve preparation and separation time while still maintaining high sensitivity. Validation tests of spiked samples showed good linearities for 27 pesticides (R = 0.9909–0.9996) over wide concentration ranges. Limits of detection (LODs) and quantification (LOQs) were measured at ng/L levels, 0.06–2 ng/L and 0.2–6 ng/L for OCPs and 0.02–3 ng/L and 0.06–7 ng/L for PYPs, respectively. Inter- and intra-day precision tests showed variations of 0.65–9.89% for OCPs and 0.98–13.99% for PYPs, respectively. Average recoveries were in the range of 47.74–120.31%, with relative standard deviations below 20%. The developed method was then applied to analyze 80 CM wine samples. Beta-BHC (Benzene hexachloride) was the most frequently detected pesticide at concentration levels of 5.67–31.55 mg/L, followed by delta-BHC, trans-chlordane, gamma-BHC, and alpha-BHC. The validated method is simple and economical, with adequate sensitivity for trace levels of multi-class pesticides. It could be adopted by laboratories for this and other types of complex matrices analysis. PMID:26883080

Trace analysis of multi-class pesticide residues in Chinese medicinal health wines using gas chromatography with electron capture detection

NASA Astrophysics Data System (ADS)

Kong, Wei-Jun; Liu, Qiu-Tao; Kong, Dan-Dan; Liu, Qian-Zhen; Ma, Xin-Ping; Yang, Mei-Hua

2016-02-01

A method is described for multi-residue, high-throughput determination of trace levels of 22 organochlorine pesticides (OCPs) and 5 pyrethroid pesticides (PYPs) in Chinese medicinal (CM) health wines using a QuEChERS (quick, easy, cheap, effective, rugged, and safe) based extraction method and gas chromatography-electron capture detection (GC-ECD). Several parameters were optimized to improve preparation and separation time while still maintaining high sensitivity. Validation tests of spiked samples showed good linearities for 27 pesticides (R = 0.9909-0.9996) over wide concentration ranges. Limits of detection (LODs) and quantification (LOQs) were measured at ng/L levels, 0.06-2 ng/L and 0.2-6 ng/L for OCPs and 0.02-3 ng/L and 0.06-7 ng/L for PYPs, respectively. Inter- and intra-day precision tests showed variations of 0.65-9.89% for OCPs and 0.98-13.99% for PYPs, respectively. Average recoveries were in the range of 47.74-120.31%, with relative standard deviations below 20%. The developed method was then applied to analyze 80 CM wine samples. Beta-BHC (Benzene hexachloride) was the most frequently detected pesticide at concentration levels of 5.67-31.55 mg/L, followed by delta-BHC, trans-chlordane, gamma-BHC, and alpha-BHC. The validated method is simple and economical, with adequate sensitivity for trace levels of multi-class pesticides. It could be adopted by laboratories for this and other types of complex matrices analysis.

When students can choose easy, medium, or hard homework problems

NASA Astrophysics Data System (ADS)

Teodorescu, Raluca E.; Seaton, Daniel T.; Cardamone, Caroline N.; Rayyan, Saif; Abbott, Jonathan E.; Barrantes, Analia; Pawl, Andrew; Pritchard, David E.

2012-02-01

We investigate student-chosen, multi-level homework in our Integrated Learning Environment for Mechanics [1] built using the LON-CAPA [2] open-source learning system. Multi-level refers to problems categorized as easy, medium, and hard. Problem levels were determined a priori based on the knowledge needed to solve them [3]. We analyze these problems using three measures: time-per-problem, LON-CAPA difficulty, and item difficulty measured by item response theory. Our analysis of student behavior in this environment suggests that time-per-problem is strongly dependent on problem category, unlike either score-based measures. We also found trends in student choice of problems, overall effort, and efficiency across the student population. Allowing students choice in problem solving seems to improve their motivation; 70% of students worked additional problems for which no credit was given.

A mixed integer bi-level DEA model for bank branch performance evaluation by Stackelberg approach

NASA Astrophysics Data System (ADS)

Shafiee, Morteza; Lotfi, Farhad Hosseinzadeh; Saleh, Hilda; Ghaderi, Mehdi

2016-03-01

One of the most complicated decision making problems for managers is the evaluation of bank performance, which involves various criteria. There are many studies about bank efficiency evaluation by network DEA in the literature review. These studies do not focus on multi-level network. Wu (Eur J Oper Res 207:856-864, 2010) proposed a bi-level structure for cost efficiency at the first time. In this model, multi-level programming and cost efficiency were used. He used a nonlinear programming to solve the model. In this paper, we have focused on multi-level structure and proposed a bi-level DEA model. We then used a liner programming to solve our model. In other hand, we significantly improved the way to achieve the optimum solution in comparison with the work by Wu (2010) by converting the NP-hard nonlinear programing into a mixed integer linear programming. This study uses a bi-level programming data envelopment analysis model that embodies internal structure with Stackelberg-game relationships to evaluate the performance of banking chain. The perspective of decentralized decisions is taken in this paper to cope with complex interactions in banking chain. The results derived from bi-level programming DEA can provide valuable insights and detailed information for managers to help them evaluate the performance of the banking chain as a whole using Stackelberg-game relationships. Finally, this model was applied in the Iranian bank to evaluate cost efficiency.

Multi-voxel pattern analysis reveals increased memory targeting and reduced use of retrieved details during single-agenda source monitoring

PubMed Central

McDuff, Susan G. R.; Frankel, Hillary C.; Norman, Kenneth A.

2009-01-01

We used multi-voxel pattern analysis (MVPA) of fMRI data to gain insight into how subjects’ retrieval agendas influence source memory judgments (was item X studied using source Y?). In Experiment 1, we used a single-agenda test where subjects judged whether items were studied with the targeted source or not. In Experiment 2, we used a multi-agenda test where subjects judged whether items were studied using the targeted source, studied using a different source, or nonstudied. To evaluate the differences between single- and multi-agenda source monitoring, we trained a classifier to detect source-specific fMRI activity at study, and then we applied the classifier to data from the test phase. We focused on trials where the targeted source and the actual source differed, so we could use MVPA to track neural activity associated with both the targeted source and the actual source. Our results indicate that single-agenda monitoring was associated with increased focus on the targeted source (as evidenced by increased targeted-source activity, relative to baseline) and reduced use of information relating to the actual, non-target source. In the multi-agenda experiment, high-levels of actual-source activity were associated with increased correct rejections, suggesting that subjects were using recollection of actual-source information to avoid source memory errors. In the single-agenda experiment, there were comparable levels of actual-source activity (suggesting that recollection was taking place), but the relationship between actual-source activity and behavior was absent (suggesting that subjects were failing to make proper use of this information). PMID:19144851

A Semi-Parametric Bayesian Mixture Modeling Approach for the Analysis of Judge Mediated Data

ERIC Educational Resources Information Center

Muckle, Timothy Joseph

2010-01-01

Existing methods for the analysis of ordinal-level data arising from judge ratings, such as the Multi-Facet Rasch model (MFRM, or the so-called Facets model) have been widely used in assessment in order to render fair examinee ability estimates in situations where the judges vary in their behavior or severity. However, this model makes certain…

Analysis of a dynamic model of guard cell signaling reveals the stability of signal propagation

NASA Astrophysics Data System (ADS)

Gan, Xiao; Albert, RéKa

Analyzing the long-term behaviors (attractors) of dynamic models of biological systems can provide valuable insight into biological phenotypes and their stability. We identified the long-term behaviors of a multi-level, 70-node discrete dynamic model of the stomatal opening process in plants. We reduce the model's huge state space by reducing unregulated nodes and simple mediator nodes, and by simplifying the regulatory functions of selected nodes while keeping the model consistent with experimental observations. We perform attractor analysis on the resulting 32-node reduced model by two methods: 1. converting it into a Boolean model, then applying two attractor-finding algorithms; 2. theoretical analysis of the regulatory functions. We conclude that all nodes except two in the reduced model have a single attractor; and only two nodes can admit oscillations. The multistability or oscillations do not affect the stomatal opening level in any situation. This conclusion applies to the original model as well in all the biologically meaningful cases. We further demonstrate the robustness of signal propagation by showing that a large percentage of single-node knockouts does not affect the stomatal opening level. Thus, we conclude that the complex structure of this signal transduction network provides multiple information propagation pathways while not allowing extensive multistability or oscillations, resulting in robust signal propagation. Our innovative combination of methods offers a promising way to analyze multi-level models.

Multi-Level Factors Affecting Entry into and Engagement in the HIV Continuum of Care in Iringa, Tanzania

PubMed Central

Layer, Erica H.; Kennedy, Caitlin E.; Beckham, Sarah W.; Mbwambo, Jessie K.; Likindikoki, Samuel; Davis, Wendy W.; Kerrigan, Deanna L.; Brahmbhatt, Heena

2014-01-01

Progression through the HIV continuum of care, from HIV testing to lifelong retention in antiretroviral therapy (ART) care and treatment programs, is critical to the success of HIV treatment and prevention efforts. However, significant losses occur at each stage of the continuum and little is known about contextual factors contributing to disengagement at these stages. This study sought to explore multi-level barriers and facilitators influencing entry into and engagement in the continuum of care in Iringa, Tanzania. We used a mixed-methods study design including facility-based assessments and interviews with providers and clients of HIV testing and treatment services; interviews, focus group discussions and observations with community-based providers and clients of HIV care and support services; and longitudinal interviews with men and women living with HIV to understand their trajectories in care. Data were analyzed using narrative analysis to identify key themes across levels and stages in the continuum of care. Participants identified multiple compounding barriers to progression through the continuum of care at the individual, facility, community and structural levels. Key barriers included the reluctance to engage in HIV services while healthy, rigid clinic policies, disrespectful treatment from service providers, stock-outs of supplies, stigma and discrimination, alternate healing systems, distance to health facilities and poverty. Social support from family, friends or support groups, home-based care providers, income generating opportunities and community mobilization activities facilitated engagement throughout the HIV continuum. Findings highlight the complex, multi-dimensional dynamics that individuals experience throughout the continuum of care and underscore the importance of a holistic and multi-level perspective to understand this process. Addressing barriers at each level is important to promoting increased engagement throughout the continuum. PMID:25119665

Multi-level obstruction in obstructive sleep apnoea: prevalence, severity and predictive factors.

PubMed

Phua, C Q; Yeo, W X; Su, C; Mok, P K H

2017-11-01

To characterise multi-level obstruction in terms of prevalence, obstructive sleep apnoea severity and predictive factors, and to collect epidemiological data on upper airway morphology in obstructive sleep apnoea patients. Retrospective review of 250 obstructive sleep apnoea patients. On clinical examination, 171 patients (68.4 per cent) had multi-level obstruction, 49 (19.6 per cent) had single-level obstruction and 30 (12 per cent) showed no obstruction. Within each category of obstructive sleep apnoea severity, multi-level obstruction was more prevalent. Multi-level obstruction was associated with severe obstructive sleep apnoea (more than 30 events per hour) (p = 0.001). Obstructive sleep apnoea severity increased with the number of obstruction sites (correlation coefficient = 0.303, p < 0.001). Multi-level obstruction was more likely in younger (p = 0.042), male (p = 0.045) patients, with high body mass index (more than 30 kg/m2) (p < 0.001). Palatal (p = 0.004), tongue (p = 0.026) and lateral pharyngeal wall obstructions (p = 0.006) were associated with severe obstructive sleep apnoea. Multi-level obstruction is more prevalent in obstructive sleep apnoea and is associated with increased severity. Obstruction at certain anatomical levels contributes more towards obstructive sleep apnoea severity.

Multilevel Dynamic Generalized Structured Component Analysis for Brain Connectivity Analysis in Functional Neuroimaging Data.

PubMed

Jung, Kwanghee; Takane, Yoshio; Hwang, Heungsun; Woodward, Todd S

2016-06-01

We extend dynamic generalized structured component analysis (GSCA) to enhance its data-analytic capability in structural equation modeling of multi-subject time series data. Time series data of multiple subjects are typically hierarchically structured, where time points are nested within subjects who are in turn nested within a group. The proposed approach, named multilevel dynamic GSCA, accommodates the nested structure in time series data. Explicitly taking the nested structure into account, the proposed method allows investigating subject-wise variability of the loadings and path coefficients by looking at the variance estimates of the corresponding random effects, as well as fixed loadings between observed and latent variables and fixed path coefficients between latent variables. We demonstrate the effectiveness of the proposed approach by applying the method to the multi-subject functional neuroimaging data for brain connectivity analysis, where time series data-level measurements are nested within subjects.

Virtual Beach v2.2 User Guide

EPA Science Inventory

Virtual Beach version 2.2 (VB 2.2) is a decision support tool. It is designed to construct site-specific Multi-Linear Regression (MLR) models to predict pathogen indicator levels (or fecal indicator bacteria, FIB) at recreational beaches. MLR analysis has outperformed persisten...

Multi-level multi-criteria analysis of alternative fuels for waste collection vehicles in the United States.

PubMed

Maimoun, Mousa; Madani, Kaveh; Reinhart, Debra

2016-04-15

Historically, the U.S. waste collection fleet was dominated by diesel-fueled waste collection vehicles (WCVs); the growing need for sustainable waste collection has urged decision makers to incorporate economically efficient alternative fuels, while mitigating environmental impacts. The pros and cons of alternative fuels complicate the decisions making process, calling for a comprehensive study that assesses the multiple factors involved. Multi-criteria decision analysis (MCDA) methods allow decision makers to select the best alternatives with respect to selection criteria. In this study, two MCDA methods, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Simple Additive Weighting (SAW), were used to rank fuel alternatives for the U.S. waste collection industry with respect to a multi-level environmental and financial decision matrix. The environmental criteria consisted of life-cycle emissions, tail-pipe emissions, water footprint (WFP), and power density, while the financial criteria comprised of vehicle cost, fuel price, fuel price stability, and fueling station availability. The overall analysis showed that conventional diesel is still the best option, followed by hydraulic-hybrid WCVs, landfill gas (LFG) sourced natural gas, fossil natural gas, and biodiesel. The elimination of the WFP and power density criteria from the environmental criteria ranked biodiesel 100 (BD100) as an environmentally better alternative compared to other fossil fuels (diesel and natural gas). This result showed that considering the WFP and power density as environmental criteria can make a difference in the decision process. The elimination of the fueling station and fuel price stability criteria from the decision matrix ranked fossil natural gas second after LFG-sourced natural gas. This scenario was found to represent the status quo of the waste collection industry. A sensitivity analysis for the status quo scenario showed the overall ranking of diesel and fossil natural gas to be more sensitive to changing fuel prices as compared to other alternatives. Copyright © 2016 Elsevier B.V. All rights reserved.

Outdoor air 1,3-butadiene monitoring: Comparison of performance of Radiello® passive samplers and active multi-sorbent bed tubes

NASA Astrophysics Data System (ADS)

Gallego, Eva; Teixidor, Pilar; Roca, Francisco Javier; Perales, José Francisco; Gadea, Enrique

2018-06-01

A comparison was made between the relative performance of active and passive sampling methods for the analysis of 1,3-butadiene in outdoor air. Active and passive sampling was conducted using multi-sorbent bed tubes (Carbotrap, Carbopack X, Carboxen 569) and RAD141 Radiello® diffusive samplers (filled with Carbopack X), respectively. Daily duplicate samples of multi-sorbent bed tubes were taken over a period of 14 days (9 + 5 days) at El Morell (Tarragona, Spain), near the petrochemical area. As 1,3-butadiene is a reactive pollutant and can be rapidly oxidized, half of the samplers were equipped with ozone scrubbers. Samples consisted in two tubes connected in series (front and back) to allow the determination of breakthrough. Quadruplicate samples of Radiello® tubes were taken over a period of 14 days (9 days and 5 days), too. During those days, ozone concentration was measured using RAD172 Radiello® samplers. In addition to this, daily duplicate samples of multi-sorbent bed tubes were taken in the city of Barcelona over a period of 8 days. Simultaneously, 4 samples of Radiello® tubes were exposed to outdoor air. Sampling was done throughout June and July 2017. Analysis was performed by thermal desorption coupled with gas chromatography/mass spectrometry. Analytical performance of the two sampling methods was evaluated by describing several quality assurance parameters, with results showing that performances are quite similar. They display low detection limits, good precision, linearity and desorption efficiency, low levels of blank values, and low breakthrough for multi-sorbent bed tubes. However, Radiello® samplers were not able to uptake episodic 1,3-butadiene high concentrations, leading to underestimation of real values. Hence, we can conclude that Radiello® samplers can be used for baseline 1,3-butadiene levels whereas multi-sorbent bed tubes would be advisable when relevant episodes are expected.

A Multi-Level Bayesian Analysis of Racial Bias in Police Shootings at the County-Level in the United States, 2011-2014.

PubMed

Ross, Cody T

2015-01-01

A geographically-resolved, multi-level Bayesian model is used to analyze the data presented in the U.S. Police-Shooting Database (USPSD) in order to investigate the extent of racial bias in the shooting of American civilians by police officers in recent years. In contrast to previous work that relied on the FBI's Supplemental Homicide Reports that were constructed from self-reported cases of police-involved homicide, this data set is less likely to be biased by police reporting practices. County-specific relative risk outcomes of being shot by police are estimated as a function of the interaction of: 1) whether suspects/civilians were armed or unarmed, and 2) the race/ethnicity of the suspects/civilians. The results provide evidence of a significant bias in the killing of unarmed black Americans relative to unarmed white Americans, in that the probability of being {black, unarmed, and shot by police} is about 3.49 times the probability of being {white, unarmed, and shot by police} on average. Furthermore, the results of multi-level modeling show that there exists significant heterogeneity across counties in the extent of racial bias in police shootings, with some counties showing relative risk ratios of 20 to 1 or more. Finally, analysis of police shooting data as a function of county-level predictors suggests that racial bias in police shootings is most likely to emerge in police departments in larger metropolitan counties with low median incomes and a sizable portion of black residents, especially when there is high financial inequality in that county. There is no relationship between county-level racial bias in police shootings and crime rates (even race-specific crime rates), meaning that the racial bias observed in police shootings in this data set is not explainable as a response to local-level crime rates.

A Multi-Level Bayesian Analysis of Racial Bias in Police Shootings at the County-Level in the United States, 2011–2014

PubMed Central

Ross, Cody T.

2015-01-01

A geographically-resolved, multi-level Bayesian model is used to analyze the data presented in the U.S. Police-Shooting Database (USPSD) in order to investigate the extent of racial bias in the shooting of American civilians by police officers in recent years. In contrast to previous work that relied on the FBI’s Supplemental Homicide Reports that were constructed from self-reported cases of police-involved homicide, this data set is less likely to be biased by police reporting practices. County-specific relative risk outcomes of being shot by police are estimated as a function of the interaction of: 1) whether suspects/civilians were armed or unarmed, and 2) the race/ethnicity of the suspects/civilians. The results provide evidence of a significant bias in the killing of unarmed black Americans relative to unarmed white Americans, in that the probability of being {black, unarmed, and shot by police} is about 3.49 times the probability of being {white, unarmed, and shot by police} on average. Furthermore, the results of multi-level modeling show that there exists significant heterogeneity across counties in the extent of racial bias in police shootings, with some counties showing relative risk ratios of 20 to 1 or more. Finally, analysis of police shooting data as a function of county-level predictors suggests that racial bias in police shootings is most likely to emerge in police departments in larger metropolitan counties with low median incomes and a sizable portion of black residents, especially when there is high financial inequality in that county. There is no relationship between county-level racial bias in police shootings and crime rates (even race-specific crime rates), meaning that the racial bias observed in police shootings in this data set is not explainable as a response to local-level crime rates. PMID:26540108

Multi-omics analysis provides insight to the Ignicoccus hospitalis - Nanoarchaeum equitans association

DOE PAGES

Rawle, Rachel A.; Hamerly, Timothy; Tripet, Brian P.; ...

2017-06-04

Studies of interspecies interactions are inherently difficult due to the complex mechanisms which enable these relationships. A model system for studying interspecies interactions is the marine hyperthermophiles Ignicoccus hospitalis and Nanoarchaeum equitans. Recent independently-conducted ‘omics’ analyses have generated insights into the molecular factors modulating this association. However, significant questions remain about the nature of the interactions between these archaea. We jointly analyzed multiple levels of omics datasets obtained from published, independent transcriptomics, proteomics, and metabolomics analyses. DAVID identified functionally-related groups enriched when I. hospitalis is grown alone or in co-culture with N. equitans. Enriched molecular pathways were subsequently visualized usingmore » interaction maps generated using STRING. Key findings of our multi-level omics analysis indicated that I. hospitalis provides precursors to N. equitans for energy metabolism. Analysis indicated an overall reduction in diversity of metabolic precursors in the I. hospitalis–N. equitans co-culture, which has been connected to the differential use of ribosomal subunits and was previously unnoticed. We also identified differences in precursors linked to amino acid metabolism, NADH metabolism, and carbon fixation, providing new insights into the metabolic adaptions of I. hospitalis enabling the growth of N. equitans. In conclusion, this multi-omics analysis builds upon previously identified cellular patterns while offering new insights into mechanisms that enable the I. hospitalis–N. equitans association. This study applies statistical and visualization techniques to a mixed-source omics dataset to yield a more global insight into a complex system, that was not readily discernable from separate omics studies.« less

Multi-omics analysis provides insight to the Ignicoccus hospitalis-Nanoarchaeum equitans association.

PubMed

Rawle, Rachel A; Hamerly, Timothy; Tripet, Brian P; Giannone, Richard J; Wurch, Louie; Hettich, Robert L; Podar, Mircea; Copié, Valerie; Bothner, Brian

2017-09-01

Studies of interspecies interactions are inherently difficult due to the complex mechanisms which enable these relationships. A model system for studying interspecies interactions is the marine hyperthermophiles Ignicoccus hospitalis and Nanoarchaeum equitans. Recent independently-conducted 'omics' analyses have generated insights into the molecular factors modulating this association. However, significant questions remain about the nature of the interactions between these archaea. We jointly analyzed multiple levels of omics datasets obtained from published, independent transcriptomics, proteomics, and metabolomics analyses. DAVID identified functionally-related groups enriched when I. hospitalis is grown alone or in co-culture with N. equitans. Enriched molecular pathways were subsequently visualized using interaction maps generated using STRING. Key findings of our multi-level omics analysis indicated that I. hospitalis provides precursors to N. equitans for energy metabolism. Analysis indicated an overall reduction in diversity of metabolic precursors in the I. hospitalis-N. equitans co-culture, which has been connected to the differential use of ribosomal subunits and was previously unnoticed. We also identified differences in precursors linked to amino acid metabolism, NADH metabolism, and carbon fixation, providing new insights into the metabolic adaptions of I. hospitalis enabling the growth of N. equitans. This multi-omics analysis builds upon previously identified cellular patterns while offering new insights into mechanisms that enable the I. hospitalis-N. equitans association. Our study applies statistical and visualization techniques to a mixed-source omics dataset to yield a more global insight into a complex system, that was not readily discernable from separate omics studies. Copyright © 2017 Elsevier B.V. All rights reserved.

Synchrotron IR microspectroscopy for protein structure analysis: Potential and questions

DOE PAGES

Yu, Peiqiang

2006-01-01

Synchrotron radiation-based Fourier transform infrared microspectroscopy (S-FTIR) has been developed as a rapid, direct, non-destructive, bioanalytical technique. This technique takes advantage of synchrotron light brightness and small effective source size and is capable of exploring the molecular chemical make-up within microstructures of a biological tissue without destruction of inherent structures at ultra-spatial resolutions within cellular dimension. To date there has been very little application of this advanced technique to the study of pure protein inherent structure at a cellular level in biological tissues. In this review, a novel approach was introduced to show the potential of the newly developed, advancedmore » synchrotron-based analytical technology, which can be used to localize relatively “pure“ protein in the plant tissues and relatively reveal protein inherent structure and protein molecular chemical make-up within intact tissue at cellular and subcellular levels. Several complex protein IR spectra data analytical techniques (Gaussian and Lorentzian multi-component peak modeling, univariate and multivariate analysis, principal component analysis (PCA), and hierarchical cluster analysis (CLA) are employed to relatively reveal features of protein inherent structure and distinguish protein inherent structure differences between varieties/species and treatments in plant tissues. By using a multi-peak modeling procedure, RELATIVE estimates (but not EXACT determinations) for protein secondary structure analysis can be made for comparison purpose. The issues of pro- and anti-multi-peaking modeling/fitting procedure for relative estimation of protein structure were discussed. By using the PCA and CLA analyses, the plant molecular structure can be qualitatively separate one group from another, statistically, even though the spectral assignments are not known. The synchrotron-based technology provides a new approach for protein structure research in biological tissues at ultraspatial resolutions.« less

Optimization of Multi-Fidelity Computer Experiments via the EQIE Criterion

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

He, Xu; Tuo, Rui; Jeff Wu, C. F.

Computer experiments based on mathematical models are powerful tools for understanding physical processes. This article addresses the problem of kriging-based optimization for deterministic computer experiments with tunable accuracy. Our approach is to use multi- delity computer experiments with increasing accuracy levels and a nonstationary Gaussian process model. We propose an optimization scheme that sequentially adds new computer runs by following two criteria. The first criterion, called EQI, scores candidate inputs with given level of accuracy, and the second criterion, called EQIE, scores candidate combinations of inputs and accuracy. Here, from simulation results and a real example using finite element analysis,more » our method out-performs the expected improvement (EI) criterion which works for single-accuracy experiments.« less

Optimization of Multi-Fidelity Computer Experiments via the EQIE Criterion

DOE PAGES

He, Xu; Tuo, Rui; Jeff Wu, C. F.

2017-01-31

Computer experiments based on mathematical models are powerful tools for understanding physical processes. This article addresses the problem of kriging-based optimization for deterministic computer experiments with tunable accuracy. Our approach is to use multi- delity computer experiments with increasing accuracy levels and a nonstationary Gaussian process model. We propose an optimization scheme that sequentially adds new computer runs by following two criteria. The first criterion, called EQI, scores candidate inputs with given level of accuracy, and the second criterion, called EQIE, scores candidate combinations of inputs and accuracy. Here, from simulation results and a real example using finite element analysis,more » our method out-performs the expected improvement (EI) criterion which works for single-accuracy experiments.« less

Nonlinear Analysis of Squeeze Film Dampers Applied to Gas Turbine Helicopter Engines.

DTIC Science & Technology

1980-11-01

calculate the stability (complex roots) of a multi-level gas turbine with aero- dynamic excitation. This program has been applied to the space shuttle...such phenomena as oil film whirl. This paper devlops an analysis technique incorporating modal analysis and fast Fourier transform tech- niques to...USING A SQUEEZE FILM BEARING By M. A. Simpson Research Engineer L. E. Barrett Reserach Assistant Professor Department of Mechanical and Aerospace

Multi-Level Analysis of Peer Support, Internet Self-Efficacy and E-Learning Outcomes--The Contextual Effects of Collectivism and Group Potency

ERIC Educational Resources Information Center

Chu, Regina Juchun; Chu, Anita Zichun

2010-01-01

The present study intends to explore the role of collectivism and group potency at group level in predicting individual Internet self-efficacy (ISE) and individual e-learning outcomes for people aged over 45. Group learning has been widely discussed in the research into online formats. However, less study has been carried out about how…

Multi-Level Sequential Pattern Mining Based on Prime Encoding

NASA Astrophysics Data System (ADS)

Lianglei, Sun; Yun, Li; Jiang, Yin

Encoding is not only to express the hierarchical relationship, but also to facilitate the identification of the relationship between different levels, which will directly affect the efficiency of the algorithm in the area of mining the multi-level sequential pattern. In this paper, we prove that one step of division operation can decide the parent-child relationship between different levels by using prime encoding and present PMSM algorithm and CROSS-PMSM algorithm which are based on prime encoding for mining multi-level sequential pattern and cross-level sequential pattern respectively. Experimental results show that the algorithm can effectively extract multi-level and cross-level sequential pattern from the sequence database.

Availability of convenience stores and adolescent alcohol use in Taiwan: a multi-level analysis of national surveys.

PubMed

Wang, Shi-Heng; Lin, I-Chin; Chen, Chuan-Yu; Chen, Duan-Rung; Chan, Ta-Chien; Chen, Wei J

2013-12-01

To examine the association between alcohol in school environments and adolescent alcohol use over the previous 6 months. A multi-level logistic regression analysis was performed of cross-sectional surveys conducted in 2004, 2005 and 2006. A total of 52 214 students aged 11-19 years from 387 middle or high schools were selected from a nationally representative, multi-stage, stratified probability sampling across Taiwan. Information on socio-demographic features and substance use experiences was collected using self-administered questionnaires. The alcohol in the environment was measured using the availability of convenience stores surrounding the schools. Using geographical information systems, the weighted numbers of convenience stores within 1 km, a 12-15-minute walk, of a school were calculated. The schools were later categorized into three subgroups via the tertile of nearby convenience stores. Considering the compositional characteristics, the availability of convenience stores was found to account for 1.5% of the school-level variance of youthful drinking. The odds ratios (95% confidence interval) of alcohol use over the previous 6 months among youth attending schools with medium and high availability were 1.04 (0.96-1.13) and 1.08 (1.00-1.17), respectively, with a P-value of 0.04 in the trend test. The greater availability of convenience stores near a school is associated with an increased risk of alcohol use among adolescents over the previous 6 months. © 2013 Society for the Study of Addiction.

UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning

NASA Astrophysics Data System (ADS)

Fernandez Galarreta, J.; Kerle, N.; Gerke, M.

2015-06-01

Structural damage assessment is critical after disasters but remains a challenge. Many studies have explored the potential of remote sensing data, but limitations of vertical data persist. Oblique imagery has been identified as more useful, though the multi-angle imagery also adds a new dimension of complexity. This paper addresses damage assessment based on multi-perspective, overlapping, very high resolution oblique images obtained with unmanned aerial vehicles (UAVs). 3-D point-cloud assessment for the entire building is combined with detailed object-based image analysis (OBIA) of façades and roofs. This research focuses not on automatic damage assessment, but on creating a methodology that supports the often ambiguous classification of intermediate damage levels, aiming at producing comprehensive per-building damage scores. We identify completely damaged structures in the 3-D point cloud, and for all other cases provide the OBIA-based damage indicators to be used as auxiliary information by damage analysts. The results demonstrate the usability of the 3-D point-cloud data to identify major damage features. Also the UAV-derived and OBIA-processed oblique images are shown to be a suitable basis for the identification of detailed damage features on façades and roofs. Finally, we also demonstrate the possibility of aggregating the multi-perspective damage information at building level.

Quantitative multi-modal NDT data analysis

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

Heideklang, René; Shokouhi, Parisa

2014-02-18

A single NDT technique is often not adequate to provide assessments about the integrity of test objects with the required coverage or accuracy. In such situations, it is often resorted to multi-modal testing, where complementary and overlapping information from different NDT techniques are combined for a more comprehensive evaluation. Multi-modal material and defect characterization is an interesting task which involves several diverse fields of research, including signal and image processing, statistics and data mining. The fusion of different modalities may improve quantitative nondestructive evaluation by effectively exploiting the augmented set of multi-sensor information about the material. It is the redundantmore » information in particular, whose quantification is expected to lead to increased reliability and robustness of the inspection results. There are different systematic approaches to data fusion, each with its specific advantages and drawbacks. In our contribution, these will be discussed in the context of nondestructive materials testing. A practical study adopting a high-level scheme for the fusion of Eddy Current, GMR and Thermography measurements on a reference metallic specimen with built-in grooves will be presented. Results show that fusion is able to outperform the best single sensor regarding detection specificity, while retaining the same level of sensitivity.« less

Are cats (Felis catus) from multi-cat households more stressed? Evidence from assessment of fecal glucocorticoid metabolite analysis.

PubMed

Ramos, D; Reche-Junior, A; Fragoso, P L; Palme, R; Yanasse, N K; Gouvêa, V R; Beck, A; Mills, D S

2013-10-02

Given the social and territorial features described in feral cats, it is commonly assumed that life in multi-cat households is stressful for domestic cats and suggested that cats kept as single pets are likely to have better welfare. On the other hand, it has been hypothesized that under high densities cats can organize themselves socially thus preventing stress when spatial dispersion is unavailable. This study was aimed at comparing the general arousal underpinning emotional distress in single housed cats and in cats from multi-cat households (2 and 3-4 cats) on the basis of fecal glucocorticoid metabolites (GCM) measured via enzyme immunoassay (EIA). GCM did not significantly vary as a function of living style (single, double or group-housing); highly stressed individuals were equally likely in the three groups. Young cats in multi-cat households had lower GCM, and overall cats that tolerate (as opposed to dislike) petting by the owners tended to have higher GCM levels. Other environmental aspects within cat houses (e.g. relationship with humans, resource availability) may play a more important role in day to day feline arousal levels than the number of cats per se. © 2013.

Absolute order-of-magnitude reasoning applied to a social multi-criteria evaluation framework

NASA Astrophysics Data System (ADS)

Afsordegan, A.; Sánchez, M.; Agell, N.; Aguado, J. C.; Gamboa, G.

2016-03-01

A social multi-criteria evaluation framework for solving a real-case problem of selecting a wind farm location in the regions of Urgell and Conca de Barberá in Catalonia (northeast of Spain) is studied. This paper applies a qualitative multi-criteria decision analysis approach based on linguistic labels assessment able to address uncertainty and deal with different levels of precision. This method is based on qualitative reasoning as an artificial intelligence technique for assessing and ranking multi-attribute alternatives with linguistic labels in order to handle uncertainty. This method is suitable for problems in the social framework such as energy planning which require the construction of a dialogue process among many social actors with high level of complexity and uncertainty. The method is compared with an existing approach, which has been applied previously in the wind farm location problem. This approach, consisting of an outranking method, is based on Condorcet's original method. The results obtained by both approaches are analysed and their performance in the selection of the wind farm location is compared in aggregation procedures. Although results show that both methods conduct to similar alternatives rankings, the study highlights both their advantages and drawbacks.

Digital analysis of Potomac River Basin ERTS imagery: Sedimentation levels at the Potomac-Anacostia confluence and strip mining in Allegheny County, Maryland

NASA Technical Reports Server (NTRS)

Schubert, J. S.; Macleod, N. H.

1973-01-01

Two simple algorithms for classification of sedimentation levels in water and for delineation of active strip mines are in use as part of the development of a more general resource management information system. ERTS MSS CCT's are processed so that each pixel in each channel is geographically referenced and can be accessed individually during whole frame, multi-channel analysis or partial frame analysis. The sedimentation analysis clearly separates classes representing the turbid Anacostia water, the less disturbed Potomac (really), and mud flats resulting from effluent of a major sewage treatment plant. Mud flats of organic or mineral origin are easily distinguished.

Interestingness measures and strategies for mining multi-ontology multi-level association rules from gene ontology annotations for the discovery of new GO relationships.

PubMed

Manda, Prashanti; McCarthy, Fiona; Bridges, Susan M

2013-10-01

The Gene Ontology (GO), a set of three sub-ontologies, is one of the most popular bio-ontologies used for describing gene product characteristics. GO annotation data containing terms from multiple sub-ontologies and at different levels in the ontologies is an important source of implicit relationships between terms from the three sub-ontologies. Data mining techniques such as association rule mining that are tailored to mine from multiple ontologies at multiple levels of abstraction are required for effective knowledge discovery from GO annotation data. We present a data mining approach, Multi-ontology data mining at All Levels (MOAL) that uses the structure and relationships of the GO to mine multi-ontology multi-level association rules. We introduce two interestingness measures: Multi-ontology Support (MOSupport) and Multi-ontology Confidence (MOConfidence) customized to evaluate multi-ontology multi-level association rules. We also describe a variety of post-processing strategies for pruning uninteresting rules. We use publicly available GO annotation data to demonstrate our methods with respect to two applications (1) the discovery of co-annotation suggestions and (2) the discovery of new cross-ontology relationships. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Integrating Model-Based Transmission Reduction into a multi-tier architecture

NASA Astrophysics Data System (ADS)

Straub, J.

A multi-tier architecture consists of numerous craft as part of the system, orbital, aerial, and surface tiers. Each tier is able to collect progressively greater levels of information. Generally, craft from lower-level tiers are deployed to a target of interest based on its identification by a higher-level craft. While the architecture promotes significant amounts of science being performed in parallel, this may overwhelm the computational and transmission capabilities of higher-tier craft and links (particularly the deep space link back to Earth). Because of this, a new paradigm in in-situ data processing is required. Model-based transmission reduction (MBTR) is such a paradigm. Under MBTR, each node (whether a single spacecraft in orbit of the Earth or another planet or a member of a multi-tier network) is given an a priori model of the phenomenon that it is assigned to study. It performs activities to validate this model. If the model is found to be erroneous, corrective changes are identified, assessed to ensure their significance for being passed on, and prioritized for transmission. A limited amount of verification data is sent with each MBTR assertion message to allow those that might rely on the data to validate the correct operation of the spacecraft and MBTR engine onboard. Integrating MBTR with a multi-tier framework creates an MBTR hierarchy. Higher levels of the MBTR hierarchy task lower levels with data collection and assessment tasks that are required to validate or correct elements of its model. A model of the expected conditions is sent to the lower level craft; which then engages its own MBTR engine to validate or correct the model. This may include tasking a yet lower level of craft to perform activities. When the MBTR engine at a given level receives all of its component data (whether directly collected or from delegation), it randomly chooses some to validate (by reprocessing the validation data), performs analysis and sends its own results (v- lidation and/or changes of model elements and supporting validation data) to its upstream node. This constrains data transmission to only significant (either because it includes a change or is validation data critical for assessing overall performance) information and reduces the processing requirements (by not having to process insignificant data) at higher-level nodes. This paper presents a framework for multi-tier MBTR and two demonstration mission concepts: an Earth sensornet and a mission to Mars. These multi-tier MBTR concepts are compared to a traditional mission approach.

Measuring Developmental Students' Mathematics Anxiety

ERIC Educational Resources Information Center

Ding, Yanqing

2016-01-01

This study conducted an item-level analysis of mathematics anxiety and examined the dimensionality of mathematics anxiety in a sample of developmental mathematics students (N = 162) by Multi-dimensional Random Coefficients Multinominal Logit Model (MRCMLM). The results indicate a moderately correlated factor structure of mathematics anxiety (r =…

Probabilistic sizing of laminates with uncertainties

NASA Technical Reports Server (NTRS)

Shah, A. R.; Liaw, D. G.; Chamis, C. C.

1993-01-01

A reliability based design methodology for laminate sizing and configuration for a special case of composite structures is described. The methodology combines probabilistic composite mechanics with probabilistic structural analysis. The uncertainties of constituent materials (fiber and matrix) to predict macroscopic behavior are simulated using probabilistic theory. Uncertainties in the degradation of composite material properties are included in this design methodology. A multi-factor interaction equation is used to evaluate load and environment dependent degradation of the composite material properties at the micromechanics level. The methodology is integrated into a computer code IPACS (Integrated Probabilistic Assessment of Composite Structures). Versatility of this design approach is demonstrated by performing a multi-level probabilistic analysis to size the laminates for design structural reliability of random type structures. The results show that laminate configurations can be selected to improve the structural reliability from three failures in 1000, to no failures in one million. Results also show that the laminates with the highest reliability are the least sensitive to the loading conditions.

Hierarchical patch-based co-registration of differently stained histopathology slides

NASA Astrophysics Data System (ADS)

Yigitsoy, Mehmet; Schmidt, Günter

2017-03-01

Over the past decades, digital pathology has emerged as an alternative way of looking at the tissue at subcellular level. It enables multiplexed analysis of different cell types at micron level. Information about cell types can be extracted by staining sections of a tissue block using different markers. However, robust fusion of structural and functional information from different stains is necessary for reproducible multiplexed analysis. Such a fusion can be obtained via image co-registration by establishing spatial correspondences between tissue sections. Spatial correspondences can then be used to transfer various statistics about cell types between sections. However, the multi-modal nature of images and sparse distribution of interesting cell types pose several challenges for the registration of differently stained tissue sections. In this work, we propose a co-registration framework that efficiently addresses such challenges. We present a hierarchical patch-based registration of intensity normalized tissue sections. Preliminary experiments demonstrate the potential of the proposed technique for the fusion of multi-modal information from differently stained digital histopathology sections.

Application of multi-criteria decision-making on strategic municipal solid waste management in Dalmatia, Croatia.

PubMed

Vego, Goran; Kucar-Dragicević, Savka; Koprivanac, Natalija

2008-11-01

The efficiency of providing a waste management system in the coastal part of Croatia consisting of four Dalmatian counties has been modelled. Two multi-criteria decision-making (MCDM) methods, PROMETHEE and GAIA, were applied to assist with the systematic analysis and evaluation of the alternatives. The analysis covered two levels; first, the potential number of waste management centres resulting from possible inter-county cooperation; and second, the relative merits of siting of waste management centres in the coastal or hinterland zone was evaluated. The problem was analysed according to several criteria; and ecological, economic, social and functional criteria sets were identified as relevant to the decision-making process. The PROMETHEE and GAIA methods were shown to be efficient tools for analysing the problem considered. Such an approach provided new insights to waste management planning at the strategic level, and gave a reason for rethinking some of the existing strategic waste management documents in Croatia.

Using of multi-walled carbon nanotubes electrode for adsorptive stripping voltammetric determination of ultratrace levels of RDX explosive in the environmental samples.

PubMed

Rezaei, Behzad; Damiri, Sajjad

2010-11-15

A study of the electrochemical behavior and determination of RDX, a high explosive, is described on a multi-walled carbon nanotubes (MWCNTs) modified glassy carbon electrode (GCE) using adsorptive stripping voltammetry and electrochemical impedance spectroscopy (EIS) techniques. The results indicated that MWCNTs electrode remarkably enhances the sensitivity of the voltammetric method and provides measurements of this explosive down to the sub-mg/l level in a wide pH range. The operational parameters were optimized and a sensitive, simple and time-saving cyclic voltammetric procedure was developed for the analysis of RDX in ground and tap water samples. Under optimized conditions, the reduction peak have two linear dynamic ranges of 0.6-20.0 and 8.0-200.0 mM with a detection limit of 25.0 nM and a precision of <4% (RSD for 8 analysis). Copyright © 2010 Elsevier B.V. All rights reserved.

Multi-Physics MRI-Based Two-Layer Fluid-Structure Interaction Anisotropic Models of Human Right and Left Ventricles with Different Patch Materials: Cardiac Function Assessment and Mechanical Stress Analysis

PubMed Central

Tang, Dalin; Yang, Chun; Geva, Tal; Gaudette, Glenn; del Nido, Pedro J.

2011-01-01

Multi-physics right and left ventricle (RV/LV) fluid-structure interaction (FSI) models were introduced to perform mechanical stress analysis and evaluate the effect of patch materials on RV function. The FSI models included three different patch materials (Dacron scaffold, treated pericardium, and contracting myocardium), two-layer construction, fiber orientation, and active anisotropic material properties. The models were constructed based on cardiac magnetic resonance (CMR) images acquired from a patient with severe RV dilatation and solved by ADINA. Our results indicate that the patch model with contracting myocardium leads to decreased stress level in the patch area, improved RV function and patch area contractility. PMID:21765559

The Quadratic Relationship between Socioeconomic Status and Learning Performance in China by Multilevel Analysis: Implications for Policies to Foster Education Equity

ERIC Educational Resources Information Center

Zhao, Ningning; Valcke, Martin; Desoete, Annemie; Verhaeghe, JeanPierre

2012-01-01

The purpose of the present study is to explore the relationship between family socioeconomic status and mathematics performance on the base of a multi-level analysis involving a large sample of Chinese primary school students. A weak relationship is found between socioeconomic status and performance in the Chinese context. The relationship does…

A full-spectrum analysis of high-speed train interior noise under multi-physical-field coupling excitations

NASA Astrophysics Data System (ADS)

Zheng, Xu; Hao, Zhiyong; Wang, Xu; Mao, Jie

2016-06-01

High-speed-railway-train interior noise at low, medium, and high frequencies could be simulated by finite element analysis (FEA) or boundary element analysis (BEA), hybrid finite element analysis-statistical energy analysis (FEA-SEA) and statistical energy analysis (SEA), respectively. First, a new method named statistical acoustic energy flow (SAEF) is proposed, which can be applied to the full-spectrum HST interior noise simulation (including low, medium, and high frequencies) with only one model. In an SAEF model, the corresponding multi-physical-field coupling excitations are firstly fully considered and coupled to excite the interior noise. The interior noise attenuated by sound insulation panels of carriage is simulated through modeling the inflow acoustic energy from the exterior excitations into the interior acoustic cavities. Rigid multi-body dynamics, fast multi-pole BEA, and large-eddy simulation with indirect boundary element analysis are first employed to extract the multi-physical-field excitations, which include the wheel-rail interaction forces/secondary suspension forces, the wheel-rail rolling noise, and aerodynamic noise, respectively. All the peak values and their frequency bands of the simulated acoustic excitations are validated with those from the noise source identification test. Besides, the measured equipment noise inside equipment compartment is used as one of the excitation sources which contribute to the interior noise. Second, a full-trimmed FE carriage model is firstly constructed, and the simulated modal shapes and frequencies agree well with the measured ones, which has validated the global FE carriage model as well as the local FE models of the aluminum alloy-trim composite panel. Thus, the sound transmission loss model of any composite panel has indirectly been validated. Finally, the SAEF model of the carriage is constructed based on the accurate FE model and stimulated by the multi-physical-field excitations. The results show that the trend of the simulated 1/3 octave band sound pressure spectrum agrees well with that of the on-site-measured one. The deviation between the simulated and measured overall sound pressure level (SPL) is 2.6 dB(A) and well controlled below the engineering tolerance limit, which has validated the SAEF model in the full-spectrum analysis of the high speed train interior noise.

Influences of system uncertainties on the numerical transfer path analysis of engine systems

NASA Astrophysics Data System (ADS)

Acri, A.; Nijman, E.; Acri, A.; Offner, G.

2017-10-01

Practical mechanical systems operate with some degree of uncertainty. In numerical models uncertainties can result from poorly known or variable parameters, from geometrical approximation, from discretization or numerical errors, from uncertain inputs or from rapidly changing forcing that can be best described in a stochastic framework. Recently, random matrix theory was introduced to take parameter uncertainties into account in numerical modeling problems. In particular in this paper, Wishart random matrix theory is applied on a multi-body dynamic system to generate random variations of the properties of system components. Multi-body dynamics is a powerful numerical tool largely implemented during the design of new engines. In this paper the influence of model parameter variability on the results obtained from the multi-body simulation of engine dynamics is investigated. The aim is to define a methodology to properly assess and rank system sources when dealing with uncertainties. Particular attention is paid to the influence of these uncertainties on the analysis and the assessment of the different engine vibration sources. Examples of the effects of different levels of uncertainties are illustrated by means of examples using a representative numerical powertrain model. A numerical transfer path analysis, based on system dynamic substructuring, is used to derive and assess the internal engine vibration sources. The results obtained from this analysis are used to derive correlations between parameter uncertainties and statistical distribution of results. The derived statistical information can be used to advance the knowledge of the multi-body analysis and the assessment of system sources when uncertainties in model parameters are considered.

Development of Viscoelastic Multi-Body Simulation and Impact Response Analysis of a Ballasted Railway Track under Cyclic Loading

PubMed Central

Nishiura, Daisuke; Sakaguchi, Hide; Aikawa, Akira

2017-01-01

Simulation of a large number of deformable bodies is often difficult because complex high-level modeling is required to address both multi-body contact and viscoelastic deformation. This necessitates the combined use of a discrete element method (DEM) and a finite element method (FEM). In this study, a quadruple discrete element method (QDEM) was developed for dynamic analysis of viscoelastic materials using a simpler algorithm compared to the standard FEM. QDEM easily incorporates the contact algorithm used in DEM. As the first step toward multi-body simulation, the fundamental performance of QDEM was investigated for viscoelastic analysis. The amplitude and frequency of cantilever elastic vibration were nearly equal to those obtained by the standard FEM. A comparison of creep recovery tests with an analytical solution showed good agreement between them. In addition, good correlation between the attenuation degree and the real physical viscosity was confirmed for viscoelastic vibration analysis. Therefore, the high accuracy of QDEM in the fundamental analysis of infinitesimal viscoelastic deformations was verified. Finally, the impact response of a ballast and sleeper under cyclic loading on a railway track was analyzed using QDEM as an application of deformable multi-body dynamics. The results showed that the vibration of the ballasted track was qualitatively in good agreement with the actual measurements. Moreover, the ballast layer with high friction reduced the ballasted track deterioration. This study suggests that QDEM, as an alternative to DEM and FEM, can provide deeper insights into the contact dynamics of a large number of deformable bodies. PMID:28772974

Development of Viscoelastic Multi-Body Simulation and Impact Response Analysis of a Ballasted Railway Track under Cyclic Loading.

PubMed

Nishiura, Daisuke; Sakaguchi, Hide; Aikawa, Akira

2017-06-03

Simulation of a large number of deformable bodies is often difficult because complex high-level modeling is required to address both multi-body contact and viscoelastic deformation. This necessitates the combined use of a discrete element method (DEM) and a finite element method (FEM). In this study, a quadruple discrete element method (QDEM) was developed for dynamic analysis of viscoelastic materials using a simpler algorithm compared to the standard FEM. QDEM easily incorporates the contact algorithm used in DEM. As the first step toward multi-body simulation, the fundamental performance of QDEM was investigated for viscoelastic analysis. The amplitude and frequency of cantilever elastic vibration were nearly equal to those obtained by the standard FEM. A comparison of creep recovery tests with an analytical solution showed good agreement between them. In addition, good correlation between the attenuation degree and the real physical viscosity was confirmed for viscoelastic vibration analysis. Therefore, the high accuracy of QDEM in the fundamental analysis of infinitesimal viscoelastic deformations was verified. Finally, the impact response of a ballast and sleeper under cyclic loading on a railway track was analyzed using QDEM as an application of deformable multi-body dynamics. The results showed that the vibration of the ballasted track was qualitatively in good agreement with the actual measurements. Moreover, the ballast layer with high friction reduced the ballasted track deterioration. This study suggests that QDEM, as an alternative to DEM and FEM, can provide deeper insights into the contact dynamics of a large number of deformable bodies.

Advanced Fault Diagnosis Methods in Molecular Networks

PubMed Central

Habibi, Iman; Emamian, Effat S.; Abdi, Ali

2014-01-01

Analysis of the failure of cell signaling networks is an important topic in systems biology and has applications in target discovery and drug development. In this paper, some advanced methods for fault diagnosis in signaling networks are developed and then applied to a caspase network and an SHP2 network. The goal is to understand how, and to what extent, the dysfunction of molecules in a network contributes to the failure of the entire network. Network dysfunction (failure) is defined as failure to produce the expected outputs in response to the input signals. Vulnerability level of a molecule is defined as the probability of the network failure, when the molecule is dysfunctional. In this study, a method to calculate the vulnerability level of single molecules for different combinations of input signals is developed. Furthermore, a more complex yet biologically meaningful method for calculating the multi-fault vulnerability levels is suggested, in which two or more molecules are simultaneously dysfunctional. Finally, a method is developed for fault diagnosis of networks based on a ternary logic model, which considers three activity levels for a molecule instead of the previously published binary logic model, and provides equations for the vulnerabilities of molecules in a ternary framework. Multi-fault analysis shows that the pairs of molecules with high vulnerability typically include a highly vulnerable molecule identified by the single fault analysis. The ternary fault analysis for the caspase network shows that predictions obtained using the more complex ternary model are about the same as the predictions of the simpler binary approach. This study suggests that by increasing the number of activity levels the complexity of the model grows; however, the predictive power of the ternary model does not appear to be increased proportionally. PMID:25290670

A multi-level analysis of the relationship between environmental factors and questing Ixodes ricinus dynamics in Belgium

PubMed Central

2012-01-01

Background Ticks are the most important pathogen vectors in Europe. They are known to be influenced by environmental factors, but these links are usually studied at specific temporal or spatial scales. Focusing on Ixodes ricinus in Belgium, we attempt to bridge the gap between current “single-sided” studies that focus on temporal or spatial variation only. Here, spatial and temporal patterns of ticks are modelled together. Methods A multi-level analysis of the Ixodes ricinus patterns in Belgium was performed. Joint effects of weather, habitat quality and hunting on field sampled tick abundance were examined at two levels, namely, sampling level, which is associated with temporal dynamics, and site level, which is related to spatial dynamics. Independent variables were collected from standard weather station records, game management data and remote sensing-based land cover data. Results At sampling level, only a marginally significant effect of daily relative humidity and temperature on the abundance of questing nymphs was identified. Average wind speed of seven days prior to the sampling day was found important to both questing nymphs and adults. At site level, a group of landscape-level forest fragmentation indices were highlighted for both questing nymph and adult abundance, including the nearest-neighbour distance, the shape and the aggregation level of forest patches. No cross-level effects or spatial autocorrelation were found. Conclusions Nymphal and adult ticks responded differently to environmental variables at different spatial and temporal scales. Our results can advise spatio-temporal extents of environment data collection for continuing empirical investigations and potential parameters for biological tick models. PMID:22830528

A multi-level, multi-jurisdictional strategy: Transnational tobacco companies' attempts to obstruct tobacco packaging restrictions.

PubMed

Hawkins, Benjamin; Holden, Chris; Mackinder, Sophie

2018-03-09

Despite the extensive literature on the tobacco industry, there has been little attempt to study how transnational tobacco companies (TTCs) coordinate their political activities globally, or to theorise TTC strategies within the context of global governance structures and policy processes. This article draws on three concepts from political science - policy transfer, multi-level governance and venue shifting - to analyse TTCs' integrated, global strategies to oppose augmented packaging requirements across multiple jurisdictions. Following Uruguay's introduction of extended labelling requirements, Australia became the first country in the world to require tobacco products to be sold in standardised ('plain') packaging in 2012. Governments in the European Union, including in the United Kingdom and Ireland, adopted similar laws, with other member states due to follow. TTCs vehemently opposed these measures and developed coordinated, global strategies to oppose their implementation, exploiting the complexity of contemporary global governance arrangements. These included a series of legal challenges in various jurisdictions, alongside political lobbying and public relations campaigns. This article draws on analysis of public documents and 32 semi-structured interviews with key policy actors. It finds that TTCs developed coordinated and highly integrated strategies to oppose packaging restrictions across multiple jurisdictions and levels of governance.

District Heating Systems Performance Analyses. Heat Energy Tariff

NASA Astrophysics Data System (ADS)

Ziemele, Jelena; Vigants, Girts; Vitolins, Valdis; Blumberga, Dagnija; Veidenbergs, Ivars

2014-12-01

The paper addresses an important element of the European energy sector: the evaluation of district heating (DH) system operations from the standpoint of increasing energy efficiency and increasing the use of renewable energy resources. This has been done by developing a new methodology for the evaluation of the heat tariff. The paper presents an algorithm of this methodology, which includes not only a data base and calculation equation systems, but also an integrated multi-criteria analysis module using MADM/MCDM (Multi-Attribute Decision Making / Multi-Criteria Decision Making) based on TOPSIS (Technique for Order Performance by Similarity to Ideal Solution). The results of the multi-criteria analysis are used to set the tariff benchmarks. The evaluation methodology has been tested for Latvian heat tariffs, and the obtained results show that only half of heating companies reach a benchmark value equal to 0.5 for the efficiency closeness to the ideal solution indicator. This means that the proposed evaluation methodology would not only allow companies to determine how they perform with regard to the proposed benchmark, but also to identify their need to restructure so that they may reach the level of a low-carbon business.

Dark Energy Survey Year 1 Results: Multi-Probe Methodology and Simulated Likelihood Analyses

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

Krause, E.; et al.

We present the methodology for and detail the implementation of the Dark Energy Survey (DES) 3x2pt DES Year 1 (Y1) analysis, which combines configuration-space two-point statistics from three different cosmological probes: cosmic shear, galaxy-galaxy lensing, and galaxy clustering, using data from the first year of DES observations. We have developed two independent modeling pipelines and describe the code validation process. We derive expressions for analytical real-space multi-probe covariances, and describe their validation with numerical simulations. We stress-test the inference pipelines in simulated likelihood analyses that vary 6-7 cosmology parameters plus 20 nuisance parameters and precisely resemble the analysis to be presented in the DES 3x2pt analysis paper, using a variety of simulated input data vectors with varying assumptions. We find that any disagreement between pipelines leads to changes in assigned likelihoodmore » $$\\Delta \\chi^2 \\le 0.045$$ with respect to the statistical error of the DES Y1 data vector. We also find that angular binning and survey mask do not impact our analytic covariance at a significant level. We determine lower bounds on scales used for analysis of galaxy clustering (8 Mpc$$~h^{-1}$$) and galaxy-galaxy lensing (12 Mpc$$~h^{-1}$$) such that the impact of modeling uncertainties in the non-linear regime is well below statistical errors, and show that our analysis choices are robust against a variety of systematics. These tests demonstrate that we have a robust analysis pipeline that yields unbiased cosmological parameter inferences for the flagship 3x2pt DES Y1 analysis. We emphasize that the level of independent code development and subsequent code comparison as demonstrated in this paper is necessary to produce credible constraints from increasingly complex multi-probe analyses of current data.« less

The evaluation of single-view and multi-view fusion 3D echocardiography using image-driven segmentation and tracking.

PubMed

Rajpoot, Kashif; Grau, Vicente; Noble, J Alison; Becher, Harald; Szmigielski, Cezary

2011-08-01

Real-time 3D echocardiography (RT3DE) promises a more objective and complete cardiac functional analysis by dynamic 3D image acquisition. Despite several efforts towards automation of left ventricle (LV) segmentation and tracking, these remain challenging research problems due to the poor-quality nature of acquired images usually containing missing anatomical information, speckle noise, and limited field-of-view (FOV). Recently, multi-view fusion 3D echocardiography has been introduced as acquiring multiple conventional single-view RT3DE images with small probe movements and fusing them together after alignment. This concept of multi-view fusion helps to improve image quality and anatomical information and extends the FOV. We now take this work further by comparing single-view and multi-view fused images in a systematic study. In order to better illustrate the differences, this work evaluates image quality and information content of single-view and multi-view fused images using image-driven LV endocardial segmentation and tracking. The image-driven methods were utilized to fully exploit image quality and anatomical information present in the image, thus purposely not including any high-level constraints like prior shape or motion knowledge in the analysis approaches. Experiments show that multi-view fused images are better suited for LV segmentation and tracking, while relatively more failures and errors were observed on single-view images. Copyright © 2011 Elsevier B.V. All rights reserved.

A FAST BAYESIAN METHOD FOR UPDATING AND FORECASTING HOURLY OZONE LEVELS

EPA Science Inventory

A Bayesian hierarchical space-time model is proposed by combining information from real-time ambient AIRNow air monitoring data, and output from a computer simulation model known as the Community Multi-scale Air Quality (Eta-CMAQ) forecast model. A model validation analysis shows...

The Role of Instructional Quality within School Sectors: A Multi-Level Analysis

ERIC Educational Resources Information Center

Miller, Saralyn J.

2013-01-01

On average, private school students outperform public school students on standardized tests. Research confirms these differences in student scores, but also shows that when student background characteristics are controlled, on average, public school students outperform private school students. Explaining achievement differences between sectors…

Program review presentation to Level 1, Interagency Coordination Committee

NASA Technical Reports Server (NTRS)

1982-01-01

Progress in the development of crop inventory technology is reported. Specific topics include the results of a thematic mapper analysis, variable selection studies/early season estimator improvements, the agricultural information system simulator, large unit proportion estimation, and development of common features for multi-satellite information extraction.

A socio-ecological analysis of barriers to the adoption, sustainablity and consistent use of sanitation facilities in rural Ethiopia.

PubMed

Alemu, Fikralem; Kumie, Abera; Medhin, Girmay; Gebre, Teshome; Godfrey, Phoebe

2017-09-13

Despite evidence showing that access to and use of improved sanitation is associated with healthier households and communities, barriers influencing the adoption and sustainablity of sanitation facilities remain unclear. We conducted a qualitative case study to explore barriers influencing the adoption, sustainablity and consistent use of sanitation facilities in rural Ethiopia. A qualitative study was conducted in the rural district of Becho, in central Ethiopia, from June to August 2016. A socio-ecological model and Integrated Behavioural Model (IBM) for a Water Hygiene and Sanitation (WASH) framework were employed to design the study and analyse data. A total of 10 in-depth interviews (IDI) were conducted with latrine adopters (n = 3), latrine non-adopters (n = 3), health extension workers (n = 3) and the district WASH coordinator (n = 1). Eight Focus Group Discussions (FGD) were undertaken with 75 participants, of which 31 were women. The FGDs and IDIs were tape-recorded, transcribed verbatim and translated into English. The analysis was supported using Nvivo version 10 software. Barriers to sustained adoption and use of sanitation facilities were categorized into 1) individual level factors (e.g., past latrine experience, lack of demand and perceived high cost to improved latrines), 2) household level factors (e.g., unaffordability, lack of space and absence of a physically strong family member), 3) community level factors (e.g., lack of access to public latrines, lack of shared rules against open defecation, lack of financial access for the poor), and 4) societal level factors (e.g., lack of strong local leadership, flooding, soil conditions, lack of appropriate sanitation technology, lack of promotion and demand creation for improved latrines). The use of the socio-ecological model and IBM-WASH framework helped to achieve a better understanding of multi-level and multi-dimensional barriers to sustained latrine adoption. The results indicate that there is a need to consider interventions that address multi-level factors concurrently.

Laser ablation inductively coupled plasma dynamic reaction cell mass spectrometry for the multi-element analysis of polymers

NASA Astrophysics Data System (ADS)

Resano, M.; García-Ruiz, E.; Vanhaecke, F.

2005-11-01

In this work, the potential of laser ablation-inductively coupled plasma-mass spectrometry for the fast analysis of polymers has been explored. Different real-life samples (polyethylene shopping bags, an acrylonitrile butadiene styrene material and various plastic bricks) as well as several reference materials (VDA 001 to 004, Cd in polyethylene) have been selected for the study. Two polyethylene reference materials (ERM-EC 680 and 681), for which a reference or indicative value for the most relevant metals is available, have proved their suitability as standards for calibration. Special attention has been paid to the difficulties expected for the determination of Cr at the μg g - 1 level in this kind of materials, due to the interference of ArC + ions on the most abundant isotopes of Cr. The use of ammonia as a reaction gas in a dynamic reaction cell is shown to alleviate this problem, resulting in a limit of detection of 0.15 μg g - 1 for this element, while limiting only modestly the possibilities of the technique for simultaneous multi-element analysis. In this regard, As is the analyte most seriously affected by the use of ammonia, and its determination has to be carried out in vented mode, at the expense of measuring time. In all cases studied, accurate results could be obtained for elements ranging in content from the sub-μg g - 1 level to tens of thousands of μg g - 1 . However, the use of an element of known concentration as internal standard may be needed for materials with a matrix significantly different from that of the standard (polyethylene in this work). Precision ranged between 5% and 10% RSD for elements found at the 10 μg g - 1 level or higher, while this value could deteriorate to 20% for analytes found at the sub-μg g - 1 level. Overall, the technique evaluated presents many advantages for the fast and accurate multi-element analysis of these materials, avoiding laborious digestion procedures and minimizing the risk of analyte losses due to the formation of volatile compounds.

Multi-class, multi-residue analysis of pesticides, polychlorinated biphenyls, polycyclic aromatic hydrocarbons, polybrominated diphenyl ethers and novel flame retardants in fish using fast, low-pressure gas chromatography-tandem mass spectrometry.

PubMed

Sapozhnikova, Yelena; Lehotay, Steven J

2013-01-03

A multi-class, multi-residue method for the analysis of 13 novel flame retardants, 18 representative pesticides, 14 polychlorinated biphenyl (PCB) congeners, 16 polycyclic aromatic hydrocarbons (PAHs), and 7 polybrominated diphenyl ether (PBDE) congeners in catfish muscle was developed and evaluated using fast low pressure gas chromatography triple quadrupole tandem mass spectrometry (LP-GC/MS-MS). The method was based on a QuEChERS (quick, easy, cheap, effective, rugged, safe) extraction with acetonitrile and dispersive solid-phase extraction (d-SPE) clean-up with zirconium-based sorbent prior to LP-GC/MS-MS analysis. The developed method was evaluated at 4 spiking levels and further validated by analysis of NIST Standard Reference Materials (SRMs) 1974B and 1947. Sample preparation for a batch of 10 homogenized samples took about 1h/analyst, and LP-GC/MS-MS analysis provided fast separation of multiple analytes within 9min achieving high throughput. With the use of isotopically labeled internal standards, recoveries of all but one analyte were between 70 and 120% with relative standard deviations less than 20% (n=5). The measured values for both SRMs agreed with certified/reference values (72-119% accuracy) for the majority of analytes. The detection limits were 0.1-0.5ng g(-1) for PCBs, 0.5-10ng g(-1) for PBDEs, 0.5-5ng g(-1) for select pesticides and PAHs and 1-10ng g(-1) for flame retardants. The developed method was successfully applied for analysis of catfish samples from the market. Published by Elsevier B.V.

Individual relocation decisions after tornadoes: a multi-level analysis.

PubMed

Cong, Zhen; Nejat, Ali; Liang, Daan; Pei, Yaolin; Javid, Roxana J

2018-04-01

This study examines how multi-level factors affected individuals' relocation decisions after EF4 and EF5 (Enhanced Fujita Tornado Intensity Scale) tornadoes struck the United States in 2013. A telephone survey was conducted with 536 respondents, including oversampled older adults, one year after these two disaster events. Respondents' addresses were used to associate individual information with block group-level variables recorded by the American Community Survey. Logistic regression revealed that residential damage and homeownership are important predictors of relocation. There was also significant interaction between these two variables, indicating less difference between homeowners and renters at higher damage levels. Homeownership diminished the likelihood of relocation among younger respondents. Random effects logistic regression found that the percentage of homeownership and of higher income households in the community buffered the effect of damage on relocation; the percentage of older adults reduced the likelihood of this group relocating. The findings are assessed from the standpoint of age difference, policy implications, and social capital and vulnerability. © 2018 The Author(s). Disasters © Overseas Development Institute, 2018.

Extended multi-configuration quasi-degenerate perturbation theory: the new approach to multi-state multi-reference perturbation theory.

PubMed

Granovsky, Alexander A

2011-06-07

The distinctive desirable features, both mathematically and physically meaningful, for all partially contracted multi-state multi-reference perturbation theories (MS-MR-PT) are explicitly formulated. The original approach to MS-MR-PT theory, called extended multi-configuration quasi-degenerate perturbation theory (XMCQDPT), having most, if not all, of the desirable properties is introduced. The new method is applied at the second order of perturbation theory (XMCQDPT2) to the 1(1)A(')-2(1)A(') conical intersection in allene molecule, the avoided crossing in LiF molecule, and the 1(1)A(1) to 2(1)A(1) electronic transition in cis-1,3-butadiene. The new theory has several advantages compared to those of well-established approaches, such as second order multi-configuration quasi-degenerate perturbation theory and multi-state-second order complete active space perturbation theory. The analysis of the prevalent approaches to the MS-MR-PT theory performed within the framework of the XMCQDPT theory unveils the origin of their common inherent problems. We describe the efficient implementation strategy that makes XMCQDPT2 an especially useful general-purpose tool in the high-level modeling of small to large molecular systems. © 2011 American Institute of Physics

Multi-stage decoding of multi-level modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Kasami, Tadao; Costello, Daniel J., Jr.

1991-01-01

Various types of multi-stage decoding for multi-level modulation codes are investigated. It is shown that if the component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. Particularly, it is shown that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum soft-decision decoding of the code is very small, only a fraction of dB loss in signal to noise ratio at a bit error rate (BER) of 10(exp -6).

Validation of the Australian diagnostic reference levels for paediatric multi detector computed tomography: a comparison of RANZCR QUDI data and subsequent NDRLS data from 2012 to 2015.

PubMed

Anna, Hayton; Wallace, Anthony; Thomas, Peter

2017-03-01

The national diagnostic reference level service (NDRLS), was launched in 2011, however no paediatric data were submitted during the first calendar year of operation. As such, Australian national diagnostic reference levels (DRLs), for paediatric multi detector computed tomography (MDCT), were established using data obtained from a Royal Australian and New Zealand College of Radiologists (RANZCR), Quality Use of Diagnostic Imaging (QUDI), study. Paediatric data were submitted to the NDRLS in 2012 through 2015. An analysis has been made of the NDRLS paediatric data using the same method as was used to analyse the QUDI data to establish the Australian national paediatric DRLs for MDCT. An analysis of the paediatric NDRLS data has also been made using the method used to calculate the Australian national adult DRLs for MDCT. A comparison between the QUDI data and subsequent NDRLS data shows the NDRLS data to be lower on average for the Head and AbdoPelvis protocol and similar for the chest protocol. Using an average of NDRLS data submitted between 2012 and 2015 implications for updated paediatric DRLS are considered.

A multi-standard approach for GIAO (13)C NMR calculations.

PubMed

Sarotti, Ariel M; Pellegrinet, Silvina C

2009-10-02

The influence of the reference standard employed in the calculation of (13)C NMR chemical shifts was investigated over a large variety of known organic compounds, using different quantum chemistry methods and basis sets. After detailed analysis of the collected data, we found that methanol and benzene are excellent reference standards for computing NMR shifts of sp(3)- and sp-sp(2)-hybridized carbon atoms, respectively. This multi-standard approach (MSTD) performs better than TMS in terms of accuracy and precision and also displays much lower dependence on the level of theory employed. The use of mPW1PW91/6-31G(d)//mPW1PW91/6-31G(d) level is recommended for accurate (13)C NMR chemical shift prediction at low computational cost.

Multi-interface level in oil tanks and applications of optical fiber sensors

NASA Astrophysics Data System (ADS)

Leal-Junior, Arnaldo G.; Marques, Carlos; Frizera, Anselmo; Pontes, Maria José

2018-01-01

On the oil production also involves the production of water, gas and suspended solids, which are separated from the oil on three-phase separators. However, the control strategies of an oil separator are limited due to unavailability of suitable multi-interface level sensors. This paper presents a description of the multi-phase level problem on the oil industry and a review of the current technologies for multi-interface level assessment. Since optical fiber sensors present chemical stability, intrinsic safety, electromagnetic immunity, lightweight and multiplexing capabilities, it can be an alternative for multi-interface level measurement that can overcome some of the limitations of the current technologies. For this reason, Fiber Bragg Gratings (FBGs) based optical fiber sensor system for multi-interface level assessment is proposed, simulated and experimentally assessed. The results show that the proposed sensor system is capable of measuring interface level with a relative error of only 2.38%. Furthermore, the proposed sensor system is also capable of measuring the oil density with an error of 0.8 kg/m3.

Post test review of a single car test of multi-level passenger equipment

DOT National Transportation Integrated Search

2008-04-22

The single car test of multi-level equipment described in : this paper was designed to help evaluate the crashworthiness of : a multi-level car in a controlled collision. The data collected : from this test will be used to refine engineering models. ...

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

PubMed

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

2014-02-01

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

Predicting multi-level drug response with gene expression profile in multiple myeloma using hierarchical ordinal regression.

PubMed

Zhang, Xinyan; Li, Bingzong; Han, Huiying; Song, Sha; Xu, Hongxia; Hong, Yating; Yi, Nengjun; Zhuang, Wenzhuo

2018-05-10

Multiple myeloma (MM), like other cancers, is caused by the accumulation of genetic abnormalities. Heterogeneity exists in the patients' response to treatments, for example, bortezomib. This urges efforts to identify biomarkers from numerous molecular features and build predictive models for identifying patients that can benefit from a certain treatment scheme. However, previous studies treated the multi-level ordinal drug response as a binary response where only responsive and non-responsive groups are considered. It is desirable to directly analyze the multi-level drug response, rather than combining the response to two groups. In this study, we present a novel method to identify significantly associated biomarkers and then develop ordinal genomic classifier using the hierarchical ordinal logistic model. The proposed hierarchical ordinal logistic model employs the heavy-tailed Cauchy prior on the coefficients and is fitted by an efficient quasi-Newton algorithm. We apply our hierarchical ordinal regression approach to analyze two publicly available datasets for MM with five-level drug response and numerous gene expression measures. Our results show that our method is able to identify genes associated with the multi-level drug response and to generate powerful predictive models for predicting the multi-level response. The proposed method allows us to jointly fit numerous correlated predictors and thus build efficient models for predicting the multi-level drug response. The predictive model for the multi-level drug response can be more informative than the previous approaches. Thus, the proposed approach provides a powerful tool for predicting multi-level drug response and has important impact on cancer studies.

Urban sustainable energy development: A case study of the city of Philadelphia

NASA Astrophysics Data System (ADS)

Argyriou, Iraklis

This study explores the role of cities in sustainable energy development through a governance-informed analysis. Despite the leading position of municipalities in energy sustainability, cities have been mostly conceptualized as sites where energy development is shaped by external policy scales, i.e. the national level. A growing body of research, however, critiques this analytical perspective, and seeks to better understand the type of factors and dynamics that influence energy sustainability within a multi-level policy context for urban energy. Given that particular circumstances are applicable across cities, a context-specific analysis can provide insight regarding how sustainable energy development takes place in urban areas. In applying such an analytical perspective on urban energy sustainability, this study undertakes a qualitative case study analysis for the city of Philadelphia, Pennsylvania, by looking at four key local policy initiatives relevant to building energy efficiency and solar electricity development at the municipal government and city-wide level. The evaluation of the initiatives suggests that renewable electricity use has increased substantially in the city over the last years but the installed capacity of local renewable electricity systems, including solar photovoltaics, is low. On the other hand, although the city has made little progress in meeting its building energy efficiency targets, more comprehensive action is taken in this area. The study finds that the above outcomes have been shaped mainly by four factors. The first is the city government's incremental policy approach aiming to develop a facilitative context for local action. The second is the role that a diverse set of stakeholders have in local sustainable energy development. The third is the constraints that systemic policy barriers create for solar power development. The fourth is the ways through which the relevant multi-level policy environment structures the city's possibilities on sustainable energy. In this context, the study identifies four areas of policy recommendation that could enhance Philadelphia's prospects for energy sustainability: integrated municipal energy planning; stable financing for market development; enhanced actor interactions; and multi-level policymaking that facilitates local action. These policy directions could be of interest to a broader body of metropolitan cities regarding their efforts in sustainable energy development.

Empirical Determination of Competence Areas to Computer Science Education

ERIC Educational Resources Information Center

Zendler, Andreas; Klaudt, Dieter; Seitz, Cornelia

2014-01-01

The authors discuss empirically determined competence areas to K-12 computer science education, emphasizing the cognitive level of competence. The results of a questionnaire with 120 professors of computer science serve as a database. By using multi-dimensional scaling and cluster analysis, four competence areas to computer science education…

Project for Global Education: Annotated Bibliography.

ERIC Educational Resources Information Center

Institute for World Order, New York, NY.

Over 260 books, textbooks, articles, pamphlets, periodicals, films, and multi-media packages appropriate for the analysis of global issues at the college level are briefly annotated. Entries include classic books and articles as well as a number of recent (1976-1981) publications. The purpose is to assist students and educators in developing a…

A functional language approach in high-speed digital simulation

NASA Technical Reports Server (NTRS)

Ercegovac, M. D.; Lu, S.-L.

1983-01-01

A functional programming approach for a multi-microprocessor architecture is presented. The language, based on Backus FP, its intermediate form and the translation process are discussed and illustrated with an example. The approach allows performance analysis to be performed at a high level as an aid in program partitioning.

Multi-platform ’Omics Analysis of Human Ebola Virus Disease Pathogenesis

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

Eisfeld, Amie J.; Halfmann, Peter J.; Wendler, Jason P.

The pathogenesis of human Ebola virus disease (EVD) is complex. EVD is characterized by high levels of virus replication and dissemination, dysregulated immune responses, extensive virus- and host-mediated tissue damage, and disordered coagulation. To clarify how host responses contribute to EVD pathophysiology, we performed multi-platform ’omics analysis of peripheral blood mononuclear cells and plasma from EVD patients. Our results indicate that EVD molecular signatures overlap with those of sepsis, imply that pancreatic enzymes contribute to tissue damage in fatal EVD, and suggest that Ebola virus infection may induce aberrant neutrophils whose activity could explain hallmarks of fatal EVD. Moreover, integratedmore » biomarker prediction identified putative biomarkers from different data platforms that differentiated survivors and fatalities early after infection. This work reveals insight into EVD pathogenesis, suggests an effective approach for biomarker identification, and provides an important community resource for further analysis of human EVD severity.« less

Multi-platform 'Omics Analysis of Human Ebola Virus Disease Pathogenesis.

PubMed

Eisfeld, Amie J; Halfmann, Peter J; Wendler, Jason P; Kyle, Jennifer E; Burnum-Johnson, Kristin E; Peralta, Zuleyma; Maemura, Tadashi; Walters, Kevin B; Watanabe, Tokiko; Fukuyama, Satoshi; Yamashita, Makoto; Jacobs, Jon M; Kim, Young-Mo; Casey, Cameron P; Stratton, Kelly G; Webb-Robertson, Bobbie-Jo M; Gritsenko, Marina A; Monroe, Matthew E; Weitz, Karl K; Shukla, Anil K; Tian, Mingyuan; Neumann, Gabriele; Reed, Jennifer L; van Bakel, Harm; Metz, Thomas O; Smith, Richard D; Waters, Katrina M; N'jai, Alhaji; Sahr, Foday; Kawaoka, Yoshihiro

2017-12-13

The pathogenesis of human Ebola virus disease (EVD) is complex. EVD is characterized by high levels of virus replication and dissemination, dysregulated immune responses, extensive virus- and host-mediated tissue damage, and disordered coagulation. To clarify how host responses contribute to EVD pathophysiology, we performed multi-platform 'omics analysis of peripheral blood mononuclear cells and plasma from EVD patients. Our results indicate that EVD molecular signatures overlap with those of sepsis, imply that pancreatic enzymes contribute to tissue damage in fatal EVD, and suggest that Ebola virus infection may induce aberrant neutrophils whose activity could explain hallmarks of fatal EVD. Moreover, integrated biomarker prediction identified putative biomarkers from different data platforms that differentiated survivors and fatalities early after infection. This work reveals insight into EVD pathogenesis, suggests an effective approach for biomarker identification, and provides an important community resource for further analysis of human EVD severity. Copyright © 2017 Elsevier Inc. All rights reserved.

A method for the inclusion of physical activity-related health benefits in cost-benefit analysis of built environment initiatives.

PubMed

Zapata-Diomedi, Belen; Gunn, Lucy; Giles-Corti, Billie; Shiell, Alan; Lennert Veerman, J

2018-01-01

The built environment has a significant influence on population levels of physical activity (PA) and therefore health. However, PA-related health benefits are seldom considered in transport and urban planning (i.e. built environment interventions) cost-benefit analysis. Cost-benefit analysis implies that the benefits of any initiative are valued in monetary terms to make them commensurable with costs. This leads to the need for monetised values of the health benefits of PA. The aim of this study was to explore a method for the incorporation of monetised PA-related health benefits in cost-benefit analysis of built environment interventions. Firstly, we estimated the change in population level of PA attributable to a change in the built environment due to the intervention. Then, changes in population levels of PA were translated into monetary values. For the first step we used estimates from the literature for the association of built environment features with physical activity outcomes. For the second step we used the multi-cohort proportional multi-state life table model to predict changes in health-adjusted life years and health care costs as a function of changes in PA. Finally, we monetised health-adjusted life years using the value of a statistical life year. Future research could adapt these methods to assess the health and economic impacts of specific urban development scenarios by working in collaboration with urban planners. Copyright © 2017 Elsevier Inc. All rights reserved.

The Human Blood Metabolome-Transcriptome Interface

PubMed Central

Schramm, Katharina; Adamski, Jerzy; Gieger, Christian; Herder, Christian; Carstensen, Maren; Peters, Annette; Rathmann, Wolfgang; Roden, Michael; Strauch, Konstantin; Suhre, Karsten; Kastenmüller, Gabi; Prokisch, Holger; Theis, Fabian J.

2015-01-01

Biological systems consist of multiple organizational levels all densely interacting with each other to ensure function and flexibility of the system. Simultaneous analysis of cross-sectional multi-omics data from large population studies is a powerful tool to comprehensively characterize the underlying molecular mechanisms on a physiological scale. In this study, we systematically analyzed the relationship between fasting serum metabolomics and whole blood transcriptomics data from 712 individuals of the German KORA F4 cohort. Correlation-based analysis identified 1,109 significant associations between 522 transcripts and 114 metabolites summarized in an integrated network, the ‘human blood metabolome-transcriptome interface’ (BMTI). Bidirectional causality analysis using Mendelian randomization did not yield any statistically significant causal associations between transcripts and metabolites. A knowledge-based interpretation and integration with a genome-scale human metabolic reconstruction revealed systematic signatures of signaling, transport and metabolic processes, i.e. metabolic reactions mainly belonging to lipid, energy and amino acid metabolism. Moreover, the construction of a network based on functional categories illustrated the cross-talk between the biological layers at a pathway level. Using a transcription factor binding site enrichment analysis, this pathway cross-talk was further confirmed at a regulatory level. Finally, we demonstrated how the constructed networks can be used to gain novel insights into molecular mechanisms associated to intermediate clinical traits. Overall, our results demonstrate the utility of a multi-omics integrative approach to understand the molecular mechanisms underlying both normal physiology and disease. PMID:26086077

Moving towards an Integrated Theory of Policy Networks: A Multi-Theoretical Approach for Examining State-Level Policy Change in U.S. Subsystems. Working Paper #45

ERIC Educational Resources Information Center

Galey, Sarah; Youngs, Peter

2014-01-01

Scholars have developed a wide range of theories to explain both stability and change in policy subsystems. In recent years, a burgeoning literature has emerged that focuses on the application of network analysis in policy research, more formally known as Policy Network Analysis (PNA). This approach, while still developing, has great potential as…

Development and application of dynamic hybrid multi-region inventory analysis for macro-level environmental policy analysis: a case study on climate policy in Taiwan.

PubMed

Chao, Chia-Wei; Heijungs, Reinout; Ma, Hwong-wen

2013-03-19

We develop a novel inventory method called Dynamic Hybrid Multi-Region Inventory analysis (DHMRI), which integrates the EEMRIOA and Integrated Hybrid LCA and applies time-dependent environmental intervention information for inventory analysis. Consequently, DHMRI is able to quantify the change in the environmental footprint caused by a specific policy while taking structural changes and technological dynamics into consideration. DHMRI is applied to assess the change in the total CO2 emissions associated with the total final demand caused by the climate policy in Taiwan to demonstrate the practicality of this novel method. The evaluation reveals that the implementation of mitigation measures included in the existing climate policy, such as an enhancement in energy efficiency, promotion of renewable energy, and limitation of the growth of energy-intensive industries, will lead to a 28% increase in the total CO2 emissions and that the main driver is the export-oriented electronics industry. Moreover, a major increase in the total emissions is predicted to occur in Southeast Asia and China. The observations from the case study reveal that DHMRI is capable of overcoming the limitations of existing assessment tools at macro-level evaluation of environmental policies.

Laser induced fluorescence lifetime characterization of Bacillus endospore species using time correlated single photon counting analysis with the multi-exponential fit method

NASA Astrophysics Data System (ADS)

Smith, Clint; Edwards, Jarrod; Fisher, Andmorgan

2010-04-01

Rapid detection of biological material is critical for determining presence/absence of bacterial endospores within various investigative programs. Even more critical is that if select material tests positive for bacillus endospores then tests should provide data at the species level. Optical detection of microbial endospore formers such as Bacillus sp. can be heavy, cumbersome, and may only identify at the genus level. Data provided from this study will aid in characterization needed by future detection systems for further rapid breakdown analysis to gain insight into a more positive signature collection of Bacillus sp. Literature has shown that fluorescence spectroscopy of endospores could be statistically separated from other vegetative genera, but could not be separated among one another. Results of this study showed endospore species separation is possible using laser-induce fluorescence with lifetime decay analysis for Bacillus endospores. Lifetime decays of B. subtilis, B. megaterium, B. coagulans, and B. anthracis Sterne strain were investigated. Using the Multi-Exponential fit method data showed three distinct lifetimes for each species within the following ranges, 0.2-1.3 ns; 2.5-7.0 ns; 7.5-15.0 ns, when laser induced at 307 nm. The four endospore species were individually separated using principle component analysis (95% CI).

Climate change and epidemics in Chinese history: A multi-scalar analysis.

PubMed

Lee, Harry F; Fei, Jie; Chan, Christopher Y S; Pei, Qing; Jia, Xin; Yue, Ricci P H

2017-02-01

This study seeks to provide further insight regarding the relationship of climate-epidemics in Chinese history through a multi-scalar analysis. Based on 5961 epidemic incidents in China during 1370-1909 CE we applied Ordinary Least Square regression and panel data regression to verify the climate-epidemic nexus over a range of spatial scales (country, macro region, and province). Results show that epidemic outbreaks were negatively correlated with the temperature in historical China at various geographic levels, while a stark reduction in the correlational strength was observed at lower geographic levels. Furthermore, cooling drove up epidemic outbreaks in northern and central China, where population pressure reached a clear threshold for amplifying the vulnerability of epidemic outbreaks to climate change. Our findings help to illustrate the modifiable areal unit and the uncertain geographic context problems in climate-epidemics research. Researchers need to consider the scale effect in the course of statistical analyses, which are currently predominantly conducted on a national/single scale; and also the importance of how the study area is delineated, an issue which is rarely discussed in the climate-epidemics literature. Future research may leverage our results and provide a cross-analysis with those derived from spatial analysis. Copyright © 2016 Elsevier Ltd. All rights reserved.

ASRM Multi-Port Igniter Flow Field Analysis

NASA Technical Reports Server (NTRS)

Kania, Lee; Dumas, Catherine; Doran, Denise

1993-01-01

The Advanced Solid Rocket Motor (ASRM) program was initiated by NASA in response to the need for a new generation rocket motor capable of providing increased thrust levels over the existing Redesigned Solid Rocket Motor (RSRM) and thus augment the lifting capacity of the space shuttle orbiter. To achieve these higher thrust levels and improve motor reliability, advanced motor design concepts were employed. In the head end of the motor, for instance, the propellent cast has been changed from the conventional annular configuration to a 'multi-slot' configuration in order to increase the burn surface area and guarantee rapid motor ignition. In addition, the igniter itself has been redesigned and currently features 12 exhaust ports in order to channel hot igniter combustion gases into the circumferential propellent slots. Due to the close proximity of the igniter ports to the propellent surfaces, new concerns over possible propellent deformation and erosive burning have arisen. The following documents the effort undertaken using computational fluid dynamics to perform a flow field analysis in the top end of the ASRM motor to determine flow field properties necessary to permit a subsequent propellent fin deformation analysis due to pressure loading and an assessment of the extent of erosive burning.

ASRM multi-port igniter flow field analysis

NASA Astrophysics Data System (ADS)

Kania, Lee; Dumas, Catherine; Doran, Denise

1993-07-01

The Advanced Solid Rocket Motor (ASRM) program was initiated by NASA in response to the need for a new generation rocket motor capable of providing increased thrust levels over the existing Redesigned Solid Rocket Motor (RSRM) and thus augment the lifting capacity of the space shuttle orbiter. To achieve these higher thrust levels and improve motor reliability, advanced motor design concepts were employed. In the head end of the motor, for instance, the propellent cast has been changed from the conventional annular configuration to a 'multi-slot' configuration in order to increase the burn surface area and guarantee rapid motor ignition. In addition, the igniter itself has been redesigned and currently features 12 exhaust ports in order to channel hot igniter combustion gases into the circumferential propellent slots. Due to the close proximity of the igniter ports to the propellent surfaces, new concerns over possible propellent deformation and erosive burning have arisen. The following documents the effort undertaken using computational fluid dynamics to perform a flow field analysis in the top end of the ASRM motor to determine flow field properties necessary to permit a subsequent propellent fin deformation analysis due to pressure loading and an assessment of the extent of erosive burning.

Propulsion Airframe Aeroacoustics Technology Evaluation and Selection Using a Multi-Attribute Decision Making Process and Non-Deterministic Design

NASA Technical Reports Server (NTRS)

Burg, Cecile M.; Hill, Geoffrey A.; Brown, Sherilyn A.; Geiselhart, Karl A.

2004-01-01

The Systems Analysis Branch at NASA Langley Research Center has investigated revolutionary Propulsion Airframe Aeroacoustics (PAA) technologies and configurations for a Blended-Wing-Body (BWB) type aircraft as part of its research for NASA s Quiet Aircraft Technology (QAT) Project. Within the context of the long-term NASA goal of reducing the perceived aircraft noise level by a factor of 4 relative to 1997 state of the art, major configuration changes in the propulsion airframe integration system were explored with noise as a primary design consideration. An initial down-select and assessment of candidate PAA technologies for the BWB was performed using a Multi-Attribute Decision Making (MADM) process consisting of organized brainstorming and decision-making tools. The assessments focused on what effect the PAA technologies had on both the overall noise level of the BWB and what effect they had on other major design considerations such as weight, performance and cost. A probabilistic systems analysis of the PAA configurations that presented the best noise reductions with the least negative impact on the system was then performed. Detailed results from the MADM study and the probabilistic systems analysis will be published in the near future.

Quantification of mold contamination in multi-level buildings using the Environmental Relative Moldiness Index

EPA Science Inventory

The goal of this study was to evaluate the possible use of the Environmental Relative Moldiness Index (ERMI) to quantify mold contamination in multi-level, office buildings. Settled-dust samples were collected in multi-level, office buildings and the ERMI value for each sample de...

A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping

NASA Astrophysics Data System (ADS)

Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

2014-12-01

Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having "very high susceptibility", with the further 31% falling into zones classified as having "high susceptibility".

A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping

PubMed Central

Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

2014-01-01

Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having “very high susceptibility”, with the further 31% falling into zones classified as having “high susceptibility”. PMID:26089577

A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping.

PubMed

Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

2014-12-01

Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having "very high susceptibility", with the further 31% falling into zones classified as having "high susceptibility".

Performance analysis of three-dimensional-triple-level cell and two-dimensional-multi-level cell NAND flash hybrid solid-state drives

NASA Astrophysics Data System (ADS)

Sakaki, Yukiya; Yamada, Tomoaki; Matsui, Chihiro; Yamaga, Yusuke; Takeuchi, Ken

2018-04-01

In order to improve performance of solid-state drives (SSDs), hybrid SSDs have been proposed. Hybrid SSDs consist of more than two types of NAND flash memories or NAND flash memories and storage-class memories (SCMs). However, the cost of hybrid SSDs adopting SCMs is more expensive than that of NAND flash only SSDs because of the high bit cost of SCMs. This paper proposes unique hybrid SSDs with two-dimensional (2D) horizontal multi-level cell (MLC)/three-dimensional (3D) vertical triple-level cell (TLC) NAND flash memories to achieve higher cost-performance. The 2D-MLC/3D-TLC hybrid SSD achieves up to 31% higher performance than the conventional 2D-MLC/2D-TLC hybrid SSD. The factors of different performance between the proposed hybrid SSD and the conventional hybrid SSD are analyzed by changing its block size, read/write/erase latencies, and write unit of 3D-TLC NAND flash memory, by means of a transaction-level modeling simulator.

49 CFR Figure 2b to Subpart B of... - Example of an Intermediate Level Seating Area of a Multi-Level Car Complying With Window Location...

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Example of an Intermediate Level Seating Area of a Multi-Level Car Complying With Window Location Requirements-§§ 238.113 and 238.114 2B Figure 2B to... Intermediate Level Seating Area of a Multi-Level Car Complying With Window Location Requirements—§§ 238.113 and...

49 CFR Figure 2a to Subpart B of... - Example of an Intermediate Level Seating Area of a Multi-Level Car Complying With Window Location...

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Example of an Intermediate Level Seating Area of a Multi-Level Car Complying With Window Location Requirements-§§ 238.113 and 238.114 2A Figure 2A to... Intermediate Level Seating Area of a Multi-Level Car Complying With Window Location Requirements—§§ 238.113 and...

Robust Optimization and Sensitivity Analysis with Multi-Objective Genetic Algorithms: Single- and Multi-Disciplinary Applications

DTIC Science & Technology

2007-01-01

multi-disciplinary optimization with uncertainty. Robust optimization and sensitivity analysis is usually used when an optimization model has...formulation is introduced in Section 2.3. We briefly discuss several definitions used in the sensitivity analysis in Section 2.4. Following in...2.5. 2.4 SENSITIVITY ANALYSIS In this section, we discuss several definitions used in Chapter 5 for Multi-Objective Sensitivity Analysis . Inner

A Multi-Level Parallelization Concept for High-Fidelity Multi-Block Solvers

NASA Technical Reports Server (NTRS)

Hatay, Ferhat F.; Jespersen, Dennis C.; Guruswamy, Guru P.; Rizk, Yehia M.; Byun, Chansup; Gee, Ken; VanDalsem, William R. (Technical Monitor)

1997-01-01

The integration of high-fidelity Computational Fluid Dynamics (CFD) analysis tools with the industrial design process benefits greatly from the robust implementations that are transportable across a wide range of computer architectures. In the present work, a hybrid domain-decomposition and parallelization concept was developed and implemented into the widely-used NASA multi-block Computational Fluid Dynamics (CFD) packages implemented in ENSAERO and OVERFLOW. The new parallel solver concept, PENS (Parallel Euler Navier-Stokes Solver), employs both fine and coarse granularity in data partitioning as well as data coalescing to obtain the desired load-balance characteristics on the available computer platforms. This multi-level parallelism implementation itself introduces no changes to the numerical results, hence the original fidelity of the packages are identically preserved. The present implementation uses the Message Passing Interface (MPI) library for interprocessor message passing and memory accessing. By choosing an appropriate combination of the available partitioning and coalescing capabilities only during the execution stage, the PENS solver becomes adaptable to different computer architectures from shared-memory to distributed-memory platforms with varying degrees of parallelism. The PENS implementation on the IBM SP2 distributed memory environment at the NASA Ames Research Center obtains 85 percent scalable parallel performance using fine-grain partitioning of single-block CFD domains using up to 128 wide computational nodes. Multi-block CFD simulations of complete aircraft simulations achieve 75 percent perfect load-balanced executions using data coalescing and the two levels of parallelism. SGI PowerChallenge, SGI Origin 2000, and a cluster of workstations are the other platforms where the robustness of the implementation is tested. The performance behavior on the other computer platforms with a variety of realistic problems will be included as this on-going study progresses.

Efficiency of static core turn-off in a system-on-a-chip with variation

DOEpatents

Cher, Chen-Yong; Coteus, Paul W; Gara, Alan; Kursun, Eren; Paulsen, David P; Schuelke, Brian A; Sheets, II, John E; Tian, Shurong

2013-10-29

A processor-implemented method for improving efficiency of a static core turn-off in a multi-core processor with variation, the method comprising: conducting via a simulation a turn-off analysis of the multi-core processor at the multi-core processor's design stage, wherein the turn-off analysis of the multi-core processor at the multi-core processor's design stage includes a first output corresponding to a first multi-core processor core to turn off; conducting a turn-off analysis of the multi-core processor at the multi-core processor's testing stage, wherein the turn-off analysis of the multi-core processor at the multi-core processor's testing stage includes a second output corresponding to a second multi-core processor core to turn off; comparing the first output and the second output to determine if the first output is referring to the same core to turn off as the second output; outputting a third output corresponding to the first multi-core processor core if the first output and the second output are both referring to the same core to turn off.

Information theoretic partitioning and confidence based weight assignment for multi-classifier decision level fusion in hyperspectral target recognition applications

NASA Astrophysics Data System (ADS)

Prasad, S.; Bruce, L. M.

2007-04-01

There is a growing interest in using multiple sources for automatic target recognition (ATR) applications. One approach is to take multiple, independent observations of a phenomenon and perform a feature level or a decision level fusion for ATR. This paper proposes a method to utilize these types of multi-source fusion techniques to exploit hyperspectral data when only a small number of training pixels are available. Conventional hyperspectral image based ATR techniques project the high dimensional reflectance signature onto a lower dimensional subspace using techniques such as Principal Components Analysis (PCA), Fisher's linear discriminant analysis (LDA), subspace LDA and stepwise LDA. While some of these techniques attempt to solve the curse of dimensionality, or small sample size problem, these are not necessarily optimal projections. In this paper, we present a divide and conquer approach to address the small sample size problem. The hyperspectral space is partitioned into contiguous subspaces such that the discriminative information within each subspace is maximized, and the statistical dependence between subspaces is minimized. We then treat each subspace as a separate source in a multi-source multi-classifier setup and test various decision fusion schemes to determine their efficacy. Unlike previous approaches which use correlation between variables for band grouping, we study the efficacy of higher order statistical information (using average mutual information) for a bottom up band grouping. We also propose a confidence measure based decision fusion technique, where the weights associated with various classifiers are based on their confidence in recognizing the training data. To this end, training accuracies of all classifiers are used for weight assignment in the fusion process of test pixels. The proposed methods are tested using hyperspectral data with known ground truth, such that the efficacy can be quantitatively measured in terms of target recognition accuracies.

A Integrated Service Platform for Remote Sensing Image 3D Interpretation and Draughting based on HTML5

NASA Astrophysics Data System (ADS)

LIU, Yiping; XU, Qing; ZhANG, Heng; LV, Liang; LU, Wanjie; WANG, Dandi

2016-11-01

The purpose of this paper is to solve the problems of the traditional single system for interpretation and draughting such as inconsistent standards, single function, dependence on plug-ins, closed system and low integration level. On the basis of the comprehensive analysis of the target elements composition, map representation and similar system features, a 3D interpretation and draughting integrated service platform for multi-source, multi-scale and multi-resolution geospatial objects is established based on HTML5 and WebGL, which not only integrates object recognition, access, retrieval, three-dimensional display and test evaluation but also achieves collection, transfer, storage, refreshing and maintenance of data about Geospatial Objects and shows value in certain prospects and potential for growth.

Deformation effects of multi-functional monatomic carbon ring device

NASA Astrophysics Data System (ADS)

Qiu, Ming; Liew, K. M.

2011-06-01

Carrying on first-principles, the deformation effects on negative differential resistance (NDR) and rectifying behaviors of two cumulenic monatomic rings connected by polyyne and sandwiched between two Au electrodes are investigated. Interestingly, the number of obvious NDR whose peak-to-valley ratios increase from 1.24 to 5.16 is more than three and reverse rectification ratios also climb up from 1.42 to 7.89 with deformations increasing. Analysis of transmission spectra and frontier orbitals reveals that the response of different levels and resonant peaks, and transfer of the extended states to localized states of frontier orbital resonances under biases are responsible for these phenomena. Our works present a potential route to develop a multi-functional pressure device which has multi-peaks of NDR and rectifying behaviors.

Longitudinal analysis on the development of hospital quality management systems in the Netherlands.

PubMed

Dückers, Michel; Makai, Peter; Vos, Leti; Groenewegen, Peter; Wagner, Cordula

2009-10-01

Many changes have been initiated in the Dutch hospital sector to optimize health-care delivery: national agenda-setting, increased competition and transparency, a new system of hospital reimbursement based on diagnosis-treatment combinations, intensified monitoring of quality and a multi-layered organizational development programme based on quality improvement collaboratives. The objective is to answer the question as to whether these changes were accompanied by a further development of hospital quality management systems and to what extent did the development within the multi-layered programme hospitals differ from that in other hospitals. Longitudinal data were collected in 1995, 2000, 2005 and 2007 using a validated questionnaire. Descriptive analyses and multi-level modelling were applied to test whether: (1) quality management system development stages in hospitals differ over time, (2) development stages and trends differ between hospitals participating or not participating in the multi-layered programme and (3) hospital size has an effect on development stage. Dutch hospital sector between 1995 and 2007. Hospital organizations. Changes through time. Quality management system development stage. Since 1995, hospital quality management systems have reached higher development levels. Programme participants have developed their quality management system more rapidly than have non-participants. However, this effect is confounded by hospital size. Study results suggest that the combination of policy measures at macro level was accompanied by an increase in hospital size and the further development of quality management systems. Hospitals are entering the stage of systematic quality improvement.

APGEN Scheduling: 15 Years of Experience in Planning Automation

NASA Technical Reports Server (NTRS)

Maldague, Pierre F.; Wissler, Steve; Lenda, Matthew; Finnerty, Daniel

2014-01-01

In this paper, we discuss the scheduling capability of APGEN (Activity Plan Generator), a multi-mission planning application that is part of the NASA AMMOS (Advanced Multi- Mission Operations System), and how APGEN scheduling evolved over its applications to specific Space Missions. Our analysis identifies two major reasons for the successful application of APGEN scheduling to real problems: an expressive DSL (Domain-Specific Language) for formulating scheduling algorithms, and a well-defined process for enlisting the help of auxiliary modeling tools in providing high-fidelity, system-level simulations of the combined spacecraft and ground support system.

A fuzzy MCDM framework based on fuzzy measure and fuzzy integral for agile supplier evaluation

NASA Astrophysics Data System (ADS)

Dursun, Mehtap

2017-06-01

Supply chains need to be agile in order to response quickly to the changes in today's competitive environment. The success of an agile supply chain depends on the firm's ability to select the most appropriate suppliers. This study proposes a multi-criteria decision making technique for conducting an analysis based on multi-level hierarchical structure and fuzzy logic for the evaluation of agile suppliers. The ideal and anti-ideal solutions are taken into consideration simultaneously in the developed approach. The proposed decision approach enables the decision-makers to use linguistic terms, and thus, reduce their cognitive burden in the evaluation process. Furthermore, a hierarchy of evaluation criteria and their related sub-criteria is employed in the presented approach in order to conduct a more effective analysis.

Multi-hazard Assessment and Scenario Toolbox (MhAST): A Framework for Analyzing Compounding Effects of Multiple Hazards

NASA Astrophysics Data System (ADS)

Sadegh, M.; Moftakhari, H.; AghaKouchak, A.

2017-12-01

Many natural hazards are driven by multiple forcing variables, and concurrence/consecutive extreme events significantly increases risk of infrastructure/system failure. It is a common practice to use univariate analysis based upon a perceived ruling driver to estimate design quantiles and/or return periods of extreme events. A multivariate analysis, however, permits modeling simultaneous occurrence of multiple forcing variables. In this presentation, we introduce the Multi-hazard Assessment and Scenario Toolbox (MhAST) that comprehensively analyzes marginal and joint probability distributions of natural hazards. MhAST also offers a wide range of scenarios of return period and design levels and their likelihoods. Contribution of this study is four-fold: 1. comprehensive analysis of marginal and joint probability of multiple drivers through 17 continuous distributions and 26 copulas, 2. multiple scenario analysis of concurrent extremes based upon the most likely joint occurrence, one ruling variable, and weighted random sampling of joint occurrences with similar exceedance probabilities, 3. weighted average scenario analysis based on a expected event, and 4. uncertainty analysis of the most likely joint occurrence scenario using a Bayesian framework.

Multi-stage decoding for multi-level block modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu

1991-01-01

In this paper, we investigate various types of multi-stage decoding for multi-level block modulation codes, in which the decoding of a component code at each stage can be either soft-decision or hard-decision, maximum likelihood or bounded-distance. Error performance of codes is analyzed for a memoryless additive channel based on various types of multi-stage decoding, and upper bounds on the probability of an incorrect decoding are derived. Based on our study and computation results, we find that, if component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. In particular, we find that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum decoding of the overall code is very small: only a fraction of dB loss in SNR at the probability of an incorrect decoding for a block of 10(exp -6). Multi-stage decoding of multi-level modulation codes really offers a way to achieve the best of three worlds, bandwidth efficiency, coding gain, and decoding complexity.

Seasonal hazards and health risks in lower-income countries: field testing a multi-disciplinary approach.

PubMed

Few, Roger; Lake, Iain; Hunter, Paul R; Tran, Pham Gia; Thien, Vu Trong

2009-12-21

Understanding how risks to human health change as a result of seasonal variations in environmental conditions is likely to become of increasing importance in the context of climatic change, especially in lower-income countries. A multi-disciplinary approach can be a useful tool for improving understanding, particularly in situations where existing data resources are limited but the environmental health implications of seasonal hazards may be high. This short article describes a multi-disciplinary approach combining analysis of changes in levels of environmental contamination, seasonal variations in disease incidence and a social scientific analysis of health behaviour. The methodology was field-tested in a peri-urban environment in the Mekong Delta, Vietnam, where poor households face alternate seasonal extremes in the local environment as the water level in the Delta changes from flood to dry season. Low-income households in the research sites rely on river water for domestic uses, including provision of drinking water, and it is commonly perceived that the seasonal changes alter risk from diarrhoeal diseases and other diseases associated with contamination of water. The discussion focuses on the implementation of the methodology in the field, and draws lessons from the research process that can help in refining and developing the approach for application in other locations where seasonal dynamics of disease risk may have important consequences for public health.

Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening

PubMed Central

Mu, Lin

2018-01-01

This work introduces a number of algebraic topology approaches, including multi-component persistent homology, multi-level persistent homology, and electrostatic persistence for the representation, characterization, and description of small molecules and biomolecular complexes. In contrast to the conventional persistent homology, multi-component persistent homology retains critical chemical and biological information during the topological simplification of biomolecular geometric complexity. Multi-level persistent homology enables a tailored topological description of inter- and/or intra-molecular interactions of interest. Electrostatic persistence incorporates partial charge information into topological invariants. These topological methods are paired with Wasserstein distance to characterize similarities between molecules and are further integrated with a variety of machine learning algorithms, including k-nearest neighbors, ensemble of trees, and deep convolutional neural networks, to manifest their descriptive and predictive powers for protein-ligand binding analysis and virtual screening of small molecules. Extensive numerical experiments involving 4,414 protein-ligand complexes from the PDBBind database and 128,374 ligand-target and decoy-target pairs in the DUD database are performed to test respectively the scoring power and the discriminatory power of the proposed topological learning strategies. It is demonstrated that the present topological learning outperforms other existing methods in protein-ligand binding affinity prediction and ligand-decoy discrimination. PMID:29309403

Hygiene and sanitation promotion strategies among ethnic minority communities in northern Vietnam: a stakeholder analysis.

PubMed

Rheinländer, Thilde; Xuan, Le Thi Thanh; Hoat, Luu Ngoc; Dalsgaard, Anders; Konradsen, Flemming

2012-10-01

Effective rural hygiene and sanitation promotion (RHSP) is a major challenge for many low-income countries. This paper investigates strategies and stakeholders' roles and responsibilities in RHSP implementation in a multi-ethnic area of northern Vietnam, in order to identify lessons learned for future RHSP. A stakeholder analysis was performed, based on 49 semi-structured individual interviews and one group interview with stakeholders in RHSP in a northern province of Vietnam. Participants came from three sectors (agriculture, health and education), unions supported by the Vietnamese government and from four administrative levels (village, commune, district and province). The study villages represented four ethnic minority groups including lowland and highland communities. Stakeholders' roles, responsibilities and promotion methods were outlined, and implementation constraints and opportunities were identified and analysed using thematic content analysis. Effective RHSP in Vietnam is severely constrained despite supporting policies and a multi-sectorial and multi-level framework. Four main barriers for effective implementation of RHSP were identified: (1) weak inter-sectorial collaborations; (2) constraints faced by frontline promoters; (3) almost exclusive information-based and passive promotion methods applied; and (4) context unadjusted promotion strategies across ethnic groups, including a limited focus on socio-economic differences, language barriers and gender roles in the target groups. Highland communities were identified as least targeted and clearly in need of more intensive and effective RHSP. It is recommended that the Vietnamese government gives priority to increasing capacities of and collaboration among stakeholders implementing RHSP activities. This should focus on frontline promoters to perform effective behaviour change communication. It is also recommended to support more participatory and community-based initiatives, which can address the complex socio-economic and cultural determinants of health in multi-ethnic population groups. These lessons learned can improve future RHSP in Vietnam and are also of relevance for health promotion in other minority population groups in the region and globally.

Plasma and serum L-selectin and clinical and subclinical the Multi-Ethnic Study of Atherosclerosis (MESA)cardiovascular disease

PubMed Central

BERARDI, CECILIA; DECKER, PAUL A.; KIRSCH, PHILLIP S.; DE ANDRADE, MARIZA; TSAI, MICHAEL Y.; PANKOW, JAMES S.; SALE, MICHELE M.; SICOTTE, HUGUES; TANG, WEIHONG; HANSON, NAOMI; POLAK, JOSEPH F.; BIELINSKI, SUZETTE J.

2014-01-01

L-selectin has been suggested to play a role in atherosclerosis. Previous studies on cardiovascular disease (CVD) and serum or plasma L-selectin are inconsistent. The association of serum L-selectin (sL-selectin) with carotid intima-media thickness, coronary artery calcium, ankle-brachial index (subclinical CVD) and incident CVD was assessed within 2403 participants in the Multi-Ethnic Study of Atherosclerosis (MESA). Regression analysis and the Tobit model were used to study subclinical disease; Cox Proportional Hazards regression for incident CVD. Mean age was 63 ± 10, 47% were males; mean sL-selectin was significantly different across ethnicities. Within each race/ethnicity, sL-selectin was associated with age and sex; among Caucasians and African Americans, it was associated with smoking status and current alcohol use. sL-selectin levels did not predict subclinical or clinical CVD after correction for multiple comparisons. Conditional logistic regression models were used to study plasma L-selectin and CVD within 154 incident CVD cases, occurred in a median follow up of 8.5 years, and 306 age-, sex-, and ethnicity-matched controls. L-selectin levels in plasma were significantly lower than in serum and the overall concordance was low. Plasma levels were not associated with CVD. In conclusion, this large multi-ethnic population, soluble L-selectin levels did not predict clinical or subclinical CVD. PMID:24631064

Exploring alternate specifications to explain agency-level effects in placement decisions regarding aboriginal children: further analysis of the Canadian Incidence Study of Reported Child Abuse and Neglect Part B.

PubMed

Chabot, Martin; Fallon, Barbara; Tonmyr, Lil; MacLaurin, Bruce; Fluke, John; Blackstock, Cindy

2013-01-01

This paper builds upon the analyses presented in two companion papers (Fluke et al., 2010; Fallon et al., 2013) using data from the 1998 and 2003 cycles of the Canadian Incidence Study of Reported Child Abuse and Neglect (CIS-1998 and CIS-2003) to examine the influence of clinical and organizational characteristics on the decision to place a child in out-of-home care at the conclusion of a child maltreatment investigation. This paper explores various model specifications to explain the effect of an agency-level factor, proportion of Aboriginal reports, which emerged as a stable and significant factor through the two data collection cycles. It addresses the issue of data comparability between the two cycles and explores various re-specifications and descriptive analyses of reported models to evaluate their solidity with regards to the sampling schemes and the precise contribution of a multi-level specification. The decision to place a child in out-of-home care was examined using data from the CIS-2003. This child welfare dataset collected information about the results of nearly 12,000 child maltreatment investigations as well as a description of the characteristics of the workers and organization responsible for conducting those investigations. Multi-level statistical models were developed using MPlus software, which can accommodate dichotomous outcome variables and are more reflective of decision-making in child welfare. The models are thus multi-level binary logistic regressions. Final models revealed that two agency-level variables, 'Education degree of majority of workers' and 'Degree of centralization in the agency' clarify the nature of the effect of 'Proportion of Aboriginal reports', a stable, key second level predictor of the placement decision. The comparability of the effect of this agency-level variable across the 1998 and 2003 cycles becomes further evident through this analysis. By using a unified database including both cycles and various specifications of models, the comparability was found to be robust, in addition to clarifying the precise contribution of a multi-level specification. This third paper in a series establishes the 'Proportion of Aboriginal reports' received by the child welfare agency as an important agency level predictor associated with a child's likelihood of being placed in the Canadian child protection system. While the more complex models give support to the notion that unequal resources subtend those results, more analyses are needed to confirm this hypothesis. Unequal resources for agencies with larger Aboriginal caseloads may explain the persistence of the results. These findings suggest that specific resource constraints related to worker education may be explanatory. Copyright © 2012 Elsevier Ltd. All rights reserved.

A structured sparse regression method for estimating isoform expression level from multi-sample RNA-seq data.

PubMed

Zhang, L; Liu, X J

2016-06-03

With the rapid development of next-generation high-throughput sequencing technology, RNA-seq has become a standard and important technique for transcriptome analysis. For multi-sample RNA-seq data, the existing expression estimation methods usually deal with each single-RNA-seq sample, and ignore that the read distributions are consistent across multiple samples. In the current study, we propose a structured sparse regression method, SSRSeq, to estimate isoform expression using multi-sample RNA-seq data. SSRSeq uses a non-parameter model to capture the general tendency of non-uniformity read distribution for all genes across multiple samples. Additionally, our method adds a structured sparse regularization, which not only incorporates the sparse specificity between a gene and its corresponding isoform expression levels, but also reduces the effects of noisy reads, especially for lowly expressed genes and isoforms. Four real datasets were used to evaluate our method on isoform expression estimation. Compared with other popular methods, SSRSeq reduced the variance between multiple samples, and produced more accurate isoform expression estimations, and thus more meaningful biological interpretations.

Evaluating Partnerships to Enhance Disaster Risk Management using Multi-Criteria Analysis: An Application at the Pan-European Level

NASA Astrophysics Data System (ADS)

Hochrainer-Stigler, Stefan; Lorant, Anna

2018-01-01

Disaster risk is increasingly recognized as a major development challenge. Recent calls emphasize the need to proactively engage in disaster risk reduction, as well as to establish new partnerships between private and public sector entities in order to decrease current and future risks. Very often such potential partnerships have to meet different objectives reflecting on the priorities of stakeholders involved. Consequently, potential partnerships need to be assessed on multiple criteria to determine weakest links and greatest threats in collaboration. This paper takes a supranational multi-sector partnership perspective, and considers possible ways to enhance disaster risk management in the European Union by better coordination between the European Union Solidarity Fund, risk reduction efforts, and insurance mechanisms. Based on flood risk estimates we employ a risk-layer approach to determine set of options for new partnerships and test them in a high-level workshop via a novel cardinal ranking based multi-criteria approach. Whilst transformative changes receive good overall scores, we also find that the incorporation of risk into budget planning is an essential condition for successful partnerships.

A hybrid solution approach for a multi-objective closed-loop logistics network under uncertainty

NASA Astrophysics Data System (ADS)

Mehrbod, Mehrdad; Tu, Nan; Miao, Lixin

2015-06-01

The design of closed-loop logistics (forward and reverse logistics) has attracted growing attention with the stringent pressures of customer expectations, environmental concerns and economic factors. This paper considers a multi-product, multi-period and multi-objective closed-loop logistics network model with regard to facility expansion as a facility location-allocation problem, which more closely approximates real-world conditions. A multi-objective mixed integer nonlinear programming formulation is linearized by defining new variables and adding new constraints to the model. By considering the aforementioned model under uncertainty, this paper develops a hybrid solution approach by combining an interactive fuzzy goal programming approach and robust counterpart optimization based on three well-known robust counterpart optimization formulations. Finally, this paper compares the results of the three formulations using different test scenarios and parameter-sensitive analysis in terms of the quality of the final solution, CPU time, the level of conservatism, the degree of closeness to the ideal solution, the degree of balance involved in developing a compromise solution, and satisfaction degree.

Saccharification efficiencies of multi-enzyme complexes produced by aerobic fungi.

PubMed

Badhan, Ajay; Huang, Jiangli; Wang, Yuxi; Abbott, D Wade; Di Falco, Marcos; Tsang, Adrian; McAllister, Tim

2018-05-24

In the present study, we have characterized high molecular weight multi-enzyme complexes in two commercial enzymes produced by Trichoderma reesei (Spezyme CP) and Penicillium funiculosum (Accellerase XC). We successfully identified 146-1000 kDa complexes using Blue native polyacrylamide gel electrophoresis (BN-PAGE) to fractionate the protein profile in both preparations. Identified complexes dissociated into lower molecular weight constituents when loaded on SDS PAGE. Unfolding of the secondary structure of multi-enzyme complexes with trimethylamine (pH >10) suggested that they were not a result of unspecific protein aggregation. Cellulase (CMCase) profiles of extracts of BN-PAGE fractionated protein bands confirmed cellulase activity within the multi-enzyme complexes. A microassay was used to identify protein bands that promoted high levels of glucose release from barley straw. Those with high saccharification yield were subjected to LC-MS analysis to identify the principal enzymatic activities responsible. The results suggest that secretion of proteins by aerobic fungi leads to the formation of high molecular weight multi-enzyme complexes that display activity against carboxymethyl cellulose and barley straw. Copyright © 2018. Published by Elsevier B.V.

What Can We Learn about Mental Health Needs from Tweets Mentioning Dementia on World Alzheimer’s Day?

PubMed Central

Yoon, Sunmoo

2017-01-01

Background Twitter can address the mental health challenges of dementia care. The aims of this study is to explore the contents and user interactions of tweets mentioning dementia to gain insights for dementia care. Methods We collected 35,260 tweets mentioning Alzheimer’s or dementia on World Alzheimer’s Day, September 21st in 2015. Topic modeling and social network analysis were applied to uncover content and structure of user communication. Results Global users generated keywords related to mental health and care including #psychology and #mental health. There were similarities and differences between the UK and the US in tweet content. The macro-level analysis uncovered substantial public interest on dementia. The meso-level network analysis revealed that top leaders of communities were spiritual organizations and traditional media. Conclusions The application of topic modeling and multi-level network analysis while incorporating visualization techniques can promote a global level understanding regarding public attention, interests, and insights regarding dementia care and mental health. PMID:27803262

Advances in combined endoscopic fluorescence confocal microscopy and optical coherence tomography

NASA Astrophysics Data System (ADS)

Risi, Matthew D.

Confocal microendoscopy provides real-time high resolution cellular level images via a minimally invasive procedure. Results from an ongoing clinical study to detect ovarian cancer with a novel confocal fluorescent microendoscope are presented. As an imaging modality, confocal fluorescence microendoscopy typically requires exogenous fluorophores, has a relatively limited penetration depth (100 μm), and often employs specialized aperture configurations to achieve real-time imaging in vivo. Two primary research directions designed to overcome these limitations and improve diagnostic capability are presented. Ideal confocal imaging performance is obtained with a scanning point illumination and confocal aperture, but this approach is often unsuitable for real-time, in vivo biomedical imaging. By scanning a slit aperture in one direction, image acquisition speeds are greatly increased, but at the cost of a reduction in image quality. The design, implementation, and experimental verification of a custom multi-point-scanning modification to a slit-scanning multi-spectral confocal microendoscope is presented. This new design improves the axial resolution while maintaining real-time imaging rates. In addition, the multi-point aperture geometry greatly reduces the effects of tissue scatter on imaging performance. Optical coherence tomography (OCT) has seen wide acceptance and FDA approval as a technique for ophthalmic retinal imaging, and has been adapted for endoscopic use. As a minimally invasive imaging technique, it provides morphological characteristics of tissues at a cellular level without requiring the use of exogenous fluorophores. OCT is capable of imaging deeper into biological tissue (˜1-2 mm) than confocal fluorescence microscopy. A theoretical analysis of the use of a fiber-bundle in spectral-domain OCT systems is presented. The fiber-bundle enables a flexible endoscopic design and provides fast, parallelized acquisition of the optical coherence tomography data. However, the multi-mode characteristic of the fibers in the fiber-bundle affects the depth sensitivity of the imaging system. A description of light interference in a multi-mode fiber is presented along with numerical simulations and experimental studies to illustrate the theoretical analysis.

Sea-level change during the last 2500 years in New Jersey, USA

USGS Publications Warehouse

Kemp, Andrew C.; Horton, Benjamin P.; Vane, Christopher H.; Bernhardt, Christopher E.; Corbett, D. Reide; Engelhart, Simon E.; Anisfeld, Shimon C.; Parnell, Andrew C.; Cahill, Niamh

2013-01-01

Relative sea-level changes during the last ∼2500 years in New Jersey, USA were reconstructed to test if late Holocene sea level was stable or included persistent and distinctive phases of variability. Foraminifera and bulk-sediment δ13C values were combined to reconstruct paleomarsh elevation with decimeter precision from sequences of salt-marsh sediment at two sites using a multi-proxy approach. The additional paleoenvironmental information provided by bulk-sediment δ13C values reduced vertical uncertainty in the sea-level reconstruction by about one third of that estimated from foraminifera alone using a transfer function. The history of sediment deposition was constrained by a composite chronology. An age–depth model developed for each core enabled reconstruction of sea level with multi-decadal resolution. Following correction for land-level change (1.4 mm/yr), four successive and sustained (multi-centennial) sea-level trends were objectively identified and quantified (95% confidence interval) using error-in-variables change point analysis to account for age and sea-level uncertainties. From at least 500 BC to 250 AD, sea-level fell at 0.11 mm/yr. The second period saw sea-level rise at 0.62 mm/yr from 250 AD to 733 AD. Between 733 AD and 1850 AD, sea level fell at 0.12 mm/yr. The reconstructed rate of sea-level rise since ∼1850 AD was 3.1 mm/yr and represents the most rapid period of change for at least 2500 years. This trend began between 1830 AD and 1873 AD. Since this change point, reconstructed sea-level rise is in agreement with regional tide-gauge records and exceeds the global average estimate for the 20th century. These positive and negative departures from background rates demonstrate that the late Holocene sea level was not stable in New Jersey.

Mission Command in the Age of Network-Enabled Operations: Social Network Analysis of Information Sharing and Situation Awareness

DTIC Science & Technology

2016-06-22

this assumption in a large-scale, 2-week military training exercise. We conducted a social network analysis of email communications among the multi...exponential random graph models challenge the aforementioned assumption, as increased email output was associated with lower individual situation... email links were more commonly formed among members of the command staff with both similar functions and levels of situation awareness, than between

Mathematical model comparing of the multi-level economics systems

NASA Astrophysics Data System (ADS)

Brykalov, S. M.; Kryanev, A. V.

2017-12-01

The mathematical model (scheme) of a multi-level comparison of the economic system, characterized by the system of indices, is worked out. In the mathematical model of the multi-level comparison of the economic systems, the indicators of peer review and forecasting of the economic system under consideration can be used. The model can take into account the uncertainty in the estimated values of the parameters or expert estimations. The model uses the multi-criteria approach based on the Pareto solutions.

Care pathways across the primary-hospital care continuum: using the multi-level framework in explaining care coordination

PubMed Central

2013-01-01

Background Care pathways are widely used in hospitals for a structured and detailed planning of the care process. There is a growing interest in extending care pathways into primary care to improve quality of care by increasing care coordination. Evidence is sparse about the relationship between care pathways and care coordination. The multi-level framework explores care coordination across organizations and states that (inter)organizational mechanisms have an effect on the relationships between healthcare professionals, resulting in quality and efficiency of care. The aim of this study was to assess the extent to which care pathways support or create elements of the multi-level framework necessary to improve care coordination across the primary - hospital care continuum. Methods This study is an in-depth analysis of five existing local community projects located in four different regions in Flanders (Belgium) to determine whether the available empirical evidence supported or refuted the theoretical expectations from the multi-level framework. Data were gathered using mixed methods, including structured face-to-face interviews, participant observations, documentation and a focus group. Multiple cases were analyzed performing a cross case synthesis to strengthen the results. Results The development of a care pathway across the primary-hospital care continuum, supported by a step-by-step scenario, led to the use of existing and newly constructed structures, data monitoring and the development of information tools. The construction and use of these inter-organizational mechanisms had a positive effect on exchanging information, formulating and sharing goals, defining and knowing each other’s roles, expectations and competences and building qualitative relationships. Conclusion Care pathways across the primary-hospital care continuum enhance the components of care coordination. PMID:23919518

Care pathways across the primary-hospital care continuum: using the multi-level framework in explaining care coordination.

PubMed

Van Houdt, Sabine; Heyrman, Jan; Vanhaecht, Kris; Sermeus, Walter; De Lepeleire, Jan

2013-08-06

Care pathways are widely used in hospitals for a structured and detailed planning of the care process. There is a growing interest in extending care pathways into primary care to improve quality of care by increasing care coordination. Evidence is sparse about the relationship between care pathways and care coordination.The multi-level framework explores care coordination across organizations and states that (inter)organizational mechanisms have an effect on the relationships between healthcare professionals, resulting in quality and efficiency of care.The aim of this study was to assess the extent to which care pathways support or create elements of the multi-level framework necessary to improve care coordination across the primary-hospital care continuum. This study is an in-depth analysis of five existing local community projects located in four different regions in Flanders (Belgium) to determine whether the available empirical evidence supported or refuted the theoretical expectations from the multi-level framework. Data were gathered using mixed methods, including structured face-to-face interviews, participant observations, documentation and a focus group. Multiple cases were analyzed performing a cross case synthesis to strengthen the results. The development of a care pathway across the primary-hospital care continuum, supported by a step-by-step scenario, led to the use of existing and newly constructed structures, data monitoring and the development of information tools. The construction and use of these inter-organizational mechanisms had a positive effect on exchanging information, formulating and sharing goals, defining and knowing each other's roles, expectations and competences and building qualitative relationships. Care pathways across the primary-hospital care continuum enhance the components of care coordination.

Automatic detection of multi-level acetowhite regions in RGB color images of the uterine cervix

NASA Astrophysics Data System (ADS)

Lange, Holger

2005-04-01

Uterine cervical cancer is the second most common cancer among women worldwide. Colposcopy is a diagnostic method used to detect cancer precursors and cancer of the uterine cervix, whereby a physician (colposcopist) visually inspects the metaplastic epithelium on the cervix for certain distinctly abnormal morphologic features. A contrast agent, a 3-5% acetic acid solution, is used, causing abnormal and metaplastic epithelia to turn white. The colposcopist considers diagnostic features such as the acetowhite, blood vessel structure, and lesion margin to derive a clinical diagnosis. STI Medical Systems is developing a Computer-Aided-Diagnosis (CAD) system for colposcopy -- ColpoCAD, a complex image analysis system that at its core assesses the same visual features as used by colposcopists. The acetowhite feature has been identified as one of the most important individual predictors of lesion severity. Here, we present the details and preliminary results of a multi-level acetowhite region detection algorithm for RGB color images of the cervix, including the detection of the anatomic features: cervix, os and columnar region, which are used for the acetowhite region detection. The RGB images are assumed to be glare free, either obtained by cross-polarized image acquisition or glare removal pre-processing. The basic approach of the algorithm is to extract a feature image from the RGB image that provides a good acetowhite to cervix background ratio, to segment the feature image using novel pixel grouping and multi-stage region-growing algorithms that provide region segmentations with different levels of detail, to extract the acetowhite regions from the region segmentations using a novel region selection algorithm, and then finally to extract the multi-levels from the acetowhite regions using multiple thresholds. The performance of the algorithm is demonstrated using human subject data.

The learner's perspective in GP teaching practices with multi-level learners: a qualitative study.

PubMed

Thomson, Jennifer S; Anderson, Katrina; Haesler, Emily; Barnard, Amanda; Glasgow, Nicholas

2014-03-19

Medical students, junior hospital doctors on rotation and general practice (GP) registrars are undertaking their training in clinical general practices in increasing numbers in Australia. Some practices have four levels of learner. This study aimed to explore how multi-level teaching (also called vertical integration of GP education and training) is occurring in clinical general practice and the impact of such teaching on the learner. A qualitative research methodology was used with face-to-face, semi-structured interviews of medical students, junior hospital doctors, GP registrars and GP teachers in eight training practices in the region that taught all levels of learners. Interviews were audio-recorded and transcribed. Qualitative analysis was conducted using thematic analysis techniques aided by the use of the software package N-Vivo 9. Primary themes were identified and categorised by the co-investigators. 52 interviews were completed and analysed. Themes were identified relating to both the practice learning environment and teaching methods used.A practice environment where there is a strong teaching culture, enjoyment of learning, and flexible learning methods, as well as learning spaces and organised teaching arrangements, all contribute to positive learning from a learners' perspective.Learners identified a number of innovative teaching methods and viewed them as positive. These included multi-level learner group tutorials in the practice, being taught by a team of teachers, including GP registrars and other health professionals, and access to a supernumerary GP supervisor (also termed "GP consultant teacher"). Other teaching methods that were viewed positively were parallel consulting, informal learning and rural hospital context integrated learning. Vertical integration of GP education and training generally impacted positively on all levels of learner. This research has provided further evidence about the learning culture, structures and teaching processes that have a positive impact on learners in the clinical general practice setting where there are multiple levels of learners. It has also identified some innovative teaching methods that will need further examination. The findings reinforce the importance of the environment for learning and learner centred approaches and will be important for training organisations developing vertically integrated practices and in their training of GP teachers.

The learner’s perspective in GP teaching practices with multi-level learners: a qualitative study

PubMed Central

2014-01-01

Background Medical students, junior hospital doctors on rotation and general practice (GP) registrars are undertaking their training in clinical general practices in increasing numbers in Australia. Some practices have four levels of learner. This study aimed to explore how multi-level teaching (also called vertical integration of GP education and training) is occurring in clinical general practice and the impact of such teaching on the learner. Methods A qualitative research methodology was used with face-to-face, semi-structured interviews of medical students, junior hospital doctors, GP registrars and GP teachers in eight training practices in the region that taught all levels of learners. Interviews were audio-recorded and transcribed. Qualitative analysis was conducted using thematic analysis techniques aided by the use of the software package N-Vivo 9. Primary themes were identified and categorised by the co-investigators. Results 52 interviews were completed and analysed. Themes were identified relating to both the practice learning environment and teaching methods used. A practice environment where there is a strong teaching culture, enjoyment of learning, and flexible learning methods, as well as learning spaces and organised teaching arrangements, all contribute to positive learning from a learners’ perspective. Learners identified a number of innovative teaching methods and viewed them as positive. These included multi-level learner group tutorials in the practice, being taught by a team of teachers, including GP registrars and other health professionals, and access to a supernumerary GP supervisor (also termed “GP consultant teacher”). Other teaching methods that were viewed positively were parallel consulting, informal learning and rural hospital context integrated learning. Conclusions Vertical integration of GP education and training generally impacted positively on all levels of learner. This research has provided further evidence about the learning culture, structures and teaching processes that have a positive impact on learners in the clinical general practice setting where there are multiple levels of learners. It has also identified some innovative teaching methods that will need further examination. The findings reinforce the importance of the environment for learning and learner centred approaches and will be important for training organisations developing vertically integrated practices and in their training of GP teachers. PMID:24645670

A Multi-Factor Analysis of Job Satisfaction among School Nurses

ERIC Educational Resources Information Center

Foley, Marcia; Lee, Julie; Wilson, Lori; Cureton, Virginia Young; Canham, Daryl

2004-01-01

Although job satisfaction has been widely studied among registered nurses working in traditional health care settings, little is known about the job-related values and perceptions of nurses working in school systems. Job satisfaction is linked to lower levels of job-related stress, burnout, and career abandonment among nurses. This study evaluated…

Transformational Leadership Related to School Climate: A Multi-Level Analysis

ERIC Educational Resources Information Center

McCarley, Troy A.; Peters, Michelle L.; Decman, John M.

2016-01-01

Across the nation, quality leadership and positive school climate are critical to the success of every principal, student, and school. As a result, this study examined the relationship between teacher perceptions of the degree to which a principal displays the factors of transformational leadership and the perceived school climate. A purposeful…

Implications of Multi-Core Architectures on the Development of Multiple Independent Levels of Security (MILS) Compliant Systems

DTIC Science & Technology

2012-10-01

REPORT 3. DATES COVERED (From - To) MAR 2010 – APR 2012 4 . TITLE AND SUBTITLE IMPLICATIONS OF MULT-CORE ARCHITECTURES ON THE DEVELOPMENT OF...Framework for Multicore Information Flow Analysis ...................................... 23 4 4.1 A Hypothetical Reference Architecture... 4 Figure 2: Pentium II Block Diagram

"City Air Makes Free": A Multi-Level, Cross-National Analysis of Self-Efficacy

ERIC Educational Resources Information Center

Debies-Carl, Jeffrey S.; Huggins, Christopher M.

2009-01-01

The effects of cities on the subjective states of individuals have been the subject of continuous inquiry. Recent research has demonstrated potential links between immediate environments and individual outcomes such as perceived powerlessness. However, the results of such studies are inconsistent and fail to account for the greater societal…

Taxonomic evaluation of unidentified Streptomyces isolates in the ARS Culture Collection (NRRL) using multi-locus sequence analysis

USDA-ARS?s Scientific Manuscript database

The ARS Culture Collection (NRRL) currently contains 7569 strains within the family Streptomycetaceae but 4368 of them have not been characterized to the species level. A gene sequence database using the Bacterial Isolate Genomic Sequence Database package (BIGSdb) (Jolley & Maiden, 2010) is availabl...

Global Citizenship and the Importance of Education in a Globally Integrated World

ERIC Educational Resources Information Center

Smith, William C.; Fraser, Pablo; Chykina, Volha; Ikoma, Sakiko; Levitan, Joseph; Liu, Jing; Mahfouz, Julia

2017-01-01

As national borders dissipate and technology allows different cultures and nationalities to communicate on a regular basis, more individuals are self-identifying as a global citizen. Using Social Network Analysis and multi-level modelling, this study explores factors associated with global citizen affinity and finds that education plays an…

After-School Programs as a Prosocial Setting for Bonding between Peers

ERIC Educational Resources Information Center

Wright, Robin; John, Lindsay; Duku, Eric; Burgos, Giovani; Krygsman, Amanda; Esposto, Charlene

2009-01-01

This study reports on the longitudinal analysis of a structured after-school arts program for Canadian youth, ages 9 to 15 years, from low-income communities where the relationship of peer social support, family interactions, and psychosocial outcomes is evaluated. Multi-level growth curve analyses suggest an increase in prosocial development with…

Evolutionary conservation, diversity and specificity of LTR retrotransposons in flowering plants: insights from genome-wide analysis and multi-specific comparison

USDA-ARS?s Scientific Manuscript database

The availability of complete or nearly complete genome sequences from several plant species permits detailed discovery and cross-species comparison of transposable elements (TEs) at the whole genome level. We initially investigated 510 LTR-retrotransposon (LTR-RT) families that are comprised of 32,...

Explaining Hong Kong Students' International Achievement in Civic Learning

ERIC Educational Resources Information Center

Kennedy, Kerry J.; Lijuan, Li

2016-01-01

This study identifies predictors of Hong Kong students' civic learning. It has adopted a cross-sectional quantitative design using secondary data from the 2009 International Civics and Citizenship Education Study (ICCS 2009; Schulz et al., 2010). Multi-level analysis reveals that most of the variance in student achievement can be accounted for by…

Pupil Performance, Absenteeism and School Drop-out: A Multi-dimensional Analysis.

ERIC Educational Resources Information Center

Smyht, Emer

1999-01-01

Assesses whether second-level schools in Ireland are equally effective regarding examination performance, absenteeism, and potential dropouts, using multivariate analyses of data from 15- and 16-year-olds in 116 schools. Absenteeism and potential dropout rates are lower in schools that enhance pupils' academic progress. (Contains 22 references.)…

Examining the Relationships among Classroom Climate, Self-Efficacy, and Achievement in Undergraduate Mathematics: A Multi-Level Analysis

ERIC Educational Resources Information Center

Peters, Michelle L.

2013-01-01

For nearly 50 years, leaders in American industry, military, education, and politics have focused considerable attention on STEM (science, technology, engineering, and mathematics) education. Given the increased societal demand for STEM careers, the relationships among classroom climate, self-efficacy, and achievement in undergraduate mathematics…

Students' Experience of Synchronous Learning in Distributed Environments

ERIC Educational Resources Information Center

Stewart, Anissa R.; Harlow, Danielle B.; DeBacco, Kim

2011-01-01

This article reports on a two-year ethnographic study of learners participating in multi-site, graduate-level education classes. Classes sometimes met face-to-face in the same physical location; at other times part of the class met physically elsewhere. Yet all were linked through the virtual space. Ethnographic analysis of four data types…

An Analysis of Rural Unemployment Using a Human Resources Development Perspective.

ERIC Educational Resources Information Center

Napier, Ted L.; Jarrett, Charles W.

Investigation indicated factors other than human resource variables must be used to understand unemployment status. Based on a 1979 survey of a random sample (N=640) of rural adult California residents from a multi-county development district, 15 human resource development factors (including educational level, job training, match of work skills…

Evolution of neuroarchitecture, multi-level analyses and calibrative reductionism

PubMed Central

Berntson, Gary G.; Norman, Greg J.; Hawkley, Louise C.; Cacioppo, John T.

2012-01-01

Evolution has sculpted the incredibly complex human nervous system, among the most complex functions of which extend beyond the individual to an intricate social structure. Although these functions are deterministic, those determinants are legion, heavily interacting and dependent on a specific evolutionary trajectory. That trajectory was directed by the adaptive significance of quasi-random genetic variations, but was also influenced by chance and caprice. With a different evolutionary pathway, the same neural elements could subserve functions distinctly different from what they do in extant human brains. Consequently, the properties of higher level neural networks cannot be derived readily from the properties of the lower level constituent elements, without studying these elements in the aggregate. Thus, a multi-level approach to integrative neuroscience may offer an optimal strategy. Moreover, the process of calibrative reductionism, by which concepts and understandings from one level of organization or analysis can mutually inform and ‘calibrate’ those from other levels (both higher and lower), may represent a viable approach to the application of reductionism in science. This is especially relevant in social neuroscience, where the basic subject matter of interest is defined by interacting organisms across diverse environments. PMID:23386961

Development and human factors analysis of an augmented reality interface for multi-robot tele-operation and control

NASA Astrophysics Data System (ADS)

Lee, Sam; Lucas, Nathan P.; Ellis, R. Darin; Pandya, Abhilash

2012-06-01

This paper presents a seamlessly controlled human multi-robot system comprised of ground and aerial robots of semiautonomous nature for source localization tasks. The system combines augmented reality interfaces capabilities with human supervisor's ability to control multiple robots. The role of this human multi-robot interface is to allow an operator to control groups of heterogeneous robots in real time in a collaborative manner. It used advanced path planning algorithms to ensure obstacles are avoided and that the operators are free for higher-level tasks. Each robot knows the environment and obstacles and can automatically generate a collision-free path to any user-selected target. It displayed sensor information from each individual robot directly on the robot in the video view. In addition, a sensor data fused AR view is displayed which helped the users pin point source information or help the operator with the goals of the mission. The paper studies a preliminary Human Factors evaluation of this system in which several interface conditions are tested for source detection tasks. Results show that the novel Augmented Reality multi-robot control (Point-and-Go and Path Planning) reduced mission completion times compared to the traditional joystick control for target detection missions. Usability tests and operator workload analysis are also investigated.

Application of the Geophysical Scale Multi-Block Transport Modeling System to Hydrodynamic Forcing of Dredged Material Placement Sediment Transport within the James River Estuary

NASA Astrophysics Data System (ADS)

Kim, S. C.; Hayter, E. J.; Pruhs, R.; Luong, P.; Lackey, T. C.

2016-12-01

The geophysical scale circulation of the Mid Atlantic Bight and hydrologic inputs from adjacent Chesapeake Bay watersheds and tributaries influences the hydrodynamics and transport of the James River estuary. Both barotropic and baroclinic transport govern the hydrodynamics of this partially stratified estuary. Modeling the placement of dredged sediment requires accommodating this wide spectrum of atmospheric and hydrodynamic scales. The Geophysical Scale Multi-Block (GSMB) Transport Modeling System is a collection of multiple well established and USACE approved process models. Taking advantage of the parallel computing capability of multi-block modeling, we performed one year three-dimensional modeling of hydrodynamics in supporting simulation of dredged sediment placements transport and morphology changes. Model forcing includes spatially and temporally varying meteorological conditions and hydrological inputs from the watershed. Surface heat flux estimates were derived from the National Solar Radiation Database (NSRDB). The open water boundary condition for water level was obtained from an ADCIRC model application of the U. S. East Coast. Temperature-salinity boundary conditions were obtained from the Environmental Protection Agency (EPA) Chesapeake Bay Program (CBP) long-term monitoring stations database. Simulated water levels were calibrated and verified by comparison with National Oceanic and Atmospheric Administration (NOAA) tide gage locations. A harmonic analysis of the modeled tides was performed and compared with NOAA tide prediction data. In addition, project specific circulation was verified using US Army Corps of Engineers (USACE) drogue data. Salinity and temperature transport was verified at seven CBP long term monitoring stations along the navigation channel. Simulation and analysis of model results suggest that GSMB is capable of resolving the long duration, multi-scale processes inherent to practical engineering problems such as dredged material placement stability.

Hybrid PV/diesel solar power system design using multi-level factor analysis optimization

NASA Astrophysics Data System (ADS)

Drake, Joshua P.

Solar power systems represent a large area of interest across a spectrum of organizations at a global level. It was determined that a clear understanding of current state of the art software and design methods, as well as optimization methods, could be used to improve the design methodology. Solar power design literature was researched for an in depth understanding of solar power system design methods and algorithms. Multiple software packages for the design and optimization of solar power systems were analyzed for a critical understanding of their design workflow. In addition, several methods of optimization were studied, including brute force, Pareto analysis, Monte Carlo, linear and nonlinear programming, and multi-way factor analysis. Factor analysis was selected as the most efficient optimization method for engineering design as it applied to solar power system design. The solar power design algorithms, software work flow analysis, and factor analysis optimization were combined to develop a solar power system design optimization software package called FireDrake. This software was used for the design of multiple solar power systems in conjunction with an energy audit case study performed in seven Tibetan refugee camps located in Mainpat, India. A report of solar system designs for the camps, as well as a proposed schedule for future installations was generated. It was determined that there were several improvements that could be made to the state of the art in modern solar power system design, though the complexity of current applications is significant.

Adaptive control of a jet turboshaft engine driving a variable pitch propeller using multiple models

NASA Astrophysics Data System (ADS)

Ahmadian, Narjes; Khosravi, Alireza; Sarhadi, Pouria

2017-08-01

In this paper, a multiple model adaptive control (MMAC) method is proposed for a gas turbine engine. The model of a twin spool turbo-shaft engine driving a variable pitch propeller includes various operating points. Variations in fuel flow and propeller pitch inputs produce different operating conditions which force the controller to be adopted rapidly. Important operating points are three idle, cruise and full thrust cases for the entire flight envelope. A multi-input multi-output (MIMO) version of second level adaptation using multiple models is developed. Also, stability analysis using Lyapunov method is presented. The proposed method is compared with two conventional first level adaptation and model reference adaptive control techniques. Simulation results for JetCat SPT5 turbo-shaft engine demonstrate the performance and fidelity of the proposed method.

NaviCom: a web application to create interactive molecular network portraits using multi-level omics data.

PubMed

Dorel, Mathurin; Viara, Eric; Barillot, Emmanuel; Zinovyev, Andrei; Kuperstein, Inna

2017-01-01

Human diseases such as cancer are routinely characterized by high-throughput molecular technologies, and multi-level omics data are accumulated in public databases at increasing rate. Retrieval and visualization of these data in the context of molecular network maps can provide insights into the pattern of regulation of molecular functions reflected by an omics profile. In order to make this task easy, we developed NaviCom, a Python package and web platform for visualization of multi-level omics data on top of biological network maps. NaviCom is bridging the gap between cBioPortal, the most used resource of large-scale cancer omics data and NaviCell, a data visualization web service that contains several molecular network map collections. NaviCom proposes several standardized modes of data display on top of molecular network maps, allowing addressing specific biological questions. We illustrate how users can easily create interactive network-based cancer molecular portraits via NaviCom web interface using the maps of Atlas of Cancer Signalling Network (ACSN) and other maps. Analysis of these molecular portraits can help in formulating a scientific hypothesis on the molecular mechanisms deregulated in the studied disease. NaviCom is available at https://navicom.curie.fr. © The Author(s) 2017. Published by Oxford University Press.

SU-E-J-110: A Novel Level Set Active Contour Algorithm for Multimodality Joint Segmentation/Registration Using the Jensen-Rényi Divergence.

PubMed

Markel, D; Naqa, I El; Freeman, C; Vallières, M

2012-06-01

To present a novel joint segmentation/registration for multimodality image-guided and adaptive radiotherapy. A major challenge to this framework is the sensitivity of many segmentation or registration algorithms to noise. Presented is a level set active contour based on the Jensen-Renyi (JR) divergence to achieve improved noise robustness in a multi-modality imaging space. To present a novel joint segmentation/registration for multimodality image-guided and adaptive radiotherapy. A major challenge to this framework is the sensitivity of many segmentation or registration algorithms to noise. Presented is a level set active contour based on the Jensen-Renyi (JR) divergence to achieve improved noise robustness in a multi-modality imaging space. It was found that JR divergence when used for segmentation has an improved robustness to noise compared to using mutual information, or other entropy-based metrics. The MI metric failed at around 2/3 the noise power than the JR divergence. The JR divergence metric is useful for the task of joint segmentation/registration of multimodality images and shows improved results compared entropy based metric. The algorithm can be easily modified to incorporate non-intensity based images, which would allow applications into multi-modality and texture analysis. © 2012 American Association of Physicists in Medicine.

Multiresolution modeling with a JMASS-JWARS HLA Federation

NASA Astrophysics Data System (ADS)

Prince, John D.; Painter, Ron D.; Pendell, Brian; Richert, Walt; Wolcott, Christopher

2002-07-01

CACI, Inc.-Federal has built, tested, and demonstrated the use of a JMASS-JWARS HLA Federation that supports multi- resolution modeling of a weapon system and its subsystems in a JMASS engineering and engagement model environment, while providing a realistic JWARS theater campaign-level synthetic battle space and operational context to assess the weapon system's value added and deployment/employment supportability in a multi-day, combined force-on-force scenario. Traditionally, acquisition analyses require a hierarchical suite of simulation models to address engineering, engagement, mission and theater/campaign measures of performance, measures of effectiveness and measures of merit. Configuring and running this suite of simulations and transferring the appropriate data between each model is both time consuming and error prone. The ideal solution would be a single simulation with the requisite resolution and fidelity to perform all four levels of acquisition analysis. However, current computer hardware technologies cannot deliver the runtime performance necessary to support the resulting extremely large simulation. One viable alternative is to integrate the current hierarchical suite of simulation models using the DoD's High Level Architecture in order to support multi- resolution modeling. An HLA integration eliminates the extremely large model problem, provides a well-defined and manageable mixed resolution simulation and minimizes VV&A issues.

Integrative Data Analysis of Multi-Platform Cancer Data with a Multimodal Deep Learning Approach.

PubMed

Liang, Muxuan; Li, Zhizhong; Chen, Ting; Zeng, Jianyang

2015-01-01

Identification of cancer subtypes plays an important role in revealing useful insights into disease pathogenesis and advancing personalized therapy. The recent development of high-throughput sequencing technologies has enabled the rapid collection of multi-platform genomic data (e.g., gene expression, miRNA expression, and DNA methylation) for the same set of tumor samples. Although numerous integrative clustering approaches have been developed to analyze cancer data, few of them are particularly designed to exploit both deep intrinsic statistical properties of each input modality and complex cross-modality correlations among multi-platform input data. In this paper, we propose a new machine learning model, called multimodal deep belief network (DBN), to cluster cancer patients from multi-platform observation data. In our integrative clustering framework, relationships among inherent features of each single modality are first encoded into multiple layers of hidden variables, and then a joint latent model is employed to fuse common features derived from multiple input modalities. A practical learning algorithm, called contrastive divergence (CD), is applied to infer the parameters of our multimodal DBN model in an unsupervised manner. Tests on two available cancer datasets show that our integrative data analysis approach can effectively extract a unified representation of latent features to capture both intra- and cross-modality correlations, and identify meaningful disease subtypes from multi-platform cancer data. In addition, our approach can identify key genes and miRNAs that may play distinct roles in the pathogenesis of different cancer subtypes. Among those key miRNAs, we found that the expression level of miR-29a is highly correlated with survival time in ovarian cancer patients. These results indicate that our multimodal DBN based data analysis approach may have practical applications in cancer pathogenesis studies and provide useful guidelines for personalized cancer therapy.

Multi-Modality Cascaded Convolutional Neural Networks for Alzheimer's Disease Diagnosis.

PubMed

Liu, Manhua; Cheng, Danni; Wang, Kundong; Wang, Yaping

2018-03-23

Accurate and early diagnosis of Alzheimer's disease (AD) plays important role for patient care and development of future treatment. Structural and functional neuroimages, such as magnetic resonance images (MRI) and positron emission tomography (PET), are providing powerful imaging modalities to help understand the anatomical and functional neural changes related to AD. In recent years, machine learning methods have been widely studied on analysis of multi-modality neuroimages for quantitative evaluation and computer-aided-diagnosis (CAD) of AD. Most existing methods extract the hand-craft imaging features after image preprocessing such as registration and segmentation, and then train a classifier to distinguish AD subjects from other groups. This paper proposes to construct cascaded convolutional neural networks (CNNs) to learn the multi-level and multimodal features of MRI and PET brain images for AD classification. First, multiple deep 3D-CNNs are constructed on different local image patches to transform the local brain image into more compact high-level features. Then, an upper high-level 2D-CNN followed by softmax layer is cascaded to ensemble the high-level features learned from the multi-modality and generate the latent multimodal correlation features of the corresponding image patches for classification task. Finally, these learned features are combined by a fully connected layer followed by softmax layer for AD classification. The proposed method can automatically learn the generic multi-level and multimodal features from multiple imaging modalities for classification, which are robust to the scale and rotation variations to some extent. No image segmentation and rigid registration are required in pre-processing the brain images. Our method is evaluated on the baseline MRI and PET images of 397 subjects including 93 AD patients, 204 mild cognitive impairment (MCI, 76 pMCI +128 sMCI) and 100 normal controls (NC) from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Experimental results show that the proposed method achieves an accuracy of 93.26% for classification of AD vs. NC and 82.95% for classification pMCI vs. NC, demonstrating the promising classification performance.

The Multi-factor Predictive Seis &Gis Model of Ecological, Genetical, Population Health Risk and Bio-geodynamic Processes In Geopathogenic Zones

NASA Astrophysics Data System (ADS)

Bondarenko, Y.

I. Goal and Scope. Human birth rate decrease, death-rate growth and increase of mu- tagenic deviations risk take place in geopathogenic and anthropogenic hazard zones. Such zones create unfavourable conditions for reproductive process of future genera- tions. These negative trends should be considered as a protective answer of the com- plex biosocial system to the appearance of natural and anthropogenic risk factors that are unfavourable for human health. The major goals of scientific evaluation and de- crease of risk of appearance of hazardous processes on the territory of Dnipropetrovsk, along with creation of the multi-factor predictive Spirit-Energy-Information Space "SEIS" & GIS Model of ecological, genetical and population health risk in connection with dangerous bio-geodynamic processes, were: multi-factor modeling and correla- tion of natural and anthropogenic environmental changes and those of human health; determination of indicators that show the risk of destruction structures appearance on different levels of organization and functioning of the city ecosystem (geophys- ical and geochemical fields, soil, hydrosphere, atmosphere, biosphere); analysis of regularities of natural, anthropogenic, and biological rhythms' interactions. II. Meth- ods. The long spatio-temporal researches (Y. Bondarenko, 1996, 2000) have proved that the ecological, genetic and epidemiological processes are in connection with de- velopment of dangerous bio-geophysical and bio-geodynamic processes. Mathemat- ical processing of space photos, lithogeochemical and geophysical maps with use of JEIS o and ERDAS o computer systems was executed at the first stage of forma- tion of multi-layer geoinformation model "Dnipropetrovsk ARC View GIS o. The multi-factor nonlinear correlation between solar activity and cosmic ray variations, geophysical, geodynamic, geochemical, atmospheric, technological, biological, socio- economical processes and oncologic case rate frequency, general and primary popula- tion sickness cases in Dnipropetrovsk City (1.2 million persons) are described by the multi-factor predictive SEIS & GIS model of geopathogenic zones that determines the human health risk and hazards. Results and Conclusions. We have created the SEIS system and multi-factor predictive SEIS model for the analysis of phase-metric spatio- 1 temporal nonlinear correlation and variations of rhythms of human health, ecological, genetic, epidemiological risks, demographic, socio-economic, bio-geophysical, bio- geodynamic processes in geopathogenic hazard zones. Cosmophotomaps "CPM" of vegetation index, anthropogenic-landscape and landscape-geophysical human health risk of Dnipropetrovsk City present synthesis-based elements of multi-layer GIS, which include multispectral images SPOT o, maps of different geophysical, geochem- ical, anthropogenic and citogenic risk factors, maps of integral oncologic case rate frequency, general and primary population sickness cases for administrative districts. Results of multi-layer spatio-temporal correlation of geophysical field parameters and variations of population sickness rate rhythms have enabled us to state grounds and to develop medico-biological and bio-geodynamic classification of geopathogenic zones. Bio-geodynamic model has served to define contours of anthropogenic-landscape and landscape-geophysical human health risk in Dnipropetrovsk City. Biorhythmic vari- ations give foundation for understanding physiological mechanisms of organism`s adaptation to extreme helio-geophysical and bio-geodynamic environmental condi- tions, which are dictated by changes in Multi-factor Correlation Stress Field "MCSF" with deformation of 5D SEIS. Interaction between organism and environment results in continuous superpositioning of external (exogenic) Nuclear-Molecular-Cristallic "NMC" MCSF rhythms on internal (endogenic) Nuclear-Molecular-Cellular "NMCl" MCSF rhythms. Their resonance wave (energy-information) integration and disinte- gration are responsible for structural and functional state of different physiological systems. Herewith, complex restructurization of defense functions blocks the adapta- tion process and may turn to be the primary reason for phase shifting, process and biorhythms hindering, appearance of different deseases. Interaction of biorhythms with natural and anthropogenic rhythms specify the peculiar features of environ- mental adaptation of living species. Such interaction results in correlation of sea- sonal rhythms in variations of thermo-baro-geodynamic "TBG" parameters of am- bient air with toxic concentration and human health risk in Dnipropetrovsk City. Bio-geodynamic analysis of medical and demographic situations has provided for search of spatio-temporal correlation between rhythms of general and primary pop- ulation sickness cases and oncologic case rate frequency, other medico-demographic rhythms, natural processes (helio-geophysical, thermodynamic, geodynamic) and an- thropogenic processes (industrial and houschold waste disposal, toxic emissions and their concentration in ambient air). The year of 1986, the year of minimum helio- geophysical activity "2G1dG1" and maximum anthropogenic processes associated with changes in sickness and death rates of the population of Earth were synchronized. With account of quantum character of SEIS rhythms, 5 reference levels of desyn- chronized helio-geophysical and bio-geodynamic processes affecting population sick- ness rate have been specified within bio-geodynamic models. The first reference level 2 of SEIS desynchronization includes rhythms with period of 22,5 years: ... 1958,2; 1980,7; 2003,2; .... The second reference level of SEIS desynchronization includes rhythms with period of 11,25 years: ... 1980,7; 1992; 2003,2;.... The third reference level covers 5,625-years periodic rhythms2:... 1980,7; 1986,3; 1992; 1997,6; 2003,2; .... The fourth quantum reference level includes rhythms 3 with period of 2,8125 years: ... 1980,7; 1983,5; 1986,3; 1989,1; 1992; 1994,8; 1997,6; 2000,4; 2003,2; .... Rhythms with 1,40625-years period fall is fifth reference level of SEIS desynchro- nization: ...1980,7; 1982,1; 1983,5; 1984,9; 1986,3; 1987,7; 1989,1; 1990,5; 1992; 1993,3; 1994,8; 1996,2; 1997,6; 1999; 2000,4; 2001,8; 2003,2;.... Analysis of alternat- ing medical and demographic situation in Ukraine (1981-1992)and in Dnipropetrovsk (1988-1995)has allowed to back up theoretical model of various-level rhythm quan- tum, with non-linear regularities due to phase-metric spatio-temporal deformation be- ing specified. Application of new technologies of Risk Analysis, Sinthesis and SEIS Modeling at the choice of a burial place for dangerous radioactive wastes in the zone of Chernobyl nuclear disaster (Shestopalov V., Bondarenko Y...., 1998) has shown their very high efficiency in comparison with GIS Analysis. IV.Recommendations and Outlook. In order to draw a conclusion regarding bio-geodynamic modeling of spatio-temporal structure of areas where common childhood sickness rate exists, it is necessary to mention that the only thing that can favour to exact predicting of where and when important catastrophes and epidemies will take place is correct and complex bio-geodynamic modeling. Imperfection of present GIS is the result of the lack of interactive facilities for multi-factor modeling of nonlinear natural and an- thropogenic processes. Equations' coefficients calculated for some areas are often irrelevant when applied to others. In this connection there arises a number of prob- lems concerning practical application and reliability of GIS-models that are used to carry out efficient ecological monitoring. References Bondarenko Y., 1997, Drawing up Cosmophotomaps and Multi-factor Forecasting of Hazard of Development of Dan- gerous Geodynamic Processes in Dnipropetrovsk,The Technically-Natural Problems of failures and catastrophes in connection with development of dangerous geological processes, Kiev, Ukraine, 1997. Bondarenko Y., 1997, The Methodology of a State the Value of Quality of the Ground and the House Level them Ecology-Genetic-Toxic of the human health risk based on multi-layer cartographical model", Experience of application GIS - Technologies for creating Cadastral Systems, Yalta, Ukraine, 1997, p. 39-40. Shestopalov V., Bondarenko Y., Zayonts I., Rudenko Y. , Bohuslavsky A., 1998, Complexation of Structural-Geodynamical and Hydrogeological Methods of Studying Areas to Reveal Geological Structural Perspectives for Deep Isolation of Radioactive Wastes, Field Testing and Associated Modeling of Potential High-Level Nuclear Waste Geologic Disposal Sites, Berkeley, USA, 1998, p.81-82. 3

Analysis by liquid chromatography and infrared spectrometry of di(2-ethylhexyl)phthalate released by multilayer infusion tubing.

PubMed

Bourdeaux, Daniel; Sautou-Miranda, Valérie; Bagel-Boithias, Sandrine; Boyer, Anne; Chopineau, Jean

2004-04-01

Di(2-ethylhexyl)phthalate (DEHP), a plasticiser present in infusion equipment, is known to be harmful to human health. Various studies have shown that DEHP is released into drug solutions from polyvinyl chloride (PVC) infusion lines. New multi-layer tubing has therefore been marketed to overcome this problem. We assessed the inertness of this tubing when placed in contact with a solution of CELLTOP. Chromatographic assay of DEHP showed no significant difference in DEHP levels in the solution when placed in contact with PVC and with multi-layer tubing. Analysis by infrared spectrometry showed that DEHP was initially present in the polyethylene layer of the multi-layer tubing even before contact with the drug solution. Contact with the solution results in release of DEHP from the container into the contents. The substance responsible for this release is in fact an excipient of CELLTOP, polysorbate. This release of DEHP further proves to depend on parameters such as temperature, time of contact between solution and tubing, and the concentration of polysorbate in the infused drug solution.

Multi-omic profiling to assess the effect of iron starvation in Streptococcus pneumoniae TIGR4

PubMed Central

Jiménez-Munguía, Irene; Calderón-Santiago, Mónica; Rodríguez-Franco, Antonio; Priego-Capote, Feliciano

2018-01-01

We applied multi-omics approaches (transcriptomics, proteomics and metabolomics) to study the effect of iron starvation on the Gram-positive human pathogen Streptococcus pneumoniae to elucidate global changes in the bacterium in a condition similar to what can be found in the host during an infectious episode. We treated the reference strain TIGR4 with the iron chelator deferoxamine mesylate. DNA microarrays revealed changes in the expression of operons involved in multiple biological processes, with a prevalence of genes coding for ion binding proteins. We also studied the changes in protein abundance by 2-DE followed by MALDI-TOF/TOF analysis of total cell extracts and secretome fractions. The main proteomic changes were found in proteins related to the primary and amino sugar metabolism, especially in enzymes with divalent cations as cofactors. Finally, the metabolomic analysis of intracellular metabolites showed altered levels of amino sugars involved in the cell wall peptidoglycan metabolism. This work shows the utility of multi-perspective studies that can provide complementary results for the comprehension of how a given condition can influence global physiological changes in microorganisms.

Follow on Research for Multi-Utility Technology Test Bed Aircraft at NASA Dryden Flight Research Center (FY13 Progress Report)

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi

2013-01-01

Modern aircraft employ a significant fraction of their weight in composite materials to reduce weight and improve performance. Aircraft aeroservoelastic models are typically characterized by significant levels of model parameter uncertainty due to the composite manufacturing process. Small modeling errors in the finite element model will eventually induce errors in the structural flexibility and mass, thus propagating into unpredictable errors in the unsteady aerodynamics and the control law design. One of the primary objectives of Multi Utility Technology Test-bed (MUTT) aircraft is the flight demonstration of active flutter suppression, and therefore in this study, the identification of the primary and secondary modes for the structural model tuning based on the flutter analysis of MUTT aircraft. The ground vibration test-validated structural dynamic finite element model of the MUTT aircraft is created in this study. The structural dynamic finite element model of MUTT aircraft is improved using the in-house Multi-disciplinary Design, Analysis, and Optimization tool. In this study, two different weight configurations of MUTT aircraft have been improved simultaneously in a single model tuning procedure.

Assessing the fitness-for-purpose of satellite multi-mission ocean color climate data records: A protocol applied to OC-CCI chlorophyll-a data.

PubMed

Mélin, F; Vantrepotte, V; Chuprin, A; Grant, M; Jackson, T; Sathyendranath, S

2017-12-15

In this work, trend estimates are used as indicators to compare the multi-annual variability of different satellite chlorophyll- a (Chl a ) data and to assess the fitness-for-purpose of multi-mission Chl a products as climate data records (CDR). Under the assumption that single-mission products are free from spurious temporal artifacts and can be used as benchmark time series, multi-mission CDRs should reproduce the main trend patterns observed by single-mission series when computed over their respective periods. This study introduces and applies quantitative metrics to compare trend distributions from different data records. First, contingency matrices compare the trend diagnostics associated with two satellite products when expressed in binary categories such as existence, significance and signs of trends. Contingency matrices can be further summarized by metrics such as Cohen's κ index that rates the overall agreement between the two distributions of diagnostics. A more quantitative measure of the discrepancies between trends is provided by the distributions of differences between trend slopes. Thirdly, maps of the level of significance P of a t -test quantifying the degree to which two trend estimates differ provide a statistical, spatially-resolved, evaluation. The proposed methodology is applied to the multi-mission Ocean Colour-Climate Change Initiative (OC-CCI) Chl a data. The agreement between trend distributions associated with OC-CCI data and single-mission products usually appears as good as when single-mission products are compared. As the period of analysis is extended beyond 2012 to 2015, the level of agreement tends to be degraded, which might be at least partly due to the aging of the MODIS sensor on-board Aqua. On the other hand, the trends displayed by the OC-CCI series over the short period 2012-2015 are very consistent with those observed with VIIRS. These results overall suggest that the OC-CCI Chl a data can be used for multi-annual time series analysis (including trend detection), but with some caution required if recent years are included, particularly in the central tropical Pacific. The study also recalls the challenges associated with creating a multi-mission ocean color data record suitable for climate research.

Stream Splitting in Support of Intrusion Detection

DTIC Science & Technology

2003-06-01

increased. Every computer on the Internet has no need to see the traffic of every other computer on the Internet. Indeed if this was so, nothing would get ...distinguishes the stream splitter from other network analysis tools. B. HIGH LEVEL DESIGN To get the desired level of performance, a multi-threaded...of greater concern than added accuracy of a Bayesian model. This is a case where close is good enough . b. PassiveSensors Though similar to active

Semantic classification of business images

NASA Astrophysics Data System (ADS)

Erol, Berna; Hull, Jonathan J.

2006-01-01

Digital cameras are becoming increasingly common for capturing information in business settings. In this paper, we describe a novel method for classifying images into the following semantic classes: document, whiteboard, business card, slide, and regular images. Our method is based on combining low-level image features, such as text color, layout, and handwriting features with high-level OCR output analysis. Several Support Vector Machine Classifiers are combined for multi-class classification of input images. The system yields 95% accuracy in classification.

Multilevel analysis of the Be Active Eat Well intervention: environmental and behavioural influences on reductions in child obesity risk.

PubMed

Johnson, B A; Kremer, P J; Swinburn, B A; de Silva-Sanigorski, A M

2012-07-01

The Be Active Eat Well (BAEW) community-based child obesity prevention intervention was successful in modestly reducing unhealthy weight gain in primary school children using a multi-strategy and multi-setting approach. To (1) examine the relationship between changes in obesity-related individual, household and school factors and changes in standardised child body mass index (zBMI), and (2) determine if the BAEW intervention moderated these effects. The longitudinal relationships between changes in individual, household and school variables and changes in zBMI were explored using multilevel modelling, with measurement time (baseline and follow-up) at level 1, individual (behaviours, n = 1812) at level 2 and households (n = 1318) and schools (n = 18) as higher levels (environments). The effect of the intervention was tested while controlling for child age, gender and maternal education level. This study confirmed that the BAEW intervention lowered child zBMI compared with the comparison group (-0.085 units, P = 0.03). The variation between household environments was found to be a large contributor to the percentage of unexplained change in child zBMI (59%), compared with contributions from the individual (23%) and school levels (1%). Across both groups, screen time (P = 0.03), sweet drink consumption (P = 0.03) and lack of household rules for television (TV) viewing (P = 0.05) were associated with increased zBMI, whereas there was a non-significant association with the frequency the TV was on during evening meals (P = 0.07). The moderating effect of the intervention was only evident for the relationship between the frequency of TV on during meals and zBMI, however, this effect was modest (P = 0.04). The development of childhood obesity involves multi-factorial and multi-level influences, some of which are amenable to change. Obesity prevention strategies should not only target individual behaviours but also the household environment and family practices. Although zBMI changes were modest, these findings are encouraging as small reductions can have population level impacts on childhood obesity levels.

Hospital and operator variations in drug-eluting stent use: a multi-level analysis of 5967 consecutive patients in Scotland.

PubMed

Austin, David; Oldroyd, Keith G; McConnachie, Alex; Slack, Rachel; Eteiba, Hany; Flapan, Andrew D; Jennings, Kevin P; Northcote, Robin J; Pell, Alistair C H; Starkey, Ian R; Pell, Jill P

2008-06-01

To determine whether drug-eluting stent (DES) use varies among Scottish hospitals, and the extent to which any variations are explained by differences between operators, patients and lesions. Multi-level analysis of consecutive patients treated with percutaneous coronary intervention (PCI) between April 2005 and March 2006 in Scotland, using the Scottish Coronary Revascularization Registry. A total of 38 operators performed 5967 PCI procedures on 8489 lesions. Crude level of DES use was 47.6%, and the results varied among hospitals (range 30.6-61.8%, chi(2) = 341.6, P < 0.0001). There was significant between-operator variation in the null model. This was attenuated by the addition of hospital as a fixed effect. Nonetheless, the final model demonstrated significant between-operator variability [sigma(2) = 0.486 (0.249-0.971)] and between-hospital variation, after case-mix adjustment. Within Scotland, marked variation existed among hospitals in the use of DES. Operator was the most important factor at patient level, and hospital of treatment, rather than case-mix, was the most important modifier of between-operator variation. Patient selection for DES is complex and may contribute to much of the variations demonstrated. Consensus criteria would provide more detail than is included in current guidance, may aid decision-making for individual patients, reduce opportunity costs and ensure equity of access.

Metabolic Network Modeling of Microbial Communities

PubMed Central

Biggs, Matthew B.; Medlock, Gregory L.; Kolling, Glynis L.

2015-01-01

Genome-scale metabolic network reconstructions and constraint-based analysis are powerful methods that have the potential to make functional predictions about microbial communities. Current use of genome-scale metabolic networks to characterize the metabolic functions of microbial communities includes species compartmentalization, separating species-level and community-level objectives, dynamic analysis, the “enzyme-soup” approach, multi-scale modeling, and others. There are many challenges inherent to the field, including a need for tools that accurately assign high-level omics signals to individual community members, new automated reconstruction methods that rival manual curation, and novel algorithms for integrating omics data and engineering communities. As technologies and modeling frameworks improve, we expect that there will be proportional advances in the fields of ecology, health science, and microbial community engineering. PMID:26109480

Decadal sea level variability in the East China Sea linked to the North Pacific Gyre Oscillation

NASA Astrophysics Data System (ADS)

Moon, Jae-Hong; Song, Y. Tony

2017-07-01

In view of coastal community's need for adapting to sea level rise (SLR), understanding and predicting regional variability on decadal to longer time scales still remain a challenging issue in SLR research. Here, we have examined the low-frequency sea level signals in the East China Sea (ECS) from the 50-year hindcast of a non-Boussinesq ocean model in comparison with data sets from altimeters, tide-gauges, and steric sea level produced by in-situ profiles. It is shown that the mean sea levels in the ECS represent significant decadal fluctuations over the past 50 years, with a multi-decadal trend shift since the mid-1980s compared to the preceding 30 years. The decadal fluctuations in sea level are more closely linked to the North Pacific Gyre Oscillation (NPGO) rather than the Pacific Decadal Oscillation, which reflects the multi-decadal trend shift. A composite analysis indicates that wind patterns associated with the NPGO is shown to control the decadal variability of the western subtropical North Pacific. A positive NPGO corresponds to cyclonic wind stress curl anomaly in the western subtropical regions that results in a higher sea level in the ECS, particularly along the continental shelf, and lower sea levels off the ECS. The reverse occurs in years of negative NPGO.

Robust design of multiple trailing edge flaps for helicopter vibration reduction: A multi-objective bat algorithm approach

NASA Astrophysics Data System (ADS)

Mallick, Rajnish; Ganguli, Ranjan; Seetharama Bhat, M.

2015-09-01

The objective of this study is to determine an optimal trailing edge flap configuration and flap location to achieve minimum hub vibration levels and flap actuation power simultaneously. An aeroelastic analysis of a soft in-plane four-bladed rotor is performed in conjunction with optimal control. A second-order polynomial response surface based on an orthogonal array (OA) with 3-level design describes both the objectives adequately. Two new orthogonal arrays called MGB2P-OA and MGB4P-OA are proposed to generate nonlinear response surfaces with all interaction terms for two and four parameters, respectively. A multi-objective bat algorithm (MOBA) approach is used to obtain the optimal design point for the mutually conflicting objectives. MOBA is a recently developed nature-inspired metaheuristic optimization algorithm that is based on the echolocation behaviour of bats. It is found that MOBA inspired Pareto optimal trailing edge flap design reduces vibration levels by 73% and flap actuation power by 27% in comparison with the baseline design.

Data and techniques for studying the urban heat island effect in Johannesburg

NASA Astrophysics Data System (ADS)

Hardy, C. H.; Nel, A. L.

2015-04-01

The city of Johannesburg contains over 10 million trees and is often referred to as an urban forest. The intra-urban spatial variability of the levels of vegetation across Johannesburg's residential regions has an influence on the urban heat island effect within the city. Residential areas with high levels of vegetation benefit from cooling due to evapo-transpirative processes and thus exhibit weaker heat island effects; while their impoverished counterparts are not so fortunate. The urban heat island effect describes a phenomenon where some urban areas exhibit temperatures that are warmer than that of surrounding areas. The factors influencing the urban heat island effect include the high density of people and buildings and low levels of vegetative cover within populated urban areas. This paper describes the remote sensing data sets and the processing techniques employed to study the heat island effect within Johannesburg. In particular we consider the use of multi-sensorial multi-temporal remote sensing data towards a predictive model, based on the analysis of influencing factors.

Investigating the chlorophyll-a variability in the Gulf of Taranto (North-western Ionian Sea) by a multi-temporal analysis of MODIS-Aqua Level 3/Level 2 data

NASA Astrophysics Data System (ADS)

Ciancia, Emanuele; Coviello, Irina; Di Polito, Carmine; Lacava, Teodosio; Pergola, Nicola; Satriano, Valeria; Tramutoli, Valerio

2018-03-01

The analysis of chlorophyll-a (chl-a) variability on a long-term basis could allow detecting possible issues in the whole marine ecosystem functioning. The Gulf of Taranto (Southern Italy), in the North-western Ionian Sea (Mediterranean Sea), has been affected by several environmental threats in the last decade, thus deserving the implementation of an adequate monitoring system able to provide accurate indications about the variability of the most relevant bio-optical parameters. In this context, the main objectives of this study are to investigate the long-term chl-a variability in the Gulf of Taranto and identify the occurrence of any past spatiotemporal anomalies by implementing the multi-temporal Robust Satellite Technique (RST) on a 12-year (2003-2015) period of MODIS/AQUA Level 3/Level 2 chlorophyll-a data. The achieved results show well-clustered near-surface positive chl-a anomalies during the January-February 2011 period. This detected offshore phytoplankton bloom may be related to sub-basin processes, such as the inflow of the Western Adriatic Coastal Current (WACC), probably fostered by the cyclonic reversal of the Bimodal Oscillating System (BiOS) mechanism. Therefore, the RST approach proved successful in detecting chl-a anomalous variations with a high level of confidence regardless of the absolute value measured, thus suggesting its exportability in other areas with different site-setting conditions.

Selecting essential information for biosurveillance--a multi-criteria decision analysis.

PubMed

Generous, Nicholas; Margevicius, Kristen J; Taylor-McCabe, Kirsten J; Brown, Mac; Daniel, W Brent; Castro, Lauren; Hengartner, Andrea; Deshpande, Alina

2014-01-01

The National Strategy for Biosurveillance defines biosurveillance as "the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better decision-making at all levels." However, the strategy does not specify how "essential information" is to be identified and integrated into the current biosurveillance enterprise, or what the metrics qualify information as being "essential". The question of data stream identification and selection requires a structured methodology that can systematically evaluate the tradeoffs between the many criteria that need to be taken in account. Multi-Attribute Utility Theory, a type of multi-criteria decision analysis, can provide a well-defined, structured approach that can offer solutions to this problem. While the use of Multi-Attribute Utility Theoryas a practical method to apply formal scientific decision theoretical approaches to complex, multi-criteria problems has been demonstrated in a variety of fields, this method has never been applied to decision support in biosurveillance.We have developed a formalized decision support analytic framework that can facilitate identification of "essential information" for use in biosurveillance systems or processes and we offer this framework to the global BSV community as a tool for optimizing the BSV enterprise. To demonstrate utility, we applied the framework to the problem of evaluating data streams for use in an integrated global infectious disease surveillance system.

Atlantic multi-decadal oscillation influence on weather regimes over Europe and the Mediterranean in spring and summer

NASA Astrophysics Data System (ADS)

Zampieri, M.; Toreti, A.; Schindler, A.; Scoccimarro, E.; Gualdi, S.

2017-04-01

We analyze the influence of the Atlantic sea surface temperature multi-decadal variability on the day-by-day sequence of large-scale atmospheric circulation patterns (i.e. the ;weather regimes;) over the Euro-Atlantic region. In particular, we examine of occurrence of weather regimes from 1871 to present. This analysis is conducted by applying a clustering technique on the daily mean sea level pressure field provided by the 20th Century Reanalysis project, which was successfully applied in other studies focused on the Atlantic Multi-decadal Oscillation (AMO). In spring and summer, results show significant changes in the frequencies of certain weather regimes associated with the phase shifts of the AMO. These changes are consistent with the seasonal surface pressure, precipitation, and temperature anomalies associated with the AMO shifts in Europe.

In Good Company? A Multi-Study, Multi-Level Investigation of the Effects of Coworker Relationships on Employee Well-Being

ERIC Educational Resources Information Center

Simon, Lauren S.; Judge, Timothy A.; Halvorsen-Ganepola, Marie D. K.

2010-01-01

Two multi-level studies were conducted to examine the effects of attitudes towards coworkers on daily well-being. Study 1 linked daily levels of coworker satisfaction to job satisfaction and life satisfaction and examined the extent to which job satisfaction mediated the relationship between coworker satisfaction and life satisfaction among 33…

MOD06 Optical and Microphysical Retrievals

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Arnold, G. T.; Dinsick, J.; Gatebe, C. K.; Gray, M. A.; Hubanks, P. A.; Moody, E. G.; Wind, B.; Wind, G.

2003-01-01

Major efforts over the past six months included: (1) submission of MOD06 Optical and Microphysical Retrieval recompetition proposal, (2) delivery of a MODIS Atmosphere Level-3 update, (3) delivery of the MODIS Atmosphere s new combined Level-2 product, (4) development of an above-cloud precipitable water research algorithm and a multi-layer cloud detection algorithm, (5) continued development of a Fortran 90 version of the retrieval code for use with MAS as well as operational MODIS processing, (6) preliminary analysis of CRYSTAL-FACE field experiment in July 2002, (7) continued analysis of data obtained during the SAFARI 2000 dry season campaign in southern Africa, and the Arctic FIRE-ACE experiment.

(n,{gamma}) Experiments on tin isotopes

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

Baramsai, B.; Mitchell, G. E.; Walker, C. L.

2013-04-19

Neutron capture experiments on highly enriched {sup 117,119}Sn isotopes were performed with the DANCE detector array located at the Los Alamos Neutron Science Center. The DANCE detector provides detailed information about the multi-step {gamma}-ray cascade following neutron capture. Analysis of the experimental data provides important information to improve understanding of the neutron capture reaction, including a test of the statistical model, the assignment of spins and parities of neutron resonances, and information concerning the Photon Strength Function (PSF) and Level Density (LD) below the neutron separation energy. Preliminary results for the (n,{gamma}) reaction on {sup 117,119}Sn are presented. Resonance spinsmore » of the odd-A tin isotopes were almost completely unknown. Resonance spins and parities have been assigned via analysis of the multi-step {gamma}-ray spectra and directional correlations.« less

A Real Time System for Multi-Sensor Image Analysis through Pyramidal Segmentation

DTIC Science & Technology

1992-01-30

A Real Time Syte for M~ulti- sensor Image Analysis S. E I0 through Pyramidal Segmentation/ / c •) L. Rudin, S. Osher, G. Koepfler, J.9. Morel 7. ytu...experiments with reconnaissance photography, multi- sensor satellite imagery, medical CT and MRI multi-band data have shown a great practi- cal potential...C ,SF _/ -- / WSM iS-I-0-d41-40450 $tltwt, kw" I (nor.- . Z-97- A real-time system for multi- sensor image analysis through pyramidal segmentation

Interevent time distributions of human multi-level activity in a virtual world

NASA Astrophysics Data System (ADS)

Mryglod, O.; Fuchs, B.; Szell, M.; Holovatch, Yu.; Thurner, S.

2015-02-01

Studying human behavior in virtual environments provides extraordinary opportunities for a quantitative analysis of social phenomena with levels of accuracy that approach those of the natural sciences. In this paper we use records of player activities in the massive multiplayer online game Pardus over 1238 consecutive days, and analyze dynamical features of sequences of actions of players. We build on previous work where temporal structures of human actions of the same type were quantified, and provide an empirical understanding of human actions of different types. This study of multi-level human activity can be seen as a dynamic counterpart of static multiplex network analysis. We show that the interevent time distributions of actions in the Pardus universe follow highly non-trivial distribution functions, from which we extract action-type specific characteristic 'decay constants'. We discuss characteristic features of interevent time distributions, including periodic patterns on different time scales, bursty dynamics, and various functional forms on different time scales. We comment on gender differences of players in emotional actions, and find that while males and females act similarly when performing some positive actions, females are slightly faster for negative actions. We also observe effects on the age of players: more experienced players are generally faster in making decisions about engaging in and terminating enmity and friendship, respectively.

Development and validation of rapid multiresidue and multi-class analysis for antibiotics and anthelmintics in feed by ultra-high-performance liquid chromatography coupled to tandem mass spectrometry.

PubMed

Robert, Christelle; Brasseur, Pierre-Yves; Dubois, Michel; Delahaut, Philippe; Gillard, Nathalie

2016-08-01

A new multi-residue method for the analysis of veterinary drugs, namely amoxicillin, chlortetracycline, colistins A and B, doxycycline, fenbendazole, flubendazole, ivermectin, lincomycin, oxytetracycline, sulfadiazine, tiamulin, tilmicosin and trimethoprim, was developed and validated for feed. After acidic extraction, the samples were centrifuged, purified by SPE and analysed by ultra-high-performance liquid chromatography coupled to tandem mass spectrometry. Quantitative validation was done in accordance with the guidelines laid down in European Commission Decision 2002/657/CE. Matrix-matched calibration with internal standards was used to reduce matrix effects. The target level was set at the authorised carryover level (1%) and validation levels were set at 0.5%, 1% and 1.5%. Method performances were evaluated by the following parameters: linearity (0.986 < R(2) < 0.999), precision (repeatability < 12.4% and reproducibility < 14.0%), accuracy (89% < recovery < 107%), sensitivity, decision limit (CCα), detection capability (CCβ), selectivity and expanded measurement uncertainty (k = 2).This method has been used successfully for three years for routine monitoring of antibiotic residues in feeds during which period 20% of samples were found to exceed the 1% authorised carryover limit and were deemed non-compliant.

Customized binary and multi-level HfO2-x-based memristors tuned by oxidation conditions.

PubMed

He, Weifan; Sun, Huajun; Zhou, Yaxiong; Lu, Ke; Xue, Kanhao; Miao, Xiangshui

2017-08-30

The memristor is a promising candidate for the next generation non-volatile memory, especially based on HfO 2-x , given its compatibility with advanced CMOS technologies. Although various resistive transitions were reported independently, customized binary and multi-level memristors in unified HfO 2-x material have not been studied. Here we report Pt/HfO 2-x /Ti memristors with double memristive modes, forming-free and low operation voltage, which were tuned by oxidation conditions of HfO 2-x films. As O/Hf ratios of HfO 2-x films increase, the forming voltages, SET voltages, and R off /R on windows increase regularly while their resistive transitions undergo from gradually to sharply in I/V sweep. Two memristors with typical resistive transitions were studied to customize binary and multi-level memristive modes, respectively. For binary mode, high-speed switching with 10 3 pulses (10 ns) and retention test at 85 °C (>10 4 s) were achieved. For multi-level mode, the 12-levels stable resistance states were confirmed by ongoing multi-window switching (ranging from 10 ns to 1 μs and completing 10 cycles of each pulse). Our customized binary and multi-level HfO 2-x -based memristors show high-speed switching, multi-level storage and excellent stability, which can be separately applied to logic computing and neuromorphic computing, further suitable for in-memory computing chip when deposition atmosphere may be fine-tuned.

Changing drug users' risk environments: peer health advocates as multi-level community change agents.

PubMed

Weeks, Margaret R; Convey, Mark; Dickson-Gomez, Julia; Li, Jianghong; Radda, Kim; Martinez, Maria; Robles, Eduardo

2009-06-01

Peer delivered, social oriented HIV prevention intervention designs are increasingly popular for addressing broader contexts of health risk beyond a focus on individual factors. Such interventions have the potential to affect multiple social levels of risk and change, including at the individual, network, and community levels, and reflect social ecological principles of interaction across social levels over time. The iterative and feedback dynamic generated by this multi-level effect increases the likelihood for sustained health improvement initiated by those trained to deliver the peer intervention. The Risk Avoidance Partnership (RAP), conducted with heroin and cocaine/crack users in Hartford, Connecticut, exemplified this intervention design and illustrated the multi-level effect on drug users' risk and harm reduction at the individual level, the social network level, and the larger community level. Implications of the RAP program for designing effective prevention programs and for analyzing long-term change to reduce HIV transmission among high-risk groups are discussed from this ecological and multi-level intervention perspective.

Multigrid Techniques for Highly Indefinite Equations

NASA Technical Reports Server (NTRS)

Shapira, Yair

1996-01-01

A multigrid method for the solution of finite difference approximations of elliptic PDE's is introduced. A parallelizable version of it, suitable for two and multi level analysis, is also defined, and serves as a theoretical tool for deriving a suitable implementation for the main version. For indefinite Helmholtz equations, this analysis provides a suitable mesh size for the coarsest grid used. Numerical experiments show that the method is applicable to diffusion equations with discontinuous coefficients and highly indefinite Helmholtz equations.

Community and household socioeconomic factors associated with pesticide-using, small farm household members' health: a multi-level, longitudinal analysis

PubMed Central

2011-01-01

Background Longitudinal studies using multi-level models to examine health inequalities in lower and middle income countries (LMICs) are rare. We explored socio-economic gradients in health among small farm members participating in a pesticide-related health and agriculture program in highland Ecuador. Methods We profiled 24 communities through key informant interviews, secondary data (percent of population with unsatisfied basic needs), and intervention implementation indicators. Pre (2005) and post (2007) surveys of the primary household and crop managers included common questions (education, age, and the health outcome - digit span scaled 0-10)) and pesticide-related practice questions specific to each. Household assets and pesticide use variables were shared across managers. We constructed multi-level models predicting 2007 digit span for each manager type, with staged introduction of predictor variables. Results 376 household managers (79% of 2005 participants) and 380 crop managers (76% of 2005 participants) had complete data for analysis. The most important predictor of 2007 digit span was 2005 digit span: β (Standard Error) of 0.31(0.05) per unit for household and 0.17(0.04) for crop managers. Household asset score was next most important: 0.14(0.06) per unit for household and 0.14(0.05) for crop managers. Community percent with unsatisfied basic needs was associated with reductions in 2007 digit span: -0.04(0.01) per percent for household and -0.03(0.01) for crop managers. Conclusions The important roles of life endowments and/or persistent neurotoxicity were exemplified by limited change in the health outcome. Gradients by household assets and community deprivation were indicative of ongoing, structural inequities within this LMIC. PMID:22094171

Oscillations in two-dimensional photon-echo signals of excitonic and vibronic systems: Stick-spectrum analysis and its computational verification

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

Egorova, Dassia

2014-01-21

Stick-spectrum expressions for electronic two-dimensional (2D) photon-echo (PE) signal of a generic multi-level system are presented and employed to interrelate oscillations in individual peaks of 2D PE signal and the underlying properties (eigenstates and coherent dynamics) of excitonic or vibronic systems. When focusing on the identification of the origin of oscillations in the rephasing part of 2D PE it is found, in particular, that multiple frequencies in the evolution of the individual peaks do not necessarily directly reflect the underlying system dynamics. They may originate from the excited-state absorption contribution to the signal, or arise due to multi-level vibrational structuremore » of the electronic ground state, and represent a superposition of system frequencies, while the latter may evolve independently. The analytical stick-spectrum predictions are verified and illustrated by numerical calculations of 2D PE signals of an excitonic trimer and of a displaced harmonic oscillator with unequal vibrational frequencies in the two electronic states. The excitonic trimer is the smallest excitonic oligomer where excited-state absorption may represent a superposition of excited-state coherences and significantly influence the phase of the observed oscillations. The displaced oscillator is used to distinguish between the frequencies of the ground-state and of the excited-state manifolds, and to demonstrate how the location of a cross peak in 2D pattern of the PE signal “predetermines” its oscillatory behavior. Although the considered models are kept as simple as possible for clarity, the stick-spectrum analysis provides a solid general basis for interpretation of oscillatory signatures in electronic 2D PE signals of much more complex systems with multi-level character of the electronic states.« less

Bacterial Adherence and Dwelling Probability: Two Drivers of Early Alveolar Infection by Streptococcus pneumoniae Identified in Multi-Level Mathematical Modeling.

PubMed

Santos, Guido; Lai, Xin; Eberhardt, Martin; Vera, Julio

2018-01-01

Pneumococcal infection is the most frequent cause of pneumonia, and one of the most prevalent diseases worldwide. The population groups at high risk of death from bacterial pneumonia are infants, elderly and immunosuppressed people. These groups are more vulnerable because they have immature or impaired immune systems, the efficacy of their response to vaccines is lower, and antibiotic treatment often does not take place until the inflammatory response triggered is already overwhelming. The immune response to bacterial lung infections involves dynamic interactions between several types of cells whose activation is driven by intracellular molecular networks. A feasible approach to the integration of knowledge and data linking tissue, cellular and intracellular events and the construction of hypotheses in this area is the use of mathematical modeling. For this paper, we used a multi-level computational model to analyse the role of cellular and molecular interactions during the first 10 h after alveolar invasion of Streptococcus pneumoniae bacteria. By "multi-level" we mean that we simulated the interplay between different temporal and spatial scales in a single computational model. In this instance, we included the intracellular scale of processes driving lung epithelial cell activation together with the scale of cell-to-cell interactions at the alveolar tissue. In our analysis, we combined systematic model simulations with logistic regression analysis and decision trees to find genotypic-phenotypic signatures that explain differences in bacteria strain infectivity. According to our simulations, pneumococci benefit from a high dwelling probability and a high proliferation rate during the first stages of infection. In addition to this, the model predicts that during the very early phases of infection the bacterial capsule could be an impediment to the establishment of the alveolar infection because it impairs bacterial colonization.

Adaptive multi-GPU Exchange Monte Carlo for the 3D Random Field Ising Model

NASA Astrophysics Data System (ADS)

Navarro, Cristóbal A.; Huang, Wei; Deng, Youjin

2016-08-01

This work presents an adaptive multi-GPU Exchange Monte Carlo approach for the simulation of the 3D Random Field Ising Model (RFIM). The design is based on a two-level parallelization. The first level, spin-level parallelism, maps the parallel computation as optimal 3D thread-blocks that simulate blocks of spins in shared memory with minimal halo surface, assuming a constant block volume. The second level, replica-level parallelism, uses multi-GPU computation to handle the simulation of an ensemble of replicas. CUDA's concurrent kernel execution feature is used in order to fill the occupancy of each GPU with many replicas, providing a performance boost that is more notorious at the smallest values of L. In addition to the two-level parallel design, the work proposes an adaptive multi-GPU approach that dynamically builds a proper temperature set free of exchange bottlenecks. The strategy is based on mid-point insertions at the temperature gaps where the exchange rate is most compromised. The extra work generated by the insertions is balanced across the GPUs independently of where the mid-point insertions were performed. Performance results show that spin-level performance is approximately two orders of magnitude faster than a single-core CPU version and one order of magnitude faster than a parallel multi-core CPU version running on 16-cores. Multi-GPU performance is highly convenient under a weak scaling setting, reaching up to 99 % efficiency as long as the number of GPUs and L increase together. The combination of the adaptive approach with the parallel multi-GPU design has extended our possibilities of simulation to sizes of L = 32 , 64 for a workstation with two GPUs. Sizes beyond L = 64 can eventually be studied using larger multi-GPU systems.

Modeling of BN Lifetime Prediction of a System Based on Integrated Multi-Level Information

PubMed Central

Wang, Xiaohong; Wang, Lizhi

2017-01-01

Predicting system lifetime is important to ensure safe and reliable operation of products, which requires integrated modeling based on multi-level, multi-sensor information. However, lifetime characteristics of equipment in a system are different and failure mechanisms are inter-coupled, which leads to complex logical correlations and the lack of a uniform lifetime measure. Based on a Bayesian network (BN), a lifetime prediction method for systems that combine multi-level sensor information is proposed. The method considers the correlation between accidental failures and degradation failure mechanisms, and achieves system modeling and lifetime prediction under complex logic correlations. This method is applied in the lifetime prediction of a multi-level solar-powered unmanned system, and the predicted results can provide guidance for the improvement of system reliability and for the maintenance and protection of the system. PMID:28926930

Modeling of BN Lifetime Prediction of a System Based on Integrated Multi-Level Information.

PubMed

Wang, Jingbin; Wang, Xiaohong; Wang, Lizhi

2017-09-15

Predicting system lifetime is important to ensure safe and reliable operation of products, which requires integrated modeling based on multi-level, multi-sensor information. However, lifetime characteristics of equipment in a system are different and failure mechanisms are inter-coupled, which leads to complex logical correlations and the lack of a uniform lifetime measure. Based on a Bayesian network (BN), a lifetime prediction method for systems that combine multi-level sensor information is proposed. The method considers the correlation between accidental failures and degradation failure mechanisms, and achieves system modeling and lifetime prediction under complex logic correlations. This method is applied in the lifetime prediction of a multi-level solar-powered unmanned system, and the predicted results can provide guidance for the improvement of system reliability and for the maintenance and protection of the system.

Multi-segmental movements as a function of experience in karate.

PubMed

Zago, Matteo; Codari, Marina; Iaia, F Marcello; Sforza, Chiarella

2017-08-01

Karate is a martial art that partly depends on subjective scoring of complex movements. Principal component analysis (PCA)-based methods can identify the fundamental synergies (principal movements) of motor system, providing a quantitative global analysis of technique. In this study, we aimed at describing the fundamental multi-joint synergies of a karate performance, under the hypothesis that the latter are skilldependent; estimate karateka's experience level, expressed as years of practice. A motion capture system recorded traditional karate techniques of 10 professional and amateur karateka. At any time point, the 3D-coordinates of body markers produced posture vectors that were normalised, concatenated from all karateka and submitted to a first PCA. Five principal movements described both gross movement synergies and individual differences. A second PCA followed by linear regression estimated the years of practice using principal movements (eigenpostures and weighting curves) and centre of mass kinematics (error: 3.71 years; R2 = 0.91, P ≪ 0.001). Principal movements and eigenpostures varied among different karateka and as functions of experience. This approach provides a framework to develop visual tools for the analysis of motor synergies in karate, allowing to detect the multi-joint motor patterns that should be restored after an injury, or to be specifically trained to increase performance.

Robust Stability Analysis of the Space Launch System Control Design: A Singular Value Approach

NASA Technical Reports Server (NTRS)

Pei, Jing; Newsome, Jerry R.

2015-01-01

Classical stability analysis consists of breaking the feedback loops one at a time and determining separately how much gain or phase variations would destabilize the stable nominal feedback system. For typical launch vehicle control design, classical control techniques are generally employed. In addition to stability margins, frequency domain Monte Carlo methods are used to evaluate the robustness of the design. However, such techniques were developed for Single-Input-Single-Output (SISO) systems and do not take into consideration the off-diagonal terms in the transfer function matrix of Multi-Input-Multi-Output (MIMO) systems. Robust stability analysis techniques such as H(sub infinity) and mu are applicable to MIMO systems but have not been adopted as standard practices within the launch vehicle controls community. This paper took advantage of a simple singular-value-based MIMO stability margin evaluation method based on work done by Mukhopadhyay and Newsom and applied it to the SLS high-fidelity dynamics model. The method computes a simultaneous multi-loop gain and phase margin that could be related back to classical margins. The results presented in this paper suggest that for the SLS system, traditional SISO stability margins are similar to the MIMO margins. This additional level of verification provides confidence in the robustness of the control design.

A computational intelligent approach to multi-factor analysis of violent crime information system

NASA Astrophysics Data System (ADS)

Liu, Hongbo; Yang, Chao; Zhang, Meng; McLoone, Seán; Sun, Yeqing

2017-02-01

Various scientific studies have explored the causes of violent behaviour from different perspectives, with psychological tests, in particular, applied to the analysis of crime factors. The relationship between bi-factors has also been extensively studied including the link between age and crime. In reality, many factors interact to contribute to criminal behaviour and as such there is a need to have a greater level of insight into its complex nature. In this article we analyse violent crime information systems containing data on psychological, environmental and genetic factors. Our approach combines elements of rough set theory with fuzzy logic and particle swarm optimisation to yield an algorithm and methodology that can effectively extract multi-knowledge from information systems. The experimental results show that our approach outperforms alternative genetic algorithm and dynamic reduct-based techniques for reduct identification and has the added advantage of identifying multiple reducts and hence multi-knowledge (rules). Identified rules are consistent with classical statistical analysis of violent crime data and also reveal new insights into the interaction between several factors. As such, the results are helpful in improving our understanding of the factors contributing to violent crime and in highlighting the existence of hidden and intangible relationships between crime factors.

Analysis of sulfonamides, tilmicosin and avermectins residues in typical animal matrices with multi-plug filtration cleanup by liquid chromatography-tandem mass spectrometry detection.

PubMed

Qin, Yuhong; Jatamunua, Freedom; Zhang, Jingru; Li, Yanjie; Han, Yongtao; Zou, Nan; Shan, Jihao; Jiang, Yanbin; Pan, Canping

2017-05-15

The frequent use of various veterinary drugs could lead to residue bioaccumulation in animal tissues, which could cause dietary risks to human health. In order to quickly analyze the residues, a liquid chromatography tandem mass spectrometry (LC-MS/MS) method was developed for detecting Sulfonamides, Tilmicosin and Avermectins (AVMs) residues in animal samples. For sample preparation, modified QuEChERS (quick, easy, cheap, effective, rugged and safe) and ultrasound-assisted extraction (UAE) methods were used. For sample cleanup, n-Hexane delipidation and multi-plug filtration cleanup (m-PFC) method based on primary-secondary amine (PSA) and octadecyl-silica (C18) were used, followed by LC-MS/MS analysis. It was validated on 7 animal matrices (bovine, caprine, swine meat and their kidneys, milk) at two fortified concentration levels of 5 and 100μg/kg. The recoveries ranged from 82 to 107% for all analytes with relative standard deviations (RSDs) less than 15%. Matrix-matched calibrations were performed with coefficients of determination above 0.998 for all analytes within concentration levels of 5-500μg/kg. The developed method was successfully used to analysis veterinary drugs of real animal samples from local markets. Copyright © 2017 Elsevier B.V. All rights reserved.

NCCN-IPI score-independent prognostic potential of pretreatment uric acid levels for clinical outcome of diffuse large B-cell lymphoma patients

PubMed Central

Prochazka, Katharina T; Melchardt, Thomas; Posch, Florian; Schlick, Konstantin; Deutsch, Alexander; Beham-Schmid, Christine; Weiss, Lukas; Gary, Thomas; Neureiter, Daniel; Klieser, Eckhard; Greil, Richard; Neumeister, Peter; Egle, Alexander; Pichler, Martin

2016-01-01

Background: Blood-based parameters are gaining increasing interest as potential prognostic biomarkers in patients with diffuse large B-cell lymphoma (DLBCL). The aim of this study was to comprehensively evaluate the prognostic significance of pretreatment plasma uric acid levels in patients with newly diagnosed DLBCL. Methods: The clinical course of 539 DLBCL patients, diagnosed and treated between 2004 and 2013 at two Austrian high-volume centres with rituximab-based immunochemotherapy was evaluated retrospectively. The prognostic influence of uric acid on overall survival (OS) and progression-free survival (PFS) were studied including multi-state modelling, and analysis of conditional survival. Results: Five-year OS and PFS were 50.4% (95% CI: 39.2–60.6) and 44.0% (33.4–54.0) in patients with uric acid levels above the 75th percentile of the uric acid distribution (Q3, cut-off: 6.8 mg dl−1), and 66.2% (60.4–71.5) and 59.6% (53.7–65.0%) in patients with lower levels (log-rank P=0.002 and P=0.0045, respectively). In univariable time-to-event analysis, elevated uric acid levels were associated with a worse PFS (hazard ratio (HR) per 1 log increase in uric acid 1.47, 95% CI: 1.10–1.97, P=0.009) and a worse OS (HR=1.60, 95% CI: 1.16–2.19, P=0.004). These associations prevailed upon multivariable adjustment for the NCCN-IPI score. Uric acid levels significantly improved the predictive performance of the R-IPI and NCCN-IPI scores, and in multi-state analysis, it emerged as a highly significant predictor of an increased risk of death without developing recurrence (transition-HR=4.47, 95% CI: 2.17–9.23, P<0.0001). Conclusions: We demonstrate that elevated uric acid levels predict poor long-term outcomes in DLBCL patients beyond the NCCN-IPI risk index. PMID:27764838

Multi-level slug tests in highly permeable formations: 2. Hydraulic conductivity identification, method verification, and field applications

USGS Publications Warehouse

Zlotnik, V.A.; McGuire, V.L.

1998-01-01

Using the developed theory and modified Springer-Gelhar (SG) model, an identification method is proposed for estimating hydraulic conductivity from multi-level slug tests. The computerized algorithm calculates hydraulic conductivity from both monotonic and oscillatory well responses obtained using a double-packer system. Field verification of the method was performed at a specially designed fully penetrating well of 0.1-m diameter with a 10-m screen in a sand and gravel alluvial aquifer (MSEA site, Shelton, Nebraska). During well installation, disturbed core samples were collected every 0.6 m using a split-spoon sampler. Vertical profiles of hydraulic conductivity were produced on the basis of grain-size analysis of the disturbed core samples. These results closely correlate with the vertical profile of horizontal hydraulic conductivity obtained by interpreting multi-level slug test responses using the modified SG model. The identification method was applied to interpret the response from 474 slug tests in 156 locations at the MSEA site. More than 60% of responses were oscillatory. The method produced a good match to experimental data for both oscillatory and monotonic responses using an automated curve matching procedure. The proposed method allowed us to drastically increase the efficiency of each well used for aquifer characterization and to process massive arrays of field data. Recommendations generalizing this experience to massive application of the proposed method are developed.Using the developed theory and modified Springer-Gelhar (SG) model, an identification method is proposed for estimating hydraulic conductivity from multi-level slug tests. The computerized algorithm calculates hydraulic conductivity from both monotonic and oscillatory well responses obtained using a double-packer system. Field verification of the method was performed at a specially designed fully penetrating well of 0.1-m diameter with a 10-m screen in a sand and gravel alluvial aquifer (MSEA site, Shelton, Nebraska). During well installation, disturbed core samples were collected every 0.6 m using a split-spoon sampler. Vertical profiles of hydraulic conductivity were produced on the basis of grain-size analysis of the disturbed core samples. These results closely correlate with the vertical profile of horizontal hydraulic conductivity obtained by interpreting multi-level slug test responses using the modified SG model. The identification method was applied to interpret the response from 474 slug tests in 156 locations at the MSEA site. More than 60% of responses were oscillatory. The method produced a good match to experimental data for both oscillatory and monotonic responses using an automated curve matching procedure. The proposed method allowed us to drastically increase the efficiency of each well used for aquifer characterization and to process massive arrays of field data. Recommendations generalizing this experience to massive application of the proposed method are developed.

Ebola-related stigma in Ghana: Individual and community level determinants.

PubMed

Tenkorang, Eric Y

2017-06-01

Although Ebola-related stigmatization continues to undermine efforts to re-integrate survivors, few studies have examined what influences such stigmatizing attitudes. This paper explores the effects of both individual- and community-level factors on Ebola-related stigma in Ghana. Data were collected from a cross-section of 800 respondents, nested within 40 communities in the Greater Accra Region of Ghana. Multi-level modelling was employed for analysis. Both individual- and community-level factors were significant determinants of stigma. Respondents who endorsed myths about Ebola were significantly more likely to also endorse Ebola-related stigma. Similarly, those who were worried about a potential outbreak of Ebola in the future, had moderate risk perceptions of contracting Ebola, had primary and secondary education, and were not confident of the quality of health care in the event of an outbreak, were more likely to endorse Ebola-related stigma. Knowledge of Ebola was significant at the community level, but not at the individual level. Communities with more knowledge were less likely to endorse Ebola-related stigma. These findings underscore the need to increase the knowledge base while countering myths that undermine preventive behaviours to fight Ebola-related stigma. It is equally important to adopt multi-level interventions that emphasize community-based strategies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dual deep modeling: multi-level modeling with dual potencies and its formalization in F-Logic.

PubMed

Neumayr, Bernd; Schuetz, Christoph G; Jeusfeld, Manfred A; Schrefl, Michael

2018-01-01

An enterprise database contains a global, integrated, and consistent representation of a company's data. Multi-level modeling facilitates the definition and maintenance of such an integrated conceptual data model in a dynamic environment of changing data requirements of diverse applications. Multi-level models transcend the traditional separation of class and object with clabjects as the central modeling primitive, which allows for a more flexible and natural representation of many real-world use cases. In deep instantiation, the number of instantiation levels of a clabject or property is indicated by a single potency. Dual deep modeling (DDM) differentiates between source potency and target potency of a property or association and supports the flexible instantiation and refinement of the property by statements connecting clabjects at different modeling levels. DDM comes with multiple generalization of clabjects, subsetting/specialization of properties, and multi-level cardinality constraints. Examples are presented using a UML-style notation for DDM together with UML class and object diagrams for the representation of two-level user views derived from the multi-level model. Syntax and semantics of DDM are formalized and implemented in F-Logic, supporting the modeler with integrity checks and rich query facilities.

The Effect of Organizational Citizenship Behaviours of Primary School Teachers on Their Burnout

ERIC Educational Resources Information Center

Inandi, Yusuf; Buyukozkan, Ayse Sezin

2013-01-01

It was examined in this study whether organizational citizenship behaviours of primary school teachers predict the level of their burnout. Correlation and multi regression analysis were used for this. Survey model was used in this descriptive study. Data were collected from 1699 primary school teachers working in Mersin. Maslach Burnout Inventory…

English Phonological Awareness in Bilinguals: A Cross-Linguistic Study of Tamil, Malay and Chinese English-Language Learners

ERIC Educational Resources Information Center

Dixon, L. Quentin; Chuang, Hui-Kai; Quiroz, Blanca

2012-01-01

To test the lexical restructuring hypothesis among bilingual English-language learners, English phonological awareness (PA), English vocabulary and ethnic language vocabulary (Mandarin Chinese, Malay or Tamil) were assessed among 284 kindergarteners (168 Chinese, 71 Malays and 45 Tamils) in Singapore. A multi-level regression analysis showed that…

Work Organisation, Forms of Employee Learning and National Systems of Education and Training

ERIC Educational Resources Information Center

Lorenz, Edward; Lundvall, Bengt-Åke; Kraemer-Mbula, Erika; Rasmussen, Palle

2016-01-01

This article uses a multi-level framework to investigate for 17 European nations the links between forms of work organisation and style of employee learning at the workplace on the one hand, and the characteristics of national educational and training systems on the other. The analysis shows that forms of work organisation characterised by…

Discourse Connectives in L1 and L2 Argumentative Writing

ERIC Educational Resources Information Center

Hu, Chunyu; Li, Yuanyuan

2015-01-01

Discourse connectives (DCs) are multi-functional devices used to connect discourse segments and fulfill interpersonal levels of discourse. This study investigates the use of selected 80 DCs within 11 categories in the argumentative essays produced by L1 and L2 university students. The analysis is based on the International Corpus Network of Asian…

Coherent Power Analysis in Multi-Level Studies Using Design Parameters from Surveys

ERIC Educational Resources Information Center

Rhoads, Christopher

2016-01-01

Current practice for conducting power analyses in hierarchical trials using survey based ICC and effect size estimates may be misestimating power because ICCs are not being adjusted to account for treatment effect heterogeneity. Results presented in Table 1 show that the necessary adjustments can be quite large or quite small. Furthermore, power…

Inorganic elemental compositions of commercial multivitamin/mineral dietary supplements: application of collision/reaction cell inductively coupled-mass spectroscopy

USDA-ARS?s Scientific Manuscript database

Microwave digestion followed by analysis using ICP-MS has been shown to be a simple, fast reliable method for the multi-element determination in multivitamin/mineral dietary supplements (MVM). A study of 35 popular MVM dietary supplements revealed that composition and levels varied among products, a...

Student-Student Relations from the Teacher versus Student Perspective: A Multi-Level Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Heemsoth, Tim; Retelsdorf, Jan

2018-01-01

Educational research emphasizes the advantages of multimethod designs. However, if the design comprises different perspectives, the question of construct validity emerges. We related this question to student and teacher ratings of student-student relations, which are of high interest in research on physical education. In our study, 2,160 students…

Incentivizing Diversity: Midwestern Performance Funding Policy and Diversity Indicators. Faculty Fellow Report 2017-1

ERIC Educational Resources Information Center

Jones, Sosanya M.

2017-01-01

This multi-case study examines the Performance funding (PF) policies in four Midwestern states to explore how PF metrics and weights address racial diversity in higher education. Performance funding policies in Illinois, Kansas, Ohio, and Minnesota were examined using both document analysis and semi-structured interviews with state level actors…

School Security Measures and Extracurricular Participation: An Exploratory Multi-Level Analysis

ERIC Educational Resources Information Center

Mowen, Thomas J.; Manierre, Matthew J.

2017-01-01

Although delinquency in US schools is near historic lows, concern over delinquency in US schools remains a pressing issue among school officials, parents, and policy-makers. Many scholars argue that the current approach to discipline in the United States is highly punitive. While some projects have assessed the effect of punitive security on…

Quality of Teaching and Dropout Risk: A Multi-Level Analysis

ERIC Educational Resources Information Center

Magen-Nagar, Noga; Shachar, Hanna

2017-01-01

The purpose of this study is to examine how the quality of teaching contributes to a sense of belonging and satisfaction, while considering students' personal and socioeconomic variables, in explaining the risk of dropping out of school. Two thousand, eight hundred and seventy 4th- to 9th-grade students from 105 classes in 18 schools participated…

Curriculum Tracking and Teacher Evaluations of Individual Students: Selection, Adjustment or Labeling?

ERIC Educational Resources Information Center

Van Houtte, Mieke; Demanet, Jannick; Stevens, Peter A. J.

2013-01-01

Past research into the consequences of tracking mainly documented on the impact of attending different tracks on students' achievement and behavior. Less attention has been paid to the impact of track positions on teachers' perceptions and expectations regarding students. By means of multi-level analysis of data of 6,545 students in 46 Flemish…

Tensions in Higher Education Leadership: Towards a Multi-Level Model of Leadership Practice

ERIC Educational Resources Information Center

Bolden, Richard; Petrov, Georgy; Gosling, Jonathan

2008-01-01

UK higher education is undergoing a period of significant change that generates a series of tensions and difficulties for universities and university leaders. This paper explores these tensions through analysis of findings from a study comprising 152 semi-structured face-to-face interviews in 12 UK universities. Building on from theories of…

Gender and Contextual Differences in Social Responsibility in Thai Schools: A Multi-Study Person versus Situation Analysis

ERIC Educational Resources Information Center

Sosik, John J.; Koul, Ravinder; Cameron, John C.

2017-01-01

Social responsibility has been linked to the moral development of students, but little prior research has examined how personal and situational variables influence students' willingness to show care and concern for social issues that reflect higher levels of moral development. We theorised and tested the hypotheses that females would endorse…

Using the PDD Behavior Inventory as a Level 2 Screener: A Classification and Regression Trees Analysis

ERIC Educational Resources Information Center

Cohen, Ira L.; Liu, Xudong; Hudson, Melissa; Gillis, Jennifer; Cavalari, Rachel N. S.; Romanczyk, Raymond G.; Karmel, Bernard Z.; Gardner, Judith M.

2016-01-01

In order to improve discrimination accuracy between Autism Spectrum Disorder (ASD) and similar neurodevelopmental disorders, a data mining procedure, Classification and Regression Trees (CART), was used on a large multi-site sample of PDD Behavior Inventory (PDDBI) forms on children with and without ASD. Discrimination accuracy exceeded 80%,…

Examining the Impact of Critical Feedback on Learner Engagement in Secondary Mathematics Classrooms: A Multi-Level Analysis

ERIC Educational Resources Information Center

Kearney, W. Sean; Webb, Michael; Goldhorn, Jeff; Peters, Michelle L.

2013-01-01

This article presents a quantitative study utilizing HLM to analyze classroom walkthrough data completed by principals within 87 secondary mathematics classrooms across 9 public schools in Texas. This research is based on the theoretical framework of learner engagement as established by Argryis & Schon (1996), and refined by Marks (2000). It…

The effectiveness of risk management: an analysis of project risk planning across industries and countries.

PubMed

Zwikael, Ofer; Ahn, Mark

2011-01-01

This article examines the effectiveness of current risk management practices to reduce project risk using a multinational, multi-industry study across different scenarios and cultures. A survey was administered to 701 project managers, and their supervisors, in seven industries and three diverse countries (New Zealand, Israel, and Japan), in multiple languages during the 2002-2007 period. Results of this study show that project context--industry and country where a project is executed--significantly impacts perceived levels of project risk, and the intensity of risk management processes. Our findings also suggest that risk management moderates the relationship between risk level and project success. Specifically, we found that even moderate levels of risk management planning are sufficient to reduce the negative effect risk levels have on project success. © 2010 Society for Risk Analysis.

Future changes to drought characteristics over the Canadian Prairie Provinces based on NARCCAP multi-RCM ensemble

NASA Astrophysics Data System (ADS)

Masud, M. B.; Khaliq, M. N.; Wheater, H. S.

2017-04-01

This study assesses projected changes to drought characteristics in Alberta, Saskatchewan and Manitoba, the prairie provinces of Canada, using a multi-regional climate model (RCM) ensemble available through the North American Regional Climate Change Assessment Program. Simulations considered include those performed with six RCMs driven by National Center for Environmental Prediction reanalysis II for the 1981-2003 period and those driven by four Atmosphere-Ocean General Circulation Models for the 1970-1999 and 2041-2070 periods (i.e. eleven current and the same number of corresponding future period simulations). Drought characteristics are extracted using two drought indices, namely the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). Regional frequency analysis is used to project changes to selected 20- and 50-year regional return levels of drought characteristics for fifteen homogeneous regions, covering the study area. In addition, multivariate analyses of drought characteristics, derived on the basis of 6-month SPI and SPEI values, are developed using the copula approach for each region. Analysis of multi-RCM ensemble-averaged projected changes to mean and selected return levels of drought characteristics show increases over the southern and south-western parts of the study area. Based on bi- and trivariate joint occurrence probabilities of drought characteristics, the southern regions along with the central regions are found highly drought vulnerable, followed by the southwestern and southeastern regions. Compared to the SPI-based analysis, the results based on SPEI suggest drier conditions over many regions in the future, indicating potential effects of rising temperatures on drought risks. These projections will be useful in the development of appropriate adaptation strategies for the water and agricultural sectors, which play an important role in the economy of the study area.

Three-way parallel independent component analysis for imaging genetics using multi-objective optimization.

PubMed

Ulloa, Alvaro; Jingyu Liu; Vergara, Victor; Jiayu Chen; Calhoun, Vince; Pattichis, Marios

2014-01-01

In the biomedical field, current technology allows for the collection of multiple data modalities from the same subject. In consequence, there is an increasing interest for methods to analyze multi-modal data sets. Methods based on independent component analysis have proven to be effective in jointly analyzing multiple modalities, including brain imaging and genetic data. This paper describes a new algorithm, three-way parallel independent component analysis (3pICA), for jointly identifying genomic loci associated with brain function and structure. The proposed algorithm relies on the use of multi-objective optimization methods to identify correlations among the modalities and maximally independent sources within modality. We test the robustness of the proposed approach by varying the effect size, cross-modality correlation, noise level, and dimensionality of the data. Simulation results suggest that 3p-ICA is robust to data with SNR levels from 0 to 10 dB and effect-sizes from 0 to 3, while presenting its best performance with high cross-modality correlations, and more than one subject per 1,000 variables. In an experimental study with 112 human subjects, the method identified links between a genetic component (pointing to brain function and mental disorder associated genes, including PPP3CC, KCNQ5, and CYP7B1), a functional component related to signal decreases in the default mode network during the task, and a brain structure component indicating increases of gray matter in brain regions of the default mode region. Although such findings need further replication, the simulation and in-vivo results validate the three-way parallel ICA algorithm presented here as a useful tool in biomedical data decomposition applications.

A multi-level anomaly detection algorithm for time-varying graph data with interactive visualization

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

Bridges, Robert A.; Collins, John P.; Ferragut, Erik M.

This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labelled, streaming graph data. We introduce a generalization of the BTER model of Seshadhri et al. by adding flexibility to community structure, and use this model to perform multi-scale graph anomaly detection. Specifically, probability models describing coarse subgraphs are built by aggregating node probabilities, and these related hierarchical models simultaneously detect deviations from expectation. This technique provides insight into a graph's structure and internal context that may shed light on a detected event. Additionally, this multi-scale analysis facilitatesmore » intuitive visualizations by allowing users to narrow focus from an anomalous graph to particular subgraphs or nodes causing the anomaly. For evaluation, two hierarchical anomaly detectors are tested against a baseline Gaussian method on a series of sampled graphs. We demonstrate that our graph statistics-based approach outperforms both a distribution-based detector and the baseline in a labeled setting with community structure, and it accurately detects anomalies in synthetic and real-world datasets at the node, subgraph, and graph levels. Furthermore, to illustrate the accessibility of information made possible via this technique, the anomaly detector and an associated interactive visualization tool are tested on NCAA football data, where teams and conferences that moved within the league are identified with perfect recall, and precision greater than 0.786.« less

A multi-level anomaly detection algorithm for time-varying graph data with interactive visualization

DOE PAGES

Bridges, Robert A.; Collins, John P.; Ferragut, Erik M.; ...

2016-01-01

This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labelled, streaming graph data. We introduce a generalization of the BTER model of Seshadhri et al. by adding flexibility to community structure, and use this model to perform multi-scale graph anomaly detection. Specifically, probability models describing coarse subgraphs are built by aggregating node probabilities, and these related hierarchical models simultaneously detect deviations from expectation. This technique provides insight into a graph's structure and internal context that may shed light on a detected event. Additionally, this multi-scale analysis facilitatesmore » intuitive visualizations by allowing users to narrow focus from an anomalous graph to particular subgraphs or nodes causing the anomaly. For evaluation, two hierarchical anomaly detectors are tested against a baseline Gaussian method on a series of sampled graphs. We demonstrate that our graph statistics-based approach outperforms both a distribution-based detector and the baseline in a labeled setting with community structure, and it accurately detects anomalies in synthetic and real-world datasets at the node, subgraph, and graph levels. Furthermore, to illustrate the accessibility of information made possible via this technique, the anomaly detector and an associated interactive visualization tool are tested on NCAA football data, where teams and conferences that moved within the league are identified with perfect recall, and precision greater than 0.786.« less

Delamination detection by Multi-Level Wavelet Processing of Continuous Scanning Laser Doppler Vibrometry data

NASA Astrophysics Data System (ADS)

Chiariotti, P.; Martarelli, M.; Revel, G. M.

2017-12-01

A novel non-destructive testing procedure for delamination detection based on the exploitation of the simultaneous time and spatial sampling provided by Continuous Scanning Laser Doppler Vibrometry (CSLDV) and the feature extraction capability of Multi-Level wavelet-based processing is presented in this paper. The processing procedure consists in a multi-step approach. Once the optimal mother-wavelet is selected as the one maximizing the Energy to Shannon Entropy Ratio criterion among the mother-wavelet space, a pruning operation aiming at identifying the best combination of nodes inside the full-binary tree given by Wavelet Packet Decomposition (WPD) is performed. The pruning algorithm exploits, in double step way, a measure of the randomness of the point pattern distribution on the damage map space with an analysis of the energy concentration of the wavelet coefficients on those nodes provided by the first pruning operation. A combination of the point pattern distributions provided by each node of the ensemble node set from the pruning algorithm allows for setting a Damage Reliability Index associated to the final damage map. The effectiveness of the whole approach is proven on both simulated and real test cases. A sensitivity analysis related to the influence of noise on the CSLDV signal provided to the algorithm is also discussed, showing that the processing developed is robust enough to measurement noise. The method is promising: damages are well identified on different materials and for different damage-structure varieties.

Plaque levels of patients with fixed orthodontic appliances measured by digital plaque image analysis.

PubMed

Klukowska, Malgorzata; Bader, Annike; Erbe, Christina; Bellamy, Philip; White, Donald J; Anastasia, Mary Kay; Wehrbein, Heiner

2011-05-01

A digital plaque image analysis system was developed to objectively assess dental plaque formation and coverage in patients treated with fixed orthodontic appliances. The technique was used to assess plaque levels of 52 patients undergoing treatment with fixed appliances in the Department of Orthodontics at Johannes Gutenberg University in Mainz, Germany. Plaque levels ranged from 5.1% to 85.3% of the analyzed tooth areas. About 37% of the patients had plaque levels over 50% of the dentition, but only 10% exhibited plaque levels below 15% of tooth coverage. The mean plaque coverage was 41.9% ± 18.8%. Plaque was mostly present along the gum line and around the orthodontic brackets and wires. The digital plaque image analysis system might provide a convenient quantitative technique to assess oral hygiene in orthodontic patients with multi-bracket appliances. Plaque coverage in orthodontic patients is extremely high and is 2 to 3 times higher than levels observed in high plaque-forming adults without appliances participating in clinical studies of the digital plaque image analysis system. Improved hygiene, chemotherapeutic regimens, and compliance are necessary in these patients. Copyright © 2011 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

On the utility of the multi-level algorithm for the solution of nearly completely decomposable Markov chains

NASA Technical Reports Server (NTRS)

Leutenegger, Scott T.; Horton, Graham

1994-01-01

Recently the Multi-Level algorithm was introduced as a general purpose solver for the solution of steady state Markov chains. In this paper, we consider the performance of the Multi-Level algorithm for solving Nearly Completely Decomposable (NCD) Markov chains, for which special-purpose iteractive aggregation/disaggregation algorithms such as the Koury-McAllister-Stewart (KMS) method have been developed that can exploit the decomposability of the the Markov chain. We present experimental results indicating that the general-purpose Multi-Level algorithm is competitive, and can be significantly faster than the special-purpose KMS algorithm when Gauss-Seidel and Gaussian Elimination are used for solving the individual blocks.

Least Reliable Bits Coding (LRBC) for high data rate satellite communications

NASA Technical Reports Server (NTRS)

Vanderaar, Mark; Wagner, Paul; Budinger, James

1992-01-01

An analysis and discussion of a bandwidth efficient multi-level/multi-stage block coded modulation technique called Least Reliable Bits Coding (LRBC) is presented. LRBC uses simple multi-level component codes that provide increased error protection on increasingly unreliable modulated bits in order to maintain an overall high code rate that increases spectral efficiency. Further, soft-decision multi-stage decoding is used to make decisions on unprotected bits through corrections made on more protected bits. Using analytical expressions and tight performance bounds it is shown that LRBC can achieve increased spectral efficiency and maintain equivalent or better power efficiency compared to that of Binary Phase Shift Keying (BPSK). Bit error rates (BER) vs. channel bit energy with Additive White Gaussian Noise (AWGN) are given for a set of LRB Reed-Solomon (RS) encoded 8PSK modulation formats with an ensemble rate of 8/9. All formats exhibit a spectral efficiency of 2.67 = (log2(8))(8/9) information bps/Hz. Bit by bit coded and uncoded error probabilities with soft-decision information are determined. These are traded with with code rate to determine parameters that achieve good performance. The relative simplicity of Galois field algebra vs. the Viterbi algorithm and the availability of high speed commercial Very Large Scale Integration (VLSI) for block codes indicates that LRBC using block codes is a desirable method for high data rate implementations.

VESsel GENeration Analysis (VESGEN): Innovative Vascular Mappings for Astronaut Exploration Health Risks and Human Terrestrial Medicine

NASA Technical Reports Server (NTRS)

Parsons-Wingerter, Patricia; Kao, David; Valizadegan, Hamed; Martin, Rodney; Murray, Matthew C.; Ramesh, Sneha; Sekaran, Srinivaas

2017-01-01

Currently, astronauts face significant health risks in future long-duration exploration missions such as colonizing the Moon and traveling to Mars. Numerous risks include greatly increased radiation exposures beyond the low earth orbit (LEO) of the ISS, and visual and ocular impairments in response to microgravity environments. The cardiovascular system is a key mediator in human physiological responses to radiation and microgravity. Moreover, blood vessels are necessarily involved in the progression and treatment of vascular-dependent terrestrial diseases such as cancer, coronary vessel disease, wound-healing, reproductive disorders, and diabetes. NASA developed an innovative, globally requested beta-level software, VESsel GENeration Analysis (VESGEN) to map and quantify vascular remodeling for application to astronaut and terrestrial health challenges. VESGEN mappings of branching vascular trees and networks are based on a weighted multi-parametric analysis derived from vascular physiological branching rules. Complex vascular branching patterns are determined by biological signaling mechanisms together with the fluid mechanics of multi-phase laminar blood flow.

Risk Governance of Multiple Natural Hazards: Centralized versus Decentralized Approach in Europe

NASA Astrophysics Data System (ADS)

Komendantova, Nadejda; Scolobig, Anna; Vinchon, Charlotte

2014-05-01

The multi-risk approach is a relatively new field and its definition includes the need to consider multiple hazards and vulnerabilities in their interdependency (Selva, 2013) and the current multi-hazards disasters, such as the 2011 Tohoku earthquake, tsunami and nuclear catastrophe, showed the need for a multi-risk approach in hazard mitigation and management. Our knowledge about multi-risk assessment, including studies from different scientific disciplines and developed assessment tools, is constantly growing (White et al., 2001). However, the link between scientific knowledge, its implementation and the results in terms of improved governance and decision-making have gained significantly less attention (IRGC, 2005; Kappes et al., 2012), even though the interest to risk governance, in general, has increased significantly during the last years (Verweiy and Thompson, 2006). Therefore, the key research question is how risk assessment is implemented and what is the potential for the implementation of a multi-risk approach in different governance systems across Europe. More precisely, how do the characteristics of risk governance, such as the degree of centralization versus decentralization, influence the implementation of a multi-risk approach. The methodology of this research includes comparative case study analysis of top-down and bottom-up interactions in governance in the city of Naples, (Italy), where the institutional landscape is marked by significant autonomy of Italian regions in decision-making processes for assessing the majority of natural risks, excluding volcanic, and in Guadeloupe, French West Indies, an overseas department of France, where the decision-making process is marked by greater centralization in decision making associated with a well established state governance within regions, delegated to the prefect and decentralised services of central ministries. The research design included documentary analysis and extensive empirical work involving policy makers, private sector actors and practitioners in risk and emergency management. This work was informed by 36 semi-structured interviews, three workshops with over seventy participants from eleven different countries, feedback from questionnaires and focus group discussions (Scolobig et al., 2013). The results show that both governance systems have their own strengths and weaknesses (Komendantova et al., 2013). Elements of the centralized multi-risk governance system could lead to improvements in interagency communication and the creation of an inter-agency environment, where the different departments at the national level can exchange information, identify the communities that are most exposed to multiple risks and set priorities, while providing consistent information about and responses to multi-risk to the relevant stakeholders at the local level. A decentralised multi-risk governance system by contrast can instead favour the creation of local multi-risk commissions to conduct discussions between experts in meteorological, geological and technological risks and practitioners, to elaborate risk and hazard maps, and to develop local capacities which would include educational and training activities. Both governance systems suffer from common deficiencies, the most important being the frequent lack of capacities at the local level, especially financial, but sometimes also technical and institutional ones, as the responsibilities for disaster risk management are often transferred from the national to local levels without sufficient resources for implementation of programs on risk management (UNISDR, 2013). The difficulty in balancing available resources between short-term and medium-term priorities often complicates the issue. Our recommendations are that the implementation of multi-risk approach can be facilitated through knowledge exchange and dialogue between different disciplinary communities, such as geological and meteorological, and between the natural and social sciences. The implementation of a multi-risk approach can be strengthened through the creation of multi-risk platforms and multi-risk commissions, which can liaise between risk management experts and local communities and to unify numerous actions on natural hazard management. However, the multi-risk approach cannot be a subsidiary to a single risk approach, and both have to be pursued. References: IRGC. (2011). Concept note: Improving the management of emerging risks: Risks from new technologies, system interactions, and unforeseen or changing circumstances. International Risk Governance Council (IRGC), Geneva. Kappes, M. S., Keiler, M., Elverfeldt, von K., & Glade, T, (2012). Challenges of analyzing multi-hazard risk: A review. Natural Hazards, 64(2), 1925-1958. doi: 10.1007/s11069-012-0294-2. Komendantova N, Scolobig A, Vinchon C (2013). Multi-risk approach in centralized and decentralized risk governance systems: Case studies of Naples, Italy and Guadeloupe, France. International Relations and Diplomacy, 1(3):224-239 (December 2013) Scolobig, A., Vichon, C., Komendantova, N., Bengoubou-Valerius, M., & Patt, A. (2013). Social and institutional barriers to effective multi-hazard and multi-risk decision-making governance. D6.3 MATRIX project. Selva, J. (2013). Long-term multi-risk assessment: statistical treatment of interaction among risks. Natural Hazards, 67(2),701-722. UNISDR. (2013). Implementing the HYOGO framework for action in Europe: Regional synthesis report 2011-2013. Verweij, M., & Thompson, M. (Eds.). (2006). Clumsy solutions for a complex world: Governance, politics, and plural perceptions. New York: Palgrave Macmillan. White, G., Kates, R., & Burton, I. (2001). Knowing better and losing even more: the use of knowledge in hazards management. Environmental Hazards, 3, 81-92.

xQTL workbench: a scalable web environment for multi-level QTL analysis.

PubMed

Arends, Danny; van der Velde, K Joeri; Prins, Pjotr; Broman, Karl W; Möller, Steffen; Jansen, Ritsert C; Swertz, Morris A

2012-04-01

xQTL workbench is a scalable web platform for the mapping of quantitative trait loci (QTLs) at multiple levels: for example gene expression (eQTL), protein abundance (pQTL), metabolite abundance (mQTL) and phenotype (phQTL) data. Popular QTL mapping methods for model organism and human populations are accessible via the web user interface. Large calculations scale easily on to multi-core computers, clusters and Cloud. All data involved can be uploaded and queried online: markers, genotypes, microarrays, NGS, LC-MS, GC-MS, NMR, etc. When new data types come available, xQTL workbench is quickly customized using the Molgenis software generator. xQTL workbench runs on all common platforms, including Linux, Mac OS X and Windows. An online demo system, installation guide, tutorials, software and source code are available under the LGPL3 license from http://www.xqtl.org. m.a.swertz@rug.nl.

xQTL workbench: a scalable web environment for multi-level QTL analysis

PubMed Central

Arends, Danny; van der Velde, K. Joeri; Prins, Pjotr; Broman, Karl W.; Möller, Steffen; Jansen, Ritsert C.; Swertz, Morris A.

2012-01-01

Summary: xQTL workbench is a scalable web platform for the mapping of quantitative trait loci (QTLs) at multiple levels: for example gene expression (eQTL), protein abundance (pQTL), metabolite abundance (mQTL) and phenotype (phQTL) data. Popular QTL mapping methods for model organism and human populations are accessible via the web user interface. Large calculations scale easily on to multi-core computers, clusters and Cloud. All data involved can be uploaded and queried online: markers, genotypes, microarrays, NGS, LC-MS, GC-MS, NMR, etc. When new data types come available, xQTL workbench is quickly customized using the Molgenis software generator. Availability: xQTL workbench runs on all common platforms, including Linux, Mac OS X and Windows. An online demo system, installation guide, tutorials, software and source code are available under the LGPL3 license from http://www.xqtl.org. Contact: m.a.swertz@rug.nl PMID:22308096

A collision dynamics model of a multi-level train

DOT National Transportation Integrated Search

2006-11-05

In train collisions, multi-level rail passenger vehicles can deform in modes that are different from the behavior of single level cars. The deformation in single level cars usually occurs at the front end during a collision. In one particular inciden...

Extending the Multi-level Method for the Simulation of Stochastic Biological Systems.

PubMed

Lester, Christopher; Baker, Ruth E; Giles, Michael B; Yates, Christian A

2016-08-01

The multi-level method for discrete-state systems, first introduced by Anderson and Higham (SIAM Multiscale Model Simul 10(1):146-179, 2012), is a highly efficient simulation technique that can be used to elucidate statistical characteristics of biochemical reaction networks. A single point estimator is produced in a cost-effective manner by combining a number of estimators of differing accuracy in a telescoping sum, and, as such, the method has the potential to revolutionise the field of stochastic simulation. In this paper, we present several refinements of the multi-level method which render it easier to understand and implement, and also more efficient. Given the substantial and complex nature of the multi-level method, the first part of this work reviews existing literature, with the aim of providing a practical guide to the use of the multi-level method. The second part provides the means for a deft implementation of the technique and concludes with a discussion of a number of open problems.

Changes in US extreme sea levels and the role of large scale climate variations

NASA Astrophysics Data System (ADS)

Wahl, T.; Chambers, D. P.

2015-12-01

We analyze a set of 20 tide gauge records covering the contiguous United States (US) coastline and the period from 1929 to 2013 to identify long-term trends and multi-decadal variations in extreme sea levels (ESLs) relative to changes in mean sea level (MSL). Significant but small long-term trends in ESLs above/below MSL are found at individual sites along most coastline stretches, but are mostly confined to the southeast coast and the winter season when storm surges are primarily driven by extra-tropical cyclones. We identify six regions with broadly coherent and considerable multi-decadal ESL variations unrelated to MSL changes. Using a quasi-non-stationary extreme value analysis approach we show that the latter would have caused variations in design relevant return water levels (RWLs; 50 to 200 year return periods) ranging from ~10 cm to as much as 110 cm across the six regions. To explore the origin of these temporal changes and the role of large-scale climate variability we develop different sets of simple and multiple linear regression models with RWLs as dependent variables and climate indices, or tailored (toward the goal of predicting multi-decadal RWL changes) versions of them, and wind stress curl as independent predictors. The models, after being tested for spatial and temporal stability, explain up to 97% of the observed variability at individual sites and almost 80% on average. Using the model predictions as covariates for the quasi-non-stationary extreme value analysis also significantly reduces the range of change in the 100-year RWLs over time, turning a non-stationary process into a stationary one. This highlights that the models - when used with regional and global climate model output of the predictors - should also be capable of projecting future RWL changes to be used by decision makers for improved flood preparedness and long-term resiliency.

Estimating Pesticide Exposure from Dietary Intake and Organic Food Choices: The Multi-Ethnic Study of Atherosclerosis (MESA)

PubMed Central

Beresford, Shirley A.A.; Fenske, Richard A.; Fitzpatrick, Annette L.; Lu, Chensheng; Nettleton, Jennifer A.; Kaufman, Joel D.

2015-01-01

Background Organophosphate pesticide (OP) exposure to the U.S. population is dominated by dietary intake. The magnitude of exposure from diet depends partly on personal decisions such as which foods to eat and whether to choose organic food. Most studies of OP exposure rely on urinary biomarkers, which are limited by short half-lives and often lack specificity to parent compounds. A reliable means of estimating long-term dietary exposure to individual OPs is needed to assess the potential relationship with adverse health effects. Objectives We assessed long-term dietary exposure to 14 OPs among 4,466 participants in the Multi-Ethnic Study of Atherosclerosis, and examined the influence of organic produce consumption on this exposure. Methods Individual-level exposure was estimated by combining information on typical intake of specific food items with average OP residue levels on those items. In an analysis restricted to a subset of participants who reported rarely or never eating organic produce (“conventional consumers”), we assessed urinary dialkylphosphate (DAP) levels across tertiles of estimated exposure (n = 480). In a second analysis, we compared DAP levels across subgroups with differing self-reported organic produce consumption habits (n = 240). Results Among conventional consumers, increasing tertile of estimated dietary OP exposure was associated with higher DAP concentrations (p < 0.05). DAP concentrations were also significantly lower in groups reporting more frequent consumption of organic produce (p < 0.02). Conclusions Long-term dietary exposure to OPs was estimated from dietary intake data, and estimates were consistent with DAP measurements. More frequent consumption of organic produce was associated with lower DAPs. Citation Curl CL, Beresford SA, Fenske RA, Fitzpatrick AL, Lu C, Nettleton JA, Kaufman JD. 2015. Estimating pesticide exposure from dietary intake and organic food choices: the Multi-Ethnic Study of Atherosclerosis (MESA). Environ Health Perspect 123:475–483; http://dx.doi.org/10.1289/ehp.1408197 PMID:25650532

Strengthening Indonesia's health workforce through partnerships.

PubMed

Kurniati, A; Rosskam, E; Afzal, M M; Suryowinoto, T B; Mukti, A G

2015-09-01

Indonesia faces critical challenges pertaining to human resources for health (HRH). These relate to HRH policy, planning, mismatch between production and demand, quality, renumeration, and mal-distribution. This paper provides a state of the art review of the existing conditions in Indonesia, innovations to tackle the problems, results of the innovations to date, and a picture of the on-going challenges that have yet to be met. Reversing this crisis level shortage of HRH requires an inclusive approach to address the underlying challenges. In 2010 the government initiated multi-stakeholder coordination for HRH, using the Country Coordination and Facilitation approach. The process requires committed engagement and coordination of relevant stakeholders to address priority health needs. This manuscript is a formative evaluation of the program using documentary study and analysis. Consistent with Indonesia's decentralized health system, since 2011 local governments also started establishing provincial multi-stakeholder committees and working groups for HRH development. Through this multi-stakeholder approach with high level government support and leadership, Indonesia was able to carry out HRH planning by engaging 164 stakeholders. Multi-stakeholder coordination has produced positive results in Indonesia by bringing about a number of innovations in HRH development to achieve UHC, fostered partnerships, attracted international attention, and galvanized multi-stakeholder support in improving the HRH situation. This approach also has facilitated mobilizing technical and financial support from domestic and international partners for HRH development. Applying the multi-stakeholder engagement and coordination process in Indonesia has proved instrumental in advancing the country's work to achieve Universal Health Coverage and the Millennium Development Goals by 2015. Indonesia continues to face an HRH crisis but the collaborative process provides an opportunity to achieve results. Indonesia's experience indicates that irrespective of geographical or economic status, countries can benefit from multi-stakeholder coordination and engagement to increase access to health workers, strengthen health systems, as well as achieve and sustain UHC. Copyright © 2015 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Reduced hypothalamic-pituitary-adrenal axis activity in chronic multi-site musculoskeletal pain: partly masked by depressive and anxiety disorders.

PubMed

Generaal, Ellen; Vogelzangs, Nicole; Macfarlane, Gary J; Geenen, Rinie; Smit, Johannes H; Penninx, Brenda W J H; Dekker, Joost

2014-07-09

Studies on hypothalamic-pituitary-adrenal axis (HPA-axis) function amongst patients with chronic pain show equivocal results and well-controlled cohort studies are rare in this field. The goal of our study was to examine whether HPA-axis dysfunction is associated with the presence and the severity of chronic multi-site musculoskeletal pain. Data are from the Netherlands Study of Depression and Anxiety including 1125 subjects with and without lifetime depressive and anxiety disorders. The Chronic Pain Grade questionnaire was used to determine the presence and severity of chronic multi-site musculoskeletal pain. Subjects were categorized into a chronic multi-site musculoskeletal pain group (n = 471) and a control group (n = 654). Salivary cortisol samples were collected to assess HPA-axis function (awakening level, 1-h awakening response, evening level, diurnal slope and post-dexamethasone level). In comparison with the control group, subjects with chronic multi-site musculoskeletal pain showed significantly lower cortisol level at awakening, lower evening level and a blunted diurnal slope. Lower cortisol level at awakening and a blunted diurnal slope appeared to be restricted to those without depressive and/or anxiety disorders, who also showed a lower 1-h awakening response. Our results suggest hypocortisolemia in chronic multi-site musculoskeletal pain. However, if chronic pain is accompanied by a depressive or anxiety disorder, typically related to hypercortisolemia, the association between cortisol levels and chronic multi-site musculoskeletal pain appears to be partly masked. Future studies should take psychopathology into account when examining HPA-axis function in chronic pain.

Reduced hypothalamic-pituitary-adrenal axis activity in chronic multi-site musculoskeletal pain: partly masked by depressive and anxiety disorders

PubMed Central

2014-01-01

Background Studies on hypothalamic-pituitary-adrenal axis (HPA-axis) function amongst patients with chronic pain show equivocal results and well-controlled cohort studies are rare in this field. The goal of our study was to examine whether HPA-axis dysfunction is associated with the presence and the severity of chronic multi-site musculoskeletal pain. Methods Data are from the Netherlands Study of Depression and Anxiety including 1125 subjects with and without lifetime depressive and anxiety disorders. The Chronic Pain Grade questionnaire was used to determine the presence and severity of chronic multi-site musculoskeletal pain. Subjects were categorized into a chronic multi-site musculoskeletal pain group (n = 471) and a control group (n = 654). Salivary cortisol samples were collected to assess HPA-axis function (awakening level, 1-h awakening response, evening level, diurnal slope and post-dexamethasone level). Results In comparison with the control group, subjects with chronic multi-site musculoskeletal pain showed significantly lower cortisol level at awakening, lower evening level and a blunted diurnal slope. Lower cortisol level at awakening and a blunted diurnal slope appeared to be restricted to those without depressive and/or anxiety disorders, who also showed a lower 1-h awakening response. Conclusions Our results suggest hypocortisolemia in chronic multi-site musculoskeletal pain. However, if chronic pain is accompanied by a depressive or anxiety disorder, typically related to hypercortisolemia, the association between cortisol levels and chronic multi-site musculoskeletal pain appears to be partly masked. Future studies should take psychopathology into account when examining HPA-axis function in chronic pain. PMID:25007969

Sensitivity Analysis Based Approaches for Mitigating the Effects of Reducible Interval Input Uncertainty on Single- and Multi-Disciplinary Systems Using Multi-Objective Optimization

DTIC Science & Technology

2010-01-01

Multi-Disciplinary, Multi-Output Sensitivity Analysis ( MIMOSA ) .........29 3.1 Introduction to Research Thrust 1...39 3.3 MIMOSA Approach ..........................................................................................41 3.3.1...Collaborative Consistency of MIMOSA .......................................................41 3.3.2 Formulation of MIMOSA

Multi-level factors influence the implementation and use of complex innovations in cancer care: a multiple case study of synoptic reporting.

PubMed

Urquhart, Robin; Porter, Geoffrey A; Sargeant, Joan; Jackson, Lois; Grunfeld, Eva

2014-09-16

The implementation of innovations (i.e., new tools and practices) in healthcare organizations remains a significant challenge. The objective of this study was to examine the key interpersonal, organizational, and system level factors that influenced the implementation and use of synoptic reporting tools in three specific areas of cancer care. Using case study methodology, we studied three cases in Nova Scotia, Canada, wherein synoptic reporting tools were implemented within clinical departments/programs. Synoptic reporting tools capture and present information about a medical or surgical procedure in a structured, checklist-like format and typically report only items critical for understanding the disease and subsequent impacts on patient care. Data were collected through semi-structured interviews with key informants, document analysis, nonparticipant observation, and tool use/examination. Analysis involved production of case histories, in-depth analysis of each case, and a cross-case analysis. Numerous techniques were used during the research design, data collection, and data analysis stages to increase the rigour of this study. The analysis revealed five common factors that were particularly influential to implementation and use of synoptic reporting tools across the three cases: stakeholder involvement, managing the change process (e.g., building demand, communication, training and support), champions and respected colleagues, administrative and managerial support, and innovation attributes (e.g., complexity, compatibility with interests and values). The direction of influence (facilitating or impeding) of each of these factors differed across and within cases. The findings demonstrate the importance of a multi-level contextual analysis to gaining both breadth and depth to our understanding of innovation implementation and use in health care. They also provide new insights into several important issues under-reported in the literature on moving innovations into healthcare practice, including the role of middle managers in implementation efforts and the importance of attending to the interpersonal aspects of implementation.

MELCOR Analysis of OSU Multi-Application Small Light Water Reactor (MASLWR) Experiment

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

Yoon, Dhongik S.; Jo, HangJin; Fu, Wen

A multi-application small light water reactor (MASLWR) conceptual design was developed by Oregon State University (OSU) with emphasis on passive safety systems. The passive containment safety system employs condensation and natural circulation to achieve the necessary heat removal from the containment in case of postulated accidents. Containment condensation experiments at the MASLWR test facility at OSU are modeled and analyzed with MELCOR, a system-level reactor accident analysis computer code. The analysis assesses its ability to predict condensation heat transfer in the presence of noncondensable gas for accidents where high-energy steam is released into the containment. This work demonstrates MELCOR’s abilitymore » to predict the pressure-temperature response of the scaled containment. Our analysis indicates that the heat removal rates are underestimated in the experiment due to the limited locations of the thermocouples and applies corrections to these measurements by conducting integral energy analyses along with CFD simulation for confirmation. Furthermore, the corrected heat removal rate measurements and the MELCOR predictions on the heat removal rate from the containment show good agreement with the experimental data.« less

MELCOR Analysis of OSU Multi-Application Small Light Water Reactor (MASLWR) Experiment

DOE PAGES

Yoon, Dhongik S.; Jo, HangJin; Fu, Wen; ...

2017-05-23

A multi-application small light water reactor (MASLWR) conceptual design was developed by Oregon State University (OSU) with emphasis on passive safety systems. The passive containment safety system employs condensation and natural circulation to achieve the necessary heat removal from the containment in case of postulated accidents. Containment condensation experiments at the MASLWR test facility at OSU are modeled and analyzed with MELCOR, a system-level reactor accident analysis computer code. The analysis assesses its ability to predict condensation heat transfer in the presence of noncondensable gas for accidents where high-energy steam is released into the containment. This work demonstrates MELCOR’s abilitymore » to predict the pressure-temperature response of the scaled containment. Our analysis indicates that the heat removal rates are underestimated in the experiment due to the limited locations of the thermocouples and applies corrections to these measurements by conducting integral energy analyses along with CFD simulation for confirmation. Furthermore, the corrected heat removal rate measurements and the MELCOR predictions on the heat removal rate from the containment show good agreement with the experimental data.« less

Energy Levels and Co-evolution of Product Innovation in Supply Chain Clusters

NASA Astrophysics Data System (ADS)

Ji, Guojun

In the last decade supply chain clusters phenomenon has emerged as a new approach in product innovation studies. This article makes three contributions to the approach by addressing some open issues. The first contribution is to explicitly incorporate the energy levels in the analysis. Hence, the unit of analysis is widened from sectoral systems of innovation to socio-technical systems. Hence, the unit of analysis is widened from sectoral systems of innovation to socio-technical systems. The second contribution is to suggest an analytical distinction between different evolution method, actors involved in them, and the institutions which guide actor's perceptions and activities. Thirdly, the article opens up the black box of institutions, making them an integral part of supply chain. The article provides a coherent conceptual multi-level perspective, using insights from sociology, institutional theory and innovation studies. The perspective is particularly useful to analyze long-term dynamics supply chain clusters phenomenon, shifts from one energy level to another and the co-evolution of product innovation.

Deep Visual Attention Prediction

NASA Astrophysics Data System (ADS)

Wang, Wenguan; Shen, Jianbing

2018-05-01

In this work, we aim to predict human eye fixation with view-free scenes based on an end-to-end deep learning architecture. Although Convolutional Neural Networks (CNNs) have made substantial improvement on human attention prediction, it is still needed to improve CNN based attention models by efficiently leveraging multi-scale features. Our visual attention network is proposed to capture hierarchical saliency information from deep, coarse layers with global saliency information to shallow, fine layers with local saliency response. Our model is based on a skip-layer network structure, which predicts human attention from multiple convolutional layers with various reception fields. Final saliency prediction is achieved via the cooperation of those global and local predictions. Our model is learned in a deep supervision manner, where supervision is directly fed into multi-level layers, instead of previous approaches of providing supervision only at the output layer and propagating this supervision back to earlier layers. Our model thus incorporates multi-level saliency predictions within a single network, which significantly decreases the redundancy of previous approaches of learning multiple network streams with different input scales. Extensive experimental analysis on various challenging benchmark datasets demonstrate our method yields state-of-the-art performance with competitive inference time.

Control of Neural Daughter Cell Proliferation by Multi-level Notch/Su(H)/E(spl)-HLH Signaling

PubMed Central

Bivik, Caroline; MacDonald, Ryan B.; Gunnar, Erika; Mazouni, Khalil; Schweisguth, Francois; Thor, Stefan

2016-01-01

The Notch pathway controls proliferation during development and in adulthood, and is frequently affected in many disorders. However, the genetic sensitivity and multi-layered transcriptional properties of the Notch pathway has made its molecular decoding challenging. Here, we address the complexity of Notch signaling with respect to proliferation, using the developing Drosophila CNS as model. We find that a Notch/Su(H)/E(spl)-HLH cascade specifically controls daughter, but not progenitor proliferation. Additionally, we find that different E(spl)-HLH genes are required in different neuroblast lineages. The Notch/Su(H)/E(spl)-HLH cascade alters daughter proliferation by regulating four key cell cycle factors: Cyclin E, String/Cdc25, E2f and Dacapo (mammalian p21CIP1/p27KIP1/p57Kip2). ChIP and DamID analysis of Su(H) and E(spl)-HLH indicates direct transcriptional regulation of the cell cycle genes, and of the Notch pathway itself. These results point to a multi-level signaling model and may help shed light on the dichotomous proliferative role of Notch signaling in many other systems. PMID:27070787

Integrated multi-choice goal programming and multi-segment goal programming for supplier selection considering imperfect-quality and price-quantity discounts in a multiple sourcing environment

NASA Astrophysics Data System (ADS)

Chang, Ching-Ter; Chen, Huang-Mu; Zhuang, Zheng-Yun

2014-05-01

Supplier selection (SS) is a multi-criteria and multi-objective problem, in which multi-segment (e.g. imperfect-quality discount (IQD) and price-quantity discount (PQD)) and multi-aspiration level problems may be significantly important; however, little attention had been given to dealing with both of them simultaneously in the past. This study proposes a model for integrating multi-choice goal programming and multi-segment goal programming to solve the above-mentioned problems by providing the following main contributions: (1) it allows decision-makers to set multiple aspiration levels on the right-hand side of each goal to suit real-world situations, (2) the PQD and IQD conditions are considered in the proposed model simultaneously and (3) the proposed model can solve a SS problem with n suppliers where each supplier offers m IQD with r PQD intervals, where only ? extra binary variables are required. The usefulness of the proposed model is explained using a real case. The results indicate that the proposed model not only can deal with a SS problem with multi-segment and multi-aspiration levels, but also can help the decision-maker to find the appropriate order quantities for each supplier by considering cost, quality and delivery.

Human connectome module pattern detection using a new multi-graph MinMax cut model.

PubMed

De, Wang; Wang, Yang; Nie, Feiping; Yan, Jingwen; Cai, Weidong; Saykin, Andrew J; Shen, Li; Huang, Heng

2014-01-01

Many recent scientific efforts have been devoted to constructing the human connectome using Diffusion Tensor Imaging (DTI) data for understanding the large-scale brain networks that underlie higher-level cognition in human. However, suitable computational network analysis tools are still lacking in human connectome research. To address this problem, we propose a novel multi-graph min-max cut model to detect the consistent network modules from the brain connectivity networks of all studied subjects. A new multi-graph MinMax cut model is introduced to solve this challenging computational neuroscience problem and the efficient optimization algorithm is derived. In the identified connectome module patterns, each network module shows similar connectivity patterns in all subjects, which potentially associate to specific brain functions shared by all subjects. We validate our method by analyzing the weighted fiber connectivity networks. The promising empirical results demonstrate the effectiveness of our method.

Multi-objective spatial tools to inform maritime spatial planning in the Adriatic Sea.

PubMed

Depellegrin, Daniel; Menegon, Stefano; Farella, Giulio; Ghezzo, Michol; Gissi, Elena; Sarretta, Alessandro; Venier, Chiara; Barbanti, Andrea

2017-12-31

This research presents a set of multi-objective spatial tools for sea planning and environmental management in the Adriatic Sea Basin. The tools address four objectives: 1) assessment of cumulative impacts from anthropogenic sea uses on environmental components of marine areas; 2) analysis of sea use conflicts; 3) 3-D hydrodynamic modelling of nutrient dispersion (nitrogen and phosphorus) from riverine sources in the Adriatic Sea Basin and 4) marine ecosystem services capacity assessment from seabed habitats based on an ES matrix approach. Geospatial modelling results were illustrated, analysed and compared on country level and for three biogeographic subdivisions, Northern-Central-Southern Adriatic Sea. The paper discusses model results for their spatial implications, relevance for sea planning, limitations and concludes with an outlook towards the need for more integrated, multi-functional tools development for sea planning. Copyright © 2017. Published by Elsevier B.V.

Multi-look fusion identification: a paradigm shift from quality to quantity in data samples

NASA Astrophysics Data System (ADS)

Wong, S.

2009-05-01

A multi-look identification method known as score-level fusion is found to be capable of achieving very high identification accuracy, even when low quality target signatures are used. Analysis using measured ground vehicle radar signatures has shown that a 97% correct identification rate can be achieved using this multi-look fusion method; in contrast, only a 37% accuracy rate is obtained when single target signature input is used. The results suggest that quantity can be used to replace quality of the target data in improving identification accuracy. With the advent of sensor technology, a large amount of target signatures of marginal quality can be captured routinely. This quantity over quality approach allows maximum exploitation of the available data to improve the target identification performance and this could have the potential of being developed into a disruptive technology.

The development of multi-level critical care competency statements for self-assessment by ICU nurses.

PubMed

Bourgault, Annette M; Smith, Sherry

2004-01-01

Multi-levelled critical care competency statements were developed based on the levels of novice to expert (Benner, 1984). These competency statements provide a framework for the development of knowledge and skills specific to critical care. The purpose of this tool is to guide personal development in critical care, facilitating the assessment of individual learning needs. Competency levels are attained through the completion of performance criteria. Multi-levelled competency statements define clear expectations for the new orientee, in addition to providing a framework for the advancement of the intermediate and experienced nurse.

[The implementation of strategy of medicinal support in multi-type hospital].

PubMed

Ludupova, E Yu

2016-01-01

The article presents brief review of implementation of strategy of medicinal support of population of the Russian Federation and experience of application of at the level of regional hospital. The necessity and importance of implementation into practice of hospitals of methodology of pharmaco-economical management of medicinal care using modern technologies of XYZ-, ABC and VEN-analysis is demonstrated. The stages of development and implementation of process of medicinal support of multifield hospital applying principles of system of quality management (processing and systemic approaches, risk management) on the basis of standards ISO 9001 are described. The significance of monitoring of results ofprocess of medicinal support of the basis of implementation of priority target programs (prevention of venous thrombo-embolic complications, system od control of anti-bacterial therapy) are demonstrated in relation to multi-field hospital using technique of ATC/DDD-analysis for evaluating indices of effectiveness and efficiency.

Effect of Hydrogen Addition on Methane HCCI Engine Ignition Timing and Emissions Using a Multi-zone Model

NASA Astrophysics Data System (ADS)

Wang, Zi-han; Wang, Chun-mei; Tang, Hua-xin; Zuo, Cheng-ji; Xu, Hong-ming

2009-06-01

Ignition timing control is of great importance in homogeneous charge compression ignition engines. The effect of hydrogen addition on methane combustion was investigated using a CHEMKIN multi-zone model. Results show that hydrogen addition advances ignition timing and enhances peak pressure and temperature. A brief analysis of chemical kinetics of methane blending hydrogen is also performed in order to investigate the scope of its application, and the analysis suggests that OH radical plays an important role in the oxidation. Hydrogen addition increases NOx while decreasing HC and CO emissions. Exhaust gas recirculation (EGR) also advances ignition timing; however, its effects on emissions are generally the opposite. By adjusting the hydrogen addition and EGR rate, the ignition timing can be regulated with a low emission level. Investigation into zones suggests that NOx is mostly formed in core zones while HC and CO mostly originate in the crevice and the quench layer.

Performance Analysis of Diversity-Controlled Multi-User Superposition Transmission for 5G Wireless Networks

PubMed Central

Yeom, Jeong Seon; Jung, Bang Chul; Jin, Hu

2018-01-01

In this paper, we propose a novel low-complexity multi-user superposition transmission (MUST) technique for 5G downlink networks, which allows multiple cell-edge users to be multiplexed with a single cell-center user. We call the proposed technique diversity-controlled MUST technique since the cell-center user enjoys the frequency diversity effect via signal repetition over multiple orthogonal frequency division multiplexing (OFDM) sub-carriers. We assume that a base station is equipped with a single antenna but users are equipped with multiple antennas. In addition, we assume that the quadrature phase shift keying (QPSK) modulation is used for users. We mathematically analyze the bit error rate (BER) of both cell-edge users and cell-center users, which is the first theoretical result in the literature to the best of our knowledge. The mathematical analysis is validated through extensive link-level simulations. PMID:29439413

Modeling Emergence in Neuroprotective Regulatory Networks

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

Sanfilippo, Antonio P.; Haack, Jereme N.; McDermott, Jason E.

2013-01-05

The use of predictive modeling in the analysis of gene expression data can greatly accelerate the pace of scientific discovery in biomedical research by enabling in silico experimentation to test disease triggers and potential drug therapies. Techniques that focus on modeling emergence, such as agent-based modeling and multi-agent simulations, are of particular interest as they support the discovery of pathways that may have never been observed in the past. Thus far, these techniques have been primarily applied at the multi-cellular level, or have focused on signaling and metabolic networks. We present an approach where emergence modeling is extended to regulatorymore » networks and demonstrate its application to the discovery of neuroprotective pathways. An initial evaluation of the approach indicates that emergence modeling provides novel insights for the analysis of regulatory networks that can advance the discovery of acute treatments for stroke and other diseases.« less

Performance Analysis of Diversity-Controlled Multi-User Superposition Transmission for 5G Wireless Networks.

PubMed

Yeom, Jeong Seon; Chu, Eunmi; Jung, Bang Chul; Jin, Hu

2018-02-10

In this paper, we propose a novel low-complexity multi-user superposition transmission (MUST) technique for 5G downlink networks, which allows multiple cell-edge users to be multiplexed with a single cell-center user. We call the proposed technique diversity-controlled MUST technique since the cell-center user enjoys the frequency diversity effect via signal repetition over multiple orthogonal frequency division multiplexing (OFDM) sub-carriers. We assume that a base station is equipped with a single antenna but users are equipped with multiple antennas. In addition, we assume that the quadrature phase shift keying (QPSK) modulation is used for users. We mathematically analyze the bit error rate (BER) of both cell-edge users and cell-center users, which is the first theoretical result in the literature to the best of our knowledge. The mathematical analysis is validated through extensive link-level simulations.

Probabilistic performance-based design for high performance control systems

NASA Astrophysics Data System (ADS)

Micheli, Laura; Cao, Liang; Gong, Yongqiang; Cancelli, Alessandro; Laflamme, Simon; Alipour, Alice

2017-04-01

High performance control systems (HPCS) are advanced damping systems capable of high damping performance over a wide frequency bandwidth, ideal for mitigation of multi-hazards. They include active, semi-active, and hybrid damping systems. However, HPCS are more expensive than typical passive mitigation systems, rely on power and hardware (e.g., sensors, actuators) to operate, and require maintenance. In this paper, a life cycle cost analysis (LCA) approach is proposed to estimate the economic benefit these systems over the entire life of the structure. The novelty resides in the life cycle cost analysis in the performance based design (PBD) tailored to multi-level wind hazards. This yields a probabilistic performance-based design approach for HPCS. Numerical simulations are conducted on a building located in Boston, MA. LCA are conducted for passive control systems and HPCS, and the concept of controller robustness is demonstrated. Results highlight the promise of the proposed performance-based design procedure.

Integrating biophysical and socioeconomic information for prioritizing watersheds in a Kashmir Himalayan lake: a remote sensing and GIS approach.

PubMed

Badar, Bazigha; Romshoo, Shakil A; Khan, M A

2013-08-01

Dal Lake, a cradle of Kashmiri civilization has strong linkage with socioeconomics of the state of Jammu and Kashmir. During last few decades, anthropogenic pressures in Dal Lake Catchment have caused environmental deterioration impairing, inter-alia, sustained biotic communities and water quality. The present research was an integrated impact analysis of socioeconomic and biophysical processes at the watershed level on the current status of Dal Lake using multi-sensor and multi-temporal satellite data, simulation modelling together with field data verification. Thirteen watersheds (designated as 'W1-W13') were identified and investigated for land use/land cover change detection, quantification of erosion and sediment loads and socioeconomic analysis (total population, total households, literacy rate and economic development status). All the data for the respective watersheds was integrated into the GIS environment based upon multi-criteria analysis and knowledge-based weightage system was adopted for watershed prioritization based on its factors and after carefully observing the field situation. The land use/land cover change detection revealed significant changes with a uniform trend of decreased vegetation and increased impervious surface cover. Increased erosion and sediment loadings were recorded for the watersheds corresponding to their changing land systems, with bare and agriculture lands being the major contributors. The prioritization analysis revealed that W5 > W2 > W6 > W8 > W1 ranked highest in priority and W13 > W3 > W4 > W11 > W7 under medium priority. W12 > W9 > W10 belonged to low-priority category. The integration of the biophysical and the socioeconomic environment at the watershed level using modern geospatial tools would be of vital importance for the conservation and management strategies of Dal Lake ecosystem.

Metabolic Reconstruction of Setaria italica: A Systems Biology Approach for Integrating Tissue-Specific Omics and Pathway Analysis of Bioenergy Grasses.

PubMed

de Oliveira Dal'Molin, Cristiana G; Orellana, Camila; Gebbie, Leigh; Steen, Jennifer; Hodson, Mark P; Chrysanthopoulos, Panagiotis; Plan, Manuel R; McQualter, Richard; Palfreyman, Robin W; Nielsen, Lars K

2016-01-01

The urgent need for major gains in industrial crops productivity and in biofuel production from bioenergy grasses have reinforced attention on understanding C4 photosynthesis. Systems biology studies of C4 model plants may reveal important features of C4 metabolism. Here we chose foxtail millet (Setaria italica), as a C4 model plant and developed protocols to perform systems biology studies. As part of the systems approach, we have developed and used a genome-scale metabolic reconstruction in combination with the use of multi-omics technologies to gain more insights into the metabolism of S. italica. mRNA, protein, and metabolite abundances, were measured in mature and immature stem/leaf phytomers, and the multi-omics data were integrated into the metabolic reconstruction framework to capture key metabolic features in different developmental stages of the plant. RNA-Seq reads were mapped to the S. italica resulting for 83% coverage of the protein coding genes of S. italica. Besides revealing similarities and differences in central metabolism of mature and immature tissues, transcriptome analysis indicates significant gene expression of two malic enzyme isoforms (NADP- ME and NAD-ME). Although much greater expression levels of NADP-ME genes are observed and confirmed by the correspondent protein abundances in the samples, the expression of multiple genes combined to the significant abundance of metabolites that participates in C4 metabolism of NAD-ME and NADP-ME subtypes suggest that S. italica may use mixed decarboxylation modes of C4 photosynthetic pathways under different plant developmental stages. The overall analysis also indicates different levels of regulation in mature and immature tissues in carbon fixation, glycolysis, TCA cycle, amino acids, fatty acids, lignin, and cellulose syntheses. Altogether, the multi-omics analysis reveals different biological entities and their interrelation and regulation over plant development. With this study, we demonstrated that this systems approach is powerful enough to complement the functional metabolic annotation of bioenergy grasses.

Metabolic Reconstruction of Setaria italica: A Systems Biology Approach for Integrating Tissue-Specific Omics and Pathway Analysis of Bioenergy Grasses

PubMed Central

de Oliveira Dal'Molin, Cristiana G.; Orellana, Camila; Gebbie, Leigh; Steen, Jennifer; Hodson, Mark P.; Chrysanthopoulos, Panagiotis; Plan, Manuel R.; McQualter, Richard; Palfreyman, Robin W.; Nielsen, Lars K.

2016-01-01

The urgent need for major gains in industrial crops productivity and in biofuel production from bioenergy grasses have reinforced attention on understanding C4 photosynthesis. Systems biology studies of C4 model plants may reveal important features of C4 metabolism. Here we chose foxtail millet (Setaria italica), as a C4 model plant and developed protocols to perform systems biology studies. As part of the systems approach, we have developed and used a genome-scale metabolic reconstruction in combination with the use of multi-omics technologies to gain more insights into the metabolism of S. italica. mRNA, protein, and metabolite abundances, were measured in mature and immature stem/leaf phytomers, and the multi-omics data were integrated into the metabolic reconstruction framework to capture key metabolic features in different developmental stages of the plant. RNA-Seq reads were mapped to the S. italica resulting for 83% coverage of the protein coding genes of S. italica. Besides revealing similarities and differences in central metabolism of mature and immature tissues, transcriptome analysis indicates significant gene expression of two malic enzyme isoforms (NADP- ME and NAD-ME). Although much greater expression levels of NADP-ME genes are observed and confirmed by the correspondent protein abundances in the samples, the expression of multiple genes combined to the significant abundance of metabolites that participates in C4 metabolism of NAD-ME and NADP-ME subtypes suggest that S. italica may use mixed decarboxylation modes of C4 photosynthetic pathways under different plant developmental stages. The overall analysis also indicates different levels of regulation in mature and immature tissues in carbon fixation, glycolysis, TCA cycle, amino acids, fatty acids, lignin, and cellulose syntheses. Altogether, the multi-omics analysis reveals different biological entities and their interrelation and regulation over plant development. With this study, we demonstrated that this systems approach is powerful enough to complement the functional metabolic annotation of bioenergy grasses. PMID:27559337

Data Parallel Bin-Based Indexing for Answering Queries on Multi-Core Architectures

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

Gosink, Luke; Wu, Kesheng; Bethel, E. Wes

2009-06-02

The multi-core trend in CPUs and general purpose graphics processing units (GPUs) offers new opportunities for the database community. The increase of cores at exponential rates is likely to affect virtually every server and client in the coming decade, and presents database management systems with a huge, compelling disruption that will radically change how processing is done. This paper presents a new parallel indexing data structure for answering queries that takes full advantage of the increasing thread-level parallelism emerging in multi-core architectures. In our approach, our Data Parallel Bin-based Index Strategy (DP-BIS) first bins the base data, and then partitionsmore » and stores the values in each bin as a separate, bin-based data cluster. In answering a query, the procedures for examining the bin numbers and the bin-based data clusters offer the maximum possible level of concurrency; each record is evaluated by a single thread and all threads are processed simultaneously in parallel. We implement and demonstrate the effectiveness of DP-BIS on two multi-core architectures: a multi-core CPU and a GPU. The concurrency afforded by DP-BIS allows us to fully utilize the thread-level parallelism provided by each architecture--for example, our GPU-based DP-BIS implementation simultaneously evaluates over 12,000 records with an equivalent number of concurrently executing threads. In comparing DP-BIS's performance across these architectures, we show that the GPU-based DP-BIS implementation requires significantly less computation time to answer a query than the CPU-based implementation. We also demonstrate in our analysis that DP-BIS provides better overall performance than the commonly utilized CPU and GPU-based projection index. Finally, due to data encoding, we show that DP-BIS accesses significantly smaller amounts of data than index strategies that operate solely on a column's base data; this smaller data footprint is critical for parallel processors that possess limited memory resources (e.g., GPUs).« less

Coarse mesh and one-cell block inversion based diffusion synthetic acceleration

NASA Astrophysics Data System (ADS)

Kim, Kang-Seog

DSA (Diffusion Synthetic Acceleration) has been developed to accelerate the SN transport iteration. We have developed solution techniques for the diffusion equations of FLBLD (Fully Lumped Bilinear Discontinuous), SCB (Simple Comer Balance) and UCB (Upstream Corner Balance) modified 4-step DSA in x-y geometry. Our first multi-level method includes a block Gauss-Seidel iteration for the discontinuous diffusion equation, uses the continuous diffusion equation derived from the asymptotic analysis, and avoids void cell calculation. We implemented this multi-level procedure and performed model problem calculations. The results showed that the FLBLD, SCB and UCB modified 4-step DSA schemes with this multi-level technique are unconditionally stable and rapidly convergent. We suggested a simplified multi-level technique for FLBLD, SCB and UCB modified 4-step DSA. This new procedure does not include iterations on the diffusion calculation or the residual calculation. Fourier analysis results showed that this new procedure was as rapidly convergent as conventional modified 4-step DSA. We developed new DSA procedures coupled with 1-CI (Cell Block Inversion) transport which can be easily parallelized. We showed that 1-CI based DSA schemes preceded by SI (Source Iteration) are efficient and rapidly convergent for LD (Linear Discontinuous) and LLD (Lumped Linear Discontinuous) in slab geometry and for BLD (Bilinear Discontinuous) and FLBLD in x-y geometry. For 1-CI based DSA without SI in slab geometry, the results showed that this procedure is very efficient and effective for all cases. We also showed that 1-CI based DSA in x-y geometry was not effective for thin mesh spacings, but is effective and rapidly convergent for intermediate and thick mesh spacings. We demonstrated that the diffusion equation discretized on a coarse mesh could be employed to accelerate the transport equation. Our results showed that coarse mesh DSA is unconditionally stable and is as rapidly convergent as fine mesh DSA in slab geometry. For x-y geometry our coarse mesh DSA is very effective for thin and intermediate mesh spacings independent of the scattering ratio, but is not effective for purely scattering problems and high aspect ratio zoning. However, if the scattering ratio is less than about 0.95, this procedure is very effective for all mesh spacing.

Multi-class, multi-residue analysis of pesticides, polychlorinated biphenyls, polycyclic aromatic hydrocarbons, polybrominated diphenyl ethers and novel flame retardants....mass spectrometry

USDA-ARS?s Scientific Manuscript database

A multi-class, multi-residue method for the analysis of 13 novel flame retardants, 18 representative pesticides, 14 polychlorinated biphenyl (PCB) congeners, 16 polycyclic aromatic hydrocarbons (PAHs), and 7 polybrominated diphenyl ether (PBDE) congeners in catfish muscle was developed and evaluated...

Selecting Essential Information for Biosurveillance—A Multi-Criteria Decision Analysis

PubMed Central

Generous, Nicholas; Margevicius, Kristen J.; Taylor-McCabe, Kirsten J.; Brown, Mac; Daniel, W. Brent; Castro, Lauren; Hengartner, Andrea; Deshpande, Alina

2014-01-01

The National Strategy for Biosurveillancedefines biosurveillance as “the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better decision-making at all levels.” However, the strategy does not specify how “essential information” is to be identified and integrated into the current biosurveillance enterprise, or what the metrics qualify information as being “essential”. Thequestion of data stream identification and selection requires a structured methodology that can systematically evaluate the tradeoffs between the many criteria that need to be taken in account. Multi-Attribute Utility Theory, a type of multi-criteria decision analysis, can provide a well-defined, structured approach that can offer solutions to this problem. While the use of Multi-Attribute Utility Theoryas a practical method to apply formal scientific decision theoretical approaches to complex, multi-criteria problems has been demonstrated in a variety of fields, this method has never been applied to decision support in biosurveillance.We have developed a formalized decision support analytic framework that can facilitate identification of “essential information” for use in biosurveillance systems or processes and we offer this framework to the global BSV community as a tool for optimizing the BSV enterprise. To demonstrate utility, we applied the framework to the problem of evaluating data streams for use in an integrated global infectious disease surveillance system. PMID:24489748

Cryptanalysis of Chatterjee-Sarkar Hierarchical Identity-Based Encryption Scheme at PKC 06

NASA Astrophysics Data System (ADS)

Park, Jong Hwan; Lee, Dong Hoon

In 2006, Chatterjee and Sarkar proposed a hierarchical identity-based encryption (HIBE) scheme which can support an unbounded number of identity levels. This property is particularly useful in providing forward secrecy by embedding time components within hierarchical identities. In this paper we show that their scheme does not provide the claimed property. Our analysis shows that if the number of identity levels becomes larger than the value of a fixed public parameter, an unintended receiver can reconstruct a new valid ciphertext and decrypt the ciphertext using his or her own private key. The analysis is similarly applied to a multi-receiver identity-based encryption scheme presented as an application of Chatterjee and Sarkar's HIBE scheme.

Community influences on modern contraceptive use among young women in low and middle-income countries: a cross-sectional multi-country analysis.

PubMed

Mutumba, Massy; Wekesa, Eliud; Stephenson, Rob

2018-04-02

Despite investment in family planning programs and education, unmet need for family planning remains high among young women (aged 15-24) in low and middle-income countries, increasing the risk for unwanted pregnancies and adverse social and reproductive health outcomes. There is a dearth of cross-national research that identifies the differential impact of community level factors among youth in low and middle-income countries (LMICs), which is imperative for the design of structural level interventions aimed at increasing family planning use. Grounded in the socio-ecological framework, this paper utilizes Demographic and Health Survey (DHS) from 52 LMICs to examine the influence of community level reproductive, gender, fertility, literacy and economic indicators on modern contraceptive use among female youth. Analyses are conducted using multi-level logistic regressions with random community-level effects. Our findings highlight the positive influence of community level education attainment and negative influence of gender and fertility related norms on young women's contraceptive use. Additionally, increased exposure to mass media did not positively influence young women's uptake of modern contraceptive methods. Taken together, findings indicate that young women's contraceptive decision-making is greatly shaped by their social contexts. The commonalities and regional variations in community level influences provide support for both structural level interventions and tailored regional approaches to family planning interventions.

Application of the Rural Development Index to Analysis of Rural Regions in Poland and Slovakia

ERIC Educational Resources Information Center

Michalek, Jerzy; Zarnekow, Nana

2012-01-01

The main purpose of this research was to construct a multi-dimensional (composite) index measuring the overall level of rural development and quality of life in individual rural regions of a given EU country. In the Rural Development Index (RDI) the rural development domains are represented by hundreds of partial socio-economic, environmental,…

Ethnic Background and the Transition from Vocational Education to Work: A Multi-Level Analysis of the Differences in Labour Market Outcomes

ERIC Educational Resources Information Center

Brekke, Idunn

2007-01-01

This article focuses on the impact of ethnic background on employment and earnings among people with a vocational education in Norway. I differentiate between three different groups: majority, first-generation non-Westerners and second-generation non-Westerners. Panel data from several public register databases of the entire population of…

Flexible Coordination in Resource-Constrained Domains

DTIC Science & Technology

1994-07-01

Experiments (TIEs) with planning technologies developed at both BBN (FMERG) and SRI ( SOCAP ). We have also exported scheduling support capabilities provided by...SRI’s SOCAP course of action (COA) plan generator. "* Development and demonstration of distributed, multi-level deployment scheduling - Through analysis...scheduler was adapted for integration with the SOCAP planning system to provide feedback on transportation feasibility during generation of the

Measuring and Modeling Intercultural Attitudes among Adolescents across Europe: A Multi-Level, Multiple-Group Analysis Examining Student Attitudes, Intergroup Contact, and School Climate

ERIC Educational Resources Information Center

Higdon, Julia Dianne

2015-01-01

European nations, built on democratic foundations, rely on participation that is inclusive of all groups. Among efforts to support social cohesion in Europe, investigating the development of intercultural attitudes--attitudes toward others on the basis of their intersecting group memberships--is a crucial area of research. Further, examining…

Placement Decisions and Disparities among Aboriginal Groups: An Application of the Decision Making Ecology through Multi-Level Analysis

ERIC Educational Resources Information Center

Fluke, John D.; Chabot, Martin; Fallon, Barbara; MacLaurin, Bruce; Blackstock, Cindy

2010-01-01

Objective: This paper examined the relative influence of clinical and organizational characteristics on the decision to place a child in out-of-home care at the conclusion of a child maltreatment investigation. It tested the hypothesis that extraneous factors, specifically, organizational characteristics, impact the decision to place a child in…

Estimating Multi-Level Discrete-Time Hazard Models Using Cross-Sectional Data: Neighborhood Effects on the Onset of Adolescent Cigarette Use.

ERIC Educational Resources Information Center

Reardon, Sean F.; Brennan, Robert T.; Buka, Stephen L.

2002-01-01

Developed procedures for constructing a retrospective person-period data set from cross-sectional data and discusses modeling strategies for estimating multilevel discrete-time event history models. Applied the methods to the analysis of cigarette use by 1,979 urban adolescents. Results show the influence of the racial composition of the…

An Item-Level Psychometric Analysis of the Personality Assessment Inventory: Clinical Scales in a Psychiatric Inpatient Unit

ERIC Educational Resources Information Center

Siefert, Caleb J.; Sinclair, Samuel J.; Kehl-Fie, Kendra A.; Blais, Mark A.

2009-01-01

Multi-item multiscale self-report measures are increasingly used in inpatient assessments. When considering a measure for this setting, it is important to evaluate the psychometric properties of the clinical scales and items to ensure that they are functioning as intended in a highly distressed clinical population. The present study examines scale…

Personnel Resource Allocation Strategies in a Time of Fiscal Stress: A Gap Analysis of Five Southern California Elementary Schools

ERIC Educational Resources Information Center

Araya, Saba Q.

2013-01-01

As pressure increases to ensure that limited resources are utilized as effectively as possible, funding adequacy remains a priority for all California public schools. The research was conducted through a multi-methods approach of principal interviews, site level resource allocation data, and overall student achievement on state assessments. The…

Race/Ethnicity and the Start of Child Care: A Multi-Level Analysis of Factors Influencing First Child Care Experiences

ERIC Educational Resources Information Center

Fram, Maryah Stella; Kim, Jinseok

2008-01-01

Early childhood education and care experiences play an important role in children's development and school readiness with, in general, sustained exposure to high quality, center-based care leading to positive outcomes. Hispanic parents have been shown to be less likely than others to place their children in center-based care, particularly when…

Mapping healthcare systems: a policy relevant analytic tool

PubMed Central

Sekhri Feachem, Neelam; Afshar, Ariana; Pruett, Cristina; Avanceña, Anton L.V.

2017-01-01

Abstract Background In the past decade, an international consensus on the value of well-functioning systems has driven considerable health systems research. This research falls into two broad categories. The first provides conceptual frameworks that take complex healthcare systems and create simplified constructs of interactions and functions. The second focuses on granular inputs and outputs. This paper presents a novel translational mapping tool – the University of California, San Francisco mapping tool (the Tool) - which bridges the gap between these two areas of research, creating a platform for multi-country comparative analysis. Methods Using the Murray-Frenk framework, we create a macro-level representation of a country's structure, focusing on how it finances and delivers healthcare. The map visually depicts the fundamental policy questions in healthcare system design: funding sources and amount spent through each source, purchasers, populations covered, provider categories; and the relationship between these entities. Results We use the Tool to provide a macro-level comparative analysis of the structure of India's and Thailand's healthcare systems. Conclusions As part of the systems strengthening arsenal, the Tool can stimulate debate about the merits and consequences of different healthcare systems structural designs, using a common framework that fosters multi-country comparative analyses. PMID:28541518

A multi-level qualitative analysis of Telehomecare in Ontario: challenges and opportunities.

PubMed

Hunting, Gemma; Shahid, Nida; Sahakyan, Yeva; Fan, Iris; Moneypenny, Crystal R; Stanimirovic, Aleksandra; North, Taylor; Petrosyan, Yelena; Krahn, Murray D; Rac, Valeria E

2015-12-09

Despite research demonstrating the potential effectiveness of Telehomecare for people with Chronic Obstructive Pulmonary Disease and Heart Failure, broad-scale comprehensive evaluations are lacking. This article discusses the qualitative component of a mixed-method program evaluation of Telehomecare in Ontario, Canada. The objective of the qualitative component was to explore the multi-level factors and processes which facilitate or impede the implementation and adoption of the program across three regions where it was first implemented. The study employs a multi-level framework as a conceptual guide to explore the facilitators and barriers to Telehomecare implementation and adoption across five levels: technology, patients, providers, organizations, and structures. In-depth semi-structured interviews and ethnographic observations with program stakeholders, as well as a Telehomecare document review were used to elicit key themes. Study participants (n = 89) included patients and/or informal caregivers (n = 39), health care providers (n = 23), technicians (n = 2), administrators (n = 12), and decision makers (n = 13) across three different Local Health Integration Networks in Ontario. Key facilitators to Telehomecare implementation and adoption at each level of the multi-level framework included: user-friendliness of Telehomecare technology, patient motivation to participate in the program, support for Telehomecare providers, the integration of Telehomecare into broader health service provision, and comprehensive program evaluation. Key barriers included: access-related issues to using the technology, patient language (if not English or French), Telehomecare provider time limitations, gaps in health care provision for patients, and structural barriers to patient participation related to geography and social location. Though Telehomecare has the potential to positively impact patient lives and strengthen models of health care provision, a number of key challenges remain. As such, further implementation and expansion of Telehomecare must involve continuous assessments of what is working and not working with all stakeholders. Increased dialogue, evaluation, and knowledge translation within and across regions to understand the contextual factors influencing Telehomecare implementation and adoption is required. This can inform decision-making that better reflects and addresses the needs of all program stakeholders.

A Multi-Level Decision Fusion Strategy for Condition Based Maintenance of Composite Structures

PubMed Central

Sharif Khodaei, Zahra; Aliabadi, M.H.

2016-01-01

In this work, a multi-level decision fusion strategy is proposed which weighs the Value of Information (VoI) against the intended functions of a Structural Health Monitoring (SHM) system. This paper presents a multi-level approach for three different maintenance strategies in which the performance of the SHM systems is evaluated against its intended functions. Level 1 diagnosis results in damage existence with minimum sensors covering a large area by finding the maximum energy difference for the guided waves propagating in pristine structure and the post-impact state; Level 2 diagnosis provides damage detection and approximate localization using an approach based on Electro-Mechanical Impedance (EMI) measures, while Level 3 characterizes damage (exact location and size) in addition to its detection by utilising a Weighted Energy Arrival Method (WEAM). The proposed multi-level strategy is verified and validated experimentally by detection of Barely Visible Impact Damage (BVID) on a curved composite fuselage panel. PMID:28773910

An Integrated Systems Genetics and Omics Toolkit to Probe Gene Function.

PubMed

Li, Hao; Wang, Xu; Rukina, Daria; Huang, Qingyao; Lin, Tao; Sorrentino, Vincenzo; Zhang, Hongbo; Bou Sleiman, Maroun; Arends, Danny; McDaid, Aaron; Luan, Peiling; Ziari, Naveed; Velázquez-Villegas, Laura A; Gariani, Karim; Kutalik, Zoltan; Schoonjans, Kristina; Radcliffe, Richard A; Prins, Pjotr; Morgenthaler, Stephan; Williams, Robert W; Auwerx, Johan

2018-01-24

Identifying genetic and environmental factors that impact complex traits and common diseases is a high biomedical priority. Here, we developed, validated, and implemented a series of multi-layered systems approaches, including (expression-based) phenome-wide association, transcriptome-/proteome-wide association, and (reverse-) mediation analysis, in an open-access web server (systems-genetics.org) to expedite the systems dissection of gene function. We applied these approaches to multi-omics datasets from the BXD mouse genetic reference population, and identified and validated associations between genes and clinical and molecular phenotypes, including previously unreported links between Rpl26 and body weight, and Cpt1a and lipid metabolism. Furthermore, through mediation and reverse-mediation analysis we established regulatory relations between genes, such as the co-regulation of BCKDHA and BCKDHB protein levels, and identified targets of transcription factors E2F6, ZFP277, and ZKSCAN1. Our multifaceted toolkit enabled the identification of gene-gene and gene-phenotype links that are robust and that translate well across populations and species, and can be universally applied to any populations with multi-omics datasets. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

The experimental study of the effect of microwave on the physical properties of multi-walled carbon nanotubes

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

Haque, A.K.M. Mahmudul; Oh, Geum Seok; Kim, Taeoh

Highlights: • We study the microwave effect on the multi-walled carbon nanotubes (MWCNTs). • We examine the non uniform heating effect on the physical structure of MWCNTs. • We examine the purification of MWCNTs by microwave. • We analyze the thermal characteristics of microwave treated MWCNTs. - Abstract: This paper reports the effect of microwave on the physical properties of multi-walled carbon nanotubes (MWCNTs) where different power levels of microwave were applied on MWCNTs in order to apprehend the effect of microwave on MWCNTs distinctly. A low energy ball milling in aqueous circumstance was also applied on both MWCNTs andmore » microwave treated MWCNTs. Temperature profile, morphological analysis by field emission scanning electron microscopy (FESEM), defect analysis by Raman spectroscopy, thermal conductivity, thermal diffusivity as well as heat transfer coefficient enhancement ratio were studied which expose some strong witnesses of the effect of microwave on the both purification and dispersion properties of MWCNTs in base fluid distilled water. The highest thermal conductivity enhancement (6.06% at 40 °C) of MWCNTs based nanofluid is achieved by five minutes microwave treatment as well as wet grinding at 500 rpm for two hours.« less

Performance implications from sizing a VM on multi-core systems: A Data analytic application s view

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

Lim, Seung-Hwan; Horey, James L; Begoli, Edmon

In this paper, we present a quantitative performance analysis of data analytics applications running on multi-core virtual machines. Such environments form the core of cloud computing. In addition, data analytics applications, such as Cassandra and Hadoop, are becoming increasingly popular on cloud computing platforms. This convergence necessitates a better understanding of the performance and cost implications of such hybrid systems. For example, the very rst step in hosting applications in virtualized environments, requires the user to con gure the number of virtual processors and the size of memory. To understand performance implications of this step, we benchmarked three Yahoo Cloudmore » Serving Benchmark (YCSB) workloads in a virtualized multi-core environment. Our measurements indicate that the performance of Cassandra for YCSB workloads does not heavily depend on the processing capacity of a system, while the size of the data set is critical to performance relative to allocated memory. We also identi ed a strong relationship between the running time of workloads and various hardware events (last level cache loads, misses, and CPU migrations). From this analysis, we provide several suggestions to improve the performance of data analytics applications running on cloud computing environments.« less

Analysis of pharmaceutical impurities using multi-heartcutting 2D LC coupled with UV-charged aerosol MS detection.

PubMed

Zhang, Kelly; Li, Yi; Tsang, Midco; Chetwyn, Nik P

2013-09-01

To overcome challenges in HPLC impurity analysis of pharmaceuticals, we developed an automated online multi-heartcutting 2D HPLC system with hyphenated UV-charged aerosol MS detection. The first dimension has a primary column and the second dimension has six orthogonal columns to enhance flexibility and selectivity. The two dimensions were interfaced by a pair of switching valves equipped with six trapping loops that allow multi-heartcutting of peaks of interest in the first dimension and also allow "peak parking." The hyphenated UV-charged aerosol MS detection provides comprehensive detection for compounds with and without UV chromophores, organics, and inorganics. It also provides structural information for impurity identification. A hidden degradation product that co-eluted with the drug main peak was revealed by RP × RP separation and thus enabled the stability-indicating method development. A poorly retained polar component with no UV chromophores was analyzed by RP × hydrophilic interaction liquid chromatography separation with charged aerosol detection. Furthermore, using this system, the structures of low-level impurities separated by a method using nonvolatile phosphate buffer were identified and tracked by MS in the second dimension. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Licit prescription drug use in a Swedish population according to age, gender and socioeconomic status after adjusting for level of multi-morbidity

PubMed Central

2012-01-01

Background There is a great variability in licit prescription drug use in the population and among patients. Factors other than purely medical ones have proven to be of importance for the prescribing of licit drugs. For example, individuals with a high age, female gender and low socioeconomic status are more likely to use licit prescription drugs. However, these results have not been adjusted for multi-morbidity level. In this study we investigate the odds of using licit prescription drugs among individuals in the population and the rate of licit prescription drug use among patients depending on gender, age and socioeconomic status after adjustment for multi-morbidity level. Methods The study was carried out on the total population aged 20 years or older in Östergötland county with about 400 000 inhabitants in year 2006. The Johns Hopkins ACG Case-mix was used as a proxy for the individual level of multi-morbidity in the population to which we have related the odds ratio for individuals and incidence rate ratio (IRR) for patients of using licit prescription drugs, defined daily doses (DDDs) and total costs of licit prescription drugs after adjusting for age, gender and socioeconomic factors (educational and income level). Results After adjustment for multi-morbidity level male individuals had less than half the odds of using licit prescription drugs (OR 0.41 (95% CI 0.40-0.42)) compared to female individuals. Among the patients, males had higher total costs (IRR 1.14 (95% CI 1.13-1.15)). Individuals above 80 years had nine times the odds of using licit prescription drugs (OR 9.09 (95% CI 8.33-10.00)) despite adjustment for multi-morbidity. Patients in the highest education and income level had the lowest DDDs (IRR 0.78 (95% CI 0.76-0.80), IRR 0.73 (95% CI 0.71-0.74)) after adjustment for multi-morbidity level. Conclusions This paper shows that there is a great variability in licit prescription drug use associated with gender, age and socioeconomic status, which is not dependent on level of multi-morbidity. PMID:22846625

Integrative Analysis of Longitudinal Metabolomics Data from a Personal Multi-Omics Profile

PubMed Central

Stanberry, Larissa; Mias, George I.; Haynes, Winston; Higdon, Roger; Snyder, Michael; Kolker, Eugene

2013-01-01

The integrative personal omics profile (iPOP) is a pioneering study that combines genomics, transcriptomics, proteomics, metabolomics and autoantibody profiles from a single individual over a 14-month period. The observation period includes two episodes of viral infection: a human rhinovirus and a respiratory syncytial virus. The profile studies give an informative snapshot into the biological functioning of an organism. We hypothesize that pathway expression levels are associated with disease status. To test this hypothesis, we use biological pathways to integrate metabolomics and proteomics iPOP data. The approach computes the pathways’ differential expression levels at each time point, while taking into account the pathway structure and the longitudinal design. The resulting pathway levels show strong association with the disease status. Further, we identify temporal patterns in metabolite expression levels. The changes in metabolite expression levels also appear to be consistent with the disease status. The results of the integrative analysis suggest that changes in biological pathways may be used to predict and monitor the disease. The iPOP experimental design, data acquisition and analysis issues are discussed within the broader context of personal profiling. PMID:24958148

Results from new multi-megabar shockless compression experiments at the Z machine

DOE PAGES

Davis, Jean-Paul; Knudson, Marcus D.; Brown, Justin L.

2017-01-01

Sandia’s Z Machine has been used to magnetically drive shockless compression of materials in a planar configuration to multi-megabar pressure levels, allowing accurate measurements of quasi-isentropic mechanical response at relatively low temperatures in the solid phase. This work details recent improvements to design and analysis of such experiments, including the use of new data on the mechanical and optical response of lithium fluoride windows. Comparison of windowed and free-surface data on copper to 350 GPa lends confidence to the window correction method. Preliminary results are presented on gold to 500 GPa and platinum to 450 GPa; both appear stiffer thanmore » existing models.« less

Bayesian Multi-Trait Analysis Reveals a Useful Tool to Increase Oil Concentration and to Decrease Toxicity in Jatropha curcas L.

PubMed Central

Silva Junqueira, Vinícius; de Azevedo Peixoto, Leonardo; Galvêas Laviola, Bruno; Lopes Bhering, Leonardo; Mendonça, Simone; Agostini Costa, Tania da Silveira; Antoniassi, Rosemar

2016-01-01

The biggest challenge for jatropha breeding is to identify superior genotypes that present high seed yield and seed oil content with reduced toxicity levels. Therefore, the objective of this study was to estimate genetic parameters for three important traits (weight of 100 seed, oil seed content, and phorbol ester concentration), and to select superior genotypes to be used as progenitors in jatropha breeding. Additionally, the genotypic values and the genetic parameters estimated under the Bayesian multi-trait approach were used to evaluate different selection indices scenarios of 179 half-sib families. Three different scenarios and economic weights were considered. It was possible to simultaneously reduce toxicity and increase seed oil content and weight of 100 seed by using index selection based on genotypic value estimated by the Bayesian multi-trait approach. Indeed, we identified two families that present these characteristics by evaluating genetic diversity using the Ward clustering method, which suggested nine homogenous clusters. Future researches must integrate the Bayesian multi-trait methods with realized relationship matrix, aiming to build accurate selection indices models. PMID:27281340

Data-driven train set crash dynamics simulation

NASA Astrophysics Data System (ADS)

Tang, Zhao; Zhu, Yunrui; Nie, Yinyu; Guo, Shihui; Liu, Fengjia; Chang, Jian; Zhang, Jianjun

2017-02-01

Traditional finite element (FE) methods are arguably expensive in computation/simulation of the train crash. High computational cost limits their direct applications in investigating dynamic behaviours of an entire train set for crashworthiness design and structural optimisation. On the contrary, multi-body modelling is widely used because of its low computational cost with the trade-off in accuracy. In this study, a data-driven train crash modelling method is proposed to improve the performance of a multi-body dynamics simulation of train set crash without increasing the computational burden. This is achieved by the parallel random forest algorithm, which is a machine learning approach that extracts useful patterns of force-displacement curves and predicts a force-displacement relation in a given collision condition from a collection of offline FE simulation data on various collision conditions, namely different crash velocities in our analysis. Using the FE simulation results as a benchmark, we compared our method with traditional multi-body modelling methods and the result shows that our data-driven method improves the accuracy over traditional multi-body models in train crash simulation and runs at the same level of efficiency.

Chemiluminometric determination of phenothiazines by means of a combined multi-commutated/multi-pumped flow assembly.

PubMed

Halaburda, P; Mateo, J V García

2012-07-15

A rapid, sensitive and fully automated chemiluminometric method is described for determination of five phenothiazine derivatives, namely, trifluoperazine, fluphenazine, perphenazine, thioridazine and chlorpromazine. The method is based on the chemiluminescence (CL) induced by the oxidation of drugs with Ce(IV) in nitric acid. A flow manifold based on the association of multi-commutation and multi-pumping flow methodologies is proposed. The active operated solenoid devices consisted of a micro-pump (propelling 50μL per stroke) and a six ports solenoid valve. Reconfiguration of the flow manifold was performed by using software settings, without physical alteration of the instrument manifold. It permits the design of flexible miniaturized networks for flow analysis based on a time-pulse-counting strategy. The proposed method allows the determination of the drugs at the ngmL(-1) level with a sample throughput of 38h(-1) (chlorpromazine) and 40h(-1) (trifluoperazine, fluphenazine, perphenazine, and thioridazine). The method was successfully applied to the determination of the phenothiazine derivatives in pharmaceuticals formulations. Copyright © 2012 Elsevier B.V. All rights reserved.

Salient contour extraction from complex natural scene in night vision image

NASA Astrophysics Data System (ADS)

Han, Jing; Yue, Jiang; Zhang, Yi; Bai, Lian-fa

2014-03-01

The theory of center-surround interaction in non-classical receptive field can be applied in night vision information processing. In this work, an optimized compound receptive field modulation method is proposed to extract salient contour from complex natural scene in low-light-level (LLL) and infrared images. The kernel idea is that multi-feature analysis can recognize the inhomogeneity in modulatory coverage more accurately and that center and surround with the grouping structure satisfying Gestalt rule deserves high connection-probability. Computationally, a multi-feature contrast weighted inhibition model is presented to suppress background and lower mutual inhibition among contour elements; a fuzzy connection facilitation model is proposed to achieve the enhancement of contour response, the connection of discontinuous contour and the further elimination of randomly distributed noise and texture; a multi-scale iterative attention method is designed to accomplish dynamic modulation process and extract contours of targets in multi-size. This work provides a series of biologically motivated computational visual models with high-performance for contour detection from cluttered scene in night vision images.

Agreement Among Dental Students, Peer Assessors, and Tutor in Assessing Students' Competence in Preclinical Skills.

PubMed

Foley, Jennifer I; Richardson, Gillian L; Drummie, Joyce

2015-11-01

The aim of this study was to determine the level of agreement regarding assessments of competence among dental students, their student peers, and their clinical skills tutors in a preclinical skills program. In 2012-13 at the University of Edinburgh, second-year dental students learned to perform the following seven cavity preparations/restorations on primary and permanent Frasaco teeth: single-surface adhesive occlusal cavity; single-surface adhesive interproximal cavity; single-surface adhesive labial cavity; multi-surface adhesive cavity; multi-surface amalgam cavity; pre-formed metal crown preparation; and composite resin buildup of a fractured maxillary central incisor tooth. Each student, a randomly allocated student peer, and the clinical skills tutor used standardized descriptors to assign a competency grade to all the students' preparations/restorations. The grades were analyzed by chi-square analysis. Data were available for all 59 second-year students in the program. The results showed that both the students and their peers overestimated the students' competence compared to the tutor at the following levels: single-surface adhesive occlusal cavity (χ(2)=10.63, p=0.005); single-surface adhesive interproximal cavity (χ(2)=11.40, p=0.003); single-surface labial cavity (χ(2)=23.70, p=0.001); multi-surface adhesive cavity (χ(2)=12.56, p=0.002); multi-surface amalgam cavity (χ(2)=38.85, p=0.001); pre-formed metal crown preparation (χ(2)=40.41, p=0.001); and composite resin buildup (χ(2)=57.31, p=0.001). As expected, the lowest levels of agreement occurred on the most complicated procedures. These findings support the need for additional ways to help students better self-assess their work.

The Control Based on Internal Average Kinetic Energy in Complex Environment for Multi-robot System

NASA Astrophysics Data System (ADS)

Yang, Mao; Tian, Yantao; Yin, Xianghua

In this paper, reference trajectory is designed according to minimum energy consumed for multi-robot system, which nonlinear programming and cubic spline interpolation are adopted. The control strategy is composed of two levels, which lower-level is simple PD control and the upper-level is based on the internal average kinetic energy for multi-robot system in the complex environment with velocity damping. Simulation tests verify the effectiveness of this control strategy.

MultiMetEval: Comparative and Multi-Objective Analysis of Genome-Scale Metabolic Models

PubMed Central

Gevorgyan, Albert; Kierzek, Andrzej M.; Breitling, Rainer; Takano, Eriko

2012-01-01

Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the context of multiple cellular objectives. Here, we present the user-friendly software framework Multi-Metabolic Evaluator (MultiMetEval), built upon SurreyFBA, which allows the user to compose collections of metabolic models that together can be subjected to flux balance analysis. Additionally, MultiMetEval implements functionalities for multi-objective analysis by calculating the Pareto front between two cellular objectives. Using a previously generated dataset of 38 actinobacterial genome-scale metabolic models, we show how these approaches can lead to exciting novel insights. Firstly, after incorporating several pathways for the biosynthesis of natural products into each of these models, comparative flux balance analysis predicted that species like Streptomyces that harbour the highest diversity of secondary metabolite biosynthetic gene clusters in their genomes do not necessarily have the metabolic network topology most suitable for compound overproduction. Secondly, multi-objective analysis of biomass production and natural product biosynthesis in these actinobacteria shows that the well-studied occurrence of discrete metabolic switches during the change of cellular objectives is inherent to their metabolic network architecture. Comparative and multi-objective modelling can lead to insights that could not be obtained by normal flux balance analyses. MultiMetEval provides a powerful platform that makes these analyses straightforward for biologists. Sources and binaries of MultiMetEval are freely available from https://github.com/PiotrZakrzewski/MetEval/downloads. PMID:23272111

Web-based multi-channel analyzer

DOEpatents

Gritzo, Russ E.

2003-12-23

The present invention provides an improved multi-channel analyzer designed to conveniently gather, process, and distribute spectrographic pulse data. The multi-channel analyzer may operate on a computer system having memory, a processor, and the capability to connect to a network and to receive digitized spectrographic pulses. The multi-channel analyzer may have a software module integrated with a general-purpose operating system that may receive digitized spectrographic pulses for at least 10,000 pulses per second. The multi-channel analyzer may further have a user-level software module that may receive user-specified controls dictating the operation of the multi-channel analyzer, making the multi-channel analyzer customizable by the end-user. The user-level software may further categorize and conveniently distribute spectrographic pulse data employing non-proprietary, standard communication protocols and formats.

Exploring the impact of different multi-level measures of physician communities in patient-centric care networks on healthcare outcomes: A multi-level regression approach.

PubMed

Uddin, Shahadat

2016-02-04

A patient-centric care network can be defined as a network among a group of healthcare professionals who provide treatments to common patients. Various multi-level attributes of the members of this network have substantial influence to its perceived level of performance. In order to assess the impact different multi-level attributes of patient-centric care networks on healthcare outcomes, this study first captured patient-centric care networks for 85 hospitals using health insurance claim dataset. From these networks, this study then constructed physician collaboration networks based on the concept of patient-sharing network among physicians. A multi-level regression model was then developed to explore the impact of different attributes that are organised at two levels on hospitalisation cost and hospital length of stay. For Level-1 model, the average visit per physician significantly predicted both hospitalisation cost and hospital length of stay. The number of different physicians significantly predicted only the hospitalisation cost, which has significantly been moderated by age, gender and Comorbidity score of patients. All Level-1 findings showed significance variance across physician collaboration networks having different community structure and density. These findings could be utilised as a reflective measure by healthcare decision makers. Moreover, healthcare managers could consider them in developing effective healthcare environments.

Estimation and analysis of the short-term variations of multi-GNSS receiver differential code biases using global ionosphere maps

NASA Astrophysics Data System (ADS)

Li, Min; Yuan, Yunbin; Wang, Ningbo; Liu, Teng; Chen, Yongchang

2017-12-01

Care should be taken to minimize the adverse impact of differential code biases (DCBs) on global navigation satellite systems (GNSS)-derived ionospheric information determinations. For the sake of convenience, satellite and receiver DCB products provided by the International GNSS Service (IGS) are treated as constants over a period of 24 h (Li et al. (2014)). However, if DCB estimates show remarkable intra-day variability, the DCBs estimated as constants over 1-day period will partially account for ionospheric modeling error; in this case DCBs will be required to be estimated over shorter time period. Therefore, it is important to further gain insight into the short-term variation characteristics of receiver DCBs. In this contribution, the IGS combined global ionospheric maps and the German Aerospace Center (DLR)-provided satellite DCBs are used in the improved method to determine the multi-GNSS receiver DCBs with an hourly time resolution. The intra-day stability of the receiver DCBs is thereby analyzed in detail. Based on 1 month of data collected within the multi-GNSS experiment of the IGS, a good agreement within the receiver DCBs is found between the resulting receiver DCB estimates and multi-GNSS DCB products from the DLR at a level of 0.24 ns for GPS, 0.28 ns for GLONASS, 0.28 ns for BDS, and 0.30 ns for Galileo. Although most of the receiver DCBs are relatively stable over a 1-day period, large fluctuations (more than 9 ns between two consecutive hours) within the receiver DCBs can be found. We also demonstrate the impact of the significant short-term variations in receiver DCBs on the extraction of ionospheric total electron content (TEC), at a level of 12.96 TECu (TEC unit). Compared to daily receiver DCB estimates, the hourly DCB estimates obtained from this study can reflect the short-term variations of the DCB estimates more dedicatedly. The main conclusion is that preliminary analysis of characteristics of receiver DCB variations over short-term intervals should be finished prior to estimate daily multi-GNSS receiver DCB products.

Validation of a multi-criteria evaluation model for animal welfare.

PubMed

Martín, P; Czycholl, I; Buxadé, C; Krieter, J

2017-04-01

The aim of this paper was to validate an alternative multi-criteria evaluation system to assess animal welfare on farms based on the Welfare Quality® (WQ) project, using an example of welfare assessment of growing pigs. This alternative methodology aimed to be more transparent for stakeholders and more flexible than the methodology proposed by WQ. The WQ assessment protocol for growing pigs was implemented to collect data in different farms in Schleswig-Holstein, Germany. In total, 44 observations were carried out. The aggregation system proposed in the WQ protocol follows a three-step aggregation process. Measures are aggregated into criteria, criteria into principles and principles into an overall assessment. This study focussed on the first two steps of the aggregation. Multi-attribute utility theory (MAUT) was used to produce a value of welfare for each criterion and principle. The utility functions and the aggregation function were constructed in two separated steps. The MACBETH (Measuring Attractiveness by a Categorical-Based Evaluation Technique) method was used for utility function determination and the Choquet integral (CI) was used as an aggregation operator. The WQ decision-makers' preferences were fitted in order to construct the utility functions and to determine the CI parameters. The validation of the MAUT model was divided into two steps, first, the results of the model were compared with the results of the WQ project at criteria and principle level, and second, a sensitivity analysis of our model was carried out to demonstrate the relative importance of welfare measures in the different steps of the multi-criteria aggregation process. Using the MAUT, similar results were obtained to those obtained when applying the WQ protocol aggregation methods, both at criteria and principle level. Thus, this model could be implemented to produce an overall assessment of animal welfare in the context of the WQ protocol for growing pigs. Furthermore, this methodology could also be used as a framework in order to produce an overall assessment of welfare for other livestock species. Two main findings are obtained from the sensitivity analysis, first, a limited number of measures had a strong influence on improving or worsening the level of welfare at criteria level and second, the MAUT model was not very sensitive to an improvement in or a worsening of single welfare measures at principle level. The use of weighted sums and the conversion of disease measures into ordinal scores should be reconsidered.

Performance Evaluation of Fusing Protected Fingerprint Minutiae Templates on the Decision Level

PubMed Central

Yang, Bian; Busch, Christoph; de Groot, Koen; Xu, Haiyun; Veldhuis, Raymond N. J.

2012-01-01

In a biometric authentication system using protected templates, a pseudonymous identifier is the part of a protected template that can be directly compared. Each compared pair of pseudonymous identifiers results in a decision testing whether both identifiers are derived from the same biometric characteristic. Compared to an unprotected system, most existing biometric template protection methods cause to a certain extent degradation in biometric performance. Fusion is therefore a promising way to enhance the biometric performance in template-protected biometric systems. Compared to feature level fusion and score level fusion, decision level fusion has not only the least fusion complexity, but also the maximum interoperability across different biometric features, template protection and recognition algorithms, templates formats, and comparison score rules. However, performance improvement via decision level fusion is not obvious. It is influenced by both the dependency and the performance gap among the conducted tests for fusion. We investigate in this paper several fusion scenarios (multi-sample, multi-instance, multi-sensor, multi-algorithm, and their combinations) on the binary decision level, and evaluate their biometric performance and fusion efficiency on a multi-sensor fingerprint database with 71,994 samples. PMID:22778583

The clinical and cost-benefits of investing in neurobehavioural rehabilitation: a multi-centre study.

PubMed

Oddy, Michael; da Silva Ramos, Sara

2013-01-01

The aim of this study was to investigate the cost-benefits of a residential post-acute neurobehavioural rehabilitation programme and its effects on care needs and social participation of adults with acquired brain injury. Retrospective multi-centre design. Data on occupation, adaptability and level of support required were collected at admission, discharge and 6-months follow-up. Cost analysis was performed on cost estimates based on level of support. Significant gains were observed in all areas of functioning, with individuals progressing towards higher levels of independence and more participation in society upon discharge. Cost-benefits of up to £1.13 million were demonstrated for individuals admitted to rehabilitation within a year of sustaining a brain injury and of up to £0.86 million for those admitted more than 1 year after injury. Functional gains and reductions in levels of care required upon discharge were maintained 6 months later. These results demonstrate that post-acute neurobehavioural rehabilitation can have a positive impact on the lives of individuals with brain injury and that the associated costs are off-set by significant savings in the longer-term.

The clinical and cost-benefits of investing in neurobehavioural rehabilitation: A multi-centre study

PubMed Central

Oddy, Michael

2013-01-01

Primary objective The aim of this study was to investigate the cost-benefits of a residential post-acute neurobehavioural rehabilitation programme and its effects on care needs and social participation of adults with acquired brain injury. Research design Retrospective multi-centre design. Methods and procedures Data on occupation, adaptability and level of support required were collected at admission, discharge and 6-months follow-up. Cost analysis was performed on cost estimates based on level of support. Main outcomes and results Significant gains were observed in all areas of functioning, with individuals progressing towards higher levels of independence and more participation in society upon discharge. Conclusions Cost-benefits of up to £1.13 million were demonstrated for individuals admitted to rehabilitation within a year of sustaining a brain injury and of up to £0.86 million for those admitted more than 1 year after injury. Functional gains and reductions in levels of care required upon discharge were maintained 6 months later. These results demonstrate that post-acute neurobehavioural rehabilitation can have a positive impact on the lives of individuals with brain injury and that the associated costs are off-set by significant savings in the longer-term. PMID:24087973

Characterizing dilute combustion instabilities in a multi-cylinder spark-ignited engine using symbolic analysis

DOE PAGES

Daw, C. Stuart; Finney, Charles E. A.; Kaul, Brian C.; ...

2014-12-29

Spark-ignited internal combustion engines have evolved considerably in recent years in response to increasingly stringent regulations for emissions and fuel-economy. One new advanced engine strategy utilizes high levels of exhaust gas recirculation (EGR) to reduce combustion temperatures, thereby increasing thermodynamic efficiency and reducing nitrogen oxide emissions. While this strategy can be highly effective, it also poses major control and design challenges due to the large combustion oscillations that develop at sufficiently high EGR levels. Previous research has documented that combustion instabilities can propagate between successive engine cycles in individual cylinders via self-generated feedback of reactive species and thermal energy inmore » the retained residual exhaust gases. In this work, we use symbolic analysis to characterize multi-cylinder combustion oscillations in an experimental engine operating with external EGR. At low levels of EGR, intra-cylinder oscillations are clearly visible and appear to be associated with brief, intermittent coupling among cylinders. As EGR is increased further, a point is reached where all four cylinders lock almost completely in phase and alternate simultaneously between two distinct bi-stable combustion states. From a practical perspective, it is important to understand the causes of this phenomenon and develop diagnostics that might be applied to ameliorate its effects. We demonstrate here that two approaches for symbolizing the engine combustion measurements can provide useful probes for characterizing these instabilities.« less

Salt stress induced lipid accumulation in heterotrophic culture cells of Chlorella protothecoides: Mechanisms based on the multi-level analysis of oxidative response, key enzyme activity and biochemical alteration.

PubMed

Wang, Tao; Ge, Haiyan; Liu, Tingting; Tian, Xiwei; Wang, Zejian; Guo, Meijin; Chu, Ju; Zhuang, Yingping

2016-06-20

Salt stress as an effective stress factor that could improve the lipid content and lipid yield of glucose in the heterotrophic culture cells of Chlorella protothecoides was demonstrated in this study. The highest lipid content of 41.2% and lipid yield of 185.8mg/g were obtained when C. protothecoides was stressed under 30g/L NaCl condition at its late logarithmic growth phase. Moreover, the effects of salt and osmotic stress on lipid accumulation were comparatively analyzed, and it was found that the effects of NaCl and KCl stress had no significant differences at the same osmolarity level of 1150mOsm/kg with lipid contents of 41.7 and 40.8% as well as lipid yields of 192.9 and 186.8mg/g, respectively, whereas these results were obviously higher than those obtained under the iso-osmotic glycerol and sorbitol stresses. Furthermore, basing on the multi-level analysis of oxidative response, key enzyme activity and biochemical alteration, the superior performance of salt stress driving lipid over-synthesis was probably ascribed to the more ROS production as a result of additional ion effect besides the osmotic effect, subsequently mediating the alteration from carbohydrate storage to lipid accumulation in signal transduction process of C. protothecoides. Copyright © 2016. Published by Elsevier B.V.

Multi-level Hierarchical Poly Tree computer architectures

NASA Technical Reports Server (NTRS)

Padovan, Joe; Gute, Doug

1990-01-01

Based on the concept of hierarchical substructuring, this paper develops an optimal multi-level Hierarchical Poly Tree (HPT) parallel computer architecture scheme which is applicable to the solution of finite element and difference simulations. Emphasis is given to minimizing computational effort, in-core/out-of-core memory requirements, and the data transfer between processors. In addition, a simplified communications network that reduces the number of I/O channels between processors is presented. HPT configurations that yield optimal superlinearities are also demonstrated. Moreover, to generalize the scope of applicability, special attention is given to developing: (1) multi-level reduction trees which provide an orderly/optimal procedure by which model densification/simplification can be achieved, as well as (2) methodologies enabling processor grading that yields architectures with varying types of multi-level granularity.

Towards multi-level biomonitoring of nematodes to assess risk of nitrogen and phosphorus pollution in Jinchuan Wetland of Northeast China.

PubMed

Wang, Yunbiao; Qiao, Jie; He, Chunguang; Wang, Zhongqiang; Luo, Wenbo; Sheng, Lianxi

2015-12-01

Cultivation for agricultural production often poses threats to nearby wetlands ecosystems in fertile landscapes. In this study, nematode ecological indexes were assessed through the main soil properties of the wetlands, farmlands, and edges of wetlands and farmlands in Jinchuan Wetland by the random sampling. Behavior and reproduction in Caenorhabditis elegans (C. elegans) exposed to the sampled waters were also examined. Stress proteins Hsp70 and Hsp90 were measured both in the living field samples of C. elegans and the lab-tested C. elegans. Our results suggested that disturbance to wetland ecosystems by nitrogen and phosphorus reduced nematode richness and proportions of bacterivore nematodes. Bacterivore nematode diversity and plant-parasitic ecological index were proven to be sensitive indicators of the ecological health of wetlands. Nematode Hsp70 were useful biosensors to monitor and assess the levels of nitrogen and phosphorus pollutions in wetlands. Furthermore, multi-level soil faunal assessments by canonical correspondence analysis showed that Jinchuan Wetland is threatened with non-point source pollution from nearby farmlands.

Multi-stage decoding for multi-level block modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Kasami, Tadao

1991-01-01

Various types of multistage decoding for multilevel block modulation codes, in which the decoding of a component code at each stage can be either soft decision or hard decision, maximum likelihood or bounded distance are discussed. Error performance for codes is analyzed for a memoryless additive channel based on various types of multi-stage decoding, and upper bounds on the probability of an incorrect decoding are derived. It was found that, if component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. It was found that the difference in performance between the suboptimum multi-stage soft decision maximum likelihood decoding of a modulation code and the single stage optimum decoding of the overall code is very small, only a fraction of dB loss in SNR at the probability of an incorrect decoding for a block of 10(exp -6). Multi-stage decoding of multi-level modulation codes really offers a way to achieve the best of three worlds, bandwidth efficiency, coding gain, and decoding complexity.

On multi-level thinking and scientific understanding

NASA Astrophysics Data System (ADS)

McIntyre, Michael Edgeworth

2017-10-01

Professor Duzheng YE's name has been familiar to me ever since my postdoctoral years at MIT with Professors Jule CHARNEY and Norman PHILLIPS, back in the late 1960s. I had the enormous pleasure of meeting Professor YE personally in 1992 in Beijing. His concern to promote the very best science and to use it well, and his thinking on multi-level orderly human activities, reminds me not only of the communication skills we need as scientists but also of the multi-level nature of science itself. Here I want to say something (a) about what science is; (b) about why multi-level thinking—and taking more than one viewpoint—is so important for scientific as well as for other forms of understanding; and (c) about what is meant, at a deep level, by "scientific understanding" and trying to communicate it, not only with lay persons but also across professional disciplines. I hope that Professor YE would approve.

Who multi-tasks and why? Multi-tasking ability, perceived multi-tasking ability, impulsivity, and sensation seeking.

PubMed

Sanbonmatsu, David M; Strayer, David L; Medeiros-Ward, Nathan; Watson, Jason M

2013-01-01

The present study examined the relationship between personality and individual differences in multi-tasking ability. Participants enrolled at the University of Utah completed measures of multi-tasking activity, perceived multi-tasking ability, impulsivity, and sensation seeking. In addition, they performed the Operation Span in order to assess their executive control and actual multi-tasking ability. The findings indicate that the persons who are most capable of multi-tasking effectively are not the persons who are most likely to engage in multiple tasks simultaneously. To the contrary, multi-tasking activity as measured by the Media Multitasking Inventory and self-reported cell phone usage while driving were negatively correlated with actual multi-tasking ability. Multi-tasking was positively correlated with participants' perceived ability to multi-task ability which was found to be significantly inflated. Participants with a strong approach orientation and a weak avoidance orientation--high levels of impulsivity and sensation seeking--reported greater multi-tasking behavior. Finally, the findings suggest that people often engage in multi-tasking because they are less able to block out distractions and focus on a singular task. Participants with less executive control--low scorers on the Operation Span task and persons high in impulsivity--tended to report higher levels of multi-tasking activity.

Analysis of Sea Level Rise in Singapore Strait

NASA Astrophysics Data System (ADS)

Tkalich, Pavel; Luu, Quang-Hung

2013-04-01

Sea level in Singapore Strait is governed by various scale phenomena, from global to local. Global signals are dominated by the climate change and multi-decadal variability and associated sea level rise; at regional scale seasonal sea level variability is caused by ENSO-modulated monsoons; locally, astronomic tides are the strongest force. Tide gauge records in Singapore Strait are analyzed to derive local sea level trend, and attempts are made to attribute observed sea level variability to phenomena at various scales, from global to local. It is found that at annual scale, sea level anomalies in Singapore Strait are quasi-periodic, of the order of ±15 cm, the highest during northeast monsoon and the lowest during southwest monsoon. Interannual regional sea level falls are associated with El Niño events, while the rises are related to La Niña episodes; both variations are in the range of ±9 cm. At multi-decadal scale, sea level in Singapore Strait has been rising at the rate 1.2-1.9 mm/year for the period 1975-2009, 2.0±0.3 mm/year for 1984-2009, and 1.3-4.7 mm/year for 1993-2009. When compared with the respective global trends of 2.0±0.3, 2.4, and 2.8±0.8 mm/year, Singapore Strait sea level rise trend was weaker at the earlier period and stronger at the recent decade.

Multi-Level Strategies in Universities: Coordination, Contestation or Creolisation?

ERIC Educational Resources Information Center

Stensaker, Bjørn; Fumasoli, Tatiana

2017-01-01

In contemporary research-intensive universities, strategies are not only found at the institutional level but also at various sub-levels in the organisation. In principle, such multi-level strategies are assumed to be a means for institutional coordination in the sense that more generic strategic objectives may give room for local adaptation…

Large scale and cloud-based multi-model analytics experiments on climate change data in the Earth System Grid Federation

NASA Astrophysics Data System (ADS)

Fiore, Sandro; Płóciennik, Marcin; Doutriaux, Charles; Blanquer, Ignacio; Barbera, Roberto; Donvito, Giacinto; Williams, Dean N.; Anantharaj, Valentine; Salomoni, Davide D.; Aloisio, Giovanni

2017-04-01

In many scientific domains such as climate, data is often n-dimensional and requires tools that support specialized data types and primitives to be properly stored, accessed, analysed and visualized. Moreover, new challenges arise in large-scale scenarios and eco-systems where petabytes (PB) of data can be available and data can be distributed and/or replicated, such as the Earth System Grid Federation (ESGF) serving the Coupled Model Intercomparison Project, Phase 5 (CMIP5) experiment, providing access to 2.5PB of data for the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). A case study on climate models intercomparison data analysis addressing several classes of multi-model experiments is being implemented in the context of the EU H2020 INDIGO-DataCloud project. Such experiments require the availability of large amount of data (multi-terabyte order) related to the output of several climate models simulations as well as the exploitation of scientific data management tools for large-scale data analytics. More specifically, the talk discusses in detail a use case on precipitation trend analysis in terms of requirements, architectural design solution, and infrastructural implementation. The experiment has been tested and validated on CMIP5 datasets, in the context of a large scale distributed testbed across EU and US involving three ESGF sites (LLNL, ORNL, and CMCC) and one central orchestrator site (PSNC). The general "environment" of the case study relates to: (i) multi-model data analysis inter-comparison challenges; (ii) addressed on CMIP5 data; and (iii) which are made available through the IS-ENES/ESGF infrastructure. The added value of the solution proposed in the INDIGO-DataCloud project are summarized in the following: (i) it implements a different paradigm (from client- to server-side); (ii) it intrinsically reduces data movement; (iii) it makes lightweight the end-user setup; (iv) it fosters re-usability (of data, final/intermediate products, workflows, sessions, etc.) since everything is managed on the server-side; (v) it complements, extends and interoperates with the ESGF stack; (vi) it provides a "tool" for scientists to run multi-model experiments, and finally; and (vii) it can drastically reduce the time-to-solution for these experiments from weeks to hours. At the time the contribution is being written, the proposed testbed represents the first concrete implementation of a distributed multi-model experiment in the ESGF/CMIP context joining server-side and parallel processing, end-to-end workflow management and cloud computing. As opposed to the current scenario based on search & discovery, data download, and client-based data analysis, the INDIGO-DataCloud architectural solution described in this contribution addresses the scientific computing & analytics requirements by providing a paradigm shift based on server-side and high performance big data frameworks jointly with two-level workflow management systems realized at the PaaS level via a cloud infrastructure.

Urban structure analysis of mega city Mexico City using multisensoral remote sensing data

NASA Astrophysics Data System (ADS)

Taubenböck, H.; Esch, T.; Wurm, M.; Thiel, M.; Ullmann, T.; Roth, A.; Schmidt, M.; Mehl, H.; Dech, S.

2008-10-01

Mega city Mexico City is ranked the third largest urban agglomeration to date around the globe. The large extension as well as dynamic urban transformation and sprawl processes lead to a lack of up-to-date and area-wide data and information to measure, monitor, and understand the urban situation. This paper focuses on the capabilities of multisensoral remotely sensed data to provide a broad range of products derived from one scientific field - remote sensing - to support urban managing and planning. Therefore optical data sets from the Landsat and Quickbird sensors as well as radar data from the Shuttle Radar Topography Mission (SRTM) and the TerraSAR-X sensor are utilised. Using the multi-sensoral data sets the analysis are scale-dependent. On the one hand change detection on city level utilising the derived urban footprints enables to monitor and to assess spatiotemporal urban transformation, areal dimension of urban sprawl, its direction, and the built-up density distribution over time. On the other hand, structural characteristics of an urban landscape - the alignment and types of buildings, streets and open spaces - provide insight in the very detailed physical pattern of urban morphology on higher scale. The results show high accuracies of the derived multi-scale products. The multi-scale analysis allows quantifying urban processes and thus leading to an assessment and interpretation of urban trends.

Arrowland v1.0

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

BIRKEL, GARRETT; GARCIA MARTIN, HECTOR; MORRELL, WILLIAM

"Arrowland" is a web-based software application primarily for mapping, integrating and visualizing a variety of metabolism data of living organisms, including but not limited to metabolomics, proteomics, transcriptomics and fluxomics. This software application makes multi-omics data analysis intuitive and interactive. It improves data sharing and communication by enabling users to visualize their omics data using a web browser (on a PC or mobile device). It increases user's productivity by simplifying multi-omics data analysis using well developed maps as a guide. Users using this tool can gain insights into their data sets that would be difficult or even impossible to teasemore » out by looking at raw number, or using their currently existing toolchains to generate static single-use maps. Arrowland helps users save time by visualizing relative changes in different conditions or over time, and helps users to produce more significant insights faster. Preexisting maps decrease the learning curve for beginners in the omics field. Sets of multi-omics data are presented in the browser, as a two-dimensional flowchart resembling a map, with varying levels of detail information, based on the scaling of the map. Users can pan and zoom to explore different maps, compare maps, upload their own research data sets onto desired maps, alter map appearance in ways that facilitate interpretation, visualization and analysis of the given data, and export data, reports and actionable items to help the user initiative.« less

Social network analysis of multi-stakeholder platforms in agricultural research for development: Opportunities and constraints for innovation and scaling.

PubMed

Hermans, Frans; Sartas, Murat; van Schagen, Boudy; van Asten, Piet; Schut, Marc

2017-01-01

Multi-stakeholder platforms (MSPs) are seen as a promising vehicle to achieve agricultural development impacts. By increasing collaboration, exchange of knowledge and influence mediation among farmers, researchers and other stakeholders, MSPs supposedly enhance their 'capacity to innovate' and contribute to the 'scaling of innovations'. The objective of this paper is to explore the capacity to innovate and scaling potential of three MSPs in Burundi, Rwanda and the South Kivu province located in the eastern part of Democratic Republic of Congo (DRC). In order to do this, we apply Social Network Analysis and Exponential Random Graph Modelling (ERGM) to investigate the structural properties of the collaborative, knowledge exchange and influence networks of these MSPs and compared them against value propositions derived from the innovation network literature. Results demonstrate a number of mismatches between collaboration, knowledge exchange and influence networks for effective innovation and scaling processes in all three countries: NGOs and private sector are respectively over- and under-represented in the MSP networks. Linkages between local and higher levels are weak, and influential organisations (e.g., high-level government actors) are often not part of the MSP or are not actively linked to by other organisations. Organisations with a central position in the knowledge network are more sought out for collaboration. The scaling of innovations is primarily between the same type of organisations across different administrative levels, but not between different types of organisations. The results illustrate the potential of Social Network Analysis and ERGMs to identify the strengths and limitations of MSPs in terms of achieving development impacts.

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

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward

There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our systemmore » detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.« less

Construction and Analysis of Multi-Rate Partitioned Runge-Kutta Methods

DTIC Science & Technology

2012-06-01

ANALYSIS OF MULTI-RATE PARTITIONED RUNGE-KUTTA METHODS by Patrick R. Mugg June 2012 Thesis Advisor: Francis Giraldo Second Reader: Hong...COVERED Master’s Thesis 4. TITLE AND SUBTITLE Construction and Analysis of Multi-Rate Partitioned Runge-Kutta Methods 5. FUNDING NUMBERS 6. AUTHOR...The most widely known and used procedure for analyzing stability is the Von Neumann Method , such that Von Neumann’s stability analysis looks at

A Comparison of Two Methods Used for Ranking Task Exposure Levels Using Simulated Multi-Task Data

DTIC Science & Technology

1999-12-17

OF OKLAHOMA HEALTH SCIENCES CENTER GRADUATE COLLEGE A COMPARISON OF TWO METHODS USED FOR RANKING TASK EXPOSURE LEVELS USING SIMULATED MULTI-TASK...COSTANTINO Oklahoma City, Oklahoma 1999 ^ooo wx °^ A COMPARISON OF TWO METHODS USED FOR RANKING TASK EXPOSURE LEVELS USING SIMULATED MULTI-TASK DATA... METHODS AND MATERIALS 9 TV. RESULTS 14 V. DISCUSSION AND CONCLUSION 28 LIST OF REFERENCES 31 APPENDICES 33 Appendix A JJ -in Appendix B Dl IV

Multi-segment trunk models used to investigate the crunch factor in golf and their relationship with selected swing and launch parameters.

PubMed

Joyce, Christopher; Chivers, Paola; Sato, Kimitake; Burnett, Angus

2016-10-01

The use of multi-segment trunk models to investigate the crunch factor in golf may be warranted. The first aim of the study was to investigate the relationship between the trunk and lower trunk for crunch factor-related variables (trunk lateral bending and trunk axial rotation velocity). The second aim was to determine the level of association between crunch factor-related variables with swing (clubhead velocity) and launch (launch angle). Thirty-five high-level amateur male golfers (Mean ± SD: age = 23.8 ± 2.1 years, registered golfing handicap = 5 ± 1.9) without low back pain had kinematic data collected from their golf swing using a 10-camera motion analysis system operating at 500 Hz. Clubhead velocity and launch angle were collected using a validated real-time launch monitor. A positive relationship was found between the trunk and lower trunk for axial rotation velocity (r(35) = .47, P < .01). Cross-correlation analysis revealed a strong coupling relationship for the crunch factor (R(2) = 0.98) between the trunk and lower trunk. Using generalised linear model analysis, it was evident that faster clubhead velocities and lower launch angles of the golf ball were related to reduced lateral bending of the lower trunk.

Methodological flaws introduce strong bias into molecular analysis of microbial populations.

PubMed

Krakat, N; Anjum, R; Demirel, B; Schröder, P

2017-02-01

In this study, we report how different cell disruption methods, PCR primers and in silico analyses can seriously bias results from microbial population studies, with consequences for the credibility and reproducibility of the findings. Our results emphasize the pitfalls of commonly used experimental methods that can seriously weaken the interpretation of results. Four different cell lysis methods, three commonly used primer pairs and various computer-based analyses were applied to investigate the microbial diversity of a fermentation sample composed of chicken dung. The fault-prone, but still frequently used, amplified rRNA gene restriction analysis was chosen to identify common weaknesses. In contrast to other studies, we focused on the complete analytical process, from cell disruption to in silico analysis, and identified potential error rates. This identified a wide disagreement of results between applied experimental approaches leading to very different community structures depending on the chosen approach. The interpretation of microbial diversity data remains a challenge. In order to accurately investigate the taxonomic diversity and structure of prokaryotic communities, we suggest a multi-level approach combining DNA-based and DNA-independent techniques. The identified weaknesses of commonly used methods to study microbial diversity can be overcome by a multi-level approach, which produces more reliable data about the fate and behaviour of microbial communities of engineered habitats such as biogas plants, so that the best performance can be ensured. © 2016 The Society for Applied Microbiology.

A conceptual review on systems biology in health and diseases: from biological networks to modern therapeutics.

PubMed

Somvanshi, Pramod Rajaram; Venkatesh, K V

2014-03-01

Human physiology is an ensemble of various biological processes spanning from intracellular molecular interactions to the whole body phenotypic response. Systems biology endures to decipher these multi-scale biological networks and bridge the link between genotype to phenotype. The structure and dynamic properties of these networks are responsible for controlling and deciding the phenotypic state of a cell. Several cells and various tissues coordinate together to generate an organ level response which further regulates the ultimate physiological state. The overall network embeds a hierarchical regulatory structure, which when unusually perturbed can lead to undesirable physiological state termed as disease. Here, we treat a disease diagnosis problem analogous to a fault diagnosis problem in engineering systems. Accordingly we review the application of engineering methodologies to address human diseases from systems biological perspective. The review highlights potential networks and modeling approaches used for analyzing human diseases. The application of such analysis is illustrated in the case of cancer and diabetes. We put forth a concept of cell-to-human framework comprising of five modules (data mining, networking, modeling, experimental and validation) for addressing human physiology and diseases based on a paradigm of system level analysis. The review overtly emphasizes on the importance of multi-scale biological networks and subsequent modeling and analysis for drug target identification and designing efficient therapies.

Empirically Examining the Performance of Approaches to Multi-Level Matching to Study the Effect of School-Level Interventions

ERIC Educational Resources Information Center

Hallberg, Kelly; Cook, Thomas D.; Figlio, David

2013-01-01

The goal of this paper is to provide guidance for applied education researchers in using multi-level data to study the effects of interventions implemented at the school level. Two primary approaches are currently employed in observational studies of the effect of school-level interventions. One approach employs intact school matching: matching…

Macro-level gender equality and alcohol consumption: a multi-level analysis across U.S. States.

PubMed

Roberts, Sarah C M

2012-07-01

Higher levels of women's alcohol consumption have long been attributed to increases in gender equality. However, only limited research examines the relationship between gender equality and alcohol consumption. This study examined associations between five measures of state-level gender equality and five alcohol consumption measures in the United States. Survey data regarding men's and women's alcohol consumption from the 2005 Behavioral Risk Factor Surveillance System were linked to state-level indicators of gender equality. Gender equality indicators included state-level women's socioeconomic status, gender equality in socioeconomic status, reproductive rights, policies relating to violence against women, and women's political participation. Alcohol consumption measures included past 30-day drinker status, drinking frequency, binge drinking, volume, and risky drinking. Other than drinker status, consumption is measured for drinkers only. Multi-level linear and logistic regression models adjusted for individual demographics as well as state-level income inequality, median income, and % Evangelical Protestant/Mormon. All gender equality indicators were positively associated with both women's and men's drinker status in models adjusting only for individual-level covariates; associations were not significant in models adjusting for other state-level characteristics. All other associations between gender equality and alcohol consumption were either negative or non-significant for both women and men in models adjusting for other state-level factors. Findings do not support the hypothesis that higher levels of gender equality are associated with higher levels of alcohol consumption by women or by men. In fact, most significant findings suggest that higher levels of equality are associated with less alcohol consumption overall. Copyright © 2012 Elsevier Ltd. All rights reserved.

Minimal impact of response shift for SF-12 mental and physical health status in homeless and vulnerably housed individuals: an item-level multi-group analysis.

PubMed

Gadermann, Anne M; Sawatzky, Richard; Palepu, Anita; Hubley, Anita M; Zumbo, Bruno D; Aubry, Tim; Farrell, Susan; Hwang, Stephen W

2017-06-01

The purpose of this study was to examine whether homeless or vulnerably housed individuals experienced response shift over a 12-month time period in their self-reported physical and mental health status. Data were obtained from the Health and Housing in Transition study, a longitudinal multi-site cohort study in Canada (N = 1190 at baseline). Multi-group confirmatory factor analysis (MG-CFA) and methods for response shift detection at the item level, based on the approach by Oort, were used to test for reconceptualization, reprioritization, and recalibration response shift on the SF-12 in four groups of individuals who were homeless (n = 170), housed (n = 437), or who reported a change in their housing status [from homeless to housed (n = 285) or housed to homeless (n = 73)] over a 12-month time period. Mean and variance adjusted weighted-least squares estimation was used to accommodate the ordinal and binary distributions of the SF-12 items. Using MG-CFA, a strict invariance model showed that the measurement model was equivalent for the four groups at baseline. Although we found small but statistically significant response shift for several measurement model parameters, the impact on the predicted average mental and physical health scores within each of the groups was small. Response shift does not appear to be a significant concern when using the SF-12 to obtain change scores over a 12-month period in this population.

Experimental and numerical analysis on noise reduction in a multi-blade centrifugal fan

NASA Astrophysics Data System (ADS)

Chen, X. J.; Y Cao, T.; Su, J.; Qin, G. L.

2013-12-01

In this work, analysis on noise source and reduction in a multi-blade centrifugal fan used for air-conditioners was carried out by experimental and numerical methods. Firstly, an experimental system using microphone mounted on volute surface for measuring surface pressure fluctuations of volute was designed and introduced, then surface pressure fluctuations of the whole volute for a multi-blade centrifugal fan were measured by this system, and the inlet noise for this fan was also obtained. And then, based on the experimental results, the aerodynamic noise source of the studied fan was analysed. The surface pressure fluctuations of the volute showed that there were largest surface pressure fluctuations near the volute tongue, and peaks appeared at the Blade Passing Frequency (BPF). The spectra of fan inlet noise showed that the peaks also appeared at BPF, and noise levels in a wide range of frequency were also larger. Secondly, the internal flow of the fan was simulated by commercial software under the same conditions with the experiment, and then the fluid flow and acoustic power field were obtained and discussed. The contours of acoustic power level showed that the larger noise was generated at the impeller area close to the outlet of scroll and at the volute tongue, which is same as that from experiment. Based on all of the results, we can find that the vortex noise is an important part of fan noise for the studied fan, and the rotation noise also cannot be neglected. Finally, several reduction methods that are thought to be effective based on experimental and numerical results were suggested.

Inexact fuzzy-stochastic mixed-integer programming approach for long-term planning of waste management--Part A: methodology.

PubMed

Guo, P; Huang, G H

2009-01-01

In this study, an inexact fuzzy chance-constrained two-stage mixed-integer linear programming (IFCTIP) approach is proposed for supporting long-term planning of waste-management systems under multiple uncertainties in the City of Regina, Canada. The method improves upon the existing inexact two-stage programming and mixed-integer linear programming techniques by incorporating uncertainties expressed as multiple uncertainties of intervals and dual probability distributions within a general optimization framework. The developed method can provide an effective linkage between the predefined environmental policies and the associated economic implications. Four special characteristics of the proposed method make it unique compared with other optimization techniques that deal with uncertainties. Firstly, it provides a linkage to predefined policies that have to be respected when a modeling effort is undertaken; secondly, it is useful for tackling uncertainties presented as intervals, probabilities, fuzzy sets and their incorporation; thirdly, it facilitates dynamic analysis for decisions of facility-expansion planning and waste-flow allocation within a multi-facility, multi-period, multi-level, and multi-option context; fourthly, the penalties are exercised with recourse against any infeasibility, which permits in-depth analyses of various policy scenarios that are associated with different levels of economic consequences when the promised solid waste-generation rates are violated. In a companion paper, the developed method is applied to a real case for the long-term planning of waste management in the City of Regina, Canada.

Associations of phthalate concentrations in floor dust and multi-surface dust with the interior materials in Japanese dwellings.

PubMed

Ait Bamai, Yu; Araki, Atsuko; Kawai, Toshio; Tsuboi, Tazuru; Saito, Ikue; Yoshioka, Eiji; Kanazawa, Ayako; Tajima, Shuji; Shi, Cong; Tamakoshi, Akiko; Kishi, Reiko

2014-01-15

Phthalates are widely used as plasticizers in numerous products. However, there has been some concern about the various effects they may have on human health. Thus, household phthalate levels are an important public health issue. While many studies have assessed phthalate levels in house dust, the association of these levels with building characteristics has scarcely been examined. The present study investigated phthalate levels in house dust samples collected from the living areas of homes, and examined associations between these phthalate levels and the interior materials. Dust was collected from two portions of the living area: floor dust from the entire floor surface, and multi-surface dust from objects more than 35 cm above the floor. The levels of seven phthalates were measured using gas chromatography/mass spectrometry in selective ion monitoring mode. Phthalate levels were higher in multi-surface dust than in floor dust. Among floor dust samples, those from dwellings with compressed wooden flooring had significantly higher levels of di-iso-butyl phthalate compared to those with other floor materials, while polyvinyl chloride (PVC) flooring was associated with higher di-2-ethylhexyl phthalate (DEHP) levels. Among multi-surface dust samples, higher levels of DEHP and di-iso-nonyl phthalate (DINP) were found in samples from homes with PVC wallpaper than without. The number of PVC interior materials was significantly positively correlated with the levels of DEHP and DINP in multi-surface dust. The phthalate levels in multi-surface dust were associated with the interior surface materials, and those in floor dust were directly related to the flooring materials. Our findings show that when using house dust as an exposure assessment, it is very important to note where the samples were collected from. The present report provides useful information about the association between phthalates and dust inside dwellings, which will assist with establishing public health provisions. © 2013. Published by Elsevier B.V. All rights reserved.

A novel method for a multi-level hierarchical composite with brick-and-mortar structure

PubMed Central

Brandt, Kristina; Wolff, Michael F. H.; Salikov, Vitalij; Heinrich, Stefan; Schneider, Gerold A.

2013-01-01

The fascination for hierarchically structured hard tissues such as enamel or nacre arises from their unique structure-properties-relationship. During the last decades this numerously motivated the synthesis of composites, mimicking the brick-and-mortar structure of nacre. However, there is still a lack in synthetic engineering materials displaying a true hierarchical structure. Here, we present a novel multi-step processing route for anisotropic 2-level hierarchical composites by combining different coating techniques on different length scales. It comprises polymer-encapsulated ceramic particles as building blocks for the first level, followed by spouted bed spray granulation for a second level, and finally directional hot pressing to anisotropically consolidate the composite. The microstructure achieved reveals a brick-and-mortar hierarchical structure with distinct, however not yet optimized mechanical properties on each level. It opens up a completely new processing route for the synthesis of multi-level hierarchically structured composites, giving prospects to multi-functional structure-properties relationships. PMID:23900554

A novel method for a multi-level hierarchical composite with brick-and-mortar structure.

PubMed

Brandt, Kristina; Wolff, Michael F H; Salikov, Vitalij; Heinrich, Stefan; Schneider, Gerold A

2013-01-01

The fascination for hierarchically structured hard tissues such as enamel or nacre arises from their unique structure-properties-relationship. During the last decades this numerously motivated the synthesis of composites, mimicking the brick-and-mortar structure of nacre. However, there is still a lack in synthetic engineering materials displaying a true hierarchical structure. Here, we present a novel multi-step processing route for anisotropic 2-level hierarchical composites by combining different coating techniques on different length scales. It comprises polymer-encapsulated ceramic particles as building blocks for the first level, followed by spouted bed spray granulation for a second level, and finally directional hot pressing to anisotropically consolidate the composite. The microstructure achieved reveals a brick-and-mortar hierarchical structure with distinct, however not yet optimized mechanical properties on each level. It opens up a completely new processing route for the synthesis of multi-level hierarchically structured composites, giving prospects to multi-functional structure-properties relationships.