Members' sensemaking in a multi-professional team.

PubMed

Rovio-Johansson, Airi; Liff, Roy

2012-01-01

The aim of this study is to investigate sensemaking as interaction among team members in a multi-professional team setting in a new public management context at a Swedish Child and Youth Psychiatric Unit. A discursive pragmatic approach grounded in ethonomethodology is taken in the analysis of a treatment conference (TC). In order to interpret and understand the multi-voiced complexity of discourse and of talk-in-interaction, the authors use dialogism in the analysis of the members' sensemaking processes. The analysis is based on the theoretical assumption that language and texts are the primary tools actors use to comprehend the social reality and to make sense of their multi-professional discussions. Health care managers are offered insights, derived from theory and empirical evidence, into how professionals' communications influence multi-professional cooperation. The team leader and members are interviewed before and after the observed TC. Team members create their identities and positions in the group by interpreting and "misinterpreting" talk-in-interaction. The analyses reveal the ways the team members relate to their treatment methods in the discussion of a patient; advocating a treatment method means that the team member and the method are intertwined. The findings may be valuable to health care professionals and managers working in teams by showing them how to achieve greater cooperation through the use of verbal abilities. The findings and methods contribute to the international research on cooperation problems in multi-professional teams and to the empirical research on institutional discourse through text and talk.

Integrating multi-scale data to create a virtual physiological mouse heart.

PubMed

Land, Sander; Niederer, Steven A; Louch, William E; Sejersted, Ole M; Smith, Nicolas P

2013-04-06

While the virtual physiological human (VPH) project has made great advances in human modelling, many of the tools and insights developed as part of this initiative are also applicable for facilitating mechanistic understanding of the physiology of a range of other species. This process, in turn, has the potential to provide human relevant insights via a different scientific path. Specifically, the increasing use of mice in experimental research, not yet fully complemented by a similar increase in computational modelling, is currently missing an important opportunity for using and interpreting this growing body of experimental data to improve our understanding of cardiac function. This overview describes our work to address this issue by creating a virtual physiological mouse model of the heart. We describe the similarities between human- and mouse-focused modelling, including the reuse of VPH tools, and the development of methods for investigating parameter sensitivity that are applicable across species. We show how previous results using this approach have already provided important biological insights, and how these can also be used to advance VPH heart models. Finally, we show an example application of this approach to test competing multi-scale hypotheses by investigating variations in length-dependent properties of cardiac muscle.

Integrating multi-scale data to create a virtual physiological mouse heart

PubMed Central

Land, Sander; Niederer, Steven A.; Louch, William E.; Sejersted, Ole M.; Smith, Nicolas P.

2013-01-01

While the virtual physiological human (VPH) project has made great advances in human modelling, many of the tools and insights developed as part of this initiative are also applicable for facilitating mechanistic understanding of the physiology of a range of other species. This process, in turn, has the potential to provide human relevant insights via a different scientific path. Specifically, the increasing use of mice in experimental research, not yet fully complemented by a similar increase in computational modelling, is currently missing an important opportunity for using and interpreting this growing body of experimental data to improve our understanding of cardiac function. This overview describes our work to address this issue by creating a virtual physiological mouse model of the heart. We describe the similarities between human- and mouse-focused modelling, including the reuse of VPH tools, and the development of methods for investigating parameter sensitivity that are applicable across species. We show how previous results using this approach have already provided important biological insights, and how these can also be used to advance VPH heart models. Finally, we show an example application of this approach to test competing multi-scale hypotheses by investigating variations in length-dependent properties of cardiac muscle. PMID:24427525

New Insight into Combined Model and Revised Model for RTD Curves in a Multi-strand Tundish

NASA Astrophysics Data System (ADS)

Lei, Hong

2015-12-01

The analysis for the residence time distribution (RTD) curve is one of the important experimental technologies to optimize the tundish design. But there are some issues about RTD analysis model. Firstly, the combined (or mixed) model and the revised model give different analysis results for the same RTD curve. Secondly, different upper limits of integral in the numerator for the mean residence time give different results for the same RTD curve. Thirdly, the negative dead volume fraction sometimes appears at the outer strand of the multi-strand tundish. In order to solve the above problems, it is necessary to have a deep insight into the RTD curve and to propose a reasonable method to analyze the RTD curve. The results show that (1) the revised model is not appropriate to treat with the RTD curve; (2) the conception of the visual single-strand tundish and the combined model with the dimensionless time at the cut-off point are applied to estimate the flow characteristics in the multi-strand tundish; and that (3) the mean residence time at each exit is the key parameter to estimate the similarity of fluid flow among strands.

Qualitative Insights from a Canadian Multi-Institutional Research Study: In Search of Meaningful E-Learning

ERIC Educational Resources Information Center

Carter, Lorraine M.; Salyers, Vince; Myers, Sue; Hipfner, Carol; Hoffart, Caroline; MacLean, Christa; White, Kathy; Matus, Theresa; Forssman, Vivian; Barrett, Penelope

2014-01-01

This paper reports the qualitative findings of a mixed methods research study conducted at three Canadian post-secondary institutions. Called the Meaningful E-learning or MEL project, the study was an exploration of the teaching and learning experiences of faculty and students as well as their perceptions of the benefits and challenges of…

National Security Challenges: Insights from Social, Neurobiological, and Complexity Sciences. Topical Strategic Multi-Layer Assessment (SMA) and U.S. Army ERDC Multi-Agency/Multi-Disciplinary White Papers in Support of National Security Challenges

DTIC Science & Technology

2012-07-01

population. The amount of information on Facebook doubles every 6 months. This under- scores the nation’s need to understand what is happening on a ...QL—Russia: Emerging Insight Into Muslim Populations (October 2011) • QL— A Trend Toward Increased Information Communication Technol- ogy (ICT...Hendrix ( College of William & Mary), Mr. Eric A . Knudson (PACOM), Mr. Joseph T. Lee (PACOM), Mr. Kalev Leetaru (University of Illinois at Urbana), Lt

Life cycle tools combined with multi-criteria and participatory methods for agricultural sustainability: Insights from a systematic and critical review.

PubMed

De Luca, Anna Irene; Iofrida, Nathalie; Leskinen, Pekka; Stillitano, Teodora; Falcone, Giacomo; Strano, Alfio; Gulisano, Giovanni

2017-10-01

Life cycle (LC) methodologies have attracted a great interest in agricultural sustainability assessments, even if, at the same time, they have sometimes been criticized for making unrealistic assumptions and subjective choices. To cope with these weaknesses, Multi-Criteria Decision Analysis (MCDA) and/or participatory methods can be used to balance and integrate different sustainability dimensions. The purpose of this study is to highlight how life cycle approaches were combined with MCDA and participatory methods to address agricultural sustainability in the published scientific literature. A systematic and critical review was developed, highlighting the following features: which multi-criterial and/or participatory methods have been associated with LC tools; how they have been integrated or complemented (methodological relationships); the intensity of the involvement of stakeholders (degree of participation); and which synergies have been achieved by combining the methods. The main typology of integration was represented by multi-criterial frameworks integrating LC evaluations. LC tools can provide MCDA studies with local and global information on how to reduce negative impacts and avoid burden shifts, while MCDA methods can help LC practitioners deal with subjective assumptions in an objective way, to take into consideration actors' values and to overcome trade-offs among the different dimensions of sustainability. Considerations concerning the further development of Life Cycle Sustainability Assessment (LCSA) have been identified as well. Copyright © 2017 Elsevier B.V. All rights reserved.

Stakeholders Opinions on Multi-Use Deep Water Offshore Platform in Hsiao-Liu-Chiu, Taiwan

PubMed Central

Sie, Ya-Tsune; Chang, Yang-Chi; Lu, Shiau-Yun

2018-01-01

This paper describes a group model building activity designed to elicit the potential effects a projected multi-use deep water offshore platform may have on its local environment, including ecological and socio-economic issues. As such a platform is proposed for construction around the island of Hsiao-Liu-Chiu, Taiwan, we organized several meetings with the local stakeholders and structured the debates using group modeling methods to promote consensus. During the process, the participants iteratively built and revised a causal-loop diagram that summarizes their opinions. Overall, local stakeholders concluded that a multi-use deep water offshore marine platform might have beneficial effects for Hsiao-Liu-Chiu because more tourists and fish could be attracted by the structure, but they also raised some potential problems regarding the law in Taiwan and the design of the offshore platform, especially its resistance to extreme weather. We report the method used and the main results and insights gained during the process. PMID:29415521

Integration of Multi-Modal Biomedical Data to Predict Cancer Grade and Patient Survival.

PubMed

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

2016-02-01

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

Determining flexor-tendon repair techniques via soft computing

NASA Technical Reports Server (NTRS)

Johnson, M.; Firoozbakhsh, K.; Moniem, M.; Jamshidi, M.

2001-01-01

An SC-based multi-objective decision-making method for determining the optimal flexor-tendon repair technique from experimental and clinical survey data, and with variable circumstances, was presented. Results were compared with those from the Taguchi method. Using the Taguchi method results in the need to perform ad-hoc decisions when the outcomes for individual objectives are contradictory to a particular preference or circumstance, whereas the SC-based multi-objective technique provides a rigorous straightforward computational process in which changing preferences and importance of differing objectives are easily accommodated. Also, adding more objectives is straightforward and easily accomplished. The use of fuzzy-set representations of information categories provides insight into their performance throughout the range of their universe of discourse. The ability of the technique to provide a "best" medical decision given a particular physician, hospital, patient, situation, and other criteria was also demonstrated.

Increasing conclusiveness of clinical breath analysis by improved baseline correction of multi capillary column - ion mobility spectrometry (MCC-IMS) data.

PubMed

Szymańska, Ewa; Tinnevelt, Gerjen H; Brodrick, Emma; Williams, Mark; Davies, Antony N; van Manen, Henk-Jan; Buydens, Lutgarde M C

2016-08-05

Current challenges of clinical breath analysis include large data size and non-clinically relevant variations observed in exhaled breath measurements, which should be urgently addressed with competent scientific data tools. In this study, three different baseline correction methods are evaluated within a previously developed data size reduction strategy for multi capillary column - ion mobility spectrometry (MCC-IMS) datasets. Introduced for the first time in breath data analysis, the Top-hat method is presented as the optimum baseline correction method. A refined data size reduction strategy is employed in the analysis of a large breathomic dataset on a healthy and respiratory disease population. New insights into MCC-IMS spectra differences associated with respiratory diseases are provided, demonstrating the additional value of the refined data analysis strategy in clinical breath analysis. Copyright © 2016 Elsevier B.V. All rights reserved.

Determining flexor-tendon repair techniques via soft computing.

PubMed

Johnson, M; Firoozbakhsh, K; Moniem, M; Jamshidi, M

2001-01-01

An SC-based multi-objective decision-making method for determining the optimal flexor-tendon repair technique from experimental and clinical survey data, and with variable circumstances, was presented. Results were compared with those from the Taguchi method. Using the Taguchi method results in the need to perform ad-hoc decisions when the outcomes for individual objectives are contradictory to a particular preference or circumstance, whereas the SC-based multi-objective technique provides a rigorous straightforward computational process in which changing preferences and importance of differing objectives are easily accommodated. Also, adding more objectives is straightforward and easily accomplished. The use of fuzzy-set representations of information categories provides insight into their performance throughout the range of their universe of discourse. The ability of the technique to provide a "best" medical decision given a particular physician, hospital, patient, situation, and other criteria was also demonstrated.

A multi-layered governance framework for incorporating social science insights into adapting to the health impacts of climate change.

PubMed

Bowen, Kathryn J; Ebi, Kristie; Friel, Sharon; McMichael, Anthony J

2013-09-10

Addressing climate change and its associated effects is a multi-dimensional and ongoing challenge. This includes recognizing that climate change will affect the health and wellbeing of all populations over short and longer terms, albeit in varied ways and intensities. That recognition has drawn attention to the need to take adaptive actions to lessen adverse impacts over the next few decades from unavoidable climate change, particularly in developing country settings. A range of sectors is responsible for appropriate adaptive policies and measures to address the health risks of climate change, including health services, water and sanitation, trade, agriculture, disaster management, and development. To broaden the framing of governance and decision-making processes by using innovative methods and assessments to illustrate the multi-sectoral nature of health-related adaptation to climate change. This is a shift from sector-specific to multi-level systems encompassing sectors and actors, across temporal and spatial scales. A review and synthesis of the current knowledge in the areas of health and climate change adaptation governance and decision-making processes. A novel framework is presented that incorporates social science insights into the formulation and implementation of adaptation activities and policies to lessen the health risks posed by climate change. Clarification of the roles that different sectors, organizations, and individuals occupy in relation to the development of health-related adaptation strategies will facilitate the inclusion of health and wellbeing within multi-sector adaptation policies, thereby strengthening the overall set of responses to minimize the adverse health effects of climate change.

A multi-layered governance framework for incorporating social science insights into adapting to the health impacts of climate change

PubMed Central

Bowen, Kathryn J.; Ebi, Kristie; Friel, Sharon; McMichael, Anthony J.

2013-01-01

Background Addressing climate change and its associated effects is a multi-dimensional and ongoing challenge. This includes recognizing that climate change will affect the health and wellbeing of all populations over short and longer terms, albeit in varied ways and intensities. That recognition has drawn attention to the need to take adaptive actions to lessen adverse impacts over the next few decades from unavoidable climate change, particularly in developing country settings. A range of sectors is responsible for appropriate adaptive policies and measures to address the health risks of climate change, including health services, water and sanitation, trade, agriculture, disaster management, and development. Objectives To broaden the framing of governance and decision-making processes by using innovative methods and assessments to illustrate the multi-sectoral nature of health-related adaptation to climate change. This is a shift from sector-specific to multi-level systems encompassing sectors and actors, across temporal and spatial scales. Design A review and synthesis of the current knowledge in the areas of health and climate change adaptation governance and decision-making processes. Results A novel framework is presented that incorporates social science insights into the formulation and implementation of adaptation activities and policies to lessen the health risks posed by climate change. Conclusion Clarification of the roles that different sectors, organizations, and individuals occupy in relation to the development of health-related adaptation strategies will facilitate the inclusion of health and wellbeing within multi-sector adaptation policies, thereby strengthening the overall set of responses to minimize the adverse health effects of climate change. PMID:24028938

A coupling method for a cardiovascular simulation model which includes the Kalman filter.

PubMed

Hasegawa, Yuki; Shimayoshi, Takao; Amano, Akira; Matsuda, Tetsuya

2012-01-01

Multi-scale models of the cardiovascular system provide new insight that was unavailable with in vivo and in vitro experiments. For the cardiovascular system, multi-scale simulations provide a valuable perspective in analyzing the interaction of three phenomenons occurring at different spatial scales: circulatory hemodynamics, ventricular structural dynamics, and myocardial excitation-contraction. In order to simulate these interactions, multiscale cardiovascular simulation systems couple models that simulate different phenomena. However, coupling methods require a significant amount of calculation, since a system of non-linear equations must be solved for each timestep. Therefore, we proposed a coupling method which decreases the amount of calculation by using the Kalman filter. In our method, the Kalman filter calculates approximations for the solution to the system of non-linear equations at each timestep. The approximations are then used as initial values for solving the system of non-linear equations. The proposed method decreases the number of iterations required by 94.0% compared to the conventional strong coupling method. When compared with a smoothing spline predictor, the proposed method required 49.4% fewer iterations.

Comprehensive comparative analysis and identification of RNA-binding protein domains: multi-class classification and feature selection.

PubMed

Jahandideh, Samad; Srinivasasainagendra, Vinodh; Zhi, Degui

2012-11-07

RNA-protein interaction plays an important role in various cellular processes, such as protein synthesis, gene regulation, post-transcriptional gene regulation, alternative splicing, and infections by RNA viruses. In this study, using Gene Ontology Annotated (GOA) and Structural Classification of Proteins (SCOP) databases an automatic procedure was designed to capture structurally solved RNA-binding protein domains in different subclasses. Subsequently, we applied tuned multi-class SVM (TMCSVM), Random Forest (RF), and multi-class ℓ1/ℓq-regularized logistic regression (MCRLR) for analysis and classifying RNA-binding protein domains based on a comprehensive set of sequence and structural features. In this study, we compared prediction accuracy of three different state-of-the-art predictor methods. From our results, TMCSVM outperforms the other methods and suggests the potential of TMCSVM as a useful tool for facilitating the multi-class prediction of RNA-binding protein domains. On the other hand, MCRLR by elucidating importance of features for their contribution in predictive accuracy of RNA-binding protein domains subclasses, helps us to provide some biological insights into the roles of sequences and structures in protein-RNA interactions.

Pilot users in agile development processes: motivational factors.

PubMed

Johannessen, Liv Karen; Gammon, Deede

2010-01-01

Despite a wealth of research on user participation, few studies offer insights into how to involve multi-organizational users in agile development methods. This paper is a case study of user involvement in developing a system for electronic laboratory requisitions using agile methodologies in a multi-organizational context. Building on an interpretive approach, we illuminate questions such as: How does collaboration between users and developers evolve and how might it be improved? What key motivational aspects are at play when users volunteer and continue contributing in the face of considerable added burdens? The study highlights how agile methods in themselves appear to facilitate mutually motivating collaboration between user groups and developers. Lessons learned for leveraging the advantages of agile development processes include acknowledging the substantial and ongoing contributions of users and their roles as co-designers of the system.

Development of Terahertz Rayleigh Scattering Diagnostics for a Solid Rocket Exhaust Plume

DTIC Science & Technology

2010-10-28

experiment. Many of these experiments involve a diagnostic of a plasma which while different from strictly particles, still provides insight into the...investigate the properties of small plasma objects. Their study developed a method that could be used as a diagnostic for small scale plasmas such...as laser sparks, avalanche-streamer transitions, and resonance-enhanced multi- photon ionizations processes. They treated a plasma as a source of

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

Hachtel, J. A.; Yu, S.; Lupini, A. R.

The combination of iron oxide and gold in a single nanoparticle results in both magnetic and plasmonic properties that can stimulate novel applications in bio-sensing, medical imaging, or therapeutics. Microwave assisted heating allows the fabrication of multi-component, multi-functional nanostructures by promoting selective heating at desired sites. Recently, we reported a microwave-assisted polyol route yielding gold nanotriangles decorated with iron oxide nanoparticles. Here, we present an in-depth microstructural and compositional characterization of the system by using scanning transmission electron microscopy (STEM) and electron energy loss (EELS) spectroscopy. A method to remove the iron oxide nanoparticles from the gold nanocrystals and somemore » insights on crystal nucleation and growth mechanisms are also provided.« less

Identification of multi-loci hubs from 4C-seq demonstrates the functional importance of simultaneous interactions.

PubMed

Jiang, Tingting; Raviram, Ramya; Snetkova, Valentina; Rocha, Pedro P; Proudhon, Charlotte; Badri, Sana; Bonneau, Richard; Skok, Jane A; Kluger, Yuval

2016-10-14

Use of low resolution single cell DNA FISH and population based high resolution chromosome conformation capture techniques have highlighted the importance of pairwise chromatin interactions in gene regulation. However, it is unlikely that associations involving regulatory elements act in isolation of other interacting partners that also influence their impact. Indeed, the influence of multi-loci interactions remains something of an enigma as beyond low-resolution DNA FISH we do not have the appropriate tools to analyze these. Here we present a method that uses standard 4C-seq data to identify multi-loci interactions from the same cell. We demonstrate the feasibility of our method using 4C-seq data sets that identify known pairwise and novel tri-loci interactions involving the Tcrb and Igk antigen receptor enhancers. We further show that the three Igk enhancers, MiEκ, 3'Eκ and Edκ, interact simultaneously in this super-enhancer cluster, which add to our previous findings showing that loss of one element decreases interactions between all three elements as well as reducing their transcriptional output. These findings underscore the functional importance of simultaneous interactions and provide new insight into the relationship between enhancer elements. Our method opens the door for studying multi-loci interactions and their impact on gene regulation in other biological settings. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Identification of multi-loci hubs from 4C-seq demonstrates the functional importance of simultaneous interactions

PubMed Central

Jiang, Tingting; Raviram, Ramya; Snetkova, Valentina; Rocha, Pedro P.; Proudhon, Charlotte; Badri, Sana; Bonneau, Richard; Skok, Jane A.; Kluger, Yuval

2016-01-01

Use of low resolution single cell DNA FISH and population based high resolution chromosome conformation capture techniques have highlighted the importance of pairwise chromatin interactions in gene regulation. However, it is unlikely that associations involving regulatory elements act in isolation of other interacting partners that also influence their impact. Indeed, the influence of multi-loci interactions remains something of an enigma as beyond low-resolution DNA FISH we do not have the appropriate tools to analyze these. Here we present a method that uses standard 4C-seq data to identify multi-loci interactions from the same cell. We demonstrate the feasibility of our method using 4C-seq data sets that identify known pairwise and novel tri-loci interactions involving the Tcrb and Igk antigen receptor enhancers. We further show that the three Igk enhancers, MiEκ, 3′Eκ and Edκ, interact simultaneously in this super-enhancer cluster, which add to our previous findings showing that loss of one element decreases interactions between all three elements as well as reducing their transcriptional output. These findings underscore the functional importance of simultaneous interactions and provide new insight into the relationship between enhancer elements. Our method opens the door for studying multi-loci interactions and their impact on gene regulation in other biological settings. PMID:27439714

Exploring the Use of Computer Simulations in Unraveling Research and Development Governance Problems

NASA Technical Reports Server (NTRS)

Balaban, Mariusz A.; Hester, Patrick T.

2012-01-01

Understanding Research and Development (R&D) enterprise relationships and processes at a governance level is not a simple task, but valuable decision-making insight and evaluation capabilities can be gained from their exploration through computer simulations. This paper discusses current Modeling and Simulation (M&S) methods, addressing their applicability to R&D enterprise governance. Specifically, the authors analyze advantages and disadvantages of the four methodologies used most often by M&S practitioners: System Dynamics (SO), Discrete Event Simulation (DES), Agent Based Modeling (ABM), and formal Analytic Methods (AM) for modeling systems at the governance level. Moreover, the paper describes nesting models using a multi-method approach. Guidance is provided to those seeking to employ modeling techniques in an R&D enterprise for the purposes of understanding enterprise governance. Further, an example is modeled and explored for potential insight. The paper concludes with recommendations regarding opportunities for concentration of future work in modeling and simulating R&D governance relationships and processes.

Efficient computation of the phylogenetic likelihood function on multi-gene alignments and multi-core architectures.

PubMed

Stamatakis, Alexandros; Ott, Michael

2008-12-27

The continuous accumulation of sequence data, for example, due to novel wet-laboratory techniques such as pyrosequencing, coupled with the increasing popularity of multi-gene phylogenies and emerging multi-core processor architectures that face problems of cache congestion, poses new challenges with respect to the efficient computation of the phylogenetic maximum-likelihood (ML) function. Here, we propose two approaches that can significantly speed up likelihood computations that typically represent over 95 per cent of the computational effort conducted by current ML or Bayesian inference programs. Initially, we present a method and an appropriate data structure to efficiently compute the likelihood score on 'gappy' multi-gene alignments. By 'gappy' we denote sampling-induced gaps owing to missing sequences in individual genes (partitions), i.e. not real alignment gaps. A first proof-of-concept implementation in RAXML indicates that this approach can accelerate inferences on large and gappy alignments by approximately one order of magnitude. Moreover, we present insights and initial performance results on multi-core architectures obtained during the transition from an OpenMP-based to a Pthreads-based fine-grained parallelization of the ML function.

A 2D multi-term time and space fractional Bloch-Torrey model based on bilinear rectangular finite elements

NASA Astrophysics Data System (ADS)

Qin, Shanlin; Liu, Fawang; Turner, Ian W.

2018-03-01

The consideration of diffusion processes in magnetic resonance imaging (MRI) signal attenuation is classically described by the Bloch-Torrey equation. However, many recent works highlight the distinct deviation in MRI signal decay due to anomalous diffusion, which motivates the fractional order generalization of the Bloch-Torrey equation. In this work, we study the two-dimensional multi-term time and space fractional diffusion equation generalized from the time and space fractional Bloch-Torrey equation. By using the Galerkin finite element method with a structured mesh consisting of rectangular elements to discretize in space and the L1 approximation of the Caputo fractional derivative in time, a fully discrete numerical scheme is derived. A rigorous analysis of stability and error estimation is provided. Numerical experiments in the square and L-shaped domains are performed to give an insight into the efficiency and reliability of our method. Then the scheme is applied to solve the multi-term time and space fractional Bloch-Torrey equation, which shows that the extra time derivative terms impact the relaxation process.

A deep learning-based multi-model ensemble method for cancer prediction.

PubMed

Xiao, Yawen; Wu, Jun; Lin, Zongli; Zhao, Xiaodong

2018-01-01

Cancer is a complex worldwide health problem associated with high mortality. With the rapid development of the high-throughput sequencing technology and the application of various machine learning methods that have emerged in recent years, progress in cancer prediction has been increasingly made based on gene expression, providing insight into effective and accurate treatment decision making. Thus, developing machine learning methods, which can successfully distinguish cancer patients from healthy persons, is of great current interest. However, among the classification methods applied to cancer prediction so far, no one method outperforms all the others. In this paper, we demonstrate a new strategy, which applies deep learning to an ensemble approach that incorporates multiple different machine learning models. We supply informative gene data selected by differential gene expression analysis to five different classification models. Then, a deep learning method is employed to ensemble the outputs of the five classifiers. The proposed deep learning-based multi-model ensemble method was tested on three public RNA-seq data sets of three kinds of cancers, Lung Adenocarcinoma, Stomach Adenocarcinoma and Breast Invasive Carcinoma. The test results indicate that it increases the prediction accuracy of cancer for all the tested RNA-seq data sets as compared to using a single classifier or the majority voting algorithm. By taking full advantage of different classifiers, the proposed deep learning-based multi-model ensemble method is shown to be accurate and effective for cancer prediction. Copyright © 2017 Elsevier B.V. All rights reserved.

An evaluation of noise reduction algorithms for particle-based fluid simulations in multi-scale applications

NASA Astrophysics Data System (ADS)

Zimoń, M. J.; Prosser, R.; Emerson, D. R.; Borg, M. K.; Bray, D. J.; Grinberg, L.; Reese, J. M.

2016-11-01

Filtering of particle-based simulation data can lead to reduced computational costs and enable more efficient information transfer in multi-scale modelling. This paper compares the effectiveness of various signal processing methods to reduce numerical noise and capture the structures of nano-flow systems. In addition, a novel combination of these algorithms is introduced, showing the potential of hybrid strategies to improve further the de-noising performance for time-dependent measurements. The methods were tested on velocity and density fields, obtained from simulations performed with molecular dynamics and dissipative particle dynamics. Comparisons between the algorithms are given in terms of performance, quality of the results and sensitivity to the choice of input parameters. The results provide useful insights on strategies for the analysis of particle-based data and the reduction of computational costs in obtaining ensemble solutions.

Use of cultural probes for representation of chronic disease experience: exploration of an innovative method for design of supportive technologies.

PubMed

Hassling, Linda; Nordfeldt, Sam; Eriksson, Henrik; Timpka, Toomas

2005-01-01

Chronic diseases do not only manifest themselves as sets of pathophysiological factors. They bring about an equally important psychosocial impact. Unfortunately, it is difficult to account for this impact in the development of supportive technologies. This study describes and explores a method for elicitation of requirements on technologies supporting self-management including emotional aspects. The method takes advantage of a self-documentary media kit for collection of data from the everyday context of chronic disease. The resulting contextual data can contribute new insights to multi-disciplinary teams in the design of supporting technologies.

Multi-atlas segmentation with joint label fusion and corrective learning—an open source implementation

PubMed Central

Wang, Hongzhi; Yushkevich, Paul A.

2013-01-01

Label fusion based multi-atlas segmentation has proven to be one of the most competitive techniques for medical image segmentation. This technique transfers segmentations from expert-labeled images, called atlases, to a novel image using deformable image registration. Errors produced by label transfer are further reduced by label fusion that combines the results produced by all atlases into a consensus solution. Among the proposed label fusion strategies, weighted voting with spatially varying weight distributions derived from atlas-target intensity similarity is a simple and highly effective label fusion technique. However, one limitation of most weighted voting methods is that the weights are computed independently for each atlas, without taking into account the fact that different atlases may produce similar label errors. To address this problem, we recently developed the joint label fusion technique and the corrective learning technique, which won the first place of the 2012 MICCAI Multi-Atlas Labeling Challenge and was one of the top performers in 2013 MICCAI Segmentation: Algorithms, Theory and Applications (SATA) challenge. To make our techniques more accessible to the scientific research community, we describe an Insight-Toolkit based open source implementation of our label fusion methods. Our implementation extends our methods to work with multi-modality imaging data and is more suitable for segmentation problems with multiple labels. We demonstrate the usage of our tools through applying them to the 2012 MICCAI Multi-Atlas Labeling Challenge brain image dataset and the 2013 SATA challenge canine leg image dataset. We report the best results on these two datasets so far. PMID:24319427

Integration of multi-omics data for integrative gene regulatory network inference.

PubMed

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

2017-01-01

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

Integration of multi-omics data for integrative gene regulatory network inference

PubMed Central

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

2017-01-01

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

Gold nanotriangles decorated with superparamagnetic iron oxide nanoparticles: a compositional and microstructural study

DOE PAGES

Hachtel, J. A.; Yu, S.; Lupini, A. R.; ...

2016-03-11

The combination of iron oxide and gold in a single nanoparticle results in both magnetic and plasmonic properties that can stimulate novel applications in bio-sensing, medical imaging, or therapeutics. Microwave assisted heating allows the fabrication of multi-component, multi-functional nanostructures by promoting selective heating at desired sites. Recently, we reported a microwave-assisted polyol route yielding gold nanotriangles decorated with iron oxide nanoparticles. Here, we present an in-depth microstructural and compositional characterization of the system by using scanning transmission electron microscopy (STEM) and electron energy loss (EELS) spectroscopy. A method to remove the iron oxide nanoparticles from the gold nanocrystals and somemore » insights on crystal nucleation and growth mechanisms are also provided.« less

Art Treasure Quests in Second Life: A Multi-Literacy Adventure

ERIC Educational Resources Information Center

Stokrocki, Mary

2014-01-01

Treasure quests in virtual worlds can help students develop multi-literacy communication skills and promote community, offering insights about art teaching and learning. As part of the new media literacy, students explore the offerings of Second Life (SL), a virtual world, as a series of quests. Multi-literacy involves communication. Through their…

Harvesting multiple electron-hole pairs generated through plasmonic excitation of Au nanoparticles.

PubMed

Kim, Youngsoo; Smith, Jeremy G; Jain, Prashant K

2018-05-07

Multi-electron redox reactions, although central to artificial photosynthesis, are kinetically sluggish. Amidst the search for synthetic catalysts for such processes, plasmonic nanoparticles have been found to catalyse multi-electron reduction of CO 2 under visible light. This example motivates the need for a general, insight-driven framework for plasmonic catalysis of such multi-electron chemistry. Here, we elucidate the principles underlying the extraction of multiple redox equivalents from a plasmonic photocatalyst. We measure the kinetics of electron harvesting from a gold nanoparticle photocatalyst as a function of photon flux. Our measurements, supported by theoretical modelling, reveal a regime where two-electron transfer from the excited gold nanoparticle becomes prevalent. Multiple electron harvesting becomes possible under continuous-wave, visible-light excitation of moderate intensity due to strong interband transitions in gold and electron-hole separation accomplished using a hole scavenger. These insights will help expand the utility of plasmonic photocatalysis beyond CO 2 reduction to other challenging multi-electron, multi-proton transformations such as N 2 fixation.

Novel images extraction model using improved delay vector variance feature extraction and multi-kernel neural network for EEG detection and prediction.

PubMed

Ge, Jing; Zhang, Guoping

2015-01-01

Advanced intelligent methodologies could help detect and predict diseases from the EEG signals in cases the manual analysis is inefficient available, for instance, the epileptic seizures detection and prediction. This is because the diversity and the evolution of the epileptic seizures make it very difficult in detecting and identifying the undergoing disease. Fortunately, the determinism and nonlinearity in a time series could characterize the state changes. Literature review indicates that the Delay Vector Variance (DVV) could examine the nonlinearity to gain insight into the EEG signals but very limited work has been done to address the quantitative DVV approach. Hence, the outcomes of the quantitative DVV should be evaluated to detect the epileptic seizures. To develop a new epileptic seizure detection method based on quantitative DVV. This new epileptic seizure detection method employed an improved delay vector variance (IDVV) to extract the nonlinearity value as a distinct feature. Then a multi-kernel functions strategy was proposed in the extreme learning machine (ELM) network to provide precise disease detection and prediction. The nonlinearity is more sensitive than the energy and entropy. 87.5% overall accuracy of recognition and 75.0% overall accuracy of forecasting were achieved. The proposed IDVV and multi-kernel ELM based method was feasible and effective for epileptic EEG detection. Hence, the newly proposed method has importance for practical applications.

Problems With Deployment of Multi-Domained, Multi-Homed Mobile Networks

NASA Technical Reports Server (NTRS)

Ivancic, William D.

2008-01-01

This document describes numerous problems associated with deployment of multi-homed mobile platforms consisting of multiple networks and traversing large geographical areas. The purpose of this document is to provide insight to real-world deployment issues and provide information to groups that are addressing many issues related to multi-homing, policy-base routing, route optimization and mobile security - particularly those groups within the Internet Engineering Task Force.

Characterising switching behaviour in perceptual multi-stability.

PubMed

Denham, Susan; Bendixen, Alexandra; Mill, Robert; Tóth, Dénes; Wennekers, Thomas; Coath, Martin; Bőhm, Tamás; Szalardy, Orsolya; Winkler, István

2012-09-15

When people experience an unchanging sensory input for a long period of time, their perception tends to switch stochastically and unavoidably between alternative interpretations of the sensation; a phenomenon known as perceptual bi-stability or multi-stability. The huge variability in the experimental data obtained in such paradigms makes it difficult to distinguish typical patterns of behaviour, or to identify differences between switching patterns. Here we propose a new approach to characterising switching behaviour based upon the extraction of transition matrices from the data, which provide a compact representation that is well-understood mathematically. On the basis of this representation we can characterise patterns of perceptual switching, visualise and simulate typical switching patterns, and calculate the likelihood of observing a particular switching pattern. The proposed method can support comparisons between different observers, experimental conditions and even experiments. We demonstrate the insights offered by this approach using examples from our experiments investigating multi-stability in auditory streaming. However, the methodology is generic and thus widely applicable in studies of multi-stability in any domain. Copyright © 2012 Elsevier B.V. All rights reserved.

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.

Global Design Optimization for Aerodynamics and Rocket Propulsion Components

NASA Technical Reports Server (NTRS)

Shyy, Wei; Papila, Nilay; Vaidyanathan, Rajkumar; Tucker, Kevin; Turner, James E. (Technical Monitor)

2000-01-01

Modern computational and experimental tools for aerodynamics and propulsion applications have matured to a stage where they can provide substantial insight into engineering processes involving fluid flows, and can be fruitfully utilized to help improve the design of practical devices. In particular, rapid and continuous development in aerospace engineering demands that new design concepts be regularly proposed to meet goals for increased performance, robustness and safety while concurrently decreasing cost. To date, the majority of the effort in design optimization of fluid dynamics has relied on gradient-based search algorithms. Global optimization methods can utilize the information collected from various sources and by different tools. These methods offer multi-criterion optimization, handle the existence of multiple design points and trade-offs via insight into the entire design space, can easily perform tasks in parallel, and are often effective in filtering the noise intrinsic to numerical and experimental data. However, a successful application of the global optimization method needs to address issues related to data requirements with an increase in the number of design variables, and methods for predicting the model performance. In this article, we review recent progress made in establishing suitable global optimization techniques employing neural network and polynomial-based response surface methodologies. Issues addressed include techniques for construction of the response surface, design of experiment techniques for supplying information in an economical manner, optimization procedures and multi-level techniques, and assessment of relative performance between polynomials and neural networks. Examples drawn from wing aerodynamics, turbulent diffuser flows, gas-gas injectors, and supersonic turbines are employed to help demonstrate the issues involved in an engineering design context. Both the usefulness of the existing knowledge to aid current design practices and the need for future research are identified.

Multi-Phenomenological Analysis of the 12 August 2015 Tianjin, China Chemical Explosion

NASA Astrophysics Data System (ADS)

Pasyanos, M.; Kim, K.; Park, J.; Stump, B. W.; Hayward, C.; Che, I. Y.; Zhao, L.; Myers, S. C.

2016-12-01

We perform a multi-phenomenological analysis of the massive near-surface chemical explosions that occurred in Tianjin, China on 12 August 2015. A recent assessment of these events was performed by Zhao et al. (2016) using local (< 100 km) seismic data. This study considers a regional assessment of the same sequence in the absence of having any local data. We provide additional insight by combining regional seismic analysis with the use of infrasound signals and an assessment of the event crater. Event locations using infrasound signals recorded at Korean and IMS arrays are estimated based on the Bayesian Infrasonic Source Location (BISL) method (Modrak et al., 2010), and improved with azimuthal corrections using a raytracing (Blom and Waxler, 2012) and the Ground-to-Space (G2S) atmospheric models (Drob et al., 2003). The location information provided from the infrasound signals is then merged with the regional seismic arrivals to produce a joint event location. The yields of the events are estimated from seismic and infrasonic observations. Seismic waveform envelope method (Pasyanos et al., 2012) including the free surface effect (Pasyanos and Ford, 2015) is applied to regional seismic signals. Waveform inversion method (Kim and Rodgers, 2016) is used for infrasound signals. A combination of the seismic and acoustic signals can provide insights on the energy partitioning and break the tradeoffs between the yield and the depth/height of explosions, resulting in a more robust estimation of event yield. The yield information from the different phenomenologies are combined through the use of likelihood functions.

Analyzing compound and project progress through multi-objective-based compound quality assessment.

PubMed

Nissink, J Willem M; Degorce, Sébastien

2013-05-01

Compound-quality scoring methods designed to evaluate multiple drug properties concurrently are useful to analyze and prioritize output from drug-design efforts. However, formalized multiparameter optimization approaches are not widely used in drug design. We rank molecules synthesized in drug-discovery projects using simple and aggregated desirability functions reflecting medicinal chemistry 'rules'. Our quality score deals transparently with missing data, a key requirement in drug-hunting projects where data availability is often limited. We further estimate confidence in the interpretation of such a compound-quality measure. Scores and associated confidences provide systematic insight in the quality of emerging chemical equity. Tracking quality of synthetic output over time yields valuable insight into the progress of drug-design teams, with potential applications in risk and resource management of a drug portfolio.

Path lumping: An efficient algorithm to identify metastable path channels for conformational dynamics of multi-body systems

NASA Astrophysics Data System (ADS)

Meng, Luming; Sheong, Fu Kit; Zeng, Xiangze; Zhu, Lizhe; Huang, Xuhui

2017-07-01

Constructing Markov state models from large-scale molecular dynamics simulation trajectories is a promising approach to dissect the kinetic mechanisms of complex chemical and biological processes. Combined with transition path theory, Markov state models can be applied to identify all pathways connecting any conformational states of interest. However, the identified pathways can be too complex to comprehend, especially for multi-body processes where numerous parallel pathways with comparable flux probability often coexist. Here, we have developed a path lumping method to group these parallel pathways into metastable path channels for analysis. We define the similarity between two pathways as the intercrossing flux between them and then apply the spectral clustering algorithm to lump these pathways into groups. We demonstrate the power of our method by applying it to two systems: a 2D-potential consisting of four metastable energy channels and the hydrophobic collapse process of two hydrophobic molecules. In both cases, our algorithm successfully reveals the metastable path channels. We expect this path lumping algorithm to be a promising tool for revealing unprecedented insights into the kinetic mechanisms of complex multi-body processes.

Integrated Assessment by the People: Insights from AgMIP Regional Teams in Sub-Saharan Africa and South Asia

NASA Astrophysics Data System (ADS)

Antle, J. M.

2017-12-01

AgMIP has developed innovative protocol-based methods for regional integrated assessment (RIA) that can be implemented by national researchers working with local and national stakeholders (http://www.agmip.org/regional-integrated-assessments-handbook/). The approach has been implemented by regional teams in Sub-Saharan Africa and South Asia. This presentation first summarizes novel elements of the AgMIP RIA methods, and their strengths and limitations, based on their application by AgMIP researchers. Key insights from the application of these methods for climate impact and adaptation in Sub-Saharan Africa and South Asia are presented. A major finding is that detailed, site-specific, systems-based analysis show much more local and regional variation in impacts than studies based on analysis of individual crops, and provide the basis for analysis of multi-faceted technology and policy options to facilitate the transition to sustainable and resilient development pathways. The presentation concludes with observations about advancing integrated assessments carried out by and for national and local researchers and stakeholders.

A molecular informatics view on best practice in multi-parameter compound optimization.

PubMed

Lusher, Scott J; McGuire, Ross; Azevedo, Rita; Boiten, Jan-Willem; van Schaik, Rene C; de Vlieg, Jacob

2011-07-01

The difference between biologically active molecules and drugs is that the latter balance an array of related and unrelated properties required for administration to patients. Inevitability, during optimization, some of these multiple factors will conflict. Although informatics has a crucial role in addressing the challenges of modern compound optimization, it is arguably still undervalued and underutilized. We present here some of the basic requirements of multi-parameter drug design, the crucial role of informatics and examples of favorable practice. The most crucial of these best practices are the need for informaticians to align their technologies and insights directly to discovery projects and for all scientists in drug discovery to become more proficient in the use of in silico methods. Copyright © 2011 Elsevier Ltd. All rights reserved.

The Potential for Double-Loop Learning to Enable Landscape Conservation Efforts

NASA Astrophysics Data System (ADS)

Petersen, Brian; Montambault, Jensen; Koopman, Marni

2014-10-01

As conservation increases its emphasis on implementing change at landscape-level scales, multi-agency, cross-boundary, and multi-stakeholder networks become more important. These elements complicate traditional notions of learning. To investigate this further, we examined structures of learning in the Landscape Conservation Cooperatives (LCCs), which include the entire US and its territories, as well as parts of Canada, Mexico, and Caribbean and Pacific island states. We used semi-structured interviews, transcribed and analyzed using NVivo, as well as a charrette-style workshop to understand the difference between the original stated goals of individual LCCs and the values and purposes expressed as the collaboration matured. We suggest double-loop learning as a theoretical framework appropriate to landscape-scale conservation, recognizing that concerns about accountability are among the valid points of view that must be considered in multi-stakeholder collaborations. Methods from the social sciences and public health sectors provide insights on how such learning might be actualized.

A Fictitious Domain Method for Resolving the Interaction of Blood Flow with Clot Growth

NASA Astrophysics Data System (ADS)

Mukherjee, Debanjan; Shadden, Shawn

2016-11-01

Thrombosis and thrombo-embolism cause a range of diseases including heart attack and stroke. Closer understanding of clot and blood flow mechanics provides valuable insights on the etiology, diagnosis, and treatment of thrombotic diseases. Such mechanics are complicated, however, by the discrete and multi-scale phenomena underlying thrombosis, and the complex interactions of unsteady, pulsatile hemodynamics with a clot of arbitrary shape and microstructure. We have developed a computational technique, based on a fictitious domain based finite element method, to study these interactions. The method can resolve arbitrary clot geometries, and dynamically couple fluid flow with static or growing clot boundaries. Macroscopic thrombus-hemodynamics interactions were investigated within idealized vessel geometries representative of the common carotid artery, with realistic unsteady flow profiles as inputs. The method was also employed successfully to resolve micro-scale interactions using a model driven by in-vivo morphology data. The results provide insights into the flow structures and hemodynamic loading around an arbitrarily grown clot at arterial length-scales, as well as flow and transport within the interstices of platelet aggregates composing the clot. The work was supported by AHA Award No: 16POST27500023.

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.

Deep Learning to Predict Falls in Older Adults Based on Daily-Life Trunk Accelerometry.

PubMed

Nait Aicha, Ahmed; Englebienne, Gwenn; van Schooten, Kimberley S; Pijnappels, Mirjam; Kröse, Ben

2018-05-22

Early detection of high fall risk is an essential component of fall prevention in older adults. Wearable sensors can provide valuable insight into daily-life activities; biomechanical features extracted from such inertial data have been shown to be of added value for the assessment of fall risk. Body-worn sensors such as accelerometers can provide valuable insight into fall risk. Currently, biomechanical features derived from accelerometer data are used for the assessment of fall risk. Here, we studied whether deep learning methods from machine learning are suited to automatically derive features from raw accelerometer data that assess fall risk. We used an existing dataset of 296 older adults. We compared the performance of three deep learning model architectures (convolutional neural network (CNN), long short-term memory (LSTM) and a combination of these two (ConvLSTM)) to each other and to a baseline model with biomechanical features on the same dataset. The results show that the deep learning models in a single-task learning mode are strong in recognition of identity of the subject, but that these models only slightly outperform the baseline method on fall risk assessment. When using multi-task learning, with gender and age as auxiliary tasks, deep learning models perform better. We also found that preprocessing of the data resulted in the best performance (AUC = 0.75). We conclude that deep learning models, and in particular multi-task learning, effectively assess fall risk on the basis of wearable sensor data.

Deep Learning to Predict Falls in Older Adults Based on Daily-Life Trunk Accelerometry

PubMed Central

Englebienne, Gwenn; Pijnappels, Mirjam

2018-01-01

Early detection of high fall risk is an essential component of fall prevention in older adults. Wearable sensors can provide valuable insight into daily-life activities; biomechanical features extracted from such inertial data have been shown to be of added value for the assessment of fall risk. Body-worn sensors such as accelerometers can provide valuable insight into fall risk. Currently, biomechanical features derived from accelerometer data are used for the assessment of fall risk. Here, we studied whether deep learning methods from machine learning are suited to automatically derive features from raw accelerometer data that assess fall risk. We used an existing dataset of 296 older adults. We compared the performance of three deep learning model architectures (convolutional neural network (CNN), long short-term memory (LSTM) and a combination of these two (ConvLSTM)) to each other and to a baseline model with biomechanical features on the same dataset. The results show that the deep learning models in a single-task learning mode are strong in recognition of identity of the subject, but that these models only slightly outperform the baseline method on fall risk assessment. When using multi-task learning, with gender and age as auxiliary tasks, deep learning models perform better. We also found that preprocessing of the data resulted in the best performance (AUC = 0.75). We conclude that deep learning models, and in particular multi-task learning, effectively assess fall risk on the basis of wearable sensor data. PMID:29786659

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.

Investigation of a dual modal method for bone pathologies using quantitative ultrasound and photoacoustics

NASA Astrophysics Data System (ADS)

Steinberg, Idan; Gannot, Israel; Eyal, Avishay

2015-03-01

Osteoporosis is a widespread disease that has a catastrophic impact on patient's lives and overwhelming related healthcare costs. In recent works, we have developed a multi-spectral, frequency domain photoacoustic method for the evaluation of bone pathologies. This method has great advantages over pure ultrasonic or optical methods as it provides both molecular information from the bone absorption spectrum and bone mechanical status from the characteristics of the ultrasound propagation. These characteristics include both the Speed of Sound (SOS) and Broadband Ultrasonic Attenuation (BUA). To test the method's quantitative predictions, we have constructed a combined ultrasound and photoacoustic setup. Here, we experimentally present a dual modality system, and compares between the methods on bone samples in-vitro. The differences between the two modalities are shown to provide valuable insight into the bone structure and functional status.

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.

Uncertainty analysis of multi-rate kinetics of uranium desorption from sediments

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

Zhang, Xiaoying; Liu, Chongxuan; Hu, Bill X.

2014-01-01

A multi-rate expression for uranyl [U(VI)] surface complexation reactions has been proposed to describe diffusion-limited U(VI) sorption/desorption in heterogeneous subsurface sediments. An important assumption in the rate expression is that its rate constants follow a certain type probability distribution. In this paper, a Bayes-based, Differential Evolution Markov Chain method was used to assess the distribution assumption and to analyze parameter and model structure uncertainties. U(VI) desorption from a contaminated sediment at the US Hanford 300 Area, Washington was used as an example for detail analysis. The results indicated that: 1) the rate constants in the multi-rate expression contain uneven uncertaintiesmore » with slower rate constants having relative larger uncertainties; 2) the lognormal distribution is an effective assumption for the rate constants in the multi-rate model to simualte U(VI) desorption; 3) however, long-term prediction and its uncertainty may be significantly biased by the lognormal assumption for the smaller rate constants; and 4) both parameter and model structure uncertainties can affect the extrapolation of the multi-rate model with a larger uncertainty from the model structure. The results provide important insights into the factors contributing to the uncertainties of the multi-rate expression commonly used to describe the diffusion or mixing-limited sorption/desorption of both organic and inorganic contaminants in subsurface sediments.« less

Versatile multi-functionalization of protein nanofibrils for biosensor applications

NASA Astrophysics Data System (ADS)

Sasso, L.; Suei, S.; Domigan, L.; Healy, J.; Nock, V.; Williams, M. A. K.; Gerrard, J. A.

2014-01-01

Protein nanofibrils offer advantages over other nanostructures due to the ease in their self-assembly and the versatility of surface chemistry available. Yet, an efficient and general methodology for their post-assembly functionalization remains a significant challenge. We introduce a generic approach, based on biotinylation and thiolation, for the multi-functionalization of protein nanofibrils self-assembled from whey proteins. Biochemical characterization shows the effects of the functionalization onto the nanofibrils' surface, giving insights into the changes in surface chemistry of the nanostructures. We show how these methods can be used to decorate whey protein nanofibrils with several components such as fluorescent quantum dots, enzymes, and metal nanoparticles. A multi-functionalization approach is used, as a proof of principle, for the development of a glucose biosensor platform, where the protein nanofibrils act as nanoscaffolds for glucose oxidase. Biotinylation is used for enzyme attachment and thiolation for nanoscaffold anchoring onto a gold electrode surface. Characterization via cyclic voltammetry shows an increase in glucose-oxidase mediated current response due to thiol-metal interactions with the gold electrode. The presented approach for protein nanofibril multi-functionalization is novel and has the potential of being applied to other protein nanostructures with similar surface chemistry.Protein nanofibrils offer advantages over other nanostructures due to the ease in their self-assembly and the versatility of surface chemistry available. Yet, an efficient and general methodology for their post-assembly functionalization remains a significant challenge. We introduce a generic approach, based on biotinylation and thiolation, for the multi-functionalization of protein nanofibrils self-assembled from whey proteins. Biochemical characterization shows the effects of the functionalization onto the nanofibrils' surface, giving insights into the changes in surface chemistry of the nanostructures. We show how these methods can be used to decorate whey protein nanofibrils with several components such as fluorescent quantum dots, enzymes, and metal nanoparticles. A multi-functionalization approach is used, as a proof of principle, for the development of a glucose biosensor platform, where the protein nanofibrils act as nanoscaffolds for glucose oxidase. Biotinylation is used for enzyme attachment and thiolation for nanoscaffold anchoring onto a gold electrode surface. Characterization via cyclic voltammetry shows an increase in glucose-oxidase mediated current response due to thiol-metal interactions with the gold electrode. The presented approach for protein nanofibril multi-functionalization is novel and has the potential of being applied to other protein nanostructures with similar surface chemistry. Electronic supplementary information (ESI) available: Cyclic voltammetry characterization of biosensor platforms including bare Au electrodes (Fig. S1), biosensor response to various glucose concentrations (Fig. S2), and AFM roughness measurements due to WPNF modifications (Fig. S3). See DOI: 10.1039/c3nr05752f

Multi-haem cytochromes in Shewanella oneidensis MR-1: structures, functions and opportunities

PubMed Central

Breuer, Marian; Rosso, Kevin M.; Blumberger, Jochen; Butt, Julea N.

2015-01-01

Multi-haem cytochromes are employed by a range of microorganisms to transport electrons over distances of up to tens of nanometres. Perhaps the most spectacular utilization of these proteins is in the reduction of extracellular solid substrates, including electrodes and insoluble mineral oxides of Fe(III) and Mn(III/IV), by species of Shewanella and Geobacter. However, multi-haem cytochromes are found in numerous and phylogenetically diverse prokaryotes where they participate in electron transfer and redox catalysis that contributes to biogeochemical cycling of N, S and Fe on the global scale. These properties of multi-haem cytochromes have attracted much interest and contributed to advances in bioenergy applications and bioremediation of contaminated soils. Looking forward, there are opportunities to engage multi-haem cytochromes for biological photovoltaic cells, microbial electrosynthesis and developing bespoke molecular devices. As a consequence, it is timely to review our present understanding of these proteins and we do this here with a focus on the multitude of functionally diverse multi-haem cytochromes in Shewanella oneidensis MR-1. We draw on findings from experimental and computational approaches which ideally complement each other in the study of these systems: computational methods can interpret experimentally determined properties in terms of molecular structure to cast light on the relation between structure and function. We show how this synergy has contributed to our understanding of multi-haem cytochromes and can be expected to continue to do so for greater insight into natural processes and their informed exploitation in biotechnologies. PMID:25411412

Topological invariant and cotranslational symmetry in strongly interacting multi-magnon systems

NASA Astrophysics Data System (ADS)

Qin, Xizhou; Mei, Feng; Ke, Yongguan; Zhang, Li; Lee, Chaohong

2018-01-01

It is still an outstanding challenge to characterize and understand the topological features of strongly interacting states such as bound states in interacting quantum systems. Here, by introducing a cotranslational symmetry in an interacting multi-particle quantum system, we systematically develop a method to define a Chern invariant, which is a generalization of the well-known Thouless-Kohmoto-Nightingale-den Nijs invariant, for identifying strongly interacting topological states. As an example, we study the topological multi-magnon states in a generalized Heisenberg XXZ model, which can be realized by the currently available experiment techniques of cold atoms (Aidelsburger et al 2013 Phys. Rev. Lett. 111, 185301; Miyake et al 2013 Phys. Rev. Lett. 111, 185302). Through calculating the two-magnon excitation spectrum and the defined Chern number, we explore the emergence of topological edge bound states and give their topological phase diagram. We also analytically derive an effective single-particle Hofstadter superlattice model for a better understanding of the topological bound states. Our results not only provide a new approach to defining a topological invariant for interacting multi-particle systems, but also give insights into the characterization and understanding of strongly interacting topological states.

Physical insights into the blood-brain barrier translocation mechanisms

NASA Astrophysics Data System (ADS)

Theodorakis, Panagiotis E.; Müller, Erich A.; Craster, Richard V.; Matar, Omar K.

2017-08-01

The number of individuals suffering from diseases of the central nervous system (CNS) is growing with an aging population. While candidate drugs for many of these diseases are available, most of these pharmaceutical agents cannot reach the brain rendering most of the drug therapies that target the CNS inefficient. The reason is the blood-brain barrier (BBB), a complex and dynamic interface that controls the influx and efflux of substances through a number of different translocation mechanisms. Here, we present these mechanisms providing, also, the necessary background related to the morphology and various characteristics of the BBB. Moreover, we discuss various numerical and simulation approaches used to study the BBB, and possible future directions based on multi-scale methods. We anticipate that this review will motivate multi-disciplinary research on the BBB aiming at the design of effective drug therapies.

Temporal Drivers of Liking Based on Functional Data Analysis and Non-Additive Models for Multi-Attribute Time-Intensity Data of Fruit Chews.

PubMed

Kuesten, Carla; Bi, Jian

2018-06-03

Conventional drivers of liking analysis was extended with a time dimension into temporal drivers of liking (TDOL) based on functional data analysis methodology and non-additive models for multiple-attribute time-intensity (MATI) data. The non-additive models, which consider both direct effects and interaction effects of attributes to consumer overall liking, include Choquet integral and fuzzy measure in the multi-criteria decision-making, and linear regression based on variance decomposition. Dynamics of TDOL, i.e., the derivatives of the relative importance functional curves were also explored. Well-established R packages 'fda', 'kappalab' and 'relaimpo' were used in the paper for developing TDOL. Applied use of these methods shows that the relative importance of MATI curves offers insights for understanding the temporal aspects of consumer liking for fruit chews.

Insights on unconventional natural gas development from shale: an interview with Anthony R. Ingraffea by Adam Law.

PubMed

Ingraffea, Anthony R

2013-01-01

Adam Law, M.D., interviewed Anthony R. Ingraffea, Ph.D., P.E., as part of a series of interviews funded by the Heinz Endowment. Dr. Ingraffea is the Dwight C. Baum Professor of Engineering at Cornell University, and has taught structural mechanics, finite element methods, and fracture mechanics at Cornell for 33 years. He discusses issues related to hydraulic fracturing, including inherent risks, spatial intensity, and the importance of a multi-disciplinary organization in establishing a chain of evidence.

On Using Meta-Modeling and Multi-Modeling to Address Complex Problems

ERIC Educational Resources Information Center

Abu Jbara, Ahmed

2013-01-01

Models, created using different modeling techniques, usually serve different purposes and provide unique insights. While each modeling technique might be capable of answering specific questions, complex problems require multiple models interoperating to complement/supplement each other; we call this Multi-Modeling. To address the syntactic and…

SubClonal Hierarchy Inference from Somatic Mutations: Automatic Reconstruction of Cancer Evolutionary Trees from Multi-region Next Generation Sequencing

PubMed Central

Niknafs, Noushin; Beleva-Guthrie, Violeta; Naiman, Daniel Q.; Karchin, Rachel

2015-01-01

Recent improvements in next-generation sequencing of tumor samples and the ability to identify somatic mutations at low allelic fractions have opened the way for new approaches to model the evolution of individual cancers. The power and utility of these models is increased when tumor samples from multiple sites are sequenced. Temporal ordering of the samples may provide insight into the etiology of both primary and metastatic lesions and rationalizations for tumor recurrence and therapeutic failures. Additional insights may be provided by temporal ordering of evolving subclones—cellular subpopulations with unique mutational profiles. Current methods for subclone hierarchy inference tightly couple the problem of temporal ordering with that of estimating the fraction of cancer cells harboring each mutation. We present a new framework that includes a rigorous statistical hypothesis test and a collection of tools that make it possible to decouple these problems, which we believe will enable substantial progress in the field of subclone hierarchy inference. The methods presented here can be flexibly combined with methods developed by others addressing either of these problems. We provide tools to interpret hypothesis test results, which inform phylogenetic tree construction, and we introduce the first genetic algorithm designed for this purpose. The utility of our framework is systematically demonstrated in simulations. For most tested combinations of tumor purity, sequencing coverage, and tree complexity, good power (≥ 0.8) can be achieved and Type 1 error is well controlled when at least three tumor samples are available from a patient. Using data from three published multi-region tumor sequencing studies of (murine) small cell lung cancer, acute myeloid leukemia, and chronic lymphocytic leukemia, in which the authors reconstructed subclonal phylogenetic trees by manual expert curation, we show how different configurations of our tools can identify either a single tree in agreement with the authors, or a small set of trees, which include the authors’ preferred tree. Our results have implications for improved modeling of tumor evolution and the importance of multi-region tumor sequencing. PMID:26436540

Addendum to foundations of multidimensional wave field signal theory: Gaussian source function

NASA Astrophysics Data System (ADS)

Baddour, Natalie

2018-02-01

Many important physical phenomena are described by wave or diffusion-wave type equations. Recent work has shown that a transform domain signal description from linear system theory can give meaningful insight to multi-dimensional wave fields. In N. Baddour [AIP Adv. 1, 022120 (2011)], certain results were derived that are mathematically useful for the inversion of multi-dimensional Fourier transforms, but more importantly provide useful insight into how source functions are related to the resulting wave field. In this short addendum to that work, it is shown that these results can be applied with a Gaussian source function, which is often useful for modelling various physical phenomena.

Approximate analytical modeling of leptospirosis infection

NASA Astrophysics Data System (ADS)

Ismail, Nur Atikah; Azmi, Amirah; Yusof, Fauzi Mohamed; Ismail, Ahmad Izani

2017-11-01

Leptospirosis is an infectious disease carried by rodents which can cause death in humans. The disease spreads directly through contact with feces, urine or through bites of infected rodents and indirectly via water contaminated with urine and droppings from them. Significant increase in the number of leptospirosis cases in Malaysia caused by the recent severe floods were recorded during heavy rainfall season. Therefore, to understand the dynamics of leptospirosis infection, a mathematical model based on fractional differential equations have been developed and analyzed. In this paper an approximate analytical method, the multi-step Laplace Adomian decomposition method, has been used to conduct numerical simulations so as to gain insight on the spread of leptospirosis infection.

Correlative Tomography

PubMed Central

Burnett, T. L.; McDonald, S. A.; Gholinia, A.; Geurts, R.; Janus, M.; Slater, T.; Haigh, S. J.; Ornek, C.; Almuaili, F.; Engelberg, D. L.; Thompson, G. E.; Withers, P. J.

2014-01-01

Increasingly researchers are looking to bring together perspectives across multiple scales, or to combine insights from different techniques, for the same region of interest. To this end, correlative microscopy has already yielded substantial new insights in two dimensions (2D). Here we develop correlative tomography where the correlative task is somewhat more challenging because the volume of interest is typically hidden beneath the sample surface. We have threaded together x-ray computed tomography, serial section FIB-SEM tomography, electron backscatter diffraction and finally TEM elemental analysis all for the same 3D region. This has allowed observation of the competition between pitting corrosion and intergranular corrosion at multiple scales revealing the structural hierarchy, crystallography and chemistry of veiled corrosion pits in stainless steel. With automated correlative workflows and co-visualization of the multi-scale or multi-modal datasets the technique promises to provide insights across biological, geological and materials science that are impossible using either individual or multiple uncorrelated techniques. PMID:24736640

Mycotoxin production by pure fungal isolates analysed by means of an uhplc-ms/ms multi-mycotoxin method with possible pitfalls and solutions for patulin-producing isolates.

PubMed

Van Pamel, Els; Vlaemynck, Geertrui; Heyndrickx, Marc; Herman, Lieve; Verbeken, Annemieke; Daeseleire, Els

2011-02-01

This study is the first report of applying an ultra high performance liquid chromatography/tandem mass spectrometric (UHPLC-MS/MS) multi-mycotoxin method to identify and quantify the mycotoxins produced by pure fungal isolates grown on Yeast Extract Sucrose (YES) agar. The method developed concerns a triple extraction procedure based on methanol, dichloromethane and ethyl acetate. The total extract was chromatographically separated on an UHPLC BEH C18 column and analyzed with a triple quadrupole mass spectrometer. Performance characteristics (specificity, linearity, possible matrix effects, recovery, repeatability, reproducibility and limit of detection) were evaluated by spiking experiments with blank agar plugs and the analytes. Verrucarol was used as internal standard. Recovery percentages varied between 56 and 125%, whereas the limit of detection ranged from 1 to 1,500 ng g(-1) with the exception of NIV, PAT and ZEA. The method was successfully applied for examining the in vitro mycotoxin production by Aspergillus fumigatus, A. flavus and A. niger. The mobile phases used for chromatographic separation were slightly modified when studying patulin-producing molds due to signal interference between this mycotoxin and an unknown metabolite. This modified method was successfully applied for Penicillium roqueforti, P. paneum and P. carneum grown on YES agar medium. Application of the multi-mycotoxin UHPLC-MS/MS method developed may be of great importance for studying the mycotoxin capacity of fungal isolates under varying growth conditions, in order to obtain a better insight into the conditions which induce or suppress mycotoxin production by pure fungal isolates or from a chemotaxonomic point of view.

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

Multi-Scale Computational Enzymology: Enhancing Our Understanding of Enzymatic Catalysis

PubMed Central

Gherib, Rami; Dokainish, Hisham M.; Gauld, James W.

2014-01-01

Elucidating the origin of enzymatic catalysis stands as one the great challenges of contemporary biochemistry and biophysics. The recent emergence of computational enzymology has enhanced our atomistic-level description of biocatalysis as well the kinetic and thermodynamic properties of their mechanisms. There exists a diversity of computational methods allowing the investigation of specific enzymatic properties. Small or large density functional theory models allow the comparison of a plethora of mechanistic reactive species and divergent catalytic pathways. Molecular docking can model different substrate conformations embedded within enzyme active sites and determine those with optimal binding affinities. Molecular dynamics simulations provide insights into the dynamics and roles of active site components as well as the interactions between substrate and enzymes. Hybrid quantum mechanical/molecular mechanical (QM/MM) can model reactions in active sites while considering steric and electrostatic contributions provided by the surrounding environment. Using previous studies done within our group, on OvoA, EgtB, ThrRS, LuxS and MsrA enzymatic systems, we will review how these methods can be used either independently or cooperatively to get insights into enzymatic catalysis. PMID:24384841

Distributed representations in memory: Insights from functional brain imaging

PubMed Central

Rissman, Jesse; Wagner, Anthony D.

2015-01-01

Forging new memories for facts and events, holding critical details in mind on a moment-to-moment basis, and retrieving knowledge in the service of current goals all depend on a complex interplay between neural ensembles throughout the brain. Over the past decade, researchers have increasingly leveraged powerful analytical tools (e.g., multi-voxel pattern analysis) to decode the information represented within distributed fMRI activity patterns. In this review, we discuss how these methods can sensitively index neural representations of perceptual and semantic content, and how leverage on the engagement of distributed representations provides unique insights into distinct aspects of memory-guided behavior. We emphasize that, in addition to characterizing the contents of memories, analyses of distributed patterns shed light on the processes that influence how information is encoded, maintained, or retrieved, and thus inform memory theory. We conclude by highlighting open questions about memory that can be addressed through distributed pattern analyses. PMID:21943171

Continually emerging mechanistic complexity of the multi-enzyme cellulosome complex.

PubMed

Smith, Steven P; Bayer, Edward A; Czjzek, Mirjam

2017-06-01

The robust plant cell wall polysaccharide-degrading properties of anaerobic bacteria are harnessed within elegant, marcomolecular assemblages called cellulosomes, in which proteins of complementary activities amass on scaffold protein networks. Research efforts have focused and continue to focus on providing detailed mechanistic insights into cellulosomal complex assembly, topology, and function. The accumulated information is expanding our fundamental understanding of the lignocellulosic biomass decomposition process and enhancing the potential of engineered cellulosomal systems for biotechnological purposes. Ongoing biochemical studies continue to reveal unexpected functional diversity within traditional cellulase families. Genomic, proteomic, and functional analyses have uncovered unanticipated cellulosomal proteins that augment the function of the native and designer cellulosomes. In addition, complementary structural and computational methods are continuing to provide much needed insights on the influence of cellulosomal interdomain linker regions on cellulosomal assembly and activity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Understanding and Improving Multi-Sectoral Partnerships for Chronic Disease Prevention: Blending Conceptual and Practical Insights

ERIC Educational Resources Information Center

Willis, Cameron; Greene, Julie; Riley, Barbara

2017-01-01

Inter-organisational partnerships are widely used approaches in public health and chronic disease prevention (CDP), and may include organisations from different sectors, such as research-policy-practice sectors, inter-governmental sectors, or public and private sectors. While multiple conceptual frameworks related to multi-sectoral partnerships…

"Martin Luther King Stopped Discrimination": Multi-Generational Latino Elementary Students' Perceptions of Social Issues

ERIC Educational Resources Information Center

Curwen, Margie Sauceda

2011-01-01

This study explored how multi-generational, middle-class, fifth-graders from Latino families responded to classroom discussions of social issues--particularly discrimination--and draws upon sociocultural views of culture, educational theory, and sociological perspectives of immigration to provide insight into the learning experiences of one group…

Multilayer Brain Networks

NASA Astrophysics Data System (ADS)

Vaiana, Michael; Muldoon, Sarah Feldt

2018-01-01

The field of neuroscience is facing an unprecedented expanse in the volume and diversity of available data. Traditionally, network models have provided key insights into the structure and function of the brain. With the advent of big data in neuroscience, both more sophisticated models capable of characterizing the increasing complexity of the data and novel methods of quantitative analysis are needed. Recently, multilayer networks, a mathematical extension of traditional networks, have gained increasing popularity in neuroscience due to their ability to capture the full information of multi-model, multi-scale, spatiotemporal data sets. Here, we review multilayer networks and their applications in neuroscience, showing how incorporating the multilayer framework into network neuroscience analysis has uncovered previously hidden features of brain networks. We specifically highlight the use of multilayer networks to model disease, structure-function relationships, network evolution, and link multi-scale data. Finally, we close with a discussion of promising new directions of multilayer network neuroscience research and propose a modified definition of multilayer networks designed to unite and clarify the use of the multilayer formalism in describing real-world systems.

Control design methods for floating wind turbines for optimal disturbance rejection

NASA Astrophysics Data System (ADS)

Lemmer, Frank; Schlipf, David; Cheng, Po Wen

2016-09-01

An analysis of the floating wind turbine as a multi-input-multi-output system investigating the effect of the control inputs on the system outputs is shown. These effects are compared to the ones of the disturbances from wind and waves in order to give insights for the selection of the control layout. The frequencies with the largest impact on the outputs due to limited effect of the controlled variables are identified. Finally, an optimal controller is designed as a benchmark and compared to a conventional PI-controller using only the rotor speed as input. Here, the previously found system properties, especially the difficulties to damp responses to wave excitation, are confirmed and verified through a spectral analysis with realistic environmental conditions. This comparison also assesses the quality of the employed simplified linear simulation model compared to the nonlinear model and shows that such an efficient frequency-domain evaluation for control design is feasible.

A multi-component evaporation model for beam melting processes

NASA Astrophysics Data System (ADS)

Klassen, Alexander; Forster, Vera E.; Körner, Carolin

2017-02-01

In additive manufacturing using laser or electron beam melting technologies, evaporation losses and changes in chemical composition are known issues when processing alloys with volatile elements. In this paper, a recently described numerical model based on a two-dimensional free surface lattice Boltzmann method is further developed to incorporate the effects of multi-component evaporation. The model takes into account the local melt pool composition during heating and fusion of metal powder. For validation, the titanium alloy Ti-6Al-4V is melted by selective electron beam melting and analysed using mass loss measurements and high-resolution microprobe imaging. Numerically determined evaporation losses and spatial distributions of aluminium compare well with experimental data. Predictions of the melt pool formation in bulk samples provide insight into the competition between the loss of volatile alloying elements from the irradiated surface and their advective redistribution within the molten region.

Multi-component quantitation of meso/nanostructural surfaces and its application to local chemical compositions of copper meso/nanostructures self-organized on silica

NASA Astrophysics Data System (ADS)

Huang, Chun-Yi; Chang, Hsin-Wei; Chang, Che-Chen

2018-03-01

Knowledge about the chemical compositions of meso/nanomaterials is fundamental to development of their applications in advanced technologies. Auger electron spectroscopy (AES) is an effective analysis method for the characterization of meso/nanomaterial structures. Although a few studies have reported the use of AES for the analysis of the local composition of these structures, none have explored in detail the validity of the meso/nanoanalysis results generated by the AES instrument. This paper addresses the limitations of AES and the corrections necessary to offset them for this otherwise powerful meso/nanoanalysis tool. The results of corrections made to the AES multi-point analysis of high-density copper-based meso/nanostructures provides major insights into their local chemical compositions and technological prospects, which the primitive composition output of the AES instrument failed to provide.

Efficient solution of 3D electromagnetic eddy-current problems within the finite volume framework of OpenFOAM

NASA Astrophysics Data System (ADS)

Beckstein, Pascal; Galindo, Vladimir; Vukčević, Vuko

2017-09-01

Eddy-current problems occur in a wide range of industrial and metallurgical applications where conducting material is processed inductively. Motivated by realising coupled multi-physics simulations, we present a new method for the solution of such problems in the finite volume framework of foam-extend, an extended version of the very popular OpenFOAM software. The numerical procedure involves a semi-coupled multi-mesh approach to solve Maxwell's equations for non-magnetic materials by means of the Coulomb gauged magnetic vector potential A and the electric scalar potential ϕ. The concept is further extended on the basis of the impressed and reduced magnetic vector potential and its usage in accordance with Biot-Savart's law to achieve a very efficient overall modelling even for complex three-dimensional geometries. Moreover, we present a special discretisation scheme to account for possible discontinuities in the electrical conductivity. To complement our numerical method, an extensive validation is completing the paper, which provides insight into the behaviour and the potential of our approach.

Alignment-free microbial phylogenomics under scenarios of sequence divergence, genome rearrangement and lateral genetic transfer.

PubMed

Bernard, Guillaume; Chan, Cheong Xin; Ragan, Mark A

2016-07-01

Alignment-free (AF) approaches have recently been highlighted as alternatives to methods based on multiple sequence alignment in phylogenetic inference. However, the sensitivity of AF methods to genome-scale evolutionary scenarios is little known. Here, using simulated microbial genome data we systematically assess the sensitivity of nine AF methods to three important evolutionary scenarios: sequence divergence, lateral genetic transfer (LGT) and genome rearrangement. Among these, AF methods are most sensitive to the extent of sequence divergence, less sensitive to low and moderate frequencies of LGT, and most robust against genome rearrangement. We describe the application of AF methods to three well-studied empirical genome datasets, and introduce a new application of the jackknife to assess node support. Our results demonstrate that AF phylogenomics is computationally scalable to multi-genome data and can generate biologically meaningful phylogenies and insights into microbial evolution.

Multi-heme Cytochromes in Shewanella oneidensis MR-1: Structures, functions and opportunities

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

Breuer, Marian; Rosso, Kevin M.; Blumberger, Jochen

Multi-heme cytochromes are employed by a range of microorganisms to transport electrons over distances of up to tens of nanometers. Perhaps the most spectacular utilization of these proteins is in the reduction of extracellular solid substrates, including electrodes and insoluble mineral oxides of Fe(III) and Mn(III/IV), by species of Shewanella and Geobacter. However, multi-heme cytochromes are found in numerous and phylogenetically diverse prokaryotes where they participate in electron transfer and redox catalysis that contributes to biogeochemical cycling of N, S and Fe on the global scale. These properties of multi-heme cytochromes have attracted much interest and contributed to advances inmore » bioenergy applications and bioremediation of contaminated soils. Looking forward there are opportunities to engage multi-heme cytochromes for biological photovoltaic cells, microbial electrosynthesis and developing bespoke molecular devices. As a consequence it is timely to review our present understanding of these proteins and we do this here with a focus on the multitude of functionally diverse multi-heme cytochromes in Shewanella oneidensis MR-1. We draw on findings from experimental and computational approaches which ideally complement each other in the study of these systems: computational methods can interpret experimentally determined properties in terms of molecular structure to cast light on the relation between structure and function. We show how this synergy has contributed to our understanding of multi-heme cytochromes and can be expected to continue to do so for greater insight into natural processes and their informed exploitation in biotechnologies.« less

Novel application of multi-stimuli network inference to synovial fibroblasts of rheumatoid arthritis patients

PubMed Central

2014-01-01

Background Network inference of gene expression data is an important challenge in systems biology. Novel algorithms may provide more detailed gene regulatory networks (GRN) for complex, chronic inflammatory diseases such as rheumatoid arthritis (RA), in which activated synovial fibroblasts (SFBs) play a major role. Since the detailed mechanisms underlying this activation are still unclear, simultaneous investigation of multi-stimuli activation of SFBs offers the possibility to elucidate the regulatory effects of multiple mediators and to gain new insights into disease pathogenesis. Methods A GRN was therefore inferred from RA-SFBs treated with 4 different stimuli (IL-1 β, TNF- α, TGF- β, and PDGF-D). Data from time series microarray experiments (0, 1, 2, 4, 12 h; Affymetrix HG-U133 Plus 2.0) were batch-corrected applying ‘ComBat’, analyzed for differentially expressed genes over time with ‘Limma’, and used for the inference of a robust GRN with NetGenerator V2.0, a heuristic ordinary differential equation-based method with soft integration of prior knowledge. Results Using all genes differentially expressed over time in RA-SFBs for any stimulus, and selecting the genes belonging to the most significant gene ontology (GO) term, i.e., ‘cartilage development’, a dynamic, robust, moderately complex multi-stimuli GRN was generated with 24 genes and 57 edges in total, 31 of which were gene-to-gene edges. Prior literature-based knowledge derived from Pathway Studio or manual searches was reflected in the final network by 25/57 confirmed edges (44%). The model contained known network motifs crucial for dynamic cellular behavior, e.g., cross-talk among pathways, positive feed-back loops, and positive feed-forward motifs (including suppression of the transcriptional repressor OSR2 by all 4 stimuli. Conclusion A multi-stimuli GRN highly concordant with literature data was successfully generated by network inference from the gene expression of stimulated RA-SFBs. The GRN showed high reliability, since 10 predicted edges were independently validated by literature findings post network inference. The selected GO term ‘cartilage development’ contained a number of differentiation markers, growth factors, and transcription factors with potential relevance for RA. Finally, the model provided new insight into the response of RA-SFBs to multiple stimuli implicated in the pathogenesis of RA, in particular to the ‘novel’ potent growth factor PDGF-D. PMID:24989895

Predicting human immunodeficiency virus inhibitors using multi-dimensional Bayesian network classifiers.

PubMed

Borchani, Hanen; Bielza, Concha; Toro, Carlos; Larrañaga, Pedro

2013-03-01

Our aim is to use multi-dimensional Bayesian network classifiers in order to predict the human immunodeficiency virus type 1 (HIV-1) reverse transcriptase and protease inhibitors given an input set of respective resistance mutations that an HIV patient carries. Multi-dimensional Bayesian network classifiers (MBCs) are probabilistic graphical models especially designed to solve multi-dimensional classification problems, where each input instance in the data set has to be assigned simultaneously to multiple output class variables that are not necessarily binary. In this paper, we introduce a new method, named MB-MBC, for learning MBCs from data by determining the Markov blanket around each class variable using the HITON algorithm. Our method is applied to both reverse transcriptase and protease data sets obtained from the Stanford HIV-1 database. Regarding the prediction of antiretroviral combination therapies, the experimental study shows promising results in terms of classification accuracy compared with state-of-the-art MBC learning algorithms. For reverse transcriptase inhibitors, we get 71% and 11% in mean and global accuracy, respectively; while for protease inhibitors, we get more than 84% and 31% in mean and global accuracy, respectively. In addition, the analysis of MBC graphical structures lets us gain insight into both known and novel interactions between reverse transcriptase and protease inhibitors and their respective resistance mutations. MB-MBC algorithm is a valuable tool to analyze the HIV-1 reverse transcriptase and protease inhibitors prediction problem and to discover interactions within and between these two classes of inhibitors. Copyright © 2012 Elsevier B.V. All rights reserved.

Insights into the government's role in food system policy making: improving access to healthy, local food alongside other priorities.

PubMed

Wegener, Jessica; Raine, Kim D; Hanning, Rhona M

2012-11-12

Government actors have an important role to play in creating healthy public policies and supportive environments to facilitate access to safe, affordable, nutritious food. The purpose of this research was to examine Waterloo Region (Ontario, Canada) as a case study for "what works" with respect to facilitating access to healthy, local food through regional food system policy making. Policy and planning approaches were explored through multi-sectoral perspectives of: (a) the development and adoption of food policies as part of the comprehensive planning process; (b) barriers to food system planning; and (c) the role and motivation of the Region's public health and planning departments in food system policy making. Forty-seven in-depth interviews with decision makers, experts in public health and planning, and local food system stakeholders provided rich insight into strategic government actions, as well as the local and historical context within which food system policies were developed. Grounded theory methods were used to identify key overarching themes including: "strategic positioning", "partnerships" and "knowledge transfer" and related sub-themes ("aligned agendas", "issue framing", "visioning" and "legitimacy"). A conceptual framework to illustrate the process and features of food system policy making is presented and can be used as a starting point to  engage multi-sectoral stakeholders in plans and actions to facilitate access to healthy food.

Visualization of anisotropic-isotropic phase transformation dynamics in battery electrode particles

DOE PAGES

Wang, Jiajun; Karen Chen-Wiegart, Yu-chen; Eng, Christopher; ...

2016-08-12

Anisotropy, or alternatively, isotropy of phase transformations extensively exist in a number of solid-state materials, with performance depending on the three-dimensional transformation features. Fundamental insights into internal chemical phase evolution allow manipulating materials with desired functionalities, and can be developed via real-time multi-dimensional imaging methods. In this paper, we report a five-dimensional imaging method to track phase transformation as a function of charging time in individual lithium iron phosphate battery cathode particles during delithiation. The electrochemically driven phase transformation is initially anisotropic with a preferred boundary migration direction, but becomes isotropic as delithiation proceeds further. We also observe the expectedmore » two-phase coexistence throughout the entire charging process. Finally, we expect this five-dimensional imaging method to be broadly applicable to problems in energy, materials, environmental and life sciences.« less

Insight into the da Vinci® Xi - technical notes for single-docking left-sided colorectal procedures.

PubMed

Ngu, James Chi-Yong; Sim, Sarah; Yusof, Sulaiman; Ng, Chee-Yung; Wong, Andrew Siang-Yih

2017-12-01

The adoption of robot-assisted laparoscopic colorectal surgery has been hampered by issues with docking, operative duration, technical difficulties in multi-quadrant access, and cost. The da Vinci® Xi has been designed to overcome some of these limitations. We describe our experience with the system and offer technical insights to its application in left-sided colorectal procedures. Our initial series of left-sided robotic colorectal procedures was evaluated. Patient demographics and operative outcomes were recorded prospectively using a predefined database. Between March 2015 and April 2016, 54 cases of robot-assisted laparoscopic left-sided colorectal procedures were successfully completed with no cases of conversion. The majority were low anterior resections for colorectal malignancies. Using the da Vinci® Xi Surgical System, multi-quadrant surgery involving dissection from the splenic flexure to the pelvis was possible without redocking. The da Vinci® Xi simplifies the docking procedure and makes single-docking feasible for multi-quadrant left-sided colorectal procedures. Copyright © 2016 John Wiley & Sons, Ltd.

Handbook of Response to Intervention: The Science and Practice of Multi-Tiered Systems of Support, 2nd Edition

ERIC Educational Resources Information Center

Jimerson, Shane R., Ed.; Burns, Matthew K., Ed.; VanDerHeyden, Amanda M., Ed.

2016-01-01

The second edition of this essential handbook provides a comprehensive, updated overview of the science that informs best practices for the implementation of response to intervention (RTI) processes within Multi-Tiered Systems of Support (MTSS) to facilitate the academic success of all students. The volume includes insights from leading scholars…

Rationalizing fragment based drug discovery for BACE1: insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies

NASA Astrophysics Data System (ADS)

Manoharan, Prabu; Vijayan, R. S. K.; Ghoshal, Nanda

2010-10-01

The ability to identify fragments that interact with a biological target is a key step in FBDD. To date, the concept of fragment based drug design (FBDD) is increasingly driven by bio-physical methods. To expand the boundaries of QSAR paradigm, and to rationalize FBDD using In silico approach, we propose a fragment based QSAR methodology referred here in as FB-QSAR. The FB-QSAR methodology was validated on a dataset consisting of 52 Hydroxy ethylamine (HEA) inhibitors, disclosed by GlaxoSmithKline Pharmaceuticals as potential anti-Alzheimer agents. To address the issue of target selectivity, a major confounding factor in the development of selective BACE1 inhibitors, FB-QSSR models were developed using the reported off target activity values. A heat map constructed, based on the activity and selectivity profile of the individual R-group fragments, and was in turn used to identify superior R-group fragments. Further, simultaneous optimization of multiple properties, an issue encountered in real-world drug discovery scenario, and often overlooked in QSAR approaches, was addressed using a Multi Objective (MO-QSPR) method that balances properties, based on the defined objectives. MO-QSPR was implemented using Derringer and Suich desirability algorithm to identify the optimal level of independent variables ( X) that could confer a trade-off between selectivity and activity. The results obtained from FB-QSAR were further substantiated using MIF (Molecular Interaction Fields) studies. To exemplify the potentials of FB-QSAR and MO-QSPR in a pragmatic fashion, the insights gleaned from the MO-QSPR study was reverse engineered using Inverse-QSAR in a combinatorial fashion to enumerate some prospective novel, potent and selective BACE1 inhibitors.

Rationalizing fragment based drug discovery for BACE1: insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies.

PubMed

Manoharan, Prabu; Vijayan, R S K; Ghoshal, Nanda

2010-10-01

The ability to identify fragments that interact with a biological target is a key step in FBDD. To date, the concept of fragment based drug design (FBDD) is increasingly driven by bio-physical methods. To expand the boundaries of QSAR paradigm, and to rationalize FBDD using In silico approach, we propose a fragment based QSAR methodology referred here in as FB-QSAR. The FB-QSAR methodology was validated on a dataset consisting of 52 Hydroxy ethylamine (HEA) inhibitors, disclosed by GlaxoSmithKline Pharmaceuticals as potential anti-Alzheimer agents. To address the issue of target selectivity, a major confounding factor in the development of selective BACE1 inhibitors, FB-QSSR models were developed using the reported off target activity values. A heat map constructed, based on the activity and selectivity profile of the individual R-group fragments, and was in turn used to identify superior R-group fragments. Further, simultaneous optimization of multiple properties, an issue encountered in real-world drug discovery scenario, and often overlooked in QSAR approaches, was addressed using a Multi Objective (MO-QSPR) method that balances properties, based on the defined objectives. MO-QSPR was implemented using Derringer and Suich desirability algorithm to identify the optimal level of independent variables (X) that could confer a trade-off between selectivity and activity. The results obtained from FB-QSAR were further substantiated using MIF (Molecular Interaction Fields) studies. To exemplify the potentials of FB-QSAR and MO-QSPR in a pragmatic fashion, the insights gleaned from the MO-QSPR study was reverse engineered using Inverse-QSAR in a combinatorial fashion to enumerate some prospective novel, potent and selective BACE1 inhibitors.

Teaching Translation and Interpreting 2: Insights, Aims, Visions. [Selection of] Papers from the Second Language International Conference (Elsinore, Denmark, June 4-6, 1993).

ERIC Educational Resources Information Center

Dollerup, Cay, Ed.; Lindegaard, Annette, Ed.

This selection of papers starts with insights into multi- and plurilingual settings, then proceeds to discussions of aims for practical work with students, and ends with visions of future developments within translation for the mass media and the impact of machine translation. Papers are: "Interpreting at the European Commission";…

Multi-analytical Approaches Informing the Risk of Sepsis

NASA Astrophysics Data System (ADS)

Gwadry-Sridhar, Femida; Lewden, Benoit; Mequanint, Selam; Bauer, Michael

Sepsis is a significant cause of mortality and morbidity and is often associated with increased hospital resource utilization, prolonged intensive care unit (ICU) and hospital stay. The economic burden associated with sepsis is huge. With advances in medicine, there are now aggressive goal oriented treatments that can be used to help these patients. If we were able to predict which patients may be at risk for sepsis we could start treatment early and potentially reduce the risk of mortality and morbidity. Analytic methods currently used in clinical research to determine the risk of a patient developing sepsis may be further enhanced by using multi-modal analytic methods that together could be used to provide greater precision. Researchers commonly use univariate and multivariate regressions to develop predictive models. We hypothesized that such models could be enhanced by using multiple analytic methods that together could be used to provide greater insight. In this paper, we analyze data about patients with and without sepsis using a decision tree approach and a cluster analysis approach. A comparison with a regression approach shows strong similarity among variables identified, though not an exact match. We compare the variables identified by the different approaches and draw conclusions about the respective predictive capabilities,while considering their clinical significance.

An overview of data integration methods for regional assessment.

PubMed

Locantore, Nicholas W; Tran, Liem T; O'Neill, Robert V; McKinnis, Peter W; Smith, Elizabeth R; O'Connell, Michael

2004-06-01

The U.S. Environmental Protections Agency's (U.S. EPA) Regional Vulnerability Assessment(ReVA) program has focused much of its research over the last five years on developing and evaluating integration methods for spatial data. An initial strategic priority was to use existing data from monitoring programs, model results, and other spatial data. Because most of these data were not collected with an intention of integrating into a regional assessment of conditions and vulnerabilities, issues exist that may preclude the use of some methods or require some sort of data preparation. Additionally, to support multi-criteria decision-making, methods need to be able to address a series of assessment questions that provide insights into where environmental risks are a priority. This paper provides an overview of twelve spatial integration methods that can be applied towards regional assessment, along with preliminary results as to how sensitive each method is to data issues that will likely be encountered with the use of existing data.

Global Design Optimization for Fluid Machinery Applications

NASA Technical Reports Server (NTRS)

Shyy, Wei; Papila, Nilay; Tucker, Kevin; Vaidyanathan, Raj; Griffin, Lisa

2000-01-01

Recent experiences in utilizing the global optimization methodology, based on polynomial and neural network techniques for fluid machinery design are summarized. Global optimization methods can utilize the information collected from various sources and by different tools. These methods offer multi-criterion optimization, handle the existence of multiple design points and trade-offs via insight into the entire design space can easily perform tasks in parallel, and are often effective in filtering the noise intrinsic to numerical and experimental data. Another advantage is that these methods do not need to calculate the sensitivity of each design variable locally. However, a successful application of the global optimization method needs to address issues related to data requirements with an increase in the number of design variables and methods for predicting the model performance. Examples of applications selected from rocket propulsion components including a supersonic turbine and an injector element and a turbulent flow diffuser are used to illustrate the usefulness of the global optimization method.

Integrating Stomach Content and Stable Isotope Analyses to Quantify the Diets of Pygoscelid Penguins

PubMed Central

Polito, Michael J.; Trivelpiece, Wayne Z.; Karnovsky, Nina J.; Ng, Elizabeth; Patterson, William P.; Emslie, Steven D.

2011-01-01

Stomach content analysis (SCA) and more recently stable isotope analysis (SIA) integrated with isotopic mixing models have become common methods for dietary studies and provide insight into the foraging ecology of seabirds. However, both methods have drawbacks and biases that may result in difficulties in quantifying inter-annual and species-specific differences in diets. We used these two methods to simultaneously quantify the chick-rearing diet of Chinstrap (Pygoscelis antarctica) and Gentoo (P. papua) penguins and highlight methods of integrating SCA data to increase accuracy of diet composition estimates using SIA. SCA biomass estimates were highly variable and underestimated the importance of soft-bodied prey such as fish. Two-source, isotopic mixing model predictions were less variable and identified inter-annual and species-specific differences in the relative amounts of fish and krill in penguin diets not readily apparent using SCA. In contrast, multi-source isotopic mixing models had difficulty estimating the dietary contribution of fish species occupying similar trophic levels without refinement using SCA-derived otolith data. Overall, our ability to track inter-annual and species-specific differences in penguin diets using SIA was enhanced by integrating SCA data to isotopic mixing modes in three ways: 1) selecting appropriate prey sources, 2) weighting combinations of isotopically similar prey in two-source mixing models and 3) refining predicted contributions of isotopically similar prey in multi-source models. PMID:22053199

A multi-refuge study to evaluate the effectiveness of growing-season and dormant-season burns to control cattail

USGS Publications Warehouse

Gleason, Robert A.; Tangen, Brian A.; Laubhan, Murray K.; Lor, Socheata

2012-01-01

Proliferation of invasive cattails (for example, Typha x glauca, T. angustifolia) is a concern of wetland managers across the country, and numerous methods have been used to control the spatial extent and density of the plant. To date, however, no single method has proven widely or consistently effective at reducing the long-term growth and spread of these species. We performed a multi-refuge study to evaluate the relative effects of growing-season and dormant-season prescribed burns on cattail production and to gain insight on variables such as soil moisture, groundwater, and biomass that affect the efficacy of burning as a control method. Results indicate total cattail cover recovers to pre-burn levels within 1 year regardless of whether the controlled burn was implemented during the growing season or dormant season. Growing-season burns, however, did result in lower aboveground and belowground cattail biomass 1-year post-burn, whereas no significant change in biomass was detected for dormant-season burns. Study results support the premise that burns implemented during the growing season should have a greater effect on nutrient reserves and cattail re-growth. Results from this and other studies suggest long-term research that incorporates multiple management strategies will be required to evaluate the potential of prescribed burning as a method to control cattail.

Agent-based model with multi-level herding for complex financial systems

NASA Astrophysics Data System (ADS)

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-02-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.

Agent-based model with multi-level herding for complex financial systems

PubMed Central

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-01-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level. PMID:25669427

Reconfigurable radio receiver with fractional sample rate converter and multi-rate ADC based on LO-derived sampling clock

NASA Astrophysics Data System (ADS)

Park, Sungkyung; Park, Chester Sungchung

2018-03-01

A composite radio receiver back-end and digital front-end, made up of a delta-sigma analogue-to-digital converter (ADC) with a high-speed low-noise sampling clock generator, and a fractional sample rate converter (FSRC), is proposed and designed for a multi-mode reconfigurable radio. The proposed radio receiver architecture contributes to saving the chip area and thus lowering the design cost. To enable inter-radio access technology handover and ultimately software-defined radio reception, a reconfigurable radio receiver consisting of a multi-rate ADC with its sampling clock derived from a local oscillator, followed by a rate-adjustable FSRC for decimation, is designed. Clock phase noise and timing jitter are examined to support the effectiveness of the proposed radio receiver. A FSRC is modelled and simulated with a cubic polynomial interpolator based on Lagrange method, and its spectral-domain view is examined in order to verify its effect on aliasing, nonlinearity and signal-to-noise ratio, giving insight into the design of the decimation chain. The sampling clock path and the radio receiver back-end data path are designed in a 90-nm CMOS process technology with 1.2V supply.

A method to assess how interactive water simulation tools influence transdisciplinary decision-making processes in water management

NASA Astrophysics Data System (ADS)

Leskens, Johannes

2015-04-01

In modern water management, often transdisciplinary work sessions are organized in which various stakeholders participate to jointly define problems, choose measures and divide responsibilities to take actions. Involved stakeholders are for example policy analysts or decision-makers from municipalities, water boards or provinces, representatives of pressure groups and researchers from knowledge institutes. Parallel to this increasing attention for transdisciplinary work sessions, we see a growing availability of interactive IT-tools that can be applied during these sessions. For example, dynamic flood risk maps have become recently available that allow users during a work sessions to instantaneously assess the impact of storm surges or dam breaches, displayed on digital maps. Other examples are serious games, realistic visualizations and participatory simulations. However, the question is if and how these interactive IT-tools contribute to better decision-making. To assess this, we take the process of knowledge construction during a work session as a measure for the quality of decision-making. Knowledge construction can be defined as the process in which ideas, perspectives and opinions of different stakeholders, all having their own expertise and experience, are confronted with each other and new shared meanings towards water management issues are created. We present an assessment method to monitor the process of knowledge construction during work sessions in water management in which interactive IT tools are being used. The assessment method is based on a literature review, focusing on studies in which knowledge construction was monitored in other contexts that water management. To test the applicability of the assessment method, we applied it during a multi-stakeholder work session in Westland, located in the southwest of the Netherlands. The discussions during the work session were observed by camera. All statements, expressed by the various members of a stakeholder session, were classified according to our assessment method. We can draw the following preliminary conclusions. First, the case study showed that the method was useful to show the knowledge construction process over time, in terms of content and cognitive level of statements and interaction, attention and response between stakeholders. It was observed that the various aspects of knowledge construction all were influenced by the use of the 3Di model. The model focused discussions on technical issues of flood risk management, non-flood specialists were able to participate in discussions and in suggesting solutions and more topics could be evaluated in respect to non-interactive flood maps. Second, the method is considered useful as a benchmark for different interactive IT tools. The method is also considered useful to gain insight in how to optimally set-up multi-stakeholder meetings in which interactive IT-tools are being used. Further, the method can provide model developers insight in how to better meet the technical requirements of interactive IT tools to support the knowledge construction process during multi-stakeholder meeting

Systems Biology Methods for Alzheimer's Disease Research Toward Molecular Signatures, Subtypes, and Stages and Precision Medicine: Application in Cohort Studies and Trials.

PubMed

Castrillo, Juan I; Lista, Simone; Hampel, Harald; Ritchie, Craig W

2018-01-01

Alzheimer's disease (AD) is a complex multifactorial disease, involving a combination of genomic, interactome, and environmental factors, with essential participation of (a) intrinsic genomic susceptibility and (b) a constant dynamic interplay between impaired pathways and central homeostatic networks of nerve cells. The proper investigation of the complexity of AD requires new holistic systems-level approaches, at both the experimental and computational level. Systems biology methods offer the potential to unveil new fundamental insights, basic mechanisms, and networks and their interplay. These may lead to the characterization of mechanism-based molecular signatures, and AD hallmarks at the earliest molecular and cellular levels (and beyond), for characterization of AD subtypes and stages, toward targeted interventions according to the evolving precision medicine paradigm. In this work, an update on advanced systems biology methods and strategies for holistic studies of multifactorial diseases-particularly AD-is presented. This includes next-generation genomics, neuroimaging and multi-omics methods, experimental and computational approaches, relevant disease models, and latest genome editing and single-cell technologies. Their progressive incorporation into basic research, cohort studies, and trials is beginning to provide novel insights into AD essential mechanisms, molecular signatures, and markers toward mechanism-based classification and staging, and tailored interventions. Selected methods which can be applied in cohort studies and trials, with the European Prevention of Alzheimer's Dementia (EPAD) project as a reference example, are presented and discussed.

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

The role of social marketing, marine turtles and sustainable tourism in reducing plastic pollution.

PubMed

Eagle, Lynne; Hamann, Mark; Low, David R

2016-06-15

Environmental plastic pollution constitutes a significant hazard to marine turtles, human health and well-being. We describe a transdisciplinary approach to draw together findings from diverse disciplines in order to highlight key environmental pollution problems and their consequences, together with social marketing-based strategies to address the problems. The example of plastic pollution and impacts to marine turtles illustrates the severity of the problem. Wildlife tourism and sustainable tourism activity have not focussed on specific behaviours to change and have had minimal impact on subsequent human behaviour regarding environmental issues, indicating the need for new strategies. Social marketing principles offer promise, but there is a need to investigate the utility of various theoretical foundations to aid the design and implementation of interventions. We offer insight towards using sophisticated multi-method research to develop insights into behaviours and segmentation-based strategies, that can aid the identification of barriers to, and enablers of, sustained behaviour change. Copyright © 2016. Published by Elsevier Ltd.

gem-Difluoroolefination of diaryl ketones and enolizable aldehydes with difluoromethyl 2-pyridyl sulfone: new insights into the Julia-Kocienski reaction.

PubMed

Gao, Bing; Zhao, Yanchuan; Hu, Mingyou; Ni, Chuanfa; Hu, Jinbo

2014-06-16

The direct conversion of diaryl ketones and enolizable aliphatic aldehydes into gem-difluoroalkenes has been a long-standing challenge in organofluorine chemistry. Herein, we report efficient strategies to tackle this problem by using difluoromethyl 2-pyridyl sulfone as a general gem-difluoroolefination reagent. The gem-difluoroolefination of diaryl ketones proceeds by acid-promoted Smiles rearrangement of the carbinol intermediate; the gem-difluoroolefination is otherwise difficult to achieve through a conventional Julia-Kocienski olefination protocol under basic conditions due to the retro-aldol type decomposition of the key intermediate. Efficient gem-difluoroolefination of aliphatic aldehydes was achieved by the use of an amide base generated in situ (from CsF and tris(trimethylsilyl)amine), which diminishes the undesired enolization of aliphatic aldehydes and provides a powerful synthetic method for chemoselective gem-difluoroolefination of multi-carbonyl compounds. Our results provide new insights into the mechanistic understanding of the classical Julia-Kocienski reaction. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Recent research about mild cognitive impairment in China

PubMed Central

CHENG, Yan; XIAO, Shifu

2014-01-01

Summary: The rapid aging of the Chinese population has spurred interest in research about the cause and prevention of dementia and its precursor, mild cognitive impairment (MCI). This review summarizes the last decade of research in China about MCI. Extensive research about the epidemiology, neuropsychological characteristics, diagnosis, genetic etiology, neuroimaging and electrophysiological changes, and treatment of MCI has provided some new insights but few breakthroughs. Further advances in the prevention and treatment of MCI will require a greater emphasis on multi-disciplinary prospective studies with large, representative samples that use standardized methods to assess and monitor changes in cognitive functioning over time. PMID:25114476

A systems theoretic approach to analysis and control of mammalian circadian dynamics

PubMed Central

Abel, John H.; Doyle, Francis J.

2016-01-01

The mammalian circadian clock is a complex multi-scale, multivariable biological control system. In the past two decades, methods from systems engineering have led to numerous insights into the architecture and functionality of this system. In this review, we examine the mammalian circadian system through a process systems lens. We present a mathematical framework for examining the cellular circadian oscillator, and show recent extensions for understanding population-scale dynamics. We provide an overview of the routes by which the circadian system can be systemically manipulated, and present in silico proof of concept results for phase resetting of the clock via model predictive control. PMID:28496287

Multi-MHz time-of-flight electronic bandstructure imaging of graphene on Ir(111)

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

Tusche, C., E-mail: c.tusche@fz-juelich.de; Peter Grünberg Institut; Goslawski, P.

2016-06-27

In the quest for detailed spectroscopic insight into the electronic structure at solid surfaces in a large momentum range, we have developed an advanced experimental approach. It combines the 3D detection scheme of a time-of-flight momentum microscope with an optimized filling pattern of the BESSY II storage ring. Here, comprehensive data sets covering the full surface Brillouin zone have been used to study faint substrate-film hybridization effects in the electronic structure of graphene on Ir(111), revealed by a pronounced linear dichroism in angular distribution. The method paves the way to 3D electronic bandmapping with unprecedented data recording efficiency.

Communication: a density functional with accurate fractional-charge and fractional-spin behaviour for s-electrons.

PubMed

Johnson, Erin R; Contreras-García, Julia

2011-08-28

We develop a new density-functional approach combining physical insight from chemical structure with treatment of multi-reference character by real-space modeling of the exchange-correlation hole. We are able to recover, for the first time, correct fractional-charge and fractional-spin behaviour for atoms of groups 1 and 2. Based on Becke's non-dynamical correlation functional [A. D. Becke, J. Chem. Phys. 119, 2972 (2003)] and explicitly accounting for core-valence separation and pairing effects, this method is able to accurately describe dissociation and strong correlation in s-shell many-electron systems. © 2011 American Institute of Physics

Joint fMRI analysis and subject clustering using sparse dictionary learning

NASA Astrophysics Data System (ADS)

Kim, Seung-Jun; Dontaraju, Krishna K.

2017-08-01

Multi-subject fMRI data analysis methods based on sparse dictionary learning are proposed. In addition to identifying the component spatial maps by exploiting the sparsity of the maps, clusters of the subjects are learned by postulating that the fMRI volumes admit a subspace clustering structure. Furthermore, in order to tune the associated hyper-parameters systematically, a cross-validation strategy is developed based on entry-wise sampling of the fMRI dataset. Efficient algorithms for solving the proposed constrained dictionary learning formulations are developed. Numerical tests performed on synthetic fMRI data show promising results and provides insights into the proposed technique.

Multi-modal porous microstructure for high temperature fuel cell application

NASA Astrophysics Data System (ADS)

Wejrzanowski, T.; Haj Ibrahim, S.; Cwieka, K.; Loeffler, M.; Milewski, J.; Zschech, E.; Lee, C.-G.

2018-01-01

In this study, the effect of microstructure of porous nickel electrode on the performance of high temperature fuel cell is investigated and presented based on a molten carbonate fuel cell (MCFC) cathode. The cathode materials are fabricated from slurry consisting of nickel powder and polymeric binder/solvent mixture, using the tape casting method. The final pore structure is shaped through modifying the slurry composition - with or without the addition of porogen(s). The manufactured materials are extensively characterized by various techniques involving: micro-computed tomography (micro-XCT), scanning electron microscopy (SEM), mercury porosimetry, BET and Archimedes method. Tomographic images are also analyzed and quantified to reveal the evolution of pore space due to nickel in situ oxidation to NiO, and infiltration by the electrolyte. Single-cell performance tests are carried out under MCFC operation conditions to estimate the performance of the manufactured materials. It is found that the multi-modal microstructure of MCFC cathode results in a significant enhancement of the power density generated by the reference cell. To give greater insight into the understanding of the effect of microstructure on the properties of the cathode, a model based on 3D tomography image transformation is proposed.

Theoretically Founded Optimization of Auctioneer's Revenues in Expanding Auctions

NASA Astrophysics Data System (ADS)

Rabin, Jonathan; Shehory, Onn

The expanding auction is a multi-unit auction which provides the auctioneer with control over the outcome of the auction by means of dynamically adding items for sale. Previous research on the expanding auction has provided a numeric method to calculate a strategy that optimizes the auctioneer's revenue. In this paper, we analyze various theoretical properties of the expanding auction, and compare it to VCG, a multi-unit auction protocol known in the art. We examine the effects of errors in the auctioneer's estimation of the buyers' maximal bidding values and prove a theoretical bound on the ratio between the revenue yielded by the Informed Decision Strategy (IDS) and the post-optimal strategy. We also analyze the relationship between the auction step and the optimal revenue and introduce a method of computing this optimizing step. We further compare the revenues yielded by the use of IDS with an expanding auction to those of the VCG mechanism and determine the conditions under which the former outperforms the latter. Our work provides new insight into the properties of the expanding auction. It further provides theoretically founded means for optimizing the revenue of auctioneer.

An interval-parameter mixed integer multi-objective programming for environment-oriented evacuation management

NASA Astrophysics Data System (ADS)

Wu, C. Z.; Huang, G. H.; Yan, X. P.; Cai, Y. P.; Li, Y. P.

2010-05-01

Large crowds are increasingly common at political, social, economic, cultural and sports events in urban areas. This has led to attention on the management of evacuations under such situations. In this study, we optimise an approximation method for vehicle allocation and route planning in case of an evacuation. This method, based on an interval-parameter multi-objective optimisation model, has potential for use in a flexible decision support system for evacuation management. The modeling solutions are obtained by sequentially solving two sub-models corresponding to lower- and upper-bounds for the desired objective function value. The interval solutions are feasible and stable in the given decision space, and this may reduce the negative effects of uncertainty, thereby improving decision makers' estimates under different conditions. The resulting model can be used for a systematic analysis of the complex relationships among evacuation time, cost and environmental considerations. The results of a case study used to validate the proposed model show that the model does generate useful solutions for planning evacuation management and practices. Furthermore, these results are useful for evacuation planners, not only in making vehicle allocation decisions but also for providing insight into the tradeoffs among evacuation time, environmental considerations and economic objectives.

Biological adaptive control model: a mechanical analogue of multi-factorial bone density adaptation.

PubMed

Davidson, Peter L; Milburn, Peter D; Wilson, Barry D

2004-03-21

The mechanism of how bone adapts to every day demands needs to be better understood to gain insight into situations in which the musculoskeletal system is perturbed. This paper offers a novel multi-factorial mathematical model of bone density adaptation which combines previous single-factor models in a single adaptation system as a means of gaining this insight. Unique aspects of the model include provision for interaction between factors and an estimation of the relative contribution of each factor. This interacting system is considered analogous to a Newtonian mechanical system and the governing response equation is derived as a linear version of the adaptation process. The transient solution to sudden environmental change is found to be exponential or oscillatory depending on the balance between cellular activation and deactivation frequencies.

Multi-Element Unstructured Analyses of Complex Valve Systems

NASA Technical Reports Server (NTRS)

Sulyma, Peter (Technical Monitor); Ahuja, Vineet; Hosangadi, Ashvin; Shipman, Jeremy

2004-01-01

The safe and reliable operation of high pressure test stands for rocket engine and component testing places an increased emphasis on the performance of control valves and flow metering devices. In this paper, we will present a series of high fidelity computational analyses of systems ranging from cryogenic control valves and pressure regulator systems to cavitating venturis that are used to support rocket engine and component testing at NASA Stennis Space Center. A generalized multi-element framework with sub-models for grid adaption, grid movement and multi-phase flow dynamics has been used to carry out the simulations. Such a framework provides the flexibility of resolving the structural and functional complexities that are typically associated with valve-based high pressure feed systems and have been difficult to deal with traditional CFD methods. Our simulations revealed a rich variety of flow phenomena such as secondary flow patterns, hydrodynamic instabilities, fluctuating vapor pockets etc. In the paper, we will discuss performance losses related to cryogenic control valves, and provide insight into the physics of the dominant multi-phase fluid transport phenomena that are responsible for the choking like behavior in cryogenic control elements. Additionally, we will provide detailed analyses of the modal instability that is observed in the operation of the dome pressure regulator valve. Such instabilities are usually not localized and manifest themselves as a system wide phenomena leading to an undesirable chatter at high flow conditions.

Qualitative research and the profound grasp of the obvious.

PubMed Central

Hurley, R E

1999-01-01

OBJECTIVE: To discuss the value of promoting coexistent and complementary relationships between qualitative and quantitative research methods as illustrated by presentations made by four respected health services researchers who described their experiences in multi-method projects. DATA SOURCES: Presentations and publications related to the four research projects, which described key substantive and methodological areas that had been addressed with qualitative techniques. PRINCIPAL FINDINGS: Sponsor interest in timely, insightful, and reality-anchored evidence has provided a strong base of support for the incorporation of qualitative methods into major contemporary policy research studies. In addition, many issues may be suitable for study only with qualitative methods because of their complexity, their emergent nature, or because of the need to revisit and reexamine previously untested assumptions. CONCLUSION: Experiences from the four projects, as well as from other recent health services studies with major qualitative components, support the assertion that the interests of sponsors in the policy realm and pressure from them suppress some of the traditional tensions and antagonisms between qualitative and quantitative methods. PMID:10591276

Microstencils to generate defined, multi-species patterns of bacteria

DOE PAGES

Timm, Collin M.; Hansen, Ryan R.; Doktycz, Mitchel J.; ...

2015-11-12

Microbial communities are complex heterogeneous systems that are influenced by physical and chemical interactions with their environment, host, and community members. Techniques that facilitate the quantitative evaluation of how microscale organization influences the morphogenesis of multispecies communities could provide valuable insights into the dynamic behavior and organization of natural communities, the design of synthetic environments for multispecies culture, and the engineering of artificial consortia. In this work, we demonstrate a method for patterning microbes into simple arrangements that allow the quantitative measurement of growth dynamics as a function of their proximity to one another. The method combines parylene-based liftoff techniquesmore » with microfluidic delivery to simultaneously pattern multiple bacterial species with high viability using low-cost, customizable methods. Furthermore, quantitative measurements of bacterial growth for two competing isolates demonstrate that spatial coordination can play a critical role in multispecies growth and structure.« less

Microstencils to generate defined, multi-species patterns of bacteria

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

Timm, Collin M.; Hansen, Ryan R.; Doktycz, Mitchel J.

Microbial communities are complex heterogeneous systems that are influenced by physical and chemical interactions with their environment, host, and community members. Techniques that facilitate the quantitative evaluation of how microscale organization influences the morphogenesis of multispecies communities could provide valuable insights into the dynamic behavior and organization of natural communities, the design of synthetic environments for multispecies culture, and the engineering of artificial consortia. In this work, we demonstrate a method for patterning microbes into simple arrangements that allow the quantitative measurement of growth dynamics as a function of their proximity to one another. The method combines parylene-based liftoff techniquesmore » with microfluidic delivery to simultaneously pattern multiple bacterial species with high viability using low-cost, customizable methods. Furthermore, quantitative measurements of bacterial growth for two competing isolates demonstrate that spatial coordination can play a critical role in multispecies growth and structure.« less

Multi-scale gyrokinetic simulations of an Alcator C-Mod, ELM-y H-mode plasma

NASA Astrophysics Data System (ADS)

Howard, N. T.; Holland, C.; White, A. E.; Greenwald, M.; Rodriguez-Fernandez, P.; Candy, J.; Creely, A. J.

2018-01-01

High fidelity, multi-scale gyrokinetic simulations capable of capturing both ion ({k}θ {ρ }s∼ { O }(1.0)) and electron-scale ({k}θ {ρ }e∼ { O }(1.0)) turbulence were performed in the core of an Alcator C-Mod ELM-y H-mode discharge which exhibits reactor-relevant characteristics. These simulations, performed with all experimental inputs and realistic ion to electron mass ratio ({({m}i/{m}e)}1/2=60.0) provide insight into the physics fidelity that may be needed for accurate simulation of the core of fusion reactor discharges. Three multi-scale simulations and series of separate ion and electron-scale simulations performed using the GYRO code (Candy and Waltz 2003 J. Comput. Phys. 186 545) are presented. As with earlier multi-scale results in L-mode conditions (Howard et al 2016 Nucl. Fusion 56 014004), both ion and multi-scale simulations results are compared with experimentally inferred ion and electron heat fluxes, as well as the measured values of electron incremental thermal diffusivities—indicative of the experimental electron temperature profile stiffness. Consistent with the L-mode results, cross-scale coupling is found to play an important role in the simulation of these H-mode conditions. Extremely stiff ion-scale transport is observed in these high-performance conditions which is shown to likely play and important role in the reproduction of measurements of perturbative transport. These results provide important insight into the role of multi-scale plasma turbulence in the core of reactor-relevant plasmas and establish important constraints on the the fidelity of models needed for predictive simulations.

Multi-level molecular modelling for plasma medicine

NASA Astrophysics Data System (ADS)

Bogaerts, Annemie; Khosravian, Narjes; Van der Paal, Jonas; Verlackt, Christof C. W.; Yusupov, Maksudbek; Kamaraj, Balu; Neyts, Erik C.

2016-02-01

Modelling at the molecular or atomic scale can be very useful for obtaining a better insight in plasma medicine. This paper gives an overview of different atomic/molecular scale modelling approaches that can be used to study the direct interaction of plasma species with biomolecules or the consequences of these interactions for the biomolecules on a somewhat longer time-scale. These approaches include density functional theory (DFT), density functional based tight binding (DFTB), classical reactive and non-reactive molecular dynamics (MD) and united-atom or coarse-grained MD, as well as hybrid quantum mechanics/molecular mechanics (QM/MM) methods. Specific examples will be given for three important types of biomolecules, present in human cells, i.e. proteins, DNA and phospholipids found in the cell membrane. The results show that each of these modelling approaches has its specific strengths and limitations, and is particularly useful for certain applications. A multi-level approach is therefore most suitable for obtaining a global picture of the plasma-biomolecule interactions.

Mapping the dynamics of force transduction at cell–cell junctions of epithelial clusters

PubMed Central

Ng, Mei Rosa; Besser, Achim; Brugge, Joan S; Danuser, Gaudenz

2014-01-01

Force transduction at cell-cell adhesions regulates tissue development, maintenance and adaptation. We developed computational and experimental approaches to quantify, with both sub-cellular and multi-cellular resolution, the dynamics of force transmission in cell clusters. Applying this technology to spontaneously-forming adherent epithelial cell clusters, we found that basal force fluctuations were coupled to E-cadherin localization at the level of individual cell-cell junctions. At the multi-cellular scale, cell-cell force exchange depended on the cell position within a cluster, and was adaptive to reconfigurations due to cell divisions or positional rearrangements. Importantly, force transmission through a cell required coordinated modulation of cell-matrix adhesion and actomyosin contractility in the cell and its neighbors. These data provide insights into mechanisms that could control mechanical stress homeostasis in dynamic epithelial tissues, and highlight our methods as a resource for the study of mechanotransduction in cell-cell adhesions. DOI: http://dx.doi.org/10.7554/eLife.03282.001 PMID:25479385

Identification of multi-insecticide residues using GC-NPD and the degradation kinetics of chlorpyrifos in sweet corn and soils.

PubMed

Wang, Peidan; Rashid, Muhammad; Liu, Jie; Hu, Meiying; Zhong, Guohua

2016-12-01

Because more than one insecticide is applied to crops to protect plants from pests, an analytical multi-residue determination method was developed using gas chromatography with a nitrogen phosphorus detector (GC-NPD). The retention time for 12 insecticides was 3.7-27.7min. Under the selected conditions, the limits of detection (LOD) and quantification (LOQ) were below the maximum residue limits (MRLs) and in the range of 0.00315-0.05μgmL(-1) and 0.01-0.165μgmL(-1), respectively. Using GC-NPD, we investigated the dissipation dynamics and final residual levels of chlorpyrifos in sweet corn and soil and determined that the half-lives was 4-7days, that is, that chlorpyrifos is safe to use on sweet corn with a pre-harvest interval of 16-22days before harvest. These results provide new insights into chlorpyrifos degradation in plants and its environmental behavior. Copyright © 2016. Published by Elsevier Ltd.

Clinical and cognitive insight in patients with acute-phase psychosis: Association with treatment and neuropsychological functioning.

PubMed

Poyraz, Burç Çağri; Arikan, Mehmet Kemal; Poyraz, Cana Aksoy; Turan, Şenol; Kani, Ayşe Sakalli; Aydin, Eser; İnce, Ezgi

2016-10-01

The severity of psychopathology cannot fully explain deficits in the multi-dimensional construct of insight. The aim of this study was to evaluate the correlates and associations of clinical and cognitive insight in patients in an acute phase of psychosis and to analyse the impact of acute treatment on these variables. This study examined 47 inpatients who were recently hospitalized with acute exacerbation of schizophrenia. All subjects were assessed at both admission and discharge with the Positive and Negative Syndrome Scale (PANSS), Schedule for the Assessment of Insight-Expanded Version (SAI-E), Beck Cognitive Insight Scale (BCIS), and a neurocognition battery. Patients with schizophrenia gained clinical insight after treatment. Cognitive insight did not change significantly after treatment. Insight showed significant negative correlations with positive symptoms and general psychopathology, but not with negative symptoms. Clinical insight was not associated with neuropsychological functioning in this cohort. Gaining clinical insight in the acute phase of illness was associated with the remission of positive symptoms, but not with neuropsychological functioning. Some significant correlations between clinical and cognitive insights were detected, which suggests that cognitive insight contributes to clinical insight but is not treatment-dependent. Long-term treatment may be required to understand the contribution of insight to the outcome of patients with schizophrenia.

Supporting Multi-view User Ontology to Understand Company Value Chains

NASA Astrophysics Data System (ADS)

Zuo, Landong; Salvadores, Manuel; Imtiaz, Sm Hazzaz; Darlington, John; Gibbins, Nicholas; Shadbolt, Nigel R.; Dobree, James

The objective of the Market Blended Insight (MBI) project is to develop web based techniques to improve the performance of UK Business to Business (B2B) marketing activities. The analysis of company value chains is a fundamental task within MBI because it is an important model for understanding the market place and the company interactions within it. The project has aggregated rich data profiles of 3.7 million companies that form the active UK business community. The profiles are augmented by Web extractions from heterogeneous sources to provide unparalleled business insight. Advances by the Semantic Web in knowledge representation and logic reasoning allow flexible integration of data from heterogeneous sources, transformation between different representations and reasoning about their meaning. The MBI project has identified that the market insight and analysis interests of different types of users are difficult to maintain using a single domain ontology. Therefore, the project has developed a technique to undertake a plurality of analyses of value chains by deploying a distributed multi-view ontology to capture different user views over the classification of companies and their various relationships.

Quantitative multi-target RNA profiling in Epstein-Barr virus infected tumor cells.

PubMed

Greijer, A E; Ramayanti, O; Verkuijlen, S A W M; Novalić, Z; Juwana, H; Middeldorp, J M

2017-03-01

Epstein-Barr virus (EBV) is etiologically linked to multiple acute, chronic and malignant diseases. Detection of EBV-RNA transcripts in tissues or biofluids besides EBV-DNA can help in diagnosing EBV related syndromes. Sensitive EBV transcription profiling yields new insights on its pathogenic role and may be useful for monitoring virus targeted therapy. Here we describe a multi-gene quantitative RT-PCR profiling method that simultaneously detects a broad spectrum (n=16) of crucial latent and lytic EBV transcripts. These transcripts include (but are not restricted to), EBNA1, EBNA2, LMP1, LMP2, BARTs, EBER1, BARF1 and ZEBRA, Rta, BGLF4 (PK), BXLF1 (TK) and BFRF3 (VCAp18) all of which have been implicated in EBV-driven oncogenesis and viral replication. With this method we determine the amount of RNA copies per infected (tumor) cell in bulk populations of various origin. While we confirm the expected RNA profiles within classic EBV latency programs, this sensitive quantitative approach revealed the presence of rare cells undergoing lytic replication. Inducing lytic replication in EBV tumor cells supports apoptosis and is considered as therapeutic approach to treat EBV-driven malignancies. This sensitive multi-primed quantitative RT-PCR approach can provide broader understanding of transcriptional activity in latent and lytic EBV infection and is suitable for monitoring virus-specific therapy responses in patients with EBV associated cancers. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Structural Optimization of a Force Balance Using a Computational Experiment Design

NASA Technical Reports Server (NTRS)

Parker, P. A.; DeLoach, R.

2002-01-01

This paper proposes a new approach to force balance structural optimization featuring a computational experiment design. Currently, this multi-dimensional design process requires the designer to perform a simplification by executing parameter studies on a small subset of design variables. This one-factor-at-a-time approach varies a single variable while holding all others at a constant level. Consequently, subtle interactions among the design variables, which can be exploited to achieve the design objectives, are undetected. The proposed method combines Modern Design of Experiments techniques to direct the exploration of the multi-dimensional design space, and a finite element analysis code to generate the experimental data. To efficiently search for an optimum combination of design variables and minimize the computational resources, a sequential design strategy was employed. Experimental results from the optimization of a non-traditional force balance measurement section are presented. An approach to overcome the unique problems associated with the simultaneous optimization of multiple response criteria is described. A quantitative single-point design procedure that reflects the designer's subjective impression of the relative importance of various design objectives, and a graphical multi-response optimization procedure that provides further insights into available tradeoffs among competing design objectives are illustrated. The proposed method enhances the intuition and experience of the designer by providing new perspectives on the relationships between the design variables and the competing design objectives providing a systematic foundation for advancements in structural design.

Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations

PubMed Central

Tebani, Abdellah; Afonso, Carlos; Marret, Stéphane; Bekri, Soumeya

2016-01-01

The rise of technologies that simultaneously measure thousands of data points represents the heart of systems biology. These technologies have had a huge impact on the discovery of next-generation diagnostics, biomarkers, and drugs in the precision medicine era. Systems biology aims to achieve systemic exploration of complex interactions in biological systems. Driven by high-throughput omics technologies and the computational surge, it enables multi-scale and insightful overviews of cells, organisms, and populations. Precision medicine capitalizes on these conceptual and technological advancements and stands on two main pillars: data generation and data modeling. High-throughput omics technologies allow the retrieval of comprehensive and holistic biological information, whereas computational capabilities enable high-dimensional data modeling and, therefore, accessible and user-friendly visualization. Furthermore, bioinformatics has enabled comprehensive multi-omics and clinical data integration for insightful interpretation. Despite their promise, the translation of these technologies into clinically actionable tools has been slow. In this review, we present state-of-the-art multi-omics data analysis strategies in a clinical context. The challenges of omics-based biomarker translation are discussed. Perspectives regarding the use of multi-omics approaches for inborn errors of metabolism (IEM) are presented by introducing a new paradigm shift in addressing IEM investigations in the post-genomic era. PMID:27649151

Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations.

PubMed

Tebani, Abdellah; Afonso, Carlos; Marret, Stéphane; Bekri, Soumeya

2016-09-14

The rise of technologies that simultaneously measure thousands of data points represents the heart of systems biology. These technologies have had a huge impact on the discovery of next-generation diagnostics, biomarkers, and drugs in the precision medicine era. Systems biology aims to achieve systemic exploration of complex interactions in biological systems. Driven by high-throughput omics technologies and the computational surge, it enables multi-scale and insightful overviews of cells, organisms, and populations. Precision medicine capitalizes on these conceptual and technological advancements and stands on two main pillars: data generation and data modeling. High-throughput omics technologies allow the retrieval of comprehensive and holistic biological information, whereas computational capabilities enable high-dimensional data modeling and, therefore, accessible and user-friendly visualization. Furthermore, bioinformatics has enabled comprehensive multi-omics and clinical data integration for insightful interpretation. Despite their promise, the translation of these technologies into clinically actionable tools has been slow. In this review, we present state-of-the-art multi-omics data analysis strategies in a clinical context. The challenges of omics-based biomarker translation are discussed. Perspectives regarding the use of multi-omics approaches for inborn errors of metabolism (IEM) are presented by introducing a new paradigm shift in addressing IEM investigations in the post-genomic era.

Insights into the Government’s Role in Food System Policy Making: Improving Access to Healthy, Local Food Alongside Other Priorities

PubMed Central

Wegener, Jessica; Raine, Kim D.; Hanning, Rhona M.

2012-01-01

Government actors have an important role to play in creating healthy public policies and supportive environments to facilitate access to safe, affordable, nutritious food. The purpose of this research was to examine Waterloo Region (Ontario, Canada) as a case study for “what works” with respect to facilitating access to healthy, local food through regional food system policy making. Policy and planning approaches were explored through multi-sectoral perspectives of: (a) the development and adoption of food policies as part of the comprehensive planning process; (b) barriers to food system planning; and (c) the role and motivation of the Region’s public health and planning departments in food system policy making. Forty-seven in-depth interviews with decision makers, experts in public health and planning, and local food system stakeholders provided rich insight into strategic government actions, as well as the local and historical context within which food system policies were developed. Grounded theory methods were used to identify key overarching themes including: “strategic positioning”, “partnerships” and “knowledge transfer” and related sub-themes (“aligned agendas”, “issue framing”, “visioning” and “legitimacy”). A conceptual framework to illustrate the process and features of food system policy making is presented and can be used as a starting point to engage multi-sectoral stakeholders in plans and actions to facilitate access to healthy food. PMID:23202834

Effects of detector dead-time on quantitative analyses involving boron and multi-hit detection events in atom probe tomography.

PubMed

Meisenkothen, Frederick; Steel, Eric B; Prosa, Ty J; Henry, Karen T; Prakash Kolli, R

2015-12-01

In atom probe tomography (APT), some elements tend to field evaporate preferentially in multi-hit detection events. Boron (B) is one such element. It is thought that a large fraction of the B signal may be lost during data acquisition and is not reported in the mass spectrum or in the 3-D APT reconstruction. Understanding the relationship between the field evaporation behavior of B and the limitations for detecting multi-hit events can provide insight into the signal loss mechanism for B and may suggest ways to improve B detection accuracy. The present work reports data for nominally pure B and for B-implanted silicon (Si) (NIST-SRM2137) at dose levels two-orders of magnitude lower than previously studied by Da Costa, et al. in 2012. Boron concentration profiles collected from SRM2137 specimens qualitatively confirmed a signal loss mechanism is at work in laser pulsed atom probe measurements of B in Si. Ion correlation analysis was used to graphically demonstrate that the detector dead-time results in few same isotope, same charge-state (SISCS) ion pairs being properly recorded in the multi-hit data, explaining why B is consistently under-represented in quantitative analyses. Given the important role of detector dead-time as a signal loss mechanism, the results from three different methods of estimating the detector dead-time are presented. The findings of this study apply to all quantitative analyses that involve multi-hit data, but the dead-time will have the greatest effect on the elements that have a significant quantity of ions detected in multi-hit events. Published by Elsevier B.V.

Hybrid LES of Detonations in Reacting Multi-Phase Mixtures

DTIC Science & Technology

2009-02-28

Distortion Theories and Linear Interaction Analyses in order to gain insight in the fundamental processes of compressible turbulence. This analytical...equilibrium. More insight into the development of supersonic mixing layers has been gained later from analytical results, Rapid Distortion Theory ...given by esgs s!t = 0.931i—=•—. Spectral closure theories (Kraichnan [1976]) can be used to evaluate the eddy viscosity formulation as ut = 0.441a -3/2

Insight-HXMT observations of the first binary neutron star merger GW170817

NASA Astrophysics Data System (ADS)

Li, TiPei; Xiong, ShaoLin; Zhang, ShuangNan; Lu, FangJun; Song, LiMing; Cao, XueLei; Chang, Zhi; Chen, Gang; Chen, Li; Chen, TianXiang; Chen, Yong; Chen, YiBao; Chen, YuPeng; Cui, Wei; Cui, WeiWei; Deng, JingKang; Dong, YongWei; Du, YuanYuan; Fu, MinXue; Gao, GuanHua; Gao, He; Gao, Min; Ge, MingYu; Gu, YuDong; Guan, Ju; Guo, ChengCheng; Han, DaWei; Hu, Wei; Huang, Yue; Huo, Jia; Jia, ShuMei; Jiang, LuHua; Jiang, WeiChun; Jin, Jing; Jin, YongJie; Li, Bing; Li, ChengKui; Li, Gang; Li, MaoShun; Li, Wei; Li, Xian; Li, XiaoBo; Li, XuFang; Li, YanGuo; Li, ZiJian; Li, ZhengWei; Liang, XiaoHua; Liao, JinYuan; Liu, CongZhan; Liu, GuoQing; Liu, HongWei; Liu, ShaoZhen; Liu, XiaoJing; Liu, Yuan; Liu, YiNong; Lu, Bo; Lu, XueFeng; Luo, Tao; Ma, Xiang; Meng, Bin; Nang, Yi; Nie, JianYin; Ou, Ge; Qu, JinLu; Sai, Na; Sun, Liang; Tan, Yin; Tao, Lian; Tao, WenHui; Tuo, YouLi; Wang, GuoFeng; Wang, HuanYu; Wang, Juan; Wang, WenShuai; Wang, YuSa; Wen, XiangYang; Wu, BoBing; Wu, Mei; Xiao, GuangCheng; Xu, He; Xu, YuPeng; Yan, LinLi; Yang, JiaWei; Yang, Sheng; Yang, YanJi; Zhang, AiMei; Zhang, ChunLei; Zhang, ChengMo; Zhang, Fan; Zhang, HongMei; Zhang, Juan; Zhang, Qiang; Zhang, Shu; Zhang, Tong; Zhang, Wei; Zhang, WanChang; Zhang, WenZhao; Zhang, Yi; Zhang, Yue; Zhang, YiFei; Zhang, YongJie; Zhang, Zhao; Zhang, ZiLiang; Zhao, HaiSheng; Zhao, JianLing; Zhao, XiaoFan; Zheng, ShiJie; Zhu, Yue; Zhu, YuXuan; Zou, ChangLin

2018-03-01

Finding the electromagnetic (EM) counterpart of binary compact star merger, especially the binary neutron star (BNS) merger, is critically important for gravitational wave (GW) astronomy, cosmology and fundamental physics. On Aug. 17, 2017, Advanced LIGO and Fermi/GBM independently triggered the first BNS merger, GW170817, and its high energy EM counterpart, GRB 170817A, respectively, resulting in a global observation campaign covering gamma-ray, X-ray, UV, optical, IR, radio as well as neutrinos. The High Energy X-ray telescope (HE) onboard Insight-HXMT (Hard X-ray Modulation Telescope) is the unique high-energy gamma-ray telescope that monitored the entire GW localization area and especially the optical counterpart (SSS17a/AT2017gfo) with very large collection area ( 1000 cm2) and microsecond time resolution in 0.2-5 MeV. In addition, Insight-HXMT quickly implemented a Target of Opportunity (ToO) observation to scan the GW localization area for potential X-ray emission from the GW source. Although Insight-HXMT did not detect any significant high energy (0.2-5 MeV) radiation from GW170817, its observation helped to confirm the unexpected weak and soft nature of GRB 170817A. Meanwhile, Insight-HXMT/HE provides one of the most stringent constraints ( 10‒7 to 10‒6 erg/cm2/s) for both GRB170817A and any other possible precursor or extended emissions in 0.2-5 MeV, which help us to better understand the properties of EM radiation from this BNS merger. Therefore the observation of Insight-HXMT constitutes an important chapter in the full context of multi-wavelength and multi-messenger observation of this historical GW event.

Identifying Multimodal Intermediate Phenotypes between Genetic Risk Factors and Disease Status in Alzheimer’s Disease

PubMed Central

Hao, Xiaoke; Yao, Xiaohui; Yan, Jingwen; Risacher, Shannon L.; Saykin, Andrew J.; Zhang, Daoqiang; Shen, Li

2016-01-01

Neuroimaging genetics has attracted growing attention and interest, which is thought to be a powerful strategy to examine the influence of genetic variants (i.e., single nucleotide polymorphisms (SNPs)) on structures or functions of human brain. In recent studies, univariate or multivariate regression analysis methods are typically used to capture the effective associations between genetic variants and quantitative traits (QTs) such as brain imaging phenotypes. The identified imaging QTs, although associated with certain genetic markers, may not be all disease specific. A useful, but underexplored, scenario could be to discover only those QTs associated with both genetic markers and disease status for revealing the chain from genotype to phenotype to symptom. In addition, multimodal brain imaging phenotypes are extracted from different perspectives and imaging markers consistently showing up in multimodalities may provide more insights for mechanistic understanding of diseases (i.e., Alzheimer’s disease (AD)). In this work, we propose a general framework to exploit multi-modal brain imaging phenotypes as intermediate traits that bridge genetic risk factors and multi-class disease status. We applied our proposed method to explore the relation between the well-known AD risk SNP APOE rs429358 and three baseline brain imaging modalities (i.e., structural magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (FDG-PET) and F-18 florbetapir PET scans amyloid imaging (AV45)) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The empirical results demonstrate that our proposed method not only helps improve the performances of imaging genetic associations, but also discovers robust and consistent regions of interests (ROIs) across multi-modalities to guide the disease-induced interpretation. PMID:27277494

Iris features-based heart disease diagnosis by computer vision

NASA Astrophysics Data System (ADS)

Nguchu, Benedictor A.; Li, Li

2017-07-01

The study takes advantage of several new breakthroughs in computer vision technology to develop a new mid-irisbiomedical platform that processes iris image for early detection of heart-disease. Guaranteeing early detection of heart disease provides a possibility of having non-surgical treatment as suggested by biomedical researchers and associated institutions. However, our observation discovered that, a clinical practicable solution which could be both sensible and specific for early detection is still lacking. Due to this, the rate of majority vulnerable to death is highly increasing. The delayed diagnostic procedures, inefficiency, and complications of available methods are the other reasons for this catastrophe. Therefore, this research proposes the novel IFB (Iris Features Based) method for diagnosis of premature, and early stage heart disease. The method incorporates computer vision and iridology to obtain a robust, non-contact, nonradioactive, and cost-effective diagnostic tool. The method analyzes abnormal inherent weakness in tissues, change in color and patterns, of a specific region of iris that responds to impulses of heart organ as per Bernard Jensen-iris Chart. The changes in iris infer the presence of degenerative abnormalities in heart organ. These changes are precisely detected and analyzed by IFB method that includes, tensor-based-gradient(TBG), multi orientations gabor filters(GF), textural oriented features(TOF), and speed-up robust features(SURF). Kernel and Multi class oriented support vector machines classifiers are used for classifying normal and pathological iris features. Experimental results demonstrated that the proposed method, not only has better diagnostic performance, but also provides an insight for early detection of other diseases.

The challenges of quantitative evaluation of a multi-setting, multi-strategy community-based childhood obesity prevention programme: lessons learnt from the eat well be active Community Programs in South Australia.

PubMed

Wilson, Annabelle M; Magarey, Anthea M; Dollman, James; Jones, Michelle; Mastersson, Nadia

2010-08-01

To describe the rationale, development and implementation of the quantitative component of evaluation of a multi-setting, multi-strategy, community-based childhood obesity prevention project (the eat well be active (ewba) Community Programs) and the challenges associated with this process and some potential solutions. ewba has a quasi-experimental design with intervention and comparison communities. Baseline data were collected in 2006 and post-intervention measures will be taken from a non-matched cohort in 2009. Schoolchildren aged 10-12 years were chosen as one litmus group for evaluation purposes. Thirty-nine primary schools in two metropolitan and two rural communities in South Australia. A total of 1732 10-12-year-old school students completed a nutrition and/or a physical activity questionnaire and 1637 had anthropometric measures taken; 983 parents, 286 teachers, thirty-six principals, twenty-six canteen and thirteen out-of-school-hours care (OSHC) workers completed Program-specific questionnaires developed for each of these target groups. The overall child response rate for the study was 49 %. Sixty-five per cent, 43 %, 90 %, 90 % and 68 % of parent, teachers, principals, canteen and OSHC workers respectively, completed and returned questionnaires. A number of practical, logistical and methodological challenges were experienced when undertaking this data collection. Learnings from the process of quantitative baseline data collection for the ewba Community Programs can provide insights for other researchers planning similar studies with similar methods, particularly those evaluating multi-strategy programmes across multiple settings.

A comparative study on dynamic stiffness in typical finite element model and multi-body model of C6-C7 cervical spine segment.

PubMed

Wang, Yawei; Wang, Lizhen; Du, Chengfei; Mo, Zhongjun; Fan, Yubo

2016-06-01

In contrast to numerous researches on static or quasi-static stiffness of cervical spine segments, very few investigations on their dynamic stiffness were published. Currently, scale factors and estimated coefficients were usually used in multi-body models for including viscoelastic properties and damping effects, meanwhile viscoelastic properties of some tissues were unavailable for establishing finite element models. Because dynamic stiffness of cervical spine segments in these models were difficult to validate because of lacking in experimental data, we tried to gain some insights on current modeling methods through studying dynamic stiffness differences between these models. A finite element model and a multi-body model of C6-C7 segment were developed through using available material data and typical modeling technologies. These two models were validated with quasi-static response data of the C6-C7 cervical spine segment. Dynamic stiffness differences were investigated through controlling motions of C6 vertebrae at different rates and then comparing their reaction forces or moments. Validation results showed that both the finite element model and the multi-body model could generate reasonable responses under quasi-static loads, but the finite element segment model exhibited more nonlinear characters. Dynamic response investigations indicated that dynamic stiffness of this finite element model might be underestimated because of the absence of dynamic stiffen effect and damping effects of annulus fibrous, while representation of these effects also need to be improved in current multi-body model. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Theoretical and experimental research on diversity reception technology in NLOS UV communication system.

PubMed

Han, Dahai; Liu, Yile; Zhang, Kai; Luo, Pengfei; Zhang, Min

2012-07-02

Diversity reception technology is introduced into ultraviolet communication area in this article with theory analysis and practical experiment. The idea of diversity reception was known as a critical effective method in wireless communication area that improves the Gain significantly especially for the multi-scattering channel. A theoretical modeling and simulation method are proposed to depict the principle and feasibility of diversity reception adopted in UV communication. Besides, an experimental test-bed using ultraviolet LED and dual receiver of photomultiplier tube is setup to characterize the effects of diversity receiving in non-line-of-sight (NLOS) ultraviolet communication system. The experiment results are compared with the theoretical ones to verify the accuracy of theoretical modeling and the effect of diversity reception. Equal gain combining (EGC) method was adopted as the diversity mechanism in this paper. The research results of theory and experiment provide insight into the channel characteristics and achievable capabilities of ultraviolet communication system with diversity receiving method.

Evaluating the status of individuals and populations: Advantages of multiple approaches and time scales: Chapter 6

USGS Publications Warehouse

Monson, Daniel H.; Bowen, Lizabeth

2015-01-01

Overall, a variety of indices used to measure population status throughout the sea otter’s range have provided insights for understanding the mechanisms driving the trajectory of various sea otter populations, which a single index could not, and we suggest using multiple methods to measure a population’s status at multiple spatial and temporal scales. The work described here also illustrates the usefulness of long-term data sets and/or approaches that can be used to assess population status retrospectively, providing information otherwise not available. While not all systems will be as amenable to using all the approaches presented here, we expect innovative researchers could adapt analogous multi-scale methods to a broad range of habitats and species including apex predators occupying the top trophic levels, which are often of conservation concern.

Combined electrical and resonant optical excitation characterization of multi-quantum well InGaN-based light-emitting diodes

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

Presa, S., E-mail: silvino.presa@tyndall.ie; School of Engineering, University College Cork, Cork; Maaskant, P. P.

We present a comprehensive study of the emission spectra and electrical characteristics of InGaN/GaN multi-quantum well light-emitting diode (LED) structures under resonant optical pumping and varying electrical bias. A 5 quantum well LED with a thin well (1.5 nm) and a relatively thick barrier (6.6 nm) shows strong bias-dependent properties in the emission spectra, poor photovoltaic carrier escape under forward bias and an increase in effective resistance when compared with a 10 quantum well LED with a thin (4 nm) barrier. These properties are due to a strong piezoelectric field in the well and associated reduced field in the thickermore » barrier. We compare the voltage ideality factors for the LEDs under electrical injection, light emission with current, photovoltaic mode (PV) and photoluminescence (PL) emission. The PV and PL methods provide similar values for the ideality which are lower than for the resistance-limited electrical method. Under optical pumping the presence of an n-type InGaN underlayer in a commercial LED sample is shown to act as a second photovoltaic source reducing the photovoltage and the extracted ideality factor to less than 1. The use of photovoltaic measurements together with bias-dependent spectrally resolved luminescence is a powerful method to provide valuable insights into the dynamics of GaN LEDs.« less

Scaling-up impact in perinatology through systems science: Bridging the collaboration and translational divides in cross-disciplinary research and public policy.

PubMed

Munar, Wolfgang; Hovmand, Peter S; Fleming, Carrie; Darmstadt, Gary L

2015-08-01

Despite progress over the past decade in reducing the global burden of newborn deaths, gaps in the knowledge base persist, and means of translating empirical findings into effective policies and programs that deliver life-saving interventions remain poorly understood. Articles in this issue highlight the relevance of transdisciplinary research in perinatology and calls for increased efforts to translate research into public policy and to integrate interventions into existing primary care delivery systems. Given the complexity and multi-causality of many of the remaining challenges in newborn health, and the effects that social and economic factors have over many newborn conditions, it has further been proposed that integrated, multi-sector public policies are also required. In this article, we discuss the application of systems science methods to advance transdisciplinary research and public policy-making in perinatology. Such approaches to research and public policy have been used to address various global challenges but have rarely been implemented in developing country settings. We propose that they hold great promise to improve not only our understanding of complex perinatology problems but can also help translate research-based insights into effective, multi-pronged solutions that deliver positive, intended effects. Examples of successful transdisciplinary science exist, but successes and failures are context specific, and there are no universal blueprints or formulae to reproduce what works in a specific context into different social system settings. Group model building is a tool, based in the field of System Dynamics, that we have used to facilitate transdisciplinary research and, to a lesser extent, policy formulation in a systematic and replicable way. In this article, we describe how group model building can be used and argue for scaling its use to further the translation of empirical evidence and insights into policy and action that increase maternal and neonatal survival and well-being. Copyright © 2015 Elsevier Inc. All rights reserved.

Computationally efficient characterization of potential energy surfaces based on fingerprint distances

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

Schaefer, Bastian; Goedecker, Stefan, E-mail: stefan.goedecker@unibas.ch

2016-07-21

An analysis of the network defined by the potential energy minima of multi-atomic systems and their connectivity via reaction pathways that go through transition states allows us to understand important characteristics like thermodynamic, dynamic, and structural properties. Unfortunately computing the transition states and reaction pathways in addition to the significant energetically low-lying local minima is a computationally demanding task. We here introduce a computationally efficient method that is based on a combination of the minima hopping global optimization method and the insight that uphill barriers tend to increase with increasing structural distances of the educt and product states. This methodmore » allows us to replace the exact connectivity information and transition state energies with alternative and approximate concepts. Without adding any significant additional cost to the minima hopping global optimization approach, this method allows us to generate an approximate network of the minima, their connectivity, and a rough measure for the energy needed for their interconversion. This can be used to obtain a first qualitative idea on important physical and chemical properties by means of a disconnectivity graph analysis. Besides the physical insight obtained by such an analysis, the gained knowledge can be used to make a decision if it is worthwhile or not to invest computational resources for an exact computation of the transition states and the reaction pathways. Furthermore it is demonstrated that the here presented method can be used for finding physically reasonable interconversion pathways that are promising input pathways for methods like transition path sampling or discrete path sampling.« less

Spatial decorrelation stretch of annual (2003-2014) Daymet precipitation summaries on a 1-km grid for California, Nevada, Arizona, and Utah.

PubMed

Ch Miliaresis, George

2016-06-01

A method is presented for elevation (H) and spatial position (X, Y) decorrelation stretch of annual precipitation summaries on a 1-km grid for SW USA for the period 2003 to 2014. Multiple linear regression analysis of the first and second principal component (PC) quantifies the variance in the multi-temporal precipitation imagery that is explained by X, Y, and elevation (h). The multi-temporal dataset is reconstructed from the PC1 and PC2 residual images and the later PCs by taking into account the variance that is not related to X, Y, and h. Clustering of the reconstructed precipitation dataset allowed the definition of positive (for example, in Sierra Nevada, Salt Lake City) and negative (for example, in San Joaquin Valley, Nevada, Colorado Plateau) precipitation anomalies. The temporal and spatial patterns defined from the spatially standardized multi-temporal precipitation imagery provide a tool of comparison for regions in different geographic environments according to the deviation from the precipitation amount that they are expected to receive as function of X, Y, and h. Such a standardization allows the definition of less or more sensitive to climatic change regions and gives an insight in the spatial impact of atmospheric circulation that causes the annual precipitation.

Developing the Students’ English Speaking Ability Through Impromptu Speaking Method.

NASA Astrophysics Data System (ADS)

Lumettu, A.; Runtuwene, T. L.

2018-01-01

Having multi -purposes, English mastery has becomea necessary for us.Of the four language skills, speaking skill should get the first priority in English teaching and speaking skills development cannot be separated from listening.One communicative way of developing speaking skill is impromptu speaking,a method sudden speaking which depends only on experience and insight by applying spontaneity or improvisation. It is delivered based on the need of the moment of speaking using simple language.This research aims to know (1). Why impromptu speaking is necessary in teaching speaking? (2). How can impromptu speaking develop the students’ speaking skills.The method of this research is qualitative method and the techniques of data collection are: observation,interview and documentation. The results of data analysis using Correlation shows a strong relation between the students’ speaking ability and impromptu speaking method (r = 0.80).The research show that by using impromptu speaking method, the students are trained to interact faster naturally and spontaneously and enrich their vocabulary and general science to support speaking development through interview, speech, presentation, discussion and storytelling.

A new approach to spike sorting for multi-neuronal activities recorded with a tetrode--how ICA can be practical.

PubMed

Takahashi, Susumu; Anzai, Yuichiro; Sakurai, Yoshio

2003-07-01

Multi-neuronal recording with a tetrode is a powerful technique to reveal neuronal interactions in local circuits. However, it is difficult to detect precise spike timings among closely neighboring neurons because the spike waveforms of individual neurons overlap on the electrode when more than two neurons fire simultaneously. In addition, the spike waveforms of single neurons, especially in the presence of complex spikes, are often non-stationary. These problems limit the ability of ordinary spike sorting to sort multi-neuronal activities recorded using tetrodes into their single-neuron components. Though sorting with independent component analysis (ICA) can solve these problems, it has one serious limitation that the number of separated neurons must be less than the number of electrodes. Using a combination of ICA and the efficiency of ordinary spike sorting technique (k-means clustering), we developed an automatic procedure to solve the spike-overlapping and the non-stationarity problems with no limitation on the number of separated neurons. The results for the procedure applied to real multi-neuronal data demonstrated that some outliers which may be assigned to distinct clusters if ordinary spike-sorting methods were used can be identified as overlapping spikes, and that there are functional connections between a putative pyramidal neuron and its putative dendrite. These findings suggest that the combination of ICA and k-means clustering can provide insights into the precise nature of functional circuits among neurons, i.e. cell assemblies.

GPU Multi-Scale Particle Tracking and Multi-Fluid Simulations of the Radiation Belts

NASA Astrophysics Data System (ADS)

Ziemba, T.; Carscadden, J.; O'Donnell, D.; Winglee, R.; Harnett, E.; Cash, M.

2007-12-01

The properties of the radiation belts can vary dramatically under the influence of magnetic storms and storm-time substorms. The task of understanding and predicting radiation belt properties is made difficult because their properties determined by global processes as well as small-scale wave-particle interactions. A full solution to the problem will require major innovations in technique and computer hardware. The proposed work will demonstrates liked particle tracking codes with new multi-scale/multi-fluid global simulations that provide the first means to include small-scale processes within the global magnetospheric context. A large hurdle to the problem is having sufficient computer hardware that is able to handle the dissipate temporal and spatial scale sizes. A major innovation of the work is that the codes are designed to run of graphics processing units (GPUs). GPUs are intrinsically highly parallelized systems that provide more than an order of magnitude computing speed over a CPU based systems, for little more cost than a high end-workstation. Recent advancements in GPU technologies allow for full IEEE float specifications with performance up to several hundred GFLOPs per GPU and new software architectures have recently become available to ease the transition from graphics based to scientific applications. This allows for a cheap alternative to standard supercomputing methods and should increase the time to discovery. A demonstration of the code pushing more than 500,000 particles faster than real time is presented, and used to provide new insight into radiation belt dynamics.

Joint explorative analysis of neuroreceptor subsystems in the human brain: application to receptor-transporter correlation using PET data.

PubMed

Cselényi, Zsolt; Lundberg, Johan; Halldin, Christer; Farde, Lars; Gulyás, Balázs

2004-10-01

Positron emission tomography (PET) has proved to be a highly successful technique in the qualitative and quantitative exploration of the human brain's neurotransmitter-receptor systems. In recent years, the number of PET radioligands, targeted to different neuroreceptor systems of the human brain, has increased considerably. This development paves the way for a simultaneous analysis of different receptor systems and subsystems in the same individual. The detailed exploration of the versatility of neuroreceptor systems requires novel technical approaches, capable of operating on huge parametric image datasets. An initial step of such explorative data processing and analysis should be the development of novel exploratory data-mining tools to gain insight into the "structure" of complex multi-individual, multi-receptor data sets. For practical reasons, a possible and feasible starting point of multi-receptor research can be the analysis of the pre- and post-synaptic binding sites of the same neurotransmitter. In the present study, we propose an unsupervised, unbiased data-mining tool for this task and demonstrate its usefulness by using quantitative receptor maps, obtained with positron emission tomography, from five healthy subjects on (pre-synaptic) serotonin transporters (5-HTT or SERT) and (post-synaptic) 5-HT(1A) receptors. Major components of the proposed technique include the projection of the input receptor maps to a feature space, the quasi-clustering and classification of projected data (neighbourhood formation), trans-individual analysis of neighbourhood properties (trajectory analysis), and the back-projection of the results of trajectory analysis to normal space (creation of multi-receptor maps). The resulting multi-receptor maps suggest that complex relationships and tendencies in the relationship between pre- and post-synaptic transporter-receptor systems can be revealed and classified by using this method. As an example, we demonstrate the regional correlation of the serotonin transporter-receptor systems. These parameter-specific multi-receptor maps can usefully guide the researchers in their endeavour to formulate models of multi-receptor interactions and changes in the human brain.

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).

Visual pathways from the perspective of cost functions and multi-task deep neural networks.

PubMed

Scholte, H Steven; Losch, Max M; Ramakrishnan, Kandan; de Haan, Edward H F; Bohte, Sander M

2018-01-01

Vision research has been shaped by the seminal insight that we can understand the higher-tier visual cortex from the perspective of multiple functional pathways with different goals. In this paper, we try to give a computational account of the functional organization of this system by reasoning from the perspective of multi-task deep neural networks. Machine learning has shown that tasks become easier to solve when they are decomposed into subtasks with their own cost function. We hypothesize that the visual system optimizes multiple cost functions of unrelated tasks and this causes the emergence of a ventral pathway dedicated to vision for perception, and a dorsal pathway dedicated to vision for action. To evaluate the functional organization in multi-task deep neural networks, we propose a method that measures the contribution of a unit towards each task, applying it to two networks that have been trained on either two related or two unrelated tasks, using an identical stimulus set. Results show that the network trained on the unrelated tasks shows a decreasing degree of feature representation sharing towards higher-tier layers while the network trained on related tasks uniformly shows high degree of sharing. We conjecture that the method we propose can be used to analyze the anatomical and functional organization of the visual system and beyond. We predict that the degree to which tasks are related is a good descriptor of the degree to which they share downstream cortical-units. Copyright © 2017 Elsevier Ltd. All rights reserved.

Unsupervised multiple kernel learning for heterogeneous data integration.

PubMed

Mariette, Jérôme; Villa-Vialaneix, Nathalie

2018-03-15

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

Experimental creation of quantum Zeno subspaces by repeated multi-spin projections in diamond

NASA Astrophysics Data System (ADS)

Kalb, N.; Cramer, J.; Twitchen, D. J.; Markham, M.; Hanson, R.; Taminiau, T. H.

2016-10-01

Repeated observations inhibit the coherent evolution of quantum states through the quantum Zeno effect. In multi-qubit systems this effect provides opportunities to control complex quantum states. Here, we experimentally demonstrate that repeatedly projecting joint observables of multiple spins creates quantum Zeno subspaces and simultaneously suppresses the dephasing caused by a quasi-static environment. We encode up to two logical qubits in these subspaces and show that the enhancement of the dephasing time with increasing number of projections follows a scaling law that is independent of the number of spins involved. These results provide experimental insight into the interplay between frequent multi-spin measurements and slowly varying noise and pave the way for tailoring the dynamics of multi-qubit systems through repeated projections.

DCE-MRI, DW-MRI, and MRS in Cancer: Challenges and Advantages of Implementing Qualitative and Quantitative Multi-parametric Imaging in the Clinic

PubMed Central

Winfield, Jessica M.; Payne, Geoffrey S.; Weller, Alex; deSouza, Nandita M.

2016-01-01

Abstract Multi-parametric magnetic resonance imaging (mpMRI) offers a unique insight into tumor biology by combining functional MRI techniques that inform on cellularity (diffusion-weighted MRI), vascular properties (dynamic contrast-enhanced MRI), and metabolites (magnetic resonance spectroscopy) and has scope to provide valuable information for prognostication and response assessment. Challenges in the application of mpMRI in the clinic include the technical considerations in acquiring good quality functional MRI data, development of robust techniques for analysis, and clinical interpretation of the results. This article summarizes the technical challenges in acquisition and analysis of multi-parametric MRI data before reviewing the key applications of multi-parametric MRI in clinical research and practice. PMID:27748710

Flexibility: Insights from successful ranchers [abstract

USDA-ARS?s Scientific Manuscript database

Successful ranching families maintain flexibility in their operations over decades to multi-generational time spans. Interviews and focus groups with ranchers in the Western Great Plains help rangeland scientists understand flexibility, and barriers to flexibility, from a “ranchers’ perspective”. I ...

GeneLab: Open Science For Exploration

NASA Technical Reports Server (NTRS)

Galazka, Jonathan

2018-01-01

The NASA GeneLab project capitalizes on multi-omic technologies to maximize the return on spaceflight experiments. The GeneLab project houses spaceflight and spaceflight-relevant multi-omics data in a publicly accessible data commons, and collaborates with NASA-funded principal investigators to maximize the omics data from spaceflight and spaceflight-relevant experiments. I will discuss the current status of GeneLab and give specific examples of how the GeneLab data system has been used to gain insight into how biology responds to spaceflight conditions.

Final Report, “Exploiting Global View for Resilience”

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

Chien, Andrew

2017-03-29

Final technical report for the "Exploiting Global View for Resilience" project. The GVR project aims to create a new approach to portable, resilient applications. The GVR approach builds on a global view data model,, adding versioning (multi-version), user control of timing and rate (multi-stream), and flexible cross layer error signalling and recovery. With a versioned array as a portable abstraction, GVR enables application programmers to exploit deep scientific and application code insights to manage resilience (and its overhead) in a flexible, portable fashion.

A new multi-angle remote sensing framework for scaling vegetation properties from tower-based spectro-radiometers to next generation "CubeSat"-satellites.

NASA Astrophysics Data System (ADS)

Hilker, T.; Hall, F. G.; Dyrud, L. P.; Slagowski, S.

2014-12-01

Frequent earth observations are essential for assessing the risks involved with global climate change, its feedbacks on carbon, energy and water cycling and consequences for live on earth. Often, satellite-remote sensing is the only practical way to provide such observations at comprehensive spatial scales, but relationships between land surface parameters and remotely sensed observations are mostly empirical and cannot easily be scaled across larger areas or over longer time intervals. For instance, optically based methods frequently depend on extraneous effects that are unrelated to the surface property of interest, including the sun-server geometry or background reflectance. As an alternative to traditional, mono-angle techniques, multi-angle remote sensing can help overcome some of these limitations by allowing vegetation properties to be derived from comprehensive reflectance models that describe changes in surface parameters based on physical principles and radiative transfer theory. Recent results have shown in theoretical and experimental research that multi-angle techniques can be used to infer and scale the photosynthetic rate of vegetation, its biochemical and structural composition robustly from remote sensing. Multi-angle remote sensing could therefore revolutionize estimates of the terrestrial carbon uptake as scaling of primary productivity may provide a quantum leap in understanding the spatial and temporal complexity of terrestrial earth science. Here, we introduce a framework of next generation tower-based instruments to a novel and unique constellation of nano-satellites (Figure 1) that will allow us to systematically scale vegetation parameters from stand to global levels. We provide technical insights, scientific rationale and present results. We conclude that future earth observation from multi-angle satellite constellations, supported by tower based remote sensing will open new opportunities for earth system science and earth system modeling.

Theoretical Study of Decomposition Pathways for HArF and HKrF

NASA Technical Reports Server (NTRS)

Chaban, Galina M.; Lundell, Jan; Gerber, R. Benny; Kwak, Donchan (Technical Monitor)

2002-01-01

To provide theoretical insights into the stability and dynamics of the new rare gas compounds HArF and HKrF, reaction paths for decomposition processes HRgF to Rg + HF and HRgF to H + Rg + F (Rg = Ar, Kr) are calculated using ab initio electronic structure methods. The bending channels, HRgF to Rg + HF, are described by single-configurational MP2 and CCSD(T) electronic structure methods, while the linear decomposition paths, HRgF to H + Rg + F, require the use of multi-configurational wave functions that include dynamic correlation and are size extensive. HArF and HKrF molecules are found to be energetically stable with respect to atomic dissociation products (H + Rg + F) and separated by substantial energy barriers from Rg + HF products, which ensure their kinetic stability. The results are compatible with experimental data on these systems.

High-resolution eye tracking using V1 neuron activity

PubMed Central

McFarland, James M.; Bondy, Adrian G.; Cumming, Bruce G.; Butts, Daniel A.

2014-01-01

Studies of high-acuity visual cortical processing have been limited by the inability to track eye position with sufficient accuracy to precisely reconstruct the visual stimulus on the retina. As a result, studies on primary visual cortex (V1) have been performed almost entirely on neurons outside the high-resolution central portion of the visual field (the fovea). Here we describe a procedure for inferring eye position using multi-electrode array recordings from V1 coupled with nonlinear stimulus processing models. We show that this method can be used to infer eye position with one arc-minute accuracy – significantly better than conventional techniques. This allows for analysis of foveal stimulus processing, and provides a means to correct for eye-movement induced biases present even outside the fovea. This method could thus reveal critical insights into the role of eye movements in cortical coding, as well as their contribution to measures of cortical variability. PMID:25197783

Carbene footprinting accurately maps binding sites in protein-ligand and protein-protein interactions

NASA Astrophysics Data System (ADS)

Manzi, Lucio; Barrow, Andrew S.; Scott, Daniel; Layfield, Robert; Wright, Timothy G.; Moses, John E.; Oldham, Neil J.

2016-11-01

Specific interactions between proteins and their binding partners are fundamental to life processes. The ability to detect protein complexes, and map their sites of binding, is crucial to understanding basic biology at the molecular level. Methods that employ sensitive analytical techniques such as mass spectrometry have the potential to provide valuable insights with very little material and on short time scales. Here we present a differential protein footprinting technique employing an efficient photo-activated probe for use with mass spectrometry. Using this methodology the location of a carbohydrate substrate was accurately mapped to the binding cleft of lysozyme, and in a more complex example, the interactions between a 100 kDa, multi-domain deubiquitinating enzyme, USP5 and a diubiquitin substrate were located to different functional domains. The much improved properties of this probe make carbene footprinting a viable method for rapid and accurate identification of protein binding sites utilizing benign, near-UV photoactivation.

High-order interactions observed in multi-task intrinsic networks are dominant indicators of aberrant brain function in schizophrenia

PubMed Central

Plis, Sergey M; Sui, Jing; Lane, Terran; Roy, Sushmita; Clark, Vincent P; Potluru, Vamsi K; Huster, Rene J; Michael, Andrew; Sponheim, Scott R; Weisend, Michael P; Calhoun, Vince D

2013-01-01

Identifying the complex activity relationships present in rich, modern neuroimaging data sets remains a key challenge for neuroscience. The problem is hard because (a) the underlying spatial and temporal networks may be nonlinear and multivariate and (b) the observed data may be driven by numerous latent factors. Further, modern experiments often produce data sets containing multiple stimulus contexts or tasks processed by the same subjects. Fusing such multi-session data sets may reveal additional structure, but raises further statistical challenges. We present a novel analysis method for extracting complex activity networks from such multifaceted imaging data sets. Compared to previous methods, we choose a new point in the trade-off space, sacrificing detailed generative probability models and explicit latent variable inference in order to achieve robust estimation of multivariate, nonlinear group factors (“network clusters”). We apply our method to identify relationships of task-specific intrinsic networks in schizophrenia patients and control subjects from a large fMRI study. After identifying network-clusters characterized by within- and between-task interactions, we find significant differences between patient and control groups in interaction strength among networks. Our results are consistent with known findings of brain regions exhibiting deviations in schizophrenic patients. However, we also find high-order, nonlinear interactions that discriminate groups but that are not detected by linear, pair-wise methods. We additionally identify high-order relationships that provide new insights into schizophrenia but that have not been found by traditional univariate or second-order methods. Overall, our approach can identify key relationships that are missed by existing analysis methods, without losing the ability to find relationships that are known to be important. PMID:23876245

A New Treatment Strategy for Inactivating Algae in Ballast Water Based on Multi-Trial Injections of Chlorine

PubMed Central

Sun, Jinyang; Wang, Junsheng; Pan, Xinxiang; Yuan, Haichao

2015-01-01

Ships’ ballast water can carry aquatic organisms into foreign ecosystems. In our previous studies, a concept using ion exchange membrane electrolysis to treat ballast water has been proven. In addition to other substantial approaches, a new strategy for inactivating algae is proposed based on the developed ballast water treatment system. In the new strategy, the means of multi-trial injection with small doses of electrolytic products is applied for inactivating algae. To demonstrate the performance of the new strategy, contrast experiments between new strategies and routine processes were conducted. Four algae species including Chlorella vulgaris, Platymonas subcordiformis, Prorocentrum micans and Karenia mikimotoi were chosen as samples. The different experimental parameters are studied including the injection times and doses of electrolytic products. Compared with the conventional one trial injection method, mortality rate time (MRT) and available chlorine concentration can be saved up to about 84% and 40%, respectively, under the application of the new strategy. The proposed new approach has great potential in practical ballast water treatment. Furthermore, the strategy is also helpful for deep insight of mechanism of algal tolerance. PMID:26068239

Multiscale recurrence analysis of spatio-temporal data

NASA Astrophysics Data System (ADS)

Riedl, M.; Marwan, N.; Kurths, J.

2015-12-01

The description and analysis of spatio-temporal dynamics is a crucial task in many scientific disciplines. In this work, we propose a method which uses the mapogram as a similarity measure between spatially distributed data instances at different time points. The resulting similarity values of the pairwise comparison are used to construct a recurrence plot in order to benefit from established tools of recurrence quantification analysis and recurrence network analysis. In contrast to other recurrence tools for this purpose, the mapogram approach allows the specific focus on different spatial scales that can be used in a multi-scale analysis of spatio-temporal dynamics. We illustrate this approach by application on mixed dynamics, such as traveling parallel wave fronts with additive noise, as well as more complicate examples, pseudo-random numbers and coupled map lattices with a semi-logistic mapping rule. Especially the complicate examples show the usefulness of the multi-scale consideration in order to take spatial pattern of different scales and with different rhythms into account. So, this mapogram approach promises new insights in problems of climatology, ecology, or medicine.

Multiscale recurrence analysis of spatio-temporal data.

PubMed

Riedl, M; Marwan, N; Kurths, J

2015-12-01

The description and analysis of spatio-temporal dynamics is a crucial task in many scientific disciplines. In this work, we propose a method which uses the mapogram as a similarity measure between spatially distributed data instances at different time points. The resulting similarity values of the pairwise comparison are used to construct a recurrence plot in order to benefit from established tools of recurrence quantification analysis and recurrence network analysis. In contrast to other recurrence tools for this purpose, the mapogram approach allows the specific focus on different spatial scales that can be used in a multi-scale analysis of spatio-temporal dynamics. We illustrate this approach by application on mixed dynamics, such as traveling parallel wave fronts with additive noise, as well as more complicate examples, pseudo-random numbers and coupled map lattices with a semi-logistic mapping rule. Especially the complicate examples show the usefulness of the multi-scale consideration in order to take spatial pattern of different scales and with different rhythms into account. So, this mapogram approach promises new insights in problems of climatology, ecology, or medicine.

Assessment of Closed-Loop Control Using Multi-Mode Sensor Fusion For a High Reynolds Number Transonic Jet

NASA Astrophysics Data System (ADS)

Low, Kerwin; Elhadidi, Basman; Glauser, Mark

2009-11-01

Understanding the different noise production mechanisms caused by the free shear flows in a turbulent jet flow provides insight to improve ``intelligent'' feedback mechanisms to control the noise. Towards this effort, a control scheme is based on feedback of azimuthal pressure measurements in the near field of the jet at two streamwise locations. Previous studies suggested that noise reduction can be achieved by azimuthal actuators perturbing the shear layer at the jet lip. The closed-loop actuation will be based on a low-dimensional Fourier representation of the hydrodynamic pressure measurements. Preliminary results show that control authority and reduction in the overall sound pressure level was possible. These results provide motivation to move forward with the overall vision of developing innovative multi-mode sensing methods to improve state estimation and derive dynamical systems. It is envisioned that estimating velocity-field and dynamic pressure information from various locations both local and in the far-field regions, sensor fusion techniques can be utilized to ascertain greater overall control authority.

Deep feature learning for knee cartilage segmentation using a triplanar convolutional neural network.

PubMed

Prasoon, Adhish; Petersen, Kersten; Igel, Christian; Lauze, François; Dam, Erik; Nielsen, Mads

2013-01-01

Segmentation of anatomical structures in medical images is often based on a voxel/pixel classification approach. Deep learning systems, such as convolutional neural networks (CNNs), can infer a hierarchical representation of images that fosters categorization. We propose a novel system for voxel classification integrating three 2D CNNs, which have a one-to-one association with the xy, yz and zx planes of 3D image, respectively. We applied our method to the segmentation of tibial cartilage in low field knee MRI scans and tested it on 114 unseen scans. Although our method uses only 2D features at a single scale, it performs better than a state-of-the-art method using 3D multi-scale features. In the latter approach, the features and the classifier have been carefully adapted to the problem at hand. That we were able to get better results by a deep learning architecture that autonomously learns the features from the images is the main insight of this study.

Separation of Intercepted Multi-Radar Signals Based on Parameterized Time-Frequency Analysis

NASA Astrophysics Data System (ADS)

Lu, W. L.; Xie, J. W.; Wang, H. M.; Sheng, C.

2016-09-01

Modern radars use complex waveforms to obtain high detection performance and low probabilities of interception and identification. Signals intercepted from multiple radars overlap considerably in both the time and frequency domains and are difficult to separate with primary time parameters. Time-frequency analysis (TFA), as a key signal-processing tool, can provide better insight into the signal than conventional methods. In particular, among the various types of TFA, parameterized time-frequency analysis (PTFA) has shown great potential to investigate the time-frequency features of such non-stationary signals. In this paper, we propose a procedure for PTFA to separate overlapped radar signals; it includes five steps: initiation, parameterized time-frequency analysis, demodulating the signal of interest, adaptive filtering and recovering the signal. The effectiveness of the method was verified with simulated data and an intercepted radar signal received in a microwave laboratory. The results show that the proposed method has good performance and has potential in electronic reconnaissance applications, such as electronic intelligence, electronic warfare support measures, and radar warning.

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

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

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-Modal Traveler Information System - Gateway Design Options

DOT National Transportation Integrated Search

1997-05-19

The purpose of this working paper is to provide insight into the options that are available from which to design the Gateway Traveler Information System (TIS). This working paper will discuss each option in a general manner without becoming overly te...

Panarchy use in environmental science for risk and resilience planning

EPA Science Inventory

Environmental sciences have an important role in informing sustainable management of built environments by providing insights about the drivers and potentially negative impacts of global environmental change. Here, we discuss panarchy theory, a multi-scale hierarchical concept th...

Multi-parameter phenotypic profiling: using cellular effects to characterize small-molecule compounds.

PubMed

Feng, Yan; Mitchison, Timothy J; Bender, Andreas; Young, Daniel W; Tallarico, John A

2009-07-01

Multi-parameter phenotypic profiling of small molecules provides important insights into their mechanisms of action, as well as a systems level understanding of biological pathways and their responses to small molecule treatments. It therefore deserves more attention at an early step in the drug discovery pipeline. Here, we summarize the technologies that are currently in use for phenotypic profiling--including mRNA-, protein- and imaging-based multi-parameter profiling--in the drug discovery context. We think that an earlier integration of phenotypic profiling technologies, combined with effective experimental and in silico target identification approaches, can improve success rates of lead selection and optimization in the drug discovery process.

A multi-level model of emerging technology: An empirical study of the evolution of biotechnology from 1976 to 2003

PubMed Central

van Witteloostuijn, Arjen

2018-01-01

In this paper, we develop an ecological, multi-level model that can be used to study the evolution of emerging technology. More specifically, by defining technology as a system composed of a set of interacting components, we can build upon the argument of multi-level density dependence from organizational ecology to develop a distribution-independent model of technological evolution. This allows us to distinguish between different stages of component development, which provides more insight into the emergence of stable component configurations, or dominant designs. We validate our hypotheses in the biotechnology industry by using patent data from the USPTO from 1976 to 2003. PMID:29795575

Multitime correlation functions in nonclassical stochastic processes

NASA Astrophysics Data System (ADS)

Krumm, F.; Sperling, J.; Vogel, W.

2016-06-01

A general method is introduced for verifying multitime quantum correlations through the characteristic function of the time-dependent P functional that generalizes the Glauber-Sudarshan P function. Quantum correlation criteria are derived which identify quantum effects for an arbitrary number of points in time. The Magnus expansion is used to visualize the impact of the required time ordering, which becomes crucial in situations when the interaction problem is explicitly time dependent. We show that the latter affects the multi-time-characteristic function and, therefore, the temporal evolution of the nonclassicality. As an example, we apply our technique to an optical parametric process with a frequency mismatch. The resulting two-time-characteristic function yields full insight into the two-time quantum correlation properties of such a system.

DNAism: exploring genomic datasets on the web with Horizon Charts.

PubMed

Rio Deiros, David; Gibbs, Richard A; Rogers, Jeffrey

2016-01-27

Computational biologists daily face the need to explore massive amounts of genomic data. New visualization techniques can help researchers navigate and understand these big data. Horizon Charts are a relatively new visualization method that, under the right circumstances, maximizes data density without losing graphical perception. Horizon Charts have been successfully applied to understand multi-metric time series data. We have adapted an existing JavaScript library (Cubism) that implements Horizon Charts for the time series domain so that it works effectively with genomic datasets. We call this new library DNAism. Horizon Charts can be an effective visual tool to explore complex and large genomic datasets. Researchers can use our library to leverage these techniques to extract additional insights from their own datasets.

On process optimization considering LCA methodology.

PubMed

Pieragostini, Carla; Mussati, Miguel C; Aguirre, Pío

2012-04-15

The goal of this work is to research the state-of-the-art in process optimization techniques and tools based on LCA, focused in the process engineering field. A collection of methods, approaches, applications, specific software packages, and insights regarding experiences and progress made in applying the LCA methodology coupled to optimization frameworks is provided, and general trends are identified. The "cradle-to-gate" concept to define the system boundaries is the most used approach in practice, instead of the "cradle-to-grave" approach. Normally, the relationship between inventory data and impact category indicators is linearly expressed by the characterization factors; then, synergic effects of the contaminants are neglected. Among the LCIA methods, the eco-indicator 99, which is based on the endpoint category and the panel method, is the most used in practice. A single environmental impact function, resulting from the aggregation of environmental impacts, is formulated as the environmental objective in most analyzed cases. SimaPro is the most used software for LCA applications in literature analyzed. The multi-objective optimization is the most used approach for dealing with this kind of problems, where the ε-constraint method for generating the Pareto set is the most applied technique. However, a renewed interest in formulating a single economic objective function in optimization frameworks can be observed, favored by the development of life cycle cost software and progress made in assessing costs of environmental externalities. Finally, a trend to deal with multi-period scenarios into integrated LCA-optimization frameworks can be distinguished providing more accurate results upon data availability. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Separable Two-Dimensional Random Field Model of Binary Response Data from Multi-Day Behavioral Experiments.

PubMed

Malem-Shinitski, Noa; Zhang, Yingzhuo; Gray, Daniel T; Burke, Sara N; Smith, Anne C; Barnes, Carol A; Ba, Demba

2018-04-18

The study of learning in populations of subjects can provide insights into the changes that occur in the brain with aging, drug intervention, and psychiatric disease. We introduce a separable two-dimensional (2D) random field (RF) model for analyzing binary response data acquired during the learning of object-reward associations across multiple days. The method can quantify the variability of performance within a day and across days, and can capture abrupt changes in learning. We apply the method to data from young and aged macaque monkeys performing a reversal-learning task. The method provides an estimate of performance within a day for each age group, and a learning rate across days for each monkey. We find that, as a group, the older monkeys require more trials to learn the object discriminations than do the young monkeys, and that the cognitive flexibility of the younger group is higher. We also use the model estimates of performance as features for clustering the monkeys into two groups. The clustering results in two groups that, for the most part, coincide with those formed by the age groups. Simulation studies suggest that clustering captures inter-individual differences in performance levels. In comparison with generalized linear models, this method is better able to capture the inherent two-dimensional nature of the data and find between group differences. Applied to binary response data from groups of individuals performing multi-day behavioral experiments, the model discriminates between-group differences and identifies subgroups. Copyright © 2018. Published by Elsevier B.V.

Unlocking the secrets of multi-flagellated propulsion: drawing insights from Tritrichomonas foetus

PubMed Central

Lenaghan, Scott C.; Nwandu-Vincent, Stefan; Reese, Benjamin E.; Zhang, Mingjun

2014-01-01

In this work, a high-speed imaging platform and a resistive force theory (RFT) based model were applied to investigate multi-flagellated propulsion, using Tritrichomonas foetus as an example. We discovered that T. foetus has distinct flagellar beating motions for linear swimming and turning, similar to the ‘run and tumble’ strategies observed in bacteria and Chlamydomonas. Quantitative analysis of the motion of each flagellum was achieved by determining the average flagella beat motion for both linear swimming and turning, and using the velocity of the flagella as inputs into the RFT model. The experimental approach was used to calculate the curvature along the length of the flagella throughout each stroke. It was found that the curvatures of the anterior flagella do not decrease monotonically along their lengths, confirming the ciliary waveform of these flagella. Further, the stiffness of the flagella was experimentally measured using nanoindentation, allowing for calculation of the flexural rigidity of T. foetus's flagella, 1.55×10−21 N m2. Finally, using the RFT model, it was discovered that the propulsive force of T. foetus was similar to that of sperm and Chlamydomonas, indicating that multi-flagellated propulsion does not necessarily contribute to greater thrust generation, and may have evolved for greater manoeuvrability or sensing. The results from this study have demonstrated the highly coordinated nature of multi-flagellated propulsion and have provided significant insights into the biology of T. foetus. PMID:24478286

The Crabapple Experience: Insights from Program Evaluations.

ERIC Educational Resources Information Center

Elmore, Randy; Wisenbaker, Joe

2000-01-01

An evaluation of a Georgia middle school's multi-age grouping program revealed significant progress regarding student self-esteem, achievement, community building, and teacher collaboration. The Crabapple experience illustrates how one model of student-centered, developmentally appropriate, and integrated learning can benefit middle-level…

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.

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

Persistent Topology and Metastable State in Conformational Dynamics

PubMed Central

Chang, Huang-Wei; Bacallado, Sergio; Pande, Vijay S.; Carlsson, Gunnar E.

2013-01-01

The large amount of molecular dynamics simulation data produced by modern computational models brings big opportunities and challenges to researchers. Clustering algorithms play an important role in understanding biomolecular kinetics from the simulation data, especially under the Markov state model framework. However, the ruggedness of the free energy landscape in a biomolecular system makes common clustering algorithms very sensitive to perturbations of the data. Here, we introduce a data-exploratory tool which provides an overview of the clustering structure under different parameters. The proposed Multi-Persistent Clustering analysis combines insights from recent studies on the dynamics of systems with dominant metastable states with the concept of multi-dimensional persistence in computational topology. We propose to explore the clustering structure of the data based on its persistence on scale and density. The analysis provides a systematic way to discover clusters that are robust to perturbations of the data. The dominant states of the system can be chosen with confidence. For the clusters on the borderline, the user can choose to do more simulation or make a decision based on their structural characteristics. Furthermore, our multi-resolution analysis gives users information about the relative potential of the clusters and their hierarchical relationship. The effectiveness of the proposed method is illustrated in three biomolecules: alanine dipeptide, Villin headpiece, and the FiP35 WW domain. PMID:23565139

Contextual analysis of immunological response through whole-organ fluorescent imaging.

PubMed

Woodruff, Matthew C; Herndon, Caroline N; Heesters, B A; Carroll, Michael C

2013-09-01

As fluorescent microscopy has developed, significant insights have been gained into the establishment of immune response within secondary lymphoid organs, particularly in draining lymph nodes. While established techniques such as confocal imaging and intravital multi-photon microscopy have proven invaluable, they provide limited insight into the architectural and structural context in which these responses occur. To interrogate the role of the lymph node environment in immune response effectively, a new set of imaging tools taking into account broader architectural context must be implemented into emerging immunological questions. Using two different methods of whole-organ imaging, optical clearing and three-dimensional reconstruction of serially sectioned lymph nodes, fluorescent representations of whole lymph nodes can be acquired at cellular resolution. Using freely available post-processing tools, images of unlimited size and depth can be assembled into cohesive, contextual snapshots of immunological response. Through the implementation of robust iterative analysis techniques, these highly complex three-dimensional images can be objectified into sortable object data sets. These data can then be used to interrogate complex questions at the cellular level within the broader context of lymph node biology. By combining existing imaging technology with complex methods of sample preparation and capture, we have developed efficient systems for contextualizing immunological phenomena within lymphatic architecture. In combination with robust approaches to image analysis, these advances provide a path to integrating scientific understanding of basic lymphatic biology into the complex nature of immunological response.

A multi-dimensional approach to insight and its evolution in first-episode psychosis: a 1-year outcome naturalistic study.

PubMed

Capdevielle, Delphine; Norton, Joanna; Jaussent, Isabelle; Prud'homme, Cindy; Raffard, Stéphane; Gelly, Françoise; Boulenger, Jean-Philippe; Ritchie, Karen

2013-12-30

The aim of the study was to describe the evolution of the different dimensions of insight at 1 year and its associations with psychopathology and symptomatic remission. Participants included 55 patients hospitalized for a first psychosis episode and followed up at 6 and 12 months after discharge. Measures included the Scale to Assess Unawareness of Mental Disorder and the Positive and Negative Syndrome Scale (PANSS). Six dimensions of insight were evaluated, for current episode at hospital discharge and at 6 and 12 month FUs and past episode (at 6 and 12 month follow-ups). Our results show that concerning the current episode, only awareness of the social consequences and of the positive symptoms significantly improved during follow-up. Insight into the past episode improved for awareness of having a mental disorder, the social consequences and the positive symptoms of mental illness. Cross-sectional associations between insight and PANSS show weak to moderate, albeit significant, associations. Most of the dimensions of insight are positively and significantly associated with remission. Our findings suggest that the main underlying dimensions of insight evolve differently over time, which could suggest different inherent processes. This could be useful for developing psychotherapeutic programmes acting upon the different aspects of insight. © 2013 Elsevier Ireland Ltd. All rights reserved.

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.

Protein Dynamics from NMR: The Slowly Relaxing Local Structure Analysis Compared with Model-Free Analysis

PubMed Central

Meirovitch, Eva; Shapiro, Yury E.; Polimeno, Antonino; Freed, Jack H.

2009-01-01

15N-1H spin relaxation is a powerful method for deriving information on protein dynamics. The traditional method of data analysis is model-free (MF), where the global and local N-H motions are independent and the local geometry is simplified. The common MF analysis consists of fitting single-field data. The results are typically field-dependent, and multi-field data cannot be fit with standard fitting schemes. Cases where known functional dynamics has not been detected by MF were identified by us and others. Recently we applied to spin relaxation in proteins the Slowly Relaxing Local Structure (SRLS) approach which accounts rigorously for mode-mixing and general features of local geometry. SRLS was shown to yield MF in appropriate asymptotic limits. We found that the experimental spectral density corresponds quite well to the SRLS spectral density. The MF formulae are often used outside of their validity ranges, allowing small data sets to be force-fitted with good statistics but inaccurate best-fit parameters. This paper focuses on the mechanism of force-fitting and its implications. It is shown that MF force-fits the experimental data because mode-mixing, the rhombic symmetry of the local ordering and general features of local geometry are not accounted for. Combined multi-field multi-temperature data analyzed by MF may lead to the detection of incorrect phenomena, while conformational entropy derived from MF order parameters may be highly inaccurate. On the other hand, fitting to more appropriate models can yield consistent physically insightful information. This requires that the complexity of the theoretical spectral densities matches the integrity of the experimental data. As shown herein, the SRLS densities comply with this requirement. PMID:16821820

Eliminating bovine tuberculosis in cattle and badgers: insight from a dynamic model.

PubMed

Brooks-Pollock, Ellen; Wood, James L N

2015-06-07

Bovine tuberculosis (BTB) is a multi-species infection that commonly affects cattle and badgers in Great Britain. Despite years of study, the impact of badgers on BTB incidence in cattle is poorly understood. Using a two-host transmission model of BTB in cattle and badgers, we find that published data and parameter estimates are most consistent with a system at the threshold of control. The most consistent explanation for data obtained from cattle and badger populations includes within-host reproduction numbers close to 1 and between-host reproduction numbers of approximately 0.05. In terms of controlling infection in cattle, reducing cattle-to-cattle transmission is essential. In some regions, even large reductions in badger prevalence can have a modest impact on cattle infection and a multi-stranded approach is necessary that also targets badger-to-cattle transmission directly. The new perspective highlighted by this two-host approach provides insight into the control of BTB in Great Britain.

Eliminating bovine tuberculosis in cattle and badgers: insight from a dynamic model

PubMed Central

Brooks-Pollock, Ellen; Wood, James L. N.

2015-01-01

Bovine tuberculosis (BTB) is a multi-species infection that commonly affects cattle and badgers in Great Britain. Despite years of study, the impact of badgers on BTB incidence in cattle is poorly understood. Using a two-host transmission model of BTB in cattle and badgers, we find that published data and parameter estimates are most consistent with a system at the threshold of control. The most consistent explanation for data obtained from cattle and badger populations includes within-host reproduction numbers close to 1 and between-host reproduction numbers of approximately 0.05. In terms of controlling infection in cattle, reducing cattle-to-cattle transmission is essential. In some regions, even large reductions in badger prevalence can have a modest impact on cattle infection and a multi-stranded approach is necessary that also targets badger-to-cattle transmission directly. The new perspective highlighted by this two-host approach provides insight into the control of BTB in Great Britain. PMID:25972466

Transforming Big Data into cancer-relevant insight: An initial, multi-tier approach to assess reproducibility and relevance

PubMed Central

2016-01-01

The Cancer Target Discovery and Development (CTD2) Network was established to accelerate the transformation of “Big Data” into novel pharmacological targets, lead compounds, and biomarkers for rapid translation into improved patient outcomes. It rapidly became clear in this collaborative network that a key central issue was to define what constitutes sufficient computational or experimental evidence to support a biologically or clinically relevant finding. This manuscript represents a first attempt to delineate the challenges of supporting and confirming discoveries arising from the systematic analysis of large-scale data resources in a collaborative work environment and to provide a framework that would begin a community discussion to resolve these challenges. The Network implemented a multi-Tier framework designed to substantiate the biological and biomedical relevance as well as the reproducibility of data and insights resulting from its collaborative activities. The same approach can be used by the broad scientific community to drive development of novel therapeutic and biomarker strategies for cancer. PMID:27401613

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

Perdikaris, Paris, E-mail: parisp@mit.edu; Grinberg, Leopold, E-mail: leopoldgrinberg@us.ibm.com; Karniadakis, George Em, E-mail: george-karniadakis@brown.edu

The aim of this work is to present an overview of recent advances in multi-scale modeling of brain blood flow. In particular, we present some approaches that enable the in silico study of multi-scale and multi-physics phenomena in the cerebral vasculature. We discuss the formulation of continuum and atomistic modeling approaches, present a consistent framework for their concurrent coupling, and list some of the challenges that one needs to overcome in achieving a seamless and scalable integration of heterogeneous numerical solvers. The effectiveness of the proposed framework is demonstrated in a realistic case involving modeling the thrombus formation process takingmore » place on the wall of a patient-specific cerebral aneurysm. This highlights the ability of multi-scale algorithms to resolve important biophysical processes that span several spatial and temporal scales, potentially yielding new insight into the key aspects of brain blood flow in health and disease. Finally, we discuss open questions in multi-scale modeling and emerging topics of future research.« less

Multiscale modeling and simulation of brain blood flow

NASA Astrophysics Data System (ADS)

Perdikaris, Paris; Grinberg, Leopold; Karniadakis, George Em

2016-02-01

The aim of this work is to present an overview of recent advances in multi-scale modeling of brain blood flow. In particular, we present some approaches that enable the in silico study of multi-scale and multi-physics phenomena in the cerebral vasculature. We discuss the formulation of continuum and atomistic modeling approaches, present a consistent framework for their concurrent coupling, and list some of the challenges that one needs to overcome in achieving a seamless and scalable integration of heterogeneous numerical solvers. The effectiveness of the proposed framework is demonstrated in a realistic case involving modeling the thrombus formation process taking place on the wall of a patient-specific cerebral aneurysm. This highlights the ability of multi-scale algorithms to resolve important biophysical processes that span several spatial and temporal scales, potentially yielding new insight into the key aspects of brain blood flow in health and disease. Finally, we discuss open questions in multi-scale modeling and emerging topics of future research.

Physical Interpretation of the Correlation Between Multi-Angle Spectral Data and Canopy Height

NASA Technical Reports Server (NTRS)

Schull, M. A.; Ganguly, S.; Samanta, A.; Huang, D.; Shabanov, N. V.; Jenkins, J. P.; Chiu, J. C.; Marshak, A.; Blair, J. B.; Myneni, R. B.;

Patient perspectives of telemedicine quality

PubMed Central

LeRouge, Cynthia M; Garfield, Monica J; Hevner, Alan R

2015-01-01

Background The purpose of this study was to explore the quality attributes required for effective telemedicine encounters from the perspective of the patient. Methods We used a multi-method (direct observation, focus groups, survey) field study to collect data from patients who had experienced telemedicine encounters. Multi-perspectives (researcher and provider) were used to interpret a rich set of data from both a research and practice perspective. Results The result of this field study is a taxonomy of quality attributes for telemedicine service encounters that prioritizes the attributes from the patient perspective. We identify opportunities to control the level of quality for each attribute (ie, who is responsible for control of each attribute and when control can be exerted in relation to the encounter process). This analysis reveals that many quality attributes are in the hands of various stakeholders, and all attributes can be addressed proactively to some degree before the encounter begins. Conclusion Identification of the quality attributes important to a telemedicine encounter from a patient perspective enables one to better design telemedicine encounters. This preliminary work not only identifies such attributes, but also ascertains who is best able to address quality issues prior to an encounter. For practitioners, explicit representation of the quality attributes of technology-based systems and processes and insight on controlling key attributes are essential to implementation, utilization, management, and common understanding. PMID:25565781

Robust Crossfeed Design for Hovering Rotorcraft

NASA Technical Reports Server (NTRS)

Catapang, David R.

1993-01-01

Control law design for rotorcraft fly-by-wire systems normally attempts to decouple angular responses using fixed-gain crossfeeds. This approach can lead to poor decoupling over the frequency range of pilot inputs and increase the load on the feedback loops. In order to improve the decoupling performance, dynamic crossfeeds may be adopted. Moreover, because of the large changes that occur in rotorcraft dynamics due to small changes about the nominal design condition, especially for near-hovering flight, the crossfeed design must be 'robust'. A new low-order matching method is presented here to design robust crossfeed compensators for multi-input, multi-output (MIMO) systems. The technique identifies degrees-of-freedom that can be decoupled using crossfeeds, given an anticipated set of parameter variations for the range of flight conditions of concern. Cross-coupling is then reduced for degrees-of-freedom that can use crossfeed compensation by minimizing off-axis response magnitude average and variance. Results are presented for the analysis of pitch, roll, yaw and heave coupling of the UH-60 Black Hawk helicopter in near-hovering flight. Robust crossfeeds are designed that show significant improvement in decoupling performance and robustness over nominal, single design point, compensators. The design method and results are presented in an easily used graphical format that lends significant physical insight to the design procedure. This plant pre-compensation technique is an appropriate preliminary step to the design of robust feedback control laws for rotorcraft.

Use of Model-Based Design Methods for Enhancing Resiliency Analysis of Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Knox, Lenora A.

The most common traditional non-functional requirement analysis is reliability. With systems becoming more complex, networked, and adaptive to environmental uncertainties, system resiliency has recently become the non-functional requirement analysis of choice. Analysis of system resiliency has challenges; which include, defining resilience for domain areas, identifying resilience metrics, determining resilience modeling strategies, and understanding how to best integrate the concepts of risk and reliability into resiliency. Formal methods that integrate all of these concepts do not currently exist in specific domain areas. Leveraging RAMSoS, a model-based reliability analysis methodology for Systems of Systems (SoS), we propose an extension that accounts for resiliency analysis through evaluation of mission performance, risk, and cost using multi-criteria decision-making (MCDM) modeling and design trade study variability modeling evaluation techniques. This proposed methodology, coined RAMSoS-RESIL, is applied to a case study in the multi-agent unmanned aerial vehicle (UAV) domain to investigate the potential benefits of a mission architecture where functionality to complete a mission is disseminated across multiple UAVs (distributed) opposed to being contained in a single UAV (monolithic). The case study based research demonstrates proof of concept for the proposed model-based technique and provides sufficient preliminary evidence to conclude which architectural design (distributed vs. monolithic) is most resilient based on insight into mission resilience performance, risk, and cost in addition to the traditional analysis of reliability.

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.

Application of multi-grid methods for solving the Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Demuren, A. O.

1989-01-01

The application of a class of multi-grid methods to the solution of the Navier-Stokes equations for two-dimensional laminar flow problems is discussed. The methods consist of combining the full approximation scheme-full multi-grid technique (FAS-FMG) with point-, line-, or plane-relaxation routines for solving the Navier-Stokes equations in primitive variables. The performance of the multi-grid methods is compared to that of several single-grid methods. The results show that much faster convergence can be procured through the use of the multi-grid approach than through the various suggestions for improving single-grid methods. The importance of the choice of relaxation scheme for the multi-grid method is illustrated.

Application of multi-grid methods for solving the Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Demuren, A. O.

1989-01-01

This paper presents the application of a class of multi-grid methods to the solution of the Navier-Stokes equations for two-dimensional laminar flow problems. The methods consists of combining the full approximation scheme-full multi-grid technique (FAS-FMG) with point-, line- or plane-relaxation routines for solving the Navier-Stokes equations in primitive variables. The performance of the multi-grid methods is compared to those of several single-grid methods. The results show that much faster convergence can be procured through the use of the multi-grid approach than through the various suggestions for improving single-grid methods. The importance of the choice of relaxation scheme for the multi-grid method is illustrated.

Design, application and testing of the Work Observation Method by Activity Timing (WOMBAT) to measure clinicians' patterns of work and communication.

PubMed

Westbrook, Johanna I; Ampt, Amanda

2009-04-01

Evidence regarding how health information technologies influence clinicians' patterns of work and support efficient practices is limited. Traditional paper-based data collection methods are unable to capture clinical work complexity and communication patterns. The use of electronic data collection tools for such studies is emerging yet is rarely assessed for reliability or validity. Our aim was to design, apply and test an observational method which incorporated the use of an electronic data collection tool for work measurement studies which would allow efficient, accurate and reliable data collection, and capture greater degrees of work complexity than current approaches. We developed an observational method and software for personal digital assistants (PDAs) which captures multiple dimensions of clinicians' work tasks, namely what task, with whom, and with what; tasks conducted in parallel (multi-tasking); interruptions and task duration. During field-testing over 7 months across four hospital wards, fifty-two nurses were observed for 250 h. Inter-rater reliability was tested and validity was measured by (i) assessing whether observational data reflected known differences in clinical role work tasks and (ii) by comparing observational data with participants' estimates of their task time distribution. Observers took 15-20 h of training to master the method and data collection process. Only 1% of tasks observed did not match the classification developed and were classified as 'other'. Inter-rater reliability scores of observers were maintained at over 85%. The results discriminated between the work patterns of enrolled and registered nurses consistent with differences in their roles. Survey data (n=27) revealed consistent ratings of tasks by nurses, and their rankings of most to least time-consuming tasks were significantly correlated with those derived from the observational data. Over 40% of nurses' time was spent in direct care or professional communication, with 11.8% of time spent multi-tasking. Nurses were interrupted approximately every 49 min. One quarter of interruptions occurred while nurses were preparing or administering medications. This method efficiently produces reliable and valid data. The multi-dimensional nature of the data collected provides greater insights into patterns of clinicians' work and communication than has previously been possible using other methods.

Mercury and methylmercury stream concentrations in a Coastal Plain watershed: A multi-scale simulation analysis

EPA Science Inventory

Mercury is a ubiquitous global environmental toxicant responsible for most US fish advisories. Processes governing mercury concentrations in rivers and streams are not well understood, particularly at multiple spatial scales. We investigate how insights gained from reach-scale me...

Structural and functional screening in human induced-pluripotent stem cell-derived cardiomyocytes accurately identifies cardiotoxicity of multiple drug types

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

Doherty, Kimberly R., E-mail: kimberly.doherty@quintiles.com; Talbert, Dominique R.; Trusk, Patricia B.

Safety pharmacology studies that evaluate new drug entities for potential cardiac liability remain a critical component of drug development. Current studies have shown that in vitro tests utilizing human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CM) may be beneficial for preclinical risk evaluation. We recently demonstrated that an in vitro multi-parameter test panel assessing overall cardiac health and function could accurately reflect the associated clinical cardiotoxicity of 4 FDA-approved targeted oncology agents using hiPS-CM. The present studies expand upon this initial observation to assess whether this in vitro screen could detect cardiotoxicity across multiple drug classes with known clinical cardiac risks.more » Thus, 24 drugs were examined for their effect on both structural (viability, reactive oxygen species generation, lipid formation, troponin secretion) and functional (beating activity) endpoints in hiPS-CM. Using this screen, the cardiac-safe drugs showed no effects on any of the tests in our panel. However, 16 of 18 compounds with known clinical cardiac risk showed drug-induced changes in hiPS-CM by at least one method. Moreover, when taking into account the Cmax values, these 16 compounds could be further classified depending on whether the effects were structural, functional, or both. Overall, the most sensitive test assessed cardiac beating using the xCELLigence platform (88.9%) while the structural endpoints provided additional insight into the mechanism of cardiotoxicity for several drugs. These studies show that a multi-parameter approach examining both cardiac cell health and function in hiPS-CM provides a comprehensive and robust assessment that can aid in the determination of potential cardiac liability. - Highlights: • 24 drugs were tested for cardiac liability using an in vitro multi-parameter screen. • Changes in beating activity were the most sensitive in predicting cardiac risk. • Structural effects add in-depth insight towards mechanism of cardiac toxicity. • Testing functional and structural endpoints enhances early cardiac risk assessment.« less

Network inference from multimodal data: A review of approaches from infectious disease transmission.

PubMed

Ray, Bisakha; Ghedin, Elodie; Chunara, Rumi

2016-12-01

Networks inference problems are commonly found in multiple biomedical subfields such as genomics, metagenomics, neuroscience, and epidemiology. Networks are useful for representing a wide range of complex interactions ranging from those between molecular biomarkers, neurons, and microbial communities, to those found in human or animal populations. Recent technological advances have resulted in an increasing amount of healthcare data in multiple modalities, increasing the preponderance of network inference problems. Multi-domain data can now be used to improve the robustness and reliability of recovered networks from unimodal data. For infectious diseases in particular, there is a body of knowledge that has been focused on combining multiple pieces of linked information. Combining or analyzing disparate modalities in concert has demonstrated greater insight into disease transmission than could be obtained from any single modality in isolation. This has been particularly helpful in understanding incidence and transmission at early stages of infections that have pandemic potential. Novel pieces of linked information in the form of spatial, temporal, and other covariates including high-throughput sequence data, clinical visits, social network information, pharmaceutical prescriptions, and clinical symptoms (reported as free-text data) also encourage further investigation of these methods. The purpose of this review is to provide an in-depth analysis of multimodal infectious disease transmission network inference methods with a specific focus on Bayesian inference. We focus on analytical Bayesian inference-based methods as this enables recovering multiple parameters simultaneously, for example, not just the disease transmission network, but also parameters of epidemic dynamics. Our review studies their assumptions, key inference parameters and limitations, and ultimately provides insights about improving future network inference methods in multiple applications. Copyright © 2016 Elsevier Inc. All rights reserved.

Computational insights of water droplet transport on graphene sheet with chemical density

NASA Astrophysics Data System (ADS)

Zhang, Liuyang; Wang, Xianqiao

2014-05-01

Surface gradient has been emerging as an intriguing technique for nanoscale particle manipulation and transportation. Owing to its outstanding and stable chemical properties, graphene with covalently bonded chemical groups represents extraordinary potential for the investigation of nanoscale transport in the area of physics and biology. Here, we employ molecular dynamics simulations to investigate the fundamental mechanism of utilizing a chemical density on a graphene sheet to control water droplet motions on it. Simulation results have demonstrated that the binding energy difference among distinct segment of graphene in terms of interaction between the covalently bonded oxygen atoms on graphene and the water molecules provides a fundamental driving force to transport the water droplet across the graphene sheet. Also, the velocity of the water droplet has showed a strong dependence on the relative concentration of oxygen atoms between successive segments. Furthermore, a multi-direction channel provides insights to guide the transportation of objects towards a targeted position, separating the mixtures with a system of specific chemical functionalization. Our findings shed illuminating lights on the surface gradient method and therefore provide a feasible way to control nanoscale motion on the surface and mimic the channelless microfluidics.

Telling Moments and Everyday Experience: Multiple Methods Research on Couple Relationships and Personal Lives

PubMed Central

Gabb, Jacqui; Fink, Janet

2015-01-01

Everyday moments and ordinary gestures create the texture of long-term couple relationships. In this article we demonstrate how, by refining our research tools and conceptual imagination, we can better understand these vibrant and visceral relationships. The ‘moments approach’ that we propose provides a lens through which to focus in on couples’ everyday experiences, to gain insight on processes, meanings and cross-cutting analytical themes whilst ensuring that feelings and emotionality remain firmly attached. Calling attention to everyday relationship practices, we draw on empirical research to illustrate and advance our conceptual and methodological argument. The Enduring Love? study included an online survey (n = 5445) and multi-sensory qualitative research with couples (n = 50) to interrogate how they experience, understand and sustain their long-term relationships. PMID:26456983

Deformation-induced localized solid-state amorphization in nanocrystalline nickel.

PubMed

Han, Shuang; Zhao, Lei; Jiang, Qing; Lian, Jianshe

2012-01-01

Although amorphous structures have been widely obtained in various multi-component metallic alloys, amorphization in pure metals has seldom been observed and remains a long-standing scientific curiosity and technological interest. Here we present experimental evidence of localized solid-state amorphization in bulk nanocrystalline nickel introduced by quasi-static compression at room temperature. High-resolution electron microscope observations illustrate that nano-scale amorphous structures present at the regions where severe deformation occurred, e.g. along crack paths or surrounding nano-voids. These findings have indicated that nanocrystalline structures are highly desirable for promoting solid-state amorphization, which may provide new insights for understanding the nature of the crystalline-to-amorphous transformation and suggested a potential method to produce elemental metallic glasses that have hardly been available hitherto through rapid solidification.

Deformation-induced localized solid-state amorphization in nanocrystalline nickel

PubMed Central

Han, Shuang; Zhao, Lei; Jiang, Qing; Lian, Jianshe

2012-01-01

Although amorphous structures have been widely obtained in various multi-component metallic alloys, amorphization in pure metals has seldom been observed and remains a long-standing scientific curiosity and technological interest. Here we present experimental evidence of localized solid-state amorphization in bulk nanocrystalline nickel introduced by quasi-static compression at room temperature. High-resolution electron microscope observations illustrate that nano-scale amorphous structures present at the regions where severe deformation occurred, e.g. along crack paths or surrounding nano-voids. These findings have indicated that nanocrystalline structures are highly desirable for promoting solid-state amorphization, which may provide new insights for understanding the nature of the crystalline-to-amorphous transformation and suggested a potential method to produce elemental metallic glasses that have hardly been available hitherto through rapid solidification. PMID:22768383

Entangled ethnography: imagining a future for young adults with learning disabilities.

PubMed

Ginsburg, Faye; Rapp, Rayna

2013-12-01

Our article draws on one aspect of our multi-sited long-term ethnographic research in New York City on cultural innovation and Learning Disabilities (LD). We focus on our efforts to help create two innovative transition programs that also became sites for our study when we discovered that young adults with disabilities were too often "transitioning to nowhere" as they left high school. Because of our stakes in this process as parents of children with learning disabilities as well as anthropologists, we have come to think of our method as entangled ethnography, bringing the insights of both insider and outsider perspectives into productive dialog, tailoring a longstanding approach in critical anthropology to research demedicalizing the experience of disability. Copyright © 2013 Elsevier Ltd. All rights reserved.

Expression of recombinant glycoproteins in mammalian cells: towards an integrative approach to structural biology.

PubMed

Aricescu, A Radu; Owens, Raymond J

2013-06-01

Mammalian cells are rapidly becoming the system of choice for the production of recombinant glycoproteins for structural biology applications. Their use has enabled the structural investigation of a whole new set of targets including large, multi-domain and highly glycosylated eukaryotic cell surface receptors and their supra-molecular assemblies. We summarize the technical advances that have been made in mammalian expression technology and highlight some of the structural insights that have been obtained using these methods. Looking forward, it is clear that mammalian cell expression will provide exciting and unique opportunities for an integrative approach to the structural study of proteins, especially of human origin and medically relevant, by bridging the gap between the purified state and the cellular context. Copyright © 2013 Elsevier Ltd. All rights reserved.

Insights into the origin and characteristics of the sedimentation process at multi-barrel culverts in Iowa : technical transfer summary.

DOT National Transportation Integrated Search

2010-06-01

The present study is an integral part of a : broader study focused on the design and : implementation of self-cleaning culverts, i.e., : configurations that prevent the formation of : sediment deposits after culvert construction or : cleaning. Sedime...

Characterizing Environmental Transformation of Multi-walled Carbon Nanotubes and Carbon Nano-Fiber Composites using Thermal Analysis and Related Hyphenated Techniques

EPA Science Inventory

Thermogravimetric analysis (TGA) coupled with gas chromatography and mass spectroscopy (TGA/GCMS), for the evolved gas analysis, has given insight to the stability and kinetics of structural changes and determining adsorbed organics to nanomaterials and nanocomposites. TGA is als...

Immunogenomics: a foundation for intelligent immune design.

PubMed

Holt, Robert A

2015-11-19

The complexity of the immune system is now being interrogated using methodologies that generate extensive multi-dimensional data. Effective collection, integration and interpretation of these data remain difficult, but overcoming these important challenges will provide new insights into immune function and opportunities for the rational design of new immune interventions.

Integrating legacy data to understand agroecosystem regional dynamics to catastrophic events

USDA-ARS?s Scientific Manuscript database

Multi-year extreme drought events are part of the history of the Earth system. Legacy data on the climate drivers, geomorphic features, and agroecosystem responses across a dynamically changing landscape throughout a region can provide important insights to a future where large-scale catastrophic ev...

TR-596 insights into the origin and characteristics of the sedimentation process at multi-barrel culverts in Iowa.

DOT National Transportation Integrated Search

2010-06-01

The present study is an integral part of a broader study focused on the design and implementation of self-cleaning culverts, i.e., : configurations that prevent the formation of sediment deposits after culvert construction or cleaning. Sediment depos...

A multi-gene phylogeny provides additional insight into the relationships between several Ascosphaera species

USDA-ARS?s Scientific Manuscript database

Ascosphaera fungi are highly associated with social and solitary bees. This genus includes an important group of bee pathogens, the chalkbrood fungi, and thus proper identification of species and an understanding of their relationships are important. However, Ascosphaera spp. are often unculturable...

Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data

EPA Science Inventory

Simulations from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions) as well as those intrinsic to the model (e.g. physical parameterization, chemical mechanism). Multi-model ensembles can improve the f...

An inverse method to determine the mechanical properties of the iris in vivo

PubMed Central

2014-01-01

Background Understanding the mechanical properties of the iris can help to have an insight into the eye diseases with abnormalities of the iris morphology. Material parameters of the iris were simply calculated relying on the ex vivo experiment. However, the mechanical response of the iris in vivo is different from that ex vivo, therefore, a method was put forward to determine the material parameters of the iris using the optimization method in combination with the finite element method based on the in vivo experiment. Material and methods Ocular hypertension was induced by rapid perfusion to the anterior chamber, during perfusion intraocular pressures in the anterior and posterior chamber were record by sensors, images of the anterior segment were captured by the ultrasonic system. The displacement of the characteristic points on the surface of the iris was calculated. A finite element model of the anterior chamber was developed using the ultrasonic image before perfusion, the multi-island genetic algorithm was employed to determine the material parameters of the iris by minimizing the difference between the finite element simulation and the experimental measurements. Results Material parameters of the iris in vivo were identified as the iris was taken as a nearly incompressible second-order Ogden solid. Values of the parameters μ1, α1, μ2 and α2 were 0.0861 ± 0.0080 MPa, 54.2546 ± 12.7180, 0.0754 ± 0.0200 MPa, and 48.0716 ± 15.7796 respectively. The stability of the inverse finite element method was verified, the sensitivity of the model parameters was investigated. Conclusion Material properties of the iris in vivo could be determined using the multi-island genetic algorithm coupled with the finite element method based on the experiment. PMID:24886660

Decoding the attended speech stream with multi-channel EEG: implications for online, daily-life applications

NASA Astrophysics Data System (ADS)

Mirkovic, Bojana; Debener, Stefan; Jaeger, Manuela; De Vos, Maarten

2015-08-01

Objective. Recent studies have provided evidence that temporal envelope driven speech decoding from high-density electroencephalography (EEG) and magnetoencephalography recordings can identify the attended speech stream in a multi-speaker scenario. The present work replicated the previous high density EEG study and investigated the necessary technical requirements for practical attended speech decoding with EEG. Approach. Twelve normal hearing participants attended to one out of two simultaneously presented audiobook stories, while high density EEG was recorded. An offline iterative procedure eliminating those channels contributing the least to decoding provided insight into the necessary channel number and optimal cross-subject channel configuration. Aiming towards the future goal of near real-time classification with an individually trained decoder, the minimum duration of training data necessary for successful classification was determined by using a chronological cross-validation approach. Main results. Close replication of the previously reported results confirmed the method robustness. Decoder performance remained stable from 96 channels down to 25. Furthermore, for less than 15 min of training data, the subject-independent (pre-trained) decoder performed better than an individually trained decoder did. Significance. Our study complements previous research and provides information suggesting that efficient low-density EEG online decoding is within reach.

SEMIPARAMETRIC ZERO-INFLATED MODELING IN MULTI-ETHNIC STUDY OF ATHEROSCLEROSIS (MESA)

PubMed Central

Liu, Hai; Ma, Shuangge; Kronmal, Richard; Chan, Kung-Sik

2013-01-01

We analyze the Agatston score of coronary artery calcium (CAC) from the Multi-Ethnic Study of Atherosclerosis (MESA) using semi-parametric zero-inflated modeling approach, where the observed CAC scores from this cohort consist of high frequency of zeroes and continuously distributed positive values. Both partially constrained and unconstrained models are considered to investigate the underlying biological processes of CAC development from zero to positive, and from small amount to large amount. Different from existing studies, a model selection procedure based on likelihood cross-validation is adopted to identify the optimal model, which is justified by comparative Monte Carlo studies. A shrinkaged version of cubic regression spline is used for model estimation and variable selection simultaneously. When applying the proposed methods to the MESA data analysis, we show that the two biological mechanisms influencing the initiation of CAC and the magnitude of CAC when it is positive are better characterized by an unconstrained zero-inflated normal model. Our results are significantly different from those in published studies, and may provide further insights into the biological mechanisms underlying CAC development in human. This highly flexible statistical framework can be applied to zero-inflated data analyses in other areas. PMID:23805172

Pressure-induced metallization of condensed phase β-HMX under shock loadings via molecular dynamics simulations in conjunction with multi-scale shock technique.

PubMed

Ge, Ni-Na; Wei, Yong-Kai; Zhao, Feng; Chen, Xiang-Rong; Ji, Guang-Fu

2014-07-01

The electronic structure and initial decomposition in high explosive HMX under conditions of shock loading are examined. The simulation is performed using quantum molecular dynamics in conjunction with multi-scale shock technique (MSST). A self-consistent charge density-functional tight-binding (SCC-DFTB) method is adapted. The results show that the N-N-C angle has a drastic change under shock wave compression along lattice vector b at shock velocity 11 km/s, which is the main reason that leads to an insulator-to-metal transition for the HMX system. The metallization pressure (about 130 GPa) of condensed-phase HMX is predicted firstly. We also detect the formation of several key products of condensed-phase HMX decomposition, such as NO2, NO, N2, N2O, H2O, CO, and CO2, and all of them have been observed in previous experimental studies. Moreover, the initial decomposition products include H2 due to the C-H bond breaking as a primary reaction pathway at extreme condition, which presents a new insight into the initial decomposition mechanism of HMX under shock loading at the atomistic level.

Rule-Based Simulation of Multi-Cellular Biological Systems—A Review of Modeling Techniques

PubMed Central

Hwang, Minki; Garbey, Marc; Berceli, Scott A.; Tran-Son-Tay, Roger

2011-01-01

Emergent behaviors of multi-cellular biological systems (MCBS) result from the behaviors of each individual cells and their interactions with other cells and with the environment. Modeling MCBS requires incorporating these complex interactions among the individual cells and the environment. Modeling approaches for MCBS can be grouped into two categories: continuum models and cell-based models. Continuum models usually take the form of partial differential equations, and the model equations provide insight into the relationship among the components in the system. Cell-based models simulate each individual cell behavior and interactions among them enabling the observation of the emergent system behavior. This review focuses on the cell-based models of MCBS, and especially, the technical aspect of the rule-based simulation method for MCBS is reviewed. How to implement the cell behaviors and the interactions with other cells and with the environment into the computational domain is discussed. The cell behaviors reviewed in this paper are division, migration, apoptosis/necrosis, and differentiation. The environmental factors such as extracellular matrix, chemicals, microvasculature, and forces are also discussed. Application examples of these cell behaviors and interactions are presented. PMID:21369345

Leveraging accelerated testing of LED drivers to model the reliability of two-stage and multi-channel drivers

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

Davis, Lynn; Perkins, Curtis; Smith, Aaron

The next wave of LED lighting technology is likely to be tunable white lighting (TWL) devices which can adjust the colour of the emitted light between warm white (~ 2700 K) and cool white (~ 6500 K). This type of lighting system uses LED assemblies of two or more colours each controlled by separate driver channels that independently adjust the current levels to achieve the desired lighting colour. Drivers used in TWL devices are inherently more complex than those found in simple SSL devices, due to the number of electrical components in the driver required to achieve this level ofmore » control. The reliability of such lighting systems can only be studied using accelerated stress tests (AST) that accelerate the aging process to time frames that can be accommodated in laboratory testing. This paper describes AST methods and findings developed from AST data that provide insights into the lifetime of the main components of one-channel and multi-channel LED devices. The use of AST protocols to confirm product reliability is necessary to ensure that the technology can meet the performance and lifetime requirements of the intended application.« less

The Scatter Search Based Algorithm to Revenue Management Problem in Broadcasting Companies

NASA Astrophysics Data System (ADS)

Pishdad, Arezoo; Sharifyazdi, Mehdi; Karimpour, Reza

2009-09-01

The problem under question in this paper which is faced by broadcasting companies is how to benefit from a limited advertising space. This problem is due to the stochastic behavior of customers (advertiser) in different fare classes. To address this issue we propose a mathematical constrained nonlinear multi period model which incorporates cancellation and overbooking. The objective function is to maximize the total expected revenue and our numerical method performs it by determining the sales limits for each class of customer to present the revenue management control policy. Scheduling the advertising spots in breaks is another area of concern and we consider it as a constraint in our model. In this paper an algorithm based on Scatter search is developed to acquire a good feasible solution. This method uses simulation over customer arrival and in a continuous finite time horizon [0, T]. Several sensitivity analyses are conducted in computational result for depicting the effectiveness of proposed method. It also provides insight into better results of considering revenue management (control policy) compared to "no sales limit" policy in which sooner demand will served first.

Challenges with secondary use of multi-source water-quality data in the United States

USGS Publications Warehouse

Sprague, Lori A.; Oelsner, Gretchen P.; Argue, Denise M.

2017-01-01

Combining water-quality data from multiple sources can help counterbalance diminishing resources for stream monitoring in the United States and lead to important regional and national insights that would not otherwise be possible. Individual monitoring organizations understand their own data very well, but issues can arise when their data are combined with data from other organizations that have used different methods for reporting the same common metadata elements. Such use of multi-source data is termed “secondary use”—the use of data beyond the original intent determined by the organization that collected the data. In this study, we surveyed more than 25 million nutrient records collected by 488 organizations in the United States since 1899 to identify major inconsistencies in metadata elements that limit the secondary use of multi-source data. Nearly 14.5 million of these records had missing or ambiguous information for one or more key metadata elements, including (in decreasing order of records affected) sample fraction, chemical form, parameter name, units of measurement, precise numerical value, and remark codes. As a result, metadata harmonization to make secondary use of these multi-source data will be time consuming, expensive, and inexact. Different data users may make different assumptions about the same ambiguous data, potentially resulting in different conclusions about important environmental issues. The value of these ambiguous data is estimated at \\$US12 billion, a substantial collective investment by water-resource organizations in the United States. By comparison, the value of unambiguous data is estimated at \\$US8.2 billion. The ambiguous data could be preserved for uses beyond the original intent by developing and implementing standardized metadata practices for future and legacy water-quality data throughout the United States.

Principles to Products: Toward Realizing MOS 2.0

NASA Technical Reports Server (NTRS)

Bindschadler, Duane L.; Delp, Christopher L.

2012-01-01

This is a report on the Operations Revitalization Initiative, part of the ongoing NASA-funded Advanced Multi-Mission Operations Systems (AMMOS) program. We are implementing products that significantly improve efficiency and effectiveness of Mission Operations Systems (MOS) for deep-space missions. We take a multi-mission approach, in keeping with our organization's charter to "provide multi-mission tools and services that enable mission customers to operate at a lower total cost to NASA." Focusing first on architectural fundamentals of the MOS, we review the effort's progress. In particular, we note the use of stakeholder interactions and consideration of past lessons learned to motivate a set of Principles that guide the evolution of the AMMOS. Thus guided, we have created essential patterns and connections (detailed in companion papers) that are explicitly modeled and support elaboration at multiple levels of detail (system, sub-system, element...) throughout a MOS. This architecture is realized in design and implementation products that provide lifecycle support to a Mission at the system and subsystem level. The products include adaptable multi-mission engineering documentation that describes essentials such as operational concepts and scenarios, requirements, interfaces and agreements, information models, and mission operations processes. Because we have adopted a model-based system engineering method, these documents and their contents are meaningfully related to one another and to the system model. This means they are both more rigorous and reusable (from mission to mission) than standard system engineering products. The use of models also enables detailed, early (e.g., formulation phase) insight into the impact of changes (e.g., to interfaces or to software) that is rigorous and complete, allowing better decisions on cost or technical trades. Finally, our work provides clear and rigorous specification of operations needs to software developers, further enabling significant gains in productivity.

Novel approach for identification of influenza virus host range and zoonotic transmissible sequences by determination of host-related associative positions in viral genome segments.

PubMed

Kargarfard, Fatemeh; Sami, Ashkan; Mohammadi-Dehcheshmeh, Manijeh; Ebrahimie, Esmaeil

2016-11-16

Recent (2013 and 2009) zoonotic transmission of avian or porcine influenza to humans highlights an increase in host range by evading species barriers. Gene reassortment or antigenic shift between viruses from two or more hosts can generate a new life-threatening virus when the new shuffled virus is no longer recognized by antibodies existing within human populations. There is no large scale study to help understand the underlying mechanisms of host transmission. Furthermore, there is no clear understanding of how different segments of the influenza genome contribute in the final determination of host range. To obtain insight into the rules underpinning host range determination, various supervised machine learning algorithms were employed to mine reassortment changes in different viral segments in a range of hosts. Our multi-host dataset contained whole segments of 674 influenza strains organized into three host categories: avian, human, and swine. Some of the sequences were assigned to multiple hosts. In point of fact, the datasets are a form of multi-labeled dataset and we utilized a multi-label learning method to identify discriminative sequence sites. Then algorithms such as CBA, Ripper, and decision tree were applied to extract informative and descriptive association rules for each viral protein segment. We found informative rules in all segments that are common within the same host class but varied between different hosts. For example, for infection of an avian host, HA14V and NS1230S were the most important discriminative and combinatorial positions. Host range identification is facilitated by high support combined rules in this study. Our major goal was to detect discriminative genomic positions that were able to identify multi host viruses, because such viruses are likely to cause pandemic or disastrous epidemics.

Size exclusion chromatography for analyses of fibroin in silk: optimization of sampling and separation conditions

NASA Astrophysics Data System (ADS)

Pawcenis, Dominika; Koperska, Monika A.; Milczarek, Jakub M.; Łojewski, Tomasz; Łojewska, Joanna

2014-02-01

A direct goal of this paper was to improve the methods of sample preparation and separation for analyses of fibroin polypeptide with the use of size exclusion chromatography (SEC). The motivation for the study arises from our interest in natural polymers included in historic textile and paper artifacts, and is a logical response to the urgent need for developing rationale-based methods for materials conservation. The first step is to develop a reliable analytical tool which would give insight into fibroin structure and its changes caused by both natural and artificial ageing. To investigate the influence of preparation conditions, two sets of artificially aged samples were prepared (with and without NaCl in sample solution) and measured by the means of SEC with multi angle laser light scattering detector. It was shown that dialysis of fibroin dissolved in LiBr solution allows removal of the salt which destroys stacks chromatographic columns and prevents reproducible analyses. Salt rich (NaCl) water solutions of fibroin improved the quality of chromatograms.

How are Curious People Viewed and How Do they Behave in Social Situations? From the Perspectives of Self, Friends, Parents, and Unacquainted Observers

PubMed Central

Kashdan, Todd B.; Sherman, Ryne A.; Yarbro, Jessica; Funder, David C.

2012-01-01

Objective People who are open and curious orient their lives around an appreciation of novelty and a strong urge to explore, discover, and grow. Researchers have recently shown that being an open, curious person is linked to healthy social outcomes. Method To better understand the benefits (and liabilities) of being a curious person, we used a multi-method design of social behavior to assess the perspectives of multiple informants including self, friends, and parents, and behavior coded from direct observations in unstructured social interactions. Results We found an impressive degree of convergence among self, friends, and parent reports of curiosity, and observer-rated behavioral correlates of curiosity. A curious personality was linked to a wide range of adaptive behaviors including tolerance of anxiety and uncertainty, positive emotional expressiveness, initiation of humor and playfulness, unconventional thinking, and a non-defensive, non-critical attitude. Conclusions This characterization of curious people provides insights into mechanisms underlying associated healthy social outcomes. PMID:22583101

Contact-free calibration of an asymmetric multi-layer interferometer for the surface force balance

NASA Astrophysics Data System (ADS)

Balabajew, Marco; van Engers, Christian D.; Perkin, Susan

2017-12-01

The Surface Force Balance (SFB, also known as Surface Force Apparatus, SFA) has provided important insights into many phenomena within the field of colloid and interface science. The technique relies on using white light interferometry to measure the distance between surfaces with sub-nanometer resolution. Up until now, the determination of the distance between the surfaces required a so-called "contact calibration," an invasive procedure during which the surfaces are brought into mechanical contact. This requirement for a contact calibration limits the range of experimental systems that can be investigated with SFB, for example, it precludes experiments with substrates that would be irreversibly modified or damaged by mechanical contact. Here we present a non-invasive method to measure absolute distances without performing a contact calibration. The method can be used for both "symmetric" and "asymmetric" systems. We foresee many applications for this general approach including, most immediately, experiments using single layer graphene electrodes in the SFB which may be damaged when brought into mechanical contact.

Nano-QSPR Modelling of Carbon-Based Nanomaterials Properties.

PubMed

Salahinejad, Maryam

2015-01-01

Evaluation of chemical and physical properties of nanomaterials is of critical importance in a broad variety of nanotechnology researches. There is an increasing interest in computational methods capable of predicting properties of new and modified nanomaterials in the absence of time-consuming and costly experimental studies. Quantitative Structure- Property Relationship (QSPR) approaches are progressive tools in modelling and prediction of many physicochemical properties of nanomaterials, which are also known as nano-QSPR. This review provides insight into the concepts, challenges and applications of QSPR modelling of carbon-based nanomaterials. First, we try to provide a general overview of QSPR implications, by focusing on the difficulties and limitations on each step of the QSPR modelling of nanomaterials. Then follows with the most significant achievements of QSPR methods in modelling of carbon-based nanomaterials properties and their recent applications to generate predictive models. This review specifically addresses the QSPR modelling of physicochemical properties of carbon-based nanomaterials including fullerenes, single-walled carbon nanotube (SWNT), multi-walled carbon nanotube (MWNT) and graphene.

Applying Jlint to Space Exploration Software

NASA Technical Reports Server (NTRS)

Artho, Cyrille; Havelund, Klaus

2004-01-01

Java is a very successful programming language which is also becoming widespread in embedded systems, where software correctness is critical. Jlint is a simple but highly efficient static analyzer that checks a Java program for several common errors, such as null pointer exceptions, and overflow errors. It also includes checks for multi-threading problems, such as deadlocks and data races. The case study described here shows the effectiveness of Jlint in find-false positives in the multi-threading warnings gives an insight into design patterns commonly used in multi-threaded code. The results show that a few analysis techniques are sufficient to avoid almost all false positives. These techniques include investigating all possible callers and a few code idioms. Verifying the correct application of these patterns is still crucial, because their correct usage is not trivial.

Uranium plume persistence impacted by hydrologic and geochemical heterogeneity in the groundwater and river water interaction zone of Hanford site

NASA Astrophysics Data System (ADS)

Chen, X.; Zachara, J. M.; Vermeul, V. R.; Freshley, M.; Hammond, G. E.

2015-12-01

The behavior of a persistent uranium plume in an extended groundwater- river water (GW-SW) interaction zone at the DOE Hanford site is dominantly controlled by river stage fluctuations in the adjacent Columbia River. The plume behavior is further complicated by substantial heterogeneity in physical and geochemical properties of the host aquifer sediments. Multi-scale field and laboratory experiments and reactive transport modeling were integrated to understand the complex plume behavior influenced by highly variable hydrologic and geochemical conditions in time and space. In this presentation we (1) describe multiple data sets from field-scale uranium adsorption and desorption experiments performed at our experimental well-field, (2) develop a reactive transport model that incorporates hydrologic and geochemical heterogeneities characterized from multi-scale and multi-type datasets and a surface complexation reaction network based on laboratory studies, and (3) compare the modeling and observation results to provide insights on how to refine the conceptual model and reduce prediction uncertainties. The experimental results revealed significant spatial variability in uranium adsorption/desorption behavior, while modeling demonstrated that ambient hydrologic and geochemical conditions and heterogeneities in sediment physical and chemical properties both contributed to complex plume behavior and its persistence. Our analysis provides important insights into the characterization, understanding, modeling, and remediation of groundwater contaminant plumes influenced by surface water and groundwater interactions.

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

INSIGHT: RFID and Bluetooth enabled automated space for the blind and visually impaired.

PubMed

Ganz, Aura; Gandhi, Siddhesh Rajan; Wilson, Carole; Mullett, Gary

2010-01-01

In this paper we introduce INSIGHT, an indoor location tracking and navigation system to help the blind and visually impaired to easily navigate to their chosen destination in a public building. INSIGHT makes use of RFID and Bluetooth technology deployed within the building to locate and track the users. The PDA based user device interacts with INSIGHT server and provides the user navigation instructions in an audio form. The proposed system provides multi-resolution localization of the users, facilitating the provision of accurate navigation instructions when the user is in the vicinity of the RFID tags as well as accommodating a PANIC button which provides navigation instructions when the user is anywhere in the building. Moreover, the system will continuously monitor the zone in which the user walks. This will enable the system to identify if the user is located in the wrong zone of the building which may not lead to the desired destination.

Performance Analysis of Millimeter-Wave Multi-hop Machine-to-Machine Networks Based on Hop Distance Statistics

PubMed Central

2018-01-01

As an intrinsic part of the Internet of Things (IoT) ecosystem, machine-to-machine (M2M) communications are expected to provide ubiquitous connectivity between machines. Millimeter-wave (mmWave) communication is another promising technology for the future communication systems to alleviate the pressure of scarce spectrum resources. For this reason, in this paper, we consider multi-hop M2M communications, where a machine-type communication (MTC) device with the limited transmit power relays to help other devices using mmWave. To be specific, we focus on hop distance statistics and their impacts on system performances in multi-hop wireless networks (MWNs) with directional antenna arrays in mmWave for M2M communications. Different from microwave systems, in mmWave communications, wireless channel suffers from blockage by obstacles that heavily attenuate line-of-sight signals, which may result in limited per-hop progress in MWNs. We consider two routing strategies aiming at different types of applications and derive the probability distributions of their hop distances. Moreover, we provide their baseline statistics assuming the blockage-free scenario to quantify the impact of blockages. Based on the hop distance analysis, we propose a method to estimate the end-to-end performances (e.g., outage probability, hop count, and transmit energy) of the mmWave MWNs, which provides important insights into mmWave MWN design without time-consuming and repetitive end-to-end simulation. PMID:29329248

Clinical multi-omics strategies for the effective cancer management.

PubMed

Yoo, Byong Chul; Kim, Kyung-Hee; Woo, Sang Myung; Myung, Jae Kyung

2017-08-15

Cancer is a global health issue as a multi-factorial complex disease, and early detection and novel therapeutic strategies are required for more effective cancer management. With the development of systemic analytical -omics strategies, the therapeutic approach and study of the molecular mechanisms of carcinogenesis and cancer progression have moved from hypothesis-driven targeted investigations to data-driven untargeted investigations focusing on the integrated diagnosis, treatment, and prevention of cancer in individual patients. Predictive, preventive, and personalized medicine (PPPM) is a promising new approach to reduce the burden of cancer and facilitate more accurate prognosis, diagnosis, as well as effective treatment. Here we review the fundamentals of, and new developments in, -omics technologies, together with the key role of a variety of practical -omics strategies in PPPM for cancer treatment and diagnosis. In this review, a comprehensive and critical overview of the systematic strategy for predictive, preventive, and personalized medicine (PPPM) for cancer disease was described in a view of cancer prognostic prediction, diagnostics, and prevention as well as cancer therapy and drug responses. We have discussed multi-dimensional data obtained from various resources and integration of multisciplinary -omics strategies with computational method which could contribute the more effective PPPM for cancer. This review has provided the novel insights of the current applications of each and combined -omics technologies, which showed their powerful potential for the establishment of PPPM for cancer. Copyright © 2017 Elsevier B.V. All rights reserved.

Toward a global multi-scale heliophysics observatory

NASA Astrophysics Data System (ADS)

Semeter, J. L.

2017-12-01

We live within the only known stellar-planetary system that supports life. What we learn about this system is not only relevant to human society and its expanding reach beyond Earth's surface, but also to our understanding of the origins and evolution of life in the universe. Heliophysics is focused on solar-terrestrial interactions mediated by the magnetic and plasma environment surrounding the planet. A defining feature of energy flow through this environment is interaction across physical scales. A solar disturbance aimed at Earth can excite geospace variability on scales ranging from thousands of kilometers (e.g., global convection, region 1 and 2 currents, electrojet intensifications) to 10's of meters (e.g., equatorial spread-F, dispersive Alfven waves, plasma instabilities). Most "geospace observatory" concepts are focused on a single modality (e.g., HF/UHF radar, magnetometer, optical) providing a limited parameter set over a particular spatiotemporal resolution. Data assimilation methods have been developed to couple heterogeneous and distributed observations, but resolution has typically been prescribed a-priori and according to physical assumptions. This paper develops a conceptual framework for the next generation multi-scale heliophysics observatory, capable of revealing and quantifying the complete spectrum of cross-scale interactions occurring globally within the geospace system. The envisioned concept leverages existing assets, enlists citizen scientists, and exploits low-cost access to the geospace environment. Examples are presented where distributed multi-scale observations have resulted in substantial new insight into the inner workings of our stellar-planetary system.

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

Performance Analysis of Millimeter-Wave Multi-hop Machine-to-Machine Networks Based on Hop Distance Statistics.

PubMed

Jung, Haejoon; Lee, In-Ho

2018-01-12

As an intrinsic part of the Internet of Things (IoT) ecosystem, machine-to-machine (M2M) communications are expected to provide ubiquitous connectivity between machines. Millimeter-wave (mmWave) communication is another promising technology for the future communication systems to alleviate the pressure of scarce spectrum resources. For this reason, in this paper, we consider multi-hop M2M communications, where a machine-type communication (MTC) device with the limited transmit power relays to help other devices using mmWave. To be specific, we focus on hop distance statistics and their impacts on system performances in multi-hop wireless networks (MWNs) with directional antenna arrays in mmWave for M2M communications. Different from microwave systems, in mmWave communications, wireless channel suffers from blockage by obstacles that heavily attenuate line-of-sight signals, which may result in limited per-hop progress in MWNs. We consider two routing strategies aiming at different types of applications and derive the probability distributions of their hop distances. Moreover, we provide their baseline statistics assuming the blockage-free scenario to quantify the impact of blockages. Based on the hop distance analysis, we propose a method to estimate the end-to-end performances (e.g., outage probability, hop count, and transmit energy) of the mmWave MWNs, which provides important insights into mmWave MWN design without time-consuming and repetitive end-to-end simulation.

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

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

PubMed Central

2014-01-01

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

Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA

USGS Publications Warehouse

Green, Christopher T.; Jurgens, Bryant; Zhang, Yong; Starn, Jeffrey; Singleton, Michael J.; Esser, Bradley K.

2016-01-01

Rates of oxygen and nitrate reduction are key factors in determining the chemical evolution of groundwater. Little is known about how these rates vary and covary in regional groundwater settings, as few studies have focused on regional datasets with multiple tracers and methods of analysis that account for effects of mixed residence times on apparent reaction rates. This study provides insight into the characteristics of residence times and rates of O2 reduction and denitrification (NO3− reduction) by comparing reaction rates using multi-model analytical residence time distributions (RTDs) applied to a data set of atmospheric tracers of groundwater age and geochemical data from 141 well samples in the Central Eastern San Joaquin Valley, CA. The RTD approach accounts for mixtures of residence times in a single sample to provide estimates of in-situ rates. Tracers included SF6, CFCs, 3H, He from 3H (tritiogenic He),14C, and terrigenic He. Parameter estimation and multi-model averaging were used to establish RTDs with lower error variances than those produced by individual RTD models. The set of multi-model RTDs was used in combination with NO3− and dissolved gas data to estimate zero order and first order rates of O2 reduction and denitrification. Results indicated that O2 reduction and denitrification rates followed approximately log-normal distributions. Rates of O2 and NO3− reduction were correlated and, on an electron milliequivalent basis, denitrification rates tended to exceed O2 reduction rates. Estimated historical NO3− trends were similar to historical measurements. Results show that the multi-model approach can improve estimation of age distributions, and that relatively easily measured O2 rates can provide information about trends in denitrification rates, which are more difficult to estimate.

Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA

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

Green, Christopher T.; Jurgens, Bryant C.; Zhang, Yong

Rates of oxygen and nitrate reduction are key factors in determining the chemical evolution of groundwater. Little is known about how these rates vary and covary in regional groundwater settings, as few studies have focused on regional datasets with multiple tracers and methods of analysis that account for effects of mixed residence times on apparent reaction rates. This study provides insight into the characteristics of residence times and rates of O 2 reduction and denitrification (NO 3 – reduction) by comparing reaction rates using multi-model analytical residence time distributions (RTDs) applied to a data set of atmospheric tracers of groundwatermore » age and geochemical data from 141 well samples in the Central Eastern San Joaquin Valley, CA. The RTD approach accounts for mixtures of residence times in a single sample to provide estimates of in-situ rates. Tracers included SF 6, CFCs, 3H, He from 3H (tritiogenic He), 14C, and terrigenic He. Parameter estimation and multi-model averaging were used to establish RTDs with lower error variances than those produced by individual RTD models. The set of multi-model RTDs was used in combination with NO 3 – and dissolved gas data to estimate zero order and first order rates of O 2 reduction and denitrification. Results indicated that O 2 reduction and denitrification rates followed approximately log-normal distributions. Rates of O 2 and NO 3 – reduction were correlated and, on an electron milliequivalent basis, denitrification rates tended to exceed O 2 reduction rates. Estimated historical NO 3 – trends were similar to historical measurements. Here, results show that the multi-model approach can improve estimation of age distributions, and that relatively easily measured O 2 rates can provide information about trends in denitrification rates, which are more difficult to estimate.« less

Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA

DOE PAGES

Green, Christopher T.; Jurgens, Bryant C.; Zhang, Yong; ...

2016-05-14

Rates of oxygen and nitrate reduction are key factors in determining the chemical evolution of groundwater. Little is known about how these rates vary and covary in regional groundwater settings, as few studies have focused on regional datasets with multiple tracers and methods of analysis that account for effects of mixed residence times on apparent reaction rates. This study provides insight into the characteristics of residence times and rates of O 2 reduction and denitrification (NO 3 – reduction) by comparing reaction rates using multi-model analytical residence time distributions (RTDs) applied to a data set of atmospheric tracers of groundwatermore » age and geochemical data from 141 well samples in the Central Eastern San Joaquin Valley, CA. The RTD approach accounts for mixtures of residence times in a single sample to provide estimates of in-situ rates. Tracers included SF 6, CFCs, 3H, He from 3H (tritiogenic He), 14C, and terrigenic He. Parameter estimation and multi-model averaging were used to establish RTDs with lower error variances than those produced by individual RTD models. The set of multi-model RTDs was used in combination with NO 3 – and dissolved gas data to estimate zero order and first order rates of O 2 reduction and denitrification. Results indicated that O 2 reduction and denitrification rates followed approximately log-normal distributions. Rates of O 2 and NO 3 – reduction were correlated and, on an electron milliequivalent basis, denitrification rates tended to exceed O 2 reduction rates. Estimated historical NO 3 – trends were similar to historical measurements. Here, results show that the multi-model approach can improve estimation of age distributions, and that relatively easily measured O 2 rates can provide information about trends in denitrification rates, which are more difficult to estimate.« less

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection

PubMed Central

Dang, Yaoguo; Mao, Wenxin

2018-01-01

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method. PMID:29510521

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection.

PubMed

Sun, Huifang; Dang, Yaoguo; Mao, Wenxin

2018-03-03

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method.

Designing multi-targeted agents: An emerging anticancer drug discovery paradigm.

PubMed

Fu, Rong-Geng; Sun, Yuan; Sheng, Wen-Bing; Liao, Duan-Fang

2017-08-18

The dominant paradigm in drug discovery is to design ligands with maximum selectivity to act on individual drug targets. With the target-based approach, many new chemical entities have been discovered, developed, and further approved as drugs. However, there are a large number of complex diseases such as cancer that cannot be effectively treated or cured only with one medicine to modulate the biological function of a single target. As simultaneous intervention of two (or multiple) cancer progression relevant targets has shown improved therapeutic efficacy, the innovation of multi-targeted drugs has become a promising and prevailing research topic and numerous multi-targeted anticancer agents are currently at various developmental stages. However, most multi-pharmacophore scaffolds are usually discovered by serendipity or screening, while rational design by combining existing pharmacophore scaffolds remains an enormous challenge. In this review, four types of multi-pharmacophore modes are discussed, and the examples from literature will be used to introduce attractive lead compounds with the capability of simultaneously interfering with different enzyme or signaling pathway of cancer progression, which will reveal the trends and insights to help the design of the next generation multi-targeted anticancer agents. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Closed form unsupervised registration of multi-temporal structure from motion-multiview stereo data using non-linearly weighted image features

NASA Astrophysics Data System (ADS)

Seers, T. D.; Hodgetts, D.

2013-12-01

Seers, T. D. & Hodgetts, D. School of Earth, Atmospheric and Environmental Sciences, University of Manchester, UK. M13 9PL. The detection of topological change at the Earth's surface is of considerable scholarly interest, allowing the quantification of the rates of geomorphic processes whilst providing lucid insights into the underlying mechanisms driving landscape evolution. In this regard, the past decade has witnessed the ever increasing proliferation of studies employing multi-temporal topographic data in within the geosciences, bolstered by continuing technical advancements in the acquisition and processing of prerequisite datasets. Provided by workers within the field of Computer Vision, multiview stereo (MVS) dense surface reconstructions, primed by structure-from-motion (SfM) based camera pose estimation represents one such development. Providing a cost effective, operationally efficient data capture medium, the modest requirement of a consumer grade camera for data collection coupled with the minimal user intervention required during post-processing makes SfM-MVS an attractive alternative to terrestrial laser scanners for collecting multi-temporal topographic datasets. However, in similitude to terrestrial scanner derived data, the co-registration of spatially coincident or partially overlapping scans produced by SfM-MVS presents a major technical challenge, particularly in the case of semi non-rigid scenes produced during topographic change detection studies. Moreover, the arbitrary scaling resulting from SfM ambiguity requires that a scale matrix must be estimated during the transformation, introducing further complexity into its formulation. Here, we present a novel, fully unsupervised algorithm which utilises non-linearly weighted image features for the solving the similarity transform (scale, translation rotation) between partially overlapping scans produced by SfM-MVS image processing. With the only initialization condition being partial intersection between input image sets, our method has major advantages over conventional iterative least squares minimization based methods (e.g. Iterative Closest Point variants), acting only on rigid areas of target scenes, being capable of reliably estimating the scaling factor and requiring no incipient estimation of the transformation to initialize (i.e. manual rough alignment). Moreover, because the solution is closed form, convergence is considerably more expedient that most iterative methods. It is hoped that the availability of improved co-registration routines, such as the one presented here, will facilitate the routine collection of multi-temporal topographic datasets by a wider range of geoscience practitioners.

Groupies and Loners: The Population of Multi-planet Systems

NASA Astrophysics Data System (ADS)

Van Laerhoven, Christa L.; Greenberg, Richard

2014-11-01

Observational surveys with Kepler and other telescopes have shown that multi-planet systems are very numerous. Considering the secular dynamcis of multi-planet systems provides substantial insight into the interactions between planets in those systems. Since the underlying secular structure of a multi-planet system (the secular eigenmodes) can be calculated using only the planets' masses and semi-major axes, one can elucidate the eccentricity and inclination behavior of planets in those systems even without knowing the planets' current eccentricities and inclinations. We have calculated both the eccentricity and inclination secular eigenmodes for the population of known multi-planet systems whose planets have well determined masses and periods. We will discuss the commonality of dynamically grouped planets ('groupies') vs dynamically uncoupled planets ('loners'), and compare to what would be expected from randomly generated systems with the same overall distribution of masses and semi-major axes. We will also discuss the occurrence of planets that strongly influence the behavior of other planets without being influenced by those others ('overlords'). Examples will be given and general trends will be discussed.

Energy Decision Science and Informatics | Integrated Energy Solutions |

Science.gov Websites

Science Advanced decision science methods include multi-objective and multi-criteria decision support. Our decision science methods, including multi-objective and multi-criteria decision support. For example, we

An Immersed-Boundary Method for Fluid-Structure Interaction in the Human Larynx

NASA Astrophysics Data System (ADS)

Luo, Haoxiang; Zheng, Xudong; Mittal, Rajat; Bielamowicz, Steven

2006-11-01

We describe a novel and accurate computational methodology for modeling the airflow and vocal fold dynamics in human larynx. The model is useful in helping us gain deeper insight into the complicated bio-physics of phonation, and may have potential clinical application in design and placement of synthetic implant in vocal fold surgery. The numerical solution of the airflow employs a previously developed immersed-boundary solver. However, in order to incorporate the vocal fold into the model, we have developed a new immersed-boundary method that can simulate the dynamics of the multi-layered, viscoelastic solids. In this method, a finite-difference scheme is used to approximate the derivatives and ghost cells are defined near the boundary. To impose the traction boundary condition, a third-order polynomial is obtained using the weighted least squares fitting to approximate the function locally. Like its analogue for the flow solver, this immersed-boundary method for the solids has the advantage of simple grid generation, and may be easily implemented on parallel computers. In the talk, we will present the simulation results on both the specified vocal fold motion and the flow-induced vocal fold vibration. Supported by NIDCD Grant R01 DC007125-01A1.

Novel ID-based anti-collision approach for RFID

NASA Astrophysics Data System (ADS)

Zhang, De-Gan; Li, Wen-Bin

2016-09-01

Novel correlation ID-based (CID) anti-collision approach for RFID under the banner of the Internet of Things (IOT) has been presented in this paper. The key insights are as follows: according to the deterministic algorithms which are based on the binary search tree, we propose a method to increase the association between tags so that tags can initiatively send their own ID under certain trigger conditions, at the same time, we present a multi-tree search method for querying. When the number of tags is small, by replacing the actual ID with the temporary ID, it can greatly reduce the number of times that the reader reads and writes to tag's ID. Active tags send data to the reader by the way of modulation binary pulses. When applying this method to the uncertain ALOHA algorithms, the reader can determine the locations of the empty slots according to the position of the binary pulse, so it can avoid the decrease in efficiency which is caused by reading empty slots when reading slots. Theory and experiment show that this method can greatly improve the recognition efficiency of the system when applied to either the search tree or the ALOHA anti-collision algorithms.

An improved method for estimating capillary pressure from 3D microtomography images and its application to the study of disconnected nonwetting phase

NASA Astrophysics Data System (ADS)

Li, Tianyi; Schlüter, Steffen; Dragila, Maria Ines; Wildenschild, Dorthe

2018-04-01

We present an improved method for estimating interfacial curvatures from x-ray computed microtomography (CMT) data that significantly advances the potential for this tool to unravel the mechanisms and phenomena associated with multi-phase fluid motion in porous media. CMT data, used to analyze the spatial distribution and capillary pressure-saturation (Pc-S) relationships of liquid phases, requires accurate estimates of interfacial curvature. Our improved method for curvature estimation combines selective interface modification and distance weighting approaches. It was verified against synthetic (analytical computer-generated) and real image data sets, demonstrating a vast improvement over previous methods. Using this new tool on a previously published data set (multiphase flow) yielded important new insights regarding the pressure state of the disconnected nonwetting phase during drainage and imbibition. The trapped and disconnected non-wetting phase delimits its own hysteretic Pc-S curve that inhabits the space within the main hysteretic Pc-S loop of the connected wetting phase. Data suggests that the pressure of the disconnected, non-wetting phase is strongly modified by the pore geometry rather than solely by the bulk liquid phase that surrounds it.

Temporal data mining for the quality assessment of hemodialysis services.

PubMed

Bellazzi, Riccardo; Larizza, Cristiana; Magni, Paolo; Bellazzi, Roberto

2005-05-01

This paper describes the temporal data mining aspects of a research project that deals with the definition of methods and tools for the assessment of the clinical performance of hemodialysis (HD) services, on the basis of the time series automatically collected during hemodialysis sessions. Intelligent data analysis and temporal data mining techniques are applied to gain insight and to discover knowledge on the causes of unsatisfactory clinical results. In particular, two new methods for association rule discovery and temporal rule discovery are applied to the time series. Such methods exploit several pre-processing techniques, comprising data reduction, multi-scale filtering and temporal abstractions. We have analyzed the data of more than 5800 dialysis sessions coming from 43 different patients monitored for 19 months. The qualitative rules associating the outcome parameters and the measured variables were examined by the domain experts, which were able to distinguish between rules confirming available background knowledge and unexpected but plausible rules. The new methods proposed in the paper are suitable tools for knowledge discovery in clinical time series. Their use in the context of an auditing system for dialysis management helped clinicians to improve their understanding of the patients' behavior.

The Role of Attention in Somatosensory Processing: A Multi-Trait, Multi-Method Analysis

ERIC Educational Resources Information Center

Wodka, Ericka L.; Puts, Nicolaas A. J.; Mahone, E. Mark; Edden, Richard A. E.; Tommerdahl, Mark; Mostofsky, Stewart H.

2016-01-01

Sensory processing abnormalities in autism have largely been described by parent report. This study used a multi-method (parent-report and measurement), multi-trait (tactile sensitivity and attention) design to evaluate somatosensory processing in ASD. Results showed multiple significant within-method (e.g., parent report of different…

Analysis of high-frequency water quality data collected during a cyanoHAB event on an inland, multi-use reservoir

EPA Science Inventory

We describe here an effort to use high frequency data collected from online, continuous monitors coupled with field collected data to describe the temporal relationship between suspected HAB drivers and observed cyanoHABs and cyanotoxin production to provide insight on the necess...

"Through the Kaleidoscope": Intersections between Theoretical Perspectives and Classroom Implications in Critical Global Citizenship Education

ERIC Educational Resources Information Center

Eidoo, Sameena; Ingram, Leigh-Anne; MacDonald, Angela; Nabavi, Maryam; Pashby, Karen; Stille, Saskia

2011-01-01

This paper presents a multi-voiced examination of educating for global citizenship from critical, interdisciplinary perspectives. The paper explores how insights from theoretical work on multiculturalism, race, religion, gender, language and literacy, and eco-justice can contribute to a critical global citizenship education practice. It reports…

Multi-Ethnic Guide, An Introduction. Working Draft.

ERIC Educational Resources Information Center

Kepler, Mary, Comp.

This developmental guide was written to help children and teachers gain an understanding and respect for all ethnic groups and learn to appreciate the strengths inherent in their differences as well as in their similarities. The introductory lessons deal with the total child: first helping him to gain a better insight into himself, then studying…

Instructor Training and Instructional Design in Online Courses Using Group Work

ERIC Educational Resources Information Center

Gibson, Patricia K.

2013-01-01

The purpose of this exploratory multi-case study was to examine the role of instructional design and instructor training on student learning outcomes and student satisfaction within the online class using group work, a form of collaborative learning. Group work has been strongly recommended for online classes. Data allowing insight into…

Unpacking Instructional Strategies of Early Childhood Teachers: Insights from Teachers' Perspectives

ERIC Educational Resources Information Center

Thompson, Mumuni

2017-01-01

Even though previous research points to the significance of early childhood teachers' practices that take into consideration the nature of children and how they learn, there is limited research regarding how instructional strategies impact children's development in diverse ways. To close this gap in literature, a qualitative multi-case study into…

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,...

Multi-perspective observations of NO2 over the Denver area during DISCOVER-AQ: Insights for future monitoring

EPA Science Inventory

The final deployment in the DISCOVER-AQ1 series of air quality field campaigns focused on the Northern Front Range of Colorado including the Denver Metropolitan Area in July-August 2014. The overarching goal of these campaigns was to improve the interpretation of satellite observ...

Unpacking Activities-Based Learning in Kindergarten Classrooms: Insights from Teachers' Perspectives

ERIC Educational Resources Information Center

Annobil, Charles Nyarko; Thompson, Mumuni

2018-01-01

Even though previous research points to the significance of kindergarten teachers' practices which consider the nature of children and how they learn, there is still limited research regarding how learning activities impact children's development. To address this gap in literature, a qualitative multi-case study into teachers' perceptions of…

Action or Reaction, Learning or Display: Interactional Development and Usage-Based Data

ERIC Educational Resources Information Center

Huth, Thorsten

2013-01-01

This paper investigates how instances of language use can serve as analytic anchors for insight into interactional development over time. I present a usage-based, longitudinal study of multi-turn sequences underlying telephone openings in order to specify if and to whom "language learning" may be relevantly ascribed. Two successive…

Single-molecule studies of multi-protein machines

NASA Astrophysics Data System (ADS)

van Oijen, Antoine

2010-03-01

Advances in optical imaging and molecular manipulation techniques have made it possible to observe individual enzymes and record molecular movies that provide new insight into their dynamics and reaction mechanisms. In a biological context, most of these enzymes function in concert with other enzymes in multi-protein complexes, so an important future direction will be the utilization of single-molecule techniques to unravel the orchestration of large macromolecular assemblies. Our group is developing the single-molecule tools that will make it possible to study biochemical pathways of arbitrary complexity at the single-molecule level. I will discuss results of single-molecule experiments on the replisome, the molecular machinery that is responsible for replication of DNA. We stretch individual DNA molecules and use their elastic properties to obtain dynamic information on the proteins that unwind the double helix and copy its genetic information. Furthermore, we visualize fluorescently labeled components of the replisome and thus obtain information on stochiometry and exchange kinetics. This simultaneous observation of catalytic activity and composition allows us to gain deeper insight into the structure-function relationship of the replisome.

Agent-based modeling of porous scaffold degradation and vascularization: Optimal scaffold design based on architecture and degradation dynamics.

PubMed

Mehdizadeh, Hamidreza; Bayrak, Elif S; Lu, Chenlin; Somo, Sami I; Akar, Banu; Brey, Eric M; Cinar, Ali

2015-11-01

A multi-layer agent-based model (ABM) of biomaterial scaffold vascularization is extended to consider the effects of scaffold degradation kinetics on blood vessel formation. A degradation model describing the bulk disintegration of porous hydrogels is incorporated into the ABM. The combined degradation-angiogenesis model is used to investigate growing blood vessel networks in the presence of a degradable scaffold structure. Simulation results indicate that higher porosity, larger mean pore size, and rapid degradation allow faster vascularization when not considering the structural support of the scaffold. However, premature loss of structural support results in failure for the material. A strategy using multi-layer scaffold with different degradation rates in each layer was investigated as a way to address this issue. Vascularization was improved with the multi-layered scaffold model compared to the single-layer model. The ABM developed provides insight into the characteristics that influence the selection of optimal geometric parameters and degradation behavior of scaffolds, and enables easy refinement of the model as new knowledge about the underlying biological phenomena becomes available. This paper proposes a multi-layer agent-based model (ABM) of biomaterial scaffold vascularization integrated with a structural-kinetic model describing bulk degradation of porous hydrogels to consider the effects of scaffold degradation kinetics on blood vessel formation. This enables the assessment of scaffold characteristics and in particular the disintegration characteristics of the scaffold on angiogenesis. Simulation results indicate that higher porosity, larger mean pore size, and rapid degradation allow faster vascularization when not considering the structural support of the scaffold. However, premature loss of structural support by scaffold disintegration results in failure of the material and disruption of angiogenesis. A strategy using multi-layer scaffold with different degradation rates in each layer was investigated as away to address this issue. Vascularization was improved with the multi-layered scaffold model compared to the single-layer model. The ABM developed provides insight into the characteristics that influence the selection of optimal geometric and degradation characteristics of tissue engineering scaffolds. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

The Blended Finite Element Method for Multi-fluid Plasma Modeling

DTIC Science & Technology

2016-07-01

Briefing Charts 3. DATES COVERED (From - To) 07 June 2016 - 01 July 2016 4. TITLE AND SUBTITLE The Blended Finite Element Method for Multi-fluid Plasma...BLENDED FINITE ELEMENT METHOD FOR MULTI-FLUID PLASMA MODELING Éder M. Sousa1, Uri Shumlak2 1ERC INC., IN-SPACE PROPULSION BRANCH (RQRS) AIR FORCE RESEARCH...MULTI-FLUID PLASMA MODEL 2 BLENDED FINITE ELEMENT METHOD Blended Finite Element Method Nodal Continuous Galerkin Modal Discontinuous Galerkin Model

Multi-scale gyrokinetic simulation of Alcator C-Mod tokamak discharges

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

Howard, N. T., E-mail: nthoward@psfc.mit.edu; White, A. E.; Greenwald, M.

2014-03-15

Alcator C-Mod tokamak discharges have been studied with nonlinear gyrokinetic simulation simultaneously spanning both ion and electron spatiotemporal scales. These multi-scale simulations utilized the gyrokinetic model implemented by GYRO code [J. Candy and R. E. Waltz, J. Comput. Phys. 186, 545 (2003)] and the approximation of reduced electron mass (μ = (m{sub D}/m{sub e}){sup .5} = 20.0) to qualitatively study a pair of Alcator C-Mod discharges: a low-power discharge, previously demonstrated (using realistic mass, ion-scale simulation) to display an under-prediction of the electron heat flux and a high-power discharge displaying agreement with both ion and electron heat flux channels [N. T. Howard et al.,more » Nucl. Fusion 53, 123011 (2013)]. These multi-scale simulations demonstrate the importance of electron-scale turbulence in the core of conventional tokamak discharges and suggest it is a viable candidate for explaining the observed under-prediction of electron heat flux. In this paper, we investigate the coupling of turbulence at the ion (k{sub θ}ρ{sub s}∼O(1.0)) and electron (k{sub θ}ρ{sub e}∼O(1.0)) scales for experimental plasma conditions both exhibiting strong (high-power) and marginally stable (low-power) low-k (k{sub θ}ρ{sub s} < 1.0) turbulence. It is found that reduced mass simulation of the plasma exhibiting marginally stable low-k turbulence fails to provide even qualitative insight into the turbulence present in the realistic plasma conditions. In contrast, multi-scale simulation of the plasma condition exhibiting strong turbulence provides valuable insight into the coupling of the ion and electron scales.« less

Multi-fidelity methods for uncertainty quantification in transport problems

NASA Astrophysics Data System (ADS)

Tartakovsky, G.; Yang, X.; Tartakovsky, A. M.; Barajas-Solano, D. A.; Scheibe, T. D.; Dai, H.; Chen, X.

2016-12-01

We compare several multi-fidelity approaches for uncertainty quantification in flow and transport simulations that have a lower computational cost than the standard Monte Carlo method. The cost reduction is achieved by combining a small number of high-resolution (high-fidelity) simulations with a large number of low-resolution (low-fidelity) simulations. We propose a new method, a re-scaled Multi Level Monte Carlo (rMLMC) method. The rMLMC is based on the idea that the statistics of quantities of interest depends on scale/resolution. We compare rMLMC with existing multi-fidelity methods such as Multi Level Monte Carlo (MLMC) and reduced basis methods and discuss advantages of each approach.

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

Wavefield complexity and stealth structures: Resolution constraints by wave physics

NASA Astrophysics Data System (ADS)

Nissen-Meyer, T.; Leng, K.

2017-12-01

Imaging the Earth's interior relies on understanding how waveforms encode information from heterogeneous multi-scale structure. This relation is given by elastodynamics, but forward modeling in the context of tomography primarily serves to deliver synthetic waveforms and gradients for the inversion procedure. While this is entirely appropriate, it depreciates a wealth of complementary inference that can be obtained from the complexity of the wavefield. Here, we are concerned with the imprint of realistic multi-scale Earth structure on the wavefield, and the question on the inherent physical resolution limit of structures encoded in seismograms. We identify parameter and scattering regimes where structures remain invisible as a function of seismic wavelength, structural multi-scale geometry, scattering strength, and propagation path. Ultimately, this will aid in interpreting tomographic images by acknowledging the scope of "forgotten" structures, and shall offer guidance for optimising the selection of seismic data for tomography. To do so, we use our novel 3D modeling method AxiSEM3D which tackles global wave propagation in visco-elastic, anisotropic 3D structures with undulating boundaries at unprecedented resolution and efficiency by exploiting the inherent azimuthal smoothness of wavefields via a coupled Fourier expansion-spectral-element approach. The method links computational cost to wavefield complexity and thereby lends itself well to exploring the relation between waveforms and structures. We will show various examples of multi-scale heterogeneities which appear or disappear in the waveform, and argue that the nature of the structural power spectrum plays a central role in this. We introduce the concept of wavefield learning to examine the true wavefield complexity for a complexity-dependent modeling framework and discriminate which scattering structures can be retrieved by surface measurements. This leads to the question of physical invisibility and the tomographic resolution limit, and offers insight as to why tomographic images still show stark differences for smaller-scale heterogeneities despite progress in modeling and data resolution. Finally, we give an outlook on how we expand this modeling framework towards an inversion procedure guided by wavefield complexity.

Robust crossfeed design for hovering rotorcraft. M.S. Thesis

NASA Technical Reports Server (NTRS)

Catapang, David R.

1993-01-01

Control law design for rotorcraft fly-by-wire systems normally attempts to decouple angular responses using fixed-gain crossfeeds. This approach can lead to poor decoupling over the frequency range of pilot inputs and increase the load on the feedback loops. In order to improve the decoupling performance, dynamic crossfeeds may be adopted. Moreover, because of the large changes that occur in rotorcraft dynamics due to small changes about the nominal design condition, especially for near-hovering flight, the crossfeed design must be 'robust.' A new low-order matching method is presented here to design robost crossfeed compensators for multi-input, multi-output (MIMO) systems. The technique identifies degrees-of-freedom that can be decoupled using crossfeeds, given an anticipated set of parameter variations for the range of flight conditions of concern. Cross-coupling is then reduced for degrees-of-freedom that can use crossfeed compensation by minimizing off-axis response magnitude average and variance. Results are presented for the analysis of pitch, roll, yaw, and heave coupling of the UH-60 Black Hawk helicopter in near-hovering flight. Robust crossfeeds are designed that show significant improvement in decoupling performance and robustness over nominal, single design point, compensators. The design method and results are presented in an easily-used graphical format that lends significant physical insight to the design procedure. This plant pre-compensation technique is an appropriate preliminary step to the design of robust feedback control laws for rotorcraft.

Probabilistic Hazard Estimation at a Densely Urbanised Area: the Neaples Volcanoes

NASA Astrophysics Data System (ADS)

de Natale, G.; Mastrolorenzo, G.; Panizza, A.; Pappalardo, L.; Claudia, T.

2005-12-01

The Neaples volcanic area (Southern Italy), including Vesuvius, Campi Flegrei caldera and Ischia island, is the highest risk one in the World, where more than 2 million people live within about 10 km from an active volcanic vent. Such an extreme risk calls for accurate methodologies aimed to quantify it, in a probabilistic way, considering all the available volcanological information as well as modelling results. In fact, simple hazard maps based on the observation of deposits from past eruptions have the major problem that eruptive history generally samples a very limited number of possible outcomes, thus resulting almost meaningless to get the event probability in the area. This work describes a methodology making the best use (from a Bayesian point of view) of volcanological data and modelling results, to compute probabilistic hazard maps from multi-vent explosive eruptions. The method, which follows an approach recently developed by the same authors for pyroclastic flows hazard, has been here improved and extended to compute also fall-out hazard. The application of the method to the Neapolitan volcanic area, including the densely populated city of Naples, allows, for the first time, to get a global picture of the areal distribution for the main hazards from multi-vent explosive eruptions. From a joint consideration of the hazard contributions from all the three volcanic areas, new insight on the volcanic hazard distribution emerges, which will have strong implications for urban and emergency planning in the area.

Emerging technologies in education and training: applications for the laboratory animal science community.

PubMed

Ketelhut, Diane Jass; Niemi, Steven M

2007-01-01

This article examines several new and exciting communication technologies. Many of the technologies were developed by the entertainment industry; however, other industries are adopting and modifying them for their own needs. These new technologies allow people to collaborate across distance and time and to learn in simulated work contexts. The article explores the potential utility of these technologies for advancing laboratory animal care and use through better education and training. Descriptions include emerging technologies such as augmented reality and multi-user virtual environments, which offer new approaches with different capabilities. Augmented reality interfaces, characterized by the use of handheld computers to infuse the virtual world into the real one, result in deeply immersive simulations. In these simulations, users can access virtual resources and communicate with real and virtual participants. Multi-user virtual environments enable multiple participants to simultaneously access computer-based three-dimensional virtual spaces, called "worlds," and to interact with digital tools. They allow for authentic experiences that promote collaboration, mentoring, and communication. Because individuals may learn or train differently, it is advantageous to combine the capabilities of these technologies and applications with more traditional methods to increase the number of students who are served by using current methods alone. The use of these technologies in animal care and use programs can create detailed training and education environments that allow students to learn the procedures more effectively, teachers to assess their progress more objectively, and researchers to gain insights into animal care.

Design of a multi-agent hydroeconomic model to simulate a complex human-water system: Early insights from the Jordan Water Project

NASA Astrophysics Data System (ADS)

Yoon, J.; Klassert, C. J. A.; Lachaut, T.; Selby, P. D.; Knox, S.; Gorelick, S.; Rajsekhar, D.; Tilmant, A.; Avisse, N.; Harou, J. J.; Gawel, E.; Klauer, B.; Mustafa, D.; Talozi, S.; Sigel, K.

2015-12-01

Our work focuses on development of a multi-agent, hydroeconomic model for purposes of water policy evaluation in Jordan. The model adopts a modular approach, integrating biophysical modules that simulate natural and engineered phenomena with human modules that represent behavior at multiple levels of decision making. The hydrologic modules are developed using spatially-distributed groundwater and surface water models, which are translated into compact simulators for efficient integration into the multi-agent model. For the groundwater model, we adopt a response matrix method approach in which a 3-dimensional MODFLOW model of a complex regional groundwater system is converted into a linear simulator of groundwater response by pre-processing drawdown results from several hundred numerical simulation runs. Surface water models for each major surface water basin in the country are developed in SWAT and similarly translated into simple rainfall-runoff functions for integration with the multi-agent model. The approach balances physically-based, spatially-explicit representation of hydrologic systems with the efficiency required for integration into a complex multi-agent model that is computationally amenable to robust scenario analysis. For the multi-agent model, we explicitly represent human agency at multiple levels of decision making, with agents representing riparian, management, supplier, and water user groups. The agents' decision making models incorporate both rule-based heuristics as well as economic optimization. The model is programmed in Python using Pynsim, a generalizable, open-source object-oriented code framework for modeling network-based water resource systems. The Jordan model is one of the first applications of Pynsim to a real-world water management case study. Preliminary results from a tanker market scenario run through year 2050 are presented in which several salient features of the water system are investigated: competition between urban and private farmer agents, the emergence of a private tanker market, disparities in economic wellbeing to different user groups caused by unique supply conditions, and response of the complex system to various policy interventions.

Reconfigurable microfluidic hanging drop network for multi-tissue interaction and analysis.

PubMed

Frey, Olivier; Misun, Patrick M; Fluri, David A; Hengstler, Jan G; Hierlemann, Andreas

2014-06-30

Integration of multiple three-dimensional microtissues into microfluidic networks enables new insights in how different organs or tissues of an organism interact. Here, we present a platform that extends the hanging-drop technology, used for multi-cellular spheroid formation, to multifunctional complex microfluidic networks. Engineered as completely open, 'hanging' microfluidic system at the bottom of a substrate, the platform features high flexibility in microtissue arrangements and interconnections, while fabrication is simple and operation robust. Multiple spheroids of different cell types are formed in parallel on the same platform; the different tissues are then connected in physiological order for multi-tissue experiments through reconfiguration of the fluidic network. Liquid flow is precisely controlled through the hanging drops, which enable nutrient supply, substance dosage and inter-organ metabolic communication. The possibility to perform parallelized microtissue formation on the same chip that is subsequently used for complex multi-tissue experiments renders the developed platform a promising technology for 'body-on-a-chip'-related research.

Smartphone application for multi-phasic interventional trials in psychiatry: Technical design of a smart server.

PubMed

Zhang, Melvyn W B; Ho, Roger C M

2017-01-01

Smartphones and their accompanying applications are currently widely utilized in various healthcare interventions. Prior to the deployment of these tools for healthcare intervention, typically, proof of concept feasibility studies, as well as randomized trials are conducted to determine that these tools are efficacious prior to their actual implementation. In the field of psychiatry, most of the current interventions seek to compare smartphone based intervention against conventional care. There remains a paucity of research evaluating different forms of interventions using a single smartphone application. In the field of nutrition, there has been recent pioneering research demonstrating how a multi-phasic randomized controlled trial could be conducted using a single smartphone application. Despite the innovativeness of the previous smartphone conceptualization, there remains a paucity of technical information underlying the conceptualization that would support a multi-phasic interventional trial. It is thus the aim of the current technical note to share insights into an innovative server design that would enable the delivery of multi-phasic trials.

Influence of dispatching rules on average production lead time for multi-stage production systems.

PubMed

Hübl, Alexander; Jodlbauer, Herbert; Altendorfer, Klaus

2013-08-01

In this paper the influence of different dispatching rules on the average production lead time is investigated. Two theorems based on covariance between processing time and production lead time are formulated and proved theoretically. Theorem 1 links the average production lead time to the "processing time weighted production lead time" for the multi-stage production systems analytically. The influence of different dispatching rules on average lead time, which is well known from simulation and empirical studies, can be proved theoretically in Theorem 2 for a single stage production system. A simulation study is conducted to gain more insight into the influence of dispatching rules on average production lead time in a multi-stage production system. We find that the "processing time weighted average production lead time" for a multi-stage production system is not invariant of the applied dispatching rule and can be used as a dispatching rule independent indicator for single-stage production systems.

Bioinspired Fabrication of one dimensional graphene fiber with collection of droplets application.

PubMed

Song, Yun-Yun; Liu, Yan; Jiang, Hao-Bo; Li, Shu-Yi; Kaya, Cigdem; Stegmaier, Thomas; Han, Zhi-Wu; Ren, Lu-Quan

2017-09-21

We designed a kind of smart bioinspired fiber with multi-gradient and multi-scale spindle knots by combining polydimethylsiloxane (PDMS) and graphene oxide (GO). Multilayered graphene structures can produce obvious wettability change after laser etching due to increased roughness. We demonstrate that the cooperation between curvature and the controllable wettability play an important role in water gathering, which regulate effectively the motion of tiny water droplets. In addition, due to the effective cooperation of multi-gradient and multi-scale hydrophilic spindle knots, the length of the three-phase contact line (TCL) can be longer, which makes a great contribution to the improvement of collecting efficiency and water-hanging ability. This study offers a novel insight into the design of smart materials that may control the transport of tiny drops reversibly in directions, which could potentially be extended to the realms of in microfluidics, fog harvesting filtration and condensers designs, and further increase water collection efficiency and hanging ability.

7th Annual Systems Biology Symposium: Systems Biology and Engineering

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

Galitski, Timothy P.

2008-04-01

Systems biology recognizes the complex multi-scale organization of biological systems, from molecules to ecosystems. The International Symposium on Systems Biology has been hosted by the Institute for Systems Biology in Seattle, Washington, since 2002. The annual two-day event gathers the most influential researchers transforming biology into an integrative discipline investingating complex systems. Engineering and application of new technology is a central element of systems biology. Genome-scale, or very small-scale, biological questions drive the enigneering of new technologies, which enable new modes of experimentation and computational analysis, leading to new biological insights and questions. Concepts and analytical methods in engineering aremore » now finding direct applications in biology. Therefore, the 2008 Symposium, funded in partnership with the Department of Energy, featured global leaders in "Systems Biology and Engineering."« less

Very-long-period seismic signals - filling the gap between deformation and seismicity

NASA Astrophysics Data System (ADS)

Neuberg, Jurgen; Smith, Paddy

2013-04-01

Good broadband seismic sensors are capable to record seismic transients with dominant wavelengths of several tens or even hundreds of seconds. This allows us to generate a multi-component record of seismic volcanic events that are located in between the conventional high to low-frequency seismic spectrum and deformation signals. With a much higher temporal resolution and accuracy than e.g. GPS records, these signals fill the gap between seismicity and deformation studies. In this contribution we will review the non-trivial processing steps necessary to retrieve ground deformation from the original velocity seismogram and explore which role the resulting displacement signals have in the analysis of volcanic events. We use examples from Soufriere Hills volcano in Montserrat, West Indies, to discuss the benefits and shortcomings of such methods regarding new insights into volcanic processes.

Neutrons and music: Imaging investigation of ancient wind musical instruments

NASA Astrophysics Data System (ADS)

Festa, G.; Tardino, G.; Pontecorvo, L.; Mannes, D. C.; Senesi, R.; Gorini, G.; Andreani, C.

2014-10-01

A set of seven musical instruments and two instruments cares from the 'Fondo Antico della Biblioteca del Sacro Convento' in Assisi, Italy, were investigated through neutron and X-ray imaging techniques. Historical and scientific interests around ancient musical instruments motivate an intense research effort for their characterization using non-destructive and non-invasive techniques. X-ray and neutron tomography/radiography were applied to the study of composite material samples containing wood, hide and metals. The study was carried out at the NEUTRA beamline, PSI (Paul Scherrer Institute, Switzerland). Results of the measurements provided new information on the composite and multi-scale structure, such as: the internal structure of the samples, position of added materials like metals, wood fiber displays, deformations, presence of adhesives and their spatial distribution and novel insight about construction methods to guide the instruments' restoration process.

Excitation, response, and fatigue life estimation methods for the structural design of externally blown flaps

NASA Technical Reports Server (NTRS)

Ungar, E. E.; Chandiramani, K. L.; Barger, J. E.

1972-01-01

Means for predicting the fluctuating pressures acting on externally blown flap surfaces are developed on the basis of generalizations derived from non-dimensionalized empirical data. Approaches for estimation of the fatigue lives of skin-stringer and honeycomb-core sandwich flap structures are derived from vibration response analyses and panel fatigue data. Approximate expressions for fluctuating pressures, structural response, and fatigue life are combined to reveal the important parametric dependences. The two-dimensional equations of motion of multi-element flap systems are derived in general form, so that they can be specialized readily for any particular system. An introduction is presented of an approach to characterizing the excitation pressures and structural responses which makes use of space-time spectral concepts and promises to provide useful insights, as well as experimental and analytical savings.

Composite material impregnation unit

NASA Technical Reports Server (NTRS)

Wilkinson, S. P.; Marchello, J. M.; Johnston, N. J.

1993-01-01

This memorandum presents an introduction to the NASA multi-purpose prepregging unit which is now installed and fully operational at the Langley Research Center in the Polymeric Materials Branch. A description of the various impregnation methods that are available to the prepregger are presented. Machine operating details and protocol are provided for its various modes of operation. These include, where appropriate, the related equations for predicting the desired prepreg specifications. Also, as the prepregger is modular in its construction, each individual section is described and discussed. Safety concerns are an important factor and a chapter has been included that highlights the major safety features. Initial experiences and observations for fiber impregnation are described. These first observations have given great insight into the areas of future work that need to be addressed. Future memorandums will focus on these individual processes and their related problems.

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

Doughty, Benjamin; Simpson, Mary Jane; Yang, Bin

Our work aims to simplify multi-dimensional femtosecond transient absorption microscopy (TAM) data into decay associated amplitude maps that describe the spatial distributions of dynamical processes occurring on various characteristic timescales. Application of this method to TAM data obtained from a model methyl-ammonium lead iodide (CH 3NH 3PbI 3) perovskite thin film allows us to simplify the dataset consisting of a 68 time-resolved images into 4 decay associated amplitude maps. Furthermore, these maps provide a simple means to visualize the complex electronic excited-state dynamics in this system by separating distinct dynamical processes evolving on characteristic timescales into individual spatial images. Thismore » approach provides new insight into subtle aspects of ultrafast relaxation dynamics associated with excitons and charge carriers in the perovskite thin film, which have recently been found to coexist at spatially distinct locations.« less

Compositional Analysis of Fine Particulate Matter in Fairbanks, Alaska

NASA Astrophysics Data System (ADS)

Nattinger, K.; Simpson, W. R.; Huff, D.

2015-12-01

Fairbanks, AK experiences extreme pollution episodes that result in winter violations of the fine particulate matter (PM2.5) National Ambient Air Quality Standards. This poses a significant health risk for the inhabitants of the area. These high levels result from trapping of pollution in a very shallow boundary layer due to local meteorology, but the role of primary (direct emission) of particulate matter versus secondary production (in the atmosphere) of particulate matter is not understood. Analysis of the PM2.5 composition is being conducted to provide insight into sources, trends, and chemistry. Methods are developed to convert carbon data from IMPROVE (post-2009 analysis method) to NIOSH (pre-2009 method) utilizing blank subtraction, sampler bias adjustment, and inter-method correlations from co-located samples. By converting all carbon measurements to a consistent basis, long-term trends can be analyzed. The approach shows excellent mass closure between PM2.5 mass reconstructed from constituents and gravimetric-analyzed mass. This approach could be utilized in other US locations where the carbon analysis methods also changed. Results include organic and inorganic fractional mass percentages, analyzed over an eight-year period for two testing sites in Fairbanks and two in the nearby city of North Pole. We focus on the wintertime (Nov—Feb) period when most air quality violations occur and find that the particles consist primarily of organic carbon, with smaller percentages of sulfate, elemental carbon, ammonium, and nitrate. The Fairbanks area PM2.5 organic carbon / elemental carbon partitioning matches the source profile of wood smoke. North Pole and Fairbanks PM2.5 have significant compositional differences, with North Pole having a larger percentage of organic matter. Mass loadings in SO42-, NO3-, and total PM2.5 mass correlate with temperature. Multi-year temporal trends show little if any change with a strong effect from temperature. Insights from this study regarding primary versus possible secondary PM2.5 production processes can help in identifying effective PM2.5 control strategies.

Model predictive control design for polytopic uncertain systems by synthesising multi-step prediction scenarios

NASA Astrophysics Data System (ADS)

Lu, Jianbo; Xi, Yugeng; Li, Dewei; Xu, Yuli; Gan, Zhongxue

2018-01-01

A common objective of model predictive control (MPC) design is the large initial feasible region, low online computational burden as well as satisfactory control performance of the resulting algorithm. It is well known that interpolation-based MPC can achieve a favourable trade-off among these different aspects. However, the existing results are usually based on fixed prediction scenarios, which inevitably limits the performance of the obtained algorithms. So by replacing the fixed prediction scenarios with the time-varying multi-step prediction scenarios, this paper provides a new insight into improvement of the existing MPC designs. The adopted control law is a combination of predetermined multi-step feedback control laws, based on which two MPC algorithms with guaranteed recursive feasibility and asymptotic stability are presented. The efficacy of the proposed algorithms is illustrated by a numerical example.

Microscopic modeling of multi-lane highway traffic flow

NASA Astrophysics Data System (ADS)

Hodas, Nathan O.; Jagota, Anand

2003-12-01

We discuss a microscopic model for the study of multi-lane highway traffic flow dynamics. Each car experiences a force resulting from a combination of the desire of the driver to attain a certain velocity, aerodynamic drag, and change of the force due to car-car interactions. The model also includes multi-lane simulation capability and the ability to add and remove obstructions. We implement the model via a Java applet, which is used to simulate traffic jam formation, the effect of bottlenecks on traffic flow, and the existence of light, medium, and heavy traffic flow. The simulations also provide insight into how the properties of individual cars result in macroscopic behavior. Because the investigation of emergent characteristics is so common in physics, the study of traffic in this manner sheds new light on how the micro-to-macro transition works in general.

Structural damage detection-oriented multi-type sensor placement with multi-objective optimization

NASA Astrophysics Data System (ADS)

Lin, Jian-Fu; Xu, You-Lin; Law, Siu-Seong

2018-05-01

A structural damage detection-oriented multi-type sensor placement method with multi-objective optimization is developed in this study. The multi-type response covariance sensitivity-based damage detection method is first introduced. Two objective functions for optimal sensor placement are then introduced in terms of the response covariance sensitivity and the response independence. The multi-objective optimization problem is formed by using the two objective functions, and the non-dominated sorting genetic algorithm (NSGA)-II is adopted to find the solution for the optimal multi-type sensor placement to achieve the best structural damage detection. The proposed method is finally applied to a nine-bay three-dimensional frame structure. Numerical results show that the optimal multi-type sensor placement determined by the proposed method can avoid redundant sensors and provide satisfactory results for structural damage detection. The restriction on the number of each type of sensors in the optimization can reduce the searching space in the optimization to make the proposed method more effective. Moreover, how to select a most optimal sensor placement from the Pareto solutions via the utility function and the knee point method is demonstrated in the case study.

Multi-layer laminate structure and manufacturing method

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

Keenihan, James R; Cleereman, Robert J; Eurich, Gerald

2012-04-24

The present invention is premised upon a multi-layer laminate structure and method of manufacture, more particularly to a method of constructing the multi-layer laminate structure utilizing a laminate frame and at least one energy activated flowable polymer.

Multi-layer laminate structure and manufacturing method

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

Keenihan, James R.; Cleereman, Robert J.; Eurich, Gerald

2013-01-29

The present invention is premised upon a multi-layer laminate structure and method of manufacture, more particularly to a method of constructing the multi-layer laminate structure utilizing a laminate frame and at least one energy activated flowable polymer.

The 1980 land cover for the Puget Sound region

NASA Technical Reports Server (NTRS)

Shinn, R. D.; Westerlund, F. V.; Eby, J. R.

1982-01-01

Both LANDSAT imagery and the video information communications and retrieval software were used to develop a land cover classifiction of the Puget Sound of Washington. Planning agencies within the region were provided with a highly accurate land cover map registered to the 1980 census tracts which could subsequently be incorporated as one data layer in a multi-layer data base. Many historical activities related to previous land cover mapping studies conducted in the Puget Sound region are summarized. Valuable insight into conducting a project with a large community of users and in establishing user confidence in a multi-purpose land cover map derived from LANDSAT is provided.

Pattern Search in Multi-structure Data: A Framework for the Next-Generation Evidence-based Medicine

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

Sukumar, Sreenivas R; Ainsworth, Keela C

With the advent of personalized and evidence-based medicine, the need for a framework to analyze/interpret quantitative measurements (blood work, toxicology, etc.) with qualitative descriptions (specialist reports after reading images, bio-medical knowledge-bases) to predict diagnostic risks is fast emerging. Addressing this need, we pose and address the following questions (i) How can we jointly analyze both qualitative and quantitative data ? (ii) Is the fusion of multi-structure data expected to provide better insights than either of them individually ? We present experiments on two bio-medical data sets - mammography and traumatic brain studies to demonstrate architectures and tools for evidence-pattern search.

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.

Insight into Best Variables for COPD Case Identification: A Random Forests Analysis.

PubMed

Leidy, Nancy K; Malley, Karen G; Steenrod, Anna W; Mannino, David M; Make, Barry J; Bowler, Russ P; Thomashow, Byron M; Barr, R G; Rennard, Stephen I; Houfek, Julia F; Yawn, Barbara P; Han, Meilan K; Meldrum, Catherine A; Bacci, Elizabeth D; Walsh, John W; Martinez, Fernando

This study is part of a larger, multi-method project to develop a questionnaire for identifying undiagnosed cases of chronic obstructive pulmonary disease (COPD) in primary care settings, with specific interest in the detection of patients with moderate to severe airway obstruction or risk of exacerbation. To examine 3 existing datasets for insight into key features of COPD that could be useful in the identification of undiagnosed COPD. Random forests analyses were applied to the following databases: COPD Foundation Peak Flow Study Cohort (N=5761), Burden of Obstructive Lung Disease (BOLD) Kentucky site (N=508), and COPDGene® (N=10,214). Four scenarios were examined to find the best, smallest sets of variables that distinguished cases and controls:(1) moderate to severe COPD (forced expiratory volume in 1 second [FEV 1 ] <50% predicted) versus no COPD; (2) undiagnosed versus diagnosed COPD; (3) COPD with and without exacerbation history; and (4) clinically significant COPD (FEV 1 <60% predicted or history of acute exacerbation) versus all others. From 4 to 8 variables were able to differentiate cases from controls, with sensitivity ≥73 (range: 73-90) and specificity >68 (range: 68-93). Across scenarios, the best models included age, smoking status or history, symptoms (cough, wheeze, phlegm), general or breathing-related activity limitation, episodes of acute bronchitis, and/or missed work days and non-work activities due to breathing or health. Results provide insight into variables that should be considered during the development of candidate items for a new questionnaire to identify undiagnosed cases of clinically significant COPD.

Insight on agglomerates of gold nanoparticles in glass based on surface plasmon resonance spectrum: study by multi-spheres T-matrix method

NASA Astrophysics Data System (ADS)

Avakyan, L. A.; Heinz, M.; Skidanenko, A. V.; Yablunovski, K. A.; Ihlemann, J.; Meinertz, J.; Patzig, C.; Dubiel, M.; Bugaev, L. A.

2018-01-01

The formation of a localized surface plasmon resonance (SPR) spectrum of randomly distributed gold nanoparticles in the surface layer of silicate float glass, generated and implanted by UV ArF-excimer laser irradiation of a thin gold layer sputter-coated on the glass surface, was studied by the T-matrix method, which enables particle agglomeration to be taken into account. The experimental technique used is promising for the production of submicron patterns of plasmonic nanoparticles (given by laser masks or gratings) without damage to the glass surface. Analysis of the applicability of the multi-spheres T-matrix (MSTM) method to the studied material was performed through calculations of SPR characteristics for differently arranged and structured gold nanoparticles (gold nanoparticles in solution, particles pairs, and core-shell silver-gold nanoparticles) for which either experimental data or results of the modeling by other methods are available. For the studied gold nanoparticles in glass, it was revealed that the theoretical description of their SPR spectrum requires consideration of the plasmon coupling between particles, which can be done effectively by MSTM calculations. The obtained statistical distributions over particle sizes and over interparticle distances demonstrated the saturation behavior with respect to the number of particles under consideration, which enabled us to determine the effective aggregate of particles, sufficient to form the SPR spectrum. The suggested technique for the fitting of an experimental SPR spectrum of gold nanoparticles in glass by varying the geometrical parameters of the particles aggregate in the recurring calculations of spectrum by MSTM method enabled us to determine statistical characteristics of the aggregate: the average distance between particles, average size, and size distribution of the particles. The fitting strategy of the SPR spectrum presented here can be applied to nanoparticles of any nature and in various substances, and, in principle, can be extended for particles with non-spherical shapes, like ellipsoids, rod-like and other T-matrix-solvable shapes.

Determination of optimum "multi-channel surface wave method" field parameters.

DOT National Transportation Integrated Search

2012-12-01

Multi-channel surface wave methods (especially the multi-channel analyses of surface wave method; MASW) are routinely used to : determine the shear-wave velocity of the subsurface to depths of 100 feet for site classification purposes. Users are awar...

Whole-canopy gas exchange in Coffea sp. is affected by supra-optimal temperature and light distribution within the canopy: the insights from an improved multi-chamber system

USDA-ARS?s Scientific Manuscript database

Given the difference of photosynthetic rate between the leaves in different positions of the canopy, leaf-level photosynthesis measurements can provide incomplete and potentially misleading information if extrapolated to quantify photosynthesis or infer differences in water demand and crop productiv...

I am from Delicious Lasagna: Exploring Cultural Identity with Digital Storytelling

ERIC Educational Resources Information Center

Fitts, Shanan; Gross, Lisa A.

2010-01-01

In an effort to gain greater insights into bilingual and bicultural children's understanding of their cultural and linguistic identities, the authors embarked on a Where I'm From (WIF) multi-media poetry project. The WIF project has great potential and value for developing students' language and communication skills, and for exploring the meaning…

A practical approach for comparing management strategies in complex forest ecosystems using meta-modelling toolkits

Treesearch

Andrew Fall; B. Sturtevant; M.-J. Fortin; M. Papaik; F. Doyon; D. Morgan; K. Berninger; C. Messier

2010-01-01

The complexity and multi-scaled nature of forests poses significant challenges to understanding and management. Models can provide useful insights into process and their interactions, and implications of alternative management options. Most models, particularly scientific models, focus on a relatively small set of processes and are designed to operate within a...

Information acquisition and behavioral change: a social marketing application.

PubMed

Golden, L L; Johnson, K

1991-01-01

Previous literature provides insight into the importance of beliefs and other intrapersonal variables for health-related information acquisition and behavioral change. The results of an empirical investigation evidence the unique strength of the role of core health beliefs for each of the multi-level measures. Directions for the development of effective marketing strategy are discussed.

Online Project-Based Learning: How Collaborative Strategies and Problem Solving Processes Impact Performance

ERIC Educational Resources Information Center

Thomas, W. Randall; Macgregor, S. Kim

2005-01-01

The goal of this study was to gain insights into the interactions that occur in online communications in a project-based learning activity implemented in an undergraduate course. A multi-case study was conducted of six collaborative groups, focusing on the types and frequencies of interactions that occurred within each group and the perceptions…

Learning from Lessons: Teachers' Insights and Intended Actions Arising from Their Learning about Student Thinking

ERIC Educational Resources Information Center

Roche, Anne; Clarke, Doug; Clarke, David; Chan, Man Ching Esther

2016-01-01

A central premise of this project is that teachers learn from the act of teaching a lesson and that this learning is evident in the planning and teaching of a subsequent lesson. We are studying the knowledge construction of mathematics teachers utilising multi-camera research techniques during lesson planning, classroom interactions and…

New insights into the aquatic photochemistry of fluoroquinolone antibiotics: Direct photodegradation, hydroxyl-radical oxidation, and antibacterial activity changes.

PubMed

Ge, Linke; Na, Guangshui; Zhang, Siyu; Li, Kai; Zhang, Peng; Ren, Honglei; Yao, Ziwei

2015-09-15

The ubiquity and photoreactivity of fluoroquinolone antibiotics (FQs) in surface waters urge new insights into their aqueous photochemical behavior. This study concerns the photochemistry of 6 FQs: ciprofloxacin, danofloxacin, levofloxacin, sarafloxacin, difloxacin and enrofloxacin. Methods were developed to calculate their solar direct photodegradation half-lives (td,E) and hydroxyl-radical oxidation half-lives (tOH,E) in sunlit surface waters. The td,E values range from 0.56 min to 28.8 min at 45° N latitude, whereas tOH,E ranges from 3.24h to 33.6h, suggesting that most FQs tend to undergo fast direct photolysis rather than hydroxyl-radical oxidation in surface waters. However, a case study for levofloxacin and sarafloxacin indicated that the hydroxyl-radical oxidation induced risky photochlorination and resulted in multi-degradation pathways, such as piperazinyl hydroxylation and clearage. Changes in the antibacterial activity of FQs caused by photodegradation in various waters were further examined using Escherichia coli, and it was found that the activity evolution depended on primary photodegradation pathways and products. Primary intermediates with intact FQ nuclei retained significant antibacterial activity. These results are important for assessing the fate and risk of FQs in surface waters. Copyright © 2015. Published by Elsevier B.V.

Genomic insights into the taxonomic status of the Bacillus cereus group

PubMed Central

Liu, Yang; Lai, Qiliang; Göker, Markus; Meier-Kolthoff, Jan P.; Wang, Meng; Sun, Yamin; Wang, Lei; Shao, Zongze

2015-01-01

The identification and phylogenetic relationships of bacteria within the Bacillus cereus group are controversial. This study aimed at determining the taxonomic affiliations of these strains using the whole-genome sequence-based Genome BLAST Distance Phylogeny (GBDP) approach. The GBDP analysis clearly separated 224 strains into 30 clusters, representing eleven known, partially merged species and accordingly 19–20 putative novel species. Additionally, 16S rRNA gene analysis, a novel variant of multi-locus sequence analysis (nMLSA) and screening of virulence genes were performed. The 16S rRNA gene sequence was not sufficient to differentiate the bacteria within this group due to its high conservation. The nMLSA results were consistent with GBDP. Moreover, a fast typing method was proposed using the pycA gene, and where necessary, the ccpA gene. The pXO plasmids and cry genes were widely distributed, suggesting little correlation with the phylogenetic positions of the host bacteria. This might explain why classifications based on virulence characteristics proved unsatisfactory in the past. In summary, this is the first large-scale and systematic study of the taxonomic status of the bacteria within the B. cereus group using whole-genome sequences, and is likely to contribute to further insights into their pathogenicity, phylogeny and adaptation to diverse environments. PMID:26373441

A manual-based individual therapy to improve metacognition in schizophrenia: protocol of a multi-center RCT

PubMed Central

2014-01-01

Background Metacognitive dysfunction has been widely recognized as a feature of schizophrenia. As it is linked with deficits in several aspects of daily life functioning, improvement of metacognition may lead to improvement in functioning. Individual psychotherapy might be a useful form of treatment to improve metacognition in patients with schizophrenia; multiple case reports and a pilot study show promising results. The present study aims to measure the effectiveness of an individual, manual-based therapy (Metacognitive Reflection and Insight Therapy, MERIT) in improving metacognition in patients with schizophrenia. We also want to examine if improvement in metacognitive abilities is correlated with improvements in aspects of daily life functioning namely social functioning, experience of symptoms, quality of life, depression, work readiness, insight and experience of stigma. Methods/Design MERIT is currently evaluated in a multicenter randomized controlled trial. Thirteen therapists in six mental health institutions in the Netherlands participate in this study. Patients are randomly assigned to either MERIT or the control condition: treatment as usual (TAU). Discussion If proven effective, MERIT can be a useful addition to the care for schizophrenia patients. The design brings along some methodological difficulties, these issues are addressed in the discussion of this paper. Trial registration Current Controlled Trials: ISRCTN16659871. PMID:24490942

Measurement of nonlinear normal modes using multi-harmonic stepped force appropriation and free decay

NASA Astrophysics Data System (ADS)

Ehrhardt, David A.; Allen, Matthew S.

2016-08-01

Nonlinear Normal Modes (NNMs) offer tremendous insight into the dynamic behavior of a nonlinear system, extending many concepts that are familiar in linear modal analysis. Hence there is interest in developing methods to experimentally and numerically determine a system's NNMs for model updating or simply to characterize its dynamic response. Previous experimental work has shown that a mono-harmonic excitation can be used to isolate a system's dynamic response in the neighborhood of a NNM along the main backbones of a system. This work shows that a multi-harmonic excitation is needed to isolate a NNM when well separated linear modes of a structure couple to produce an internal resonance. It is shown that one can tune the multiple harmonics of the input excitation using a plot of the input force versus the response velocity until the area enclosed by the force-velocity curve is minimized. Once an appropriated NNM is measured, one can increase the force level and retune the frequency to obtain a NNM at a higher amplitude or remove the excitation and measure the structure's decay down a NNM backbone. This work explores both methods using simulations and measurements of a nominally-flat clamped-clamped beam excited at a single point with a magnetic force. Numerical simulations are used to validate the method in a well defined environment and to provide comparison with the experimentally measured NNMs. The experimental results seem to produce a good estimate of two NNMs along their backbone and part of an internal resonance branch. Full-field measurements are then used to further explore the couplings between the underlying linear modes along the identified NNMs.

Investigating Hydrocarbon Seep Environments with High-Resolution, Three-Dimensional Geographic Visualizations.

NASA Astrophysics Data System (ADS)

Doolittle, D. F.; Gharib, J. J.; Mitchell, G. A.

2015-12-01

Detailed photographic imagery and bathymetric maps of the seafloor acquired by deep submergence vehicles such as Autonomous Underwater Vehicles (AUV) and Remotely Operated Vehicles (ROV) are expanding how scientists and the public view and ultimately understand the seafloor and the processes that modify it. Several recently acquired optical and acoustic datasets, collected during ECOGIG (Ecosystem Impacts of Oil and Gas Inputs to the Gulf) and other Gulf of Mexico expeditions using the National Institute for Undersea Science Technology (NIUST) Eagle Ray, and Mola Mola AUVs, have been fused with lower resolution data to create unique three-dimensional geovisualizations. Included in these data are multi-scale and multi-resolution visualizations over hydrocarbon seeps and seep related features. Resolution of the data range from 10s of mm to 10s of m. When multi-resolution data is integrated into a single three-dimensional visual environment, new insights into seafloor and seep processes can be obtained from the intuitive nature of three-dimensional data exploration. We provide examples and demonstrate how integration of multibeam bathymetry, seafloor backscatter data, sub-bottom profiler data, textured photomosaics, and hull-mounted multibeam acoustic midwater imagery are made into a series a three-dimensional geovisualizations of actively seeping sites and associated chemosynthetic communities. From these combined and merged datasets, insights on seep community structure, morphology, ecology, fluid migration dynamics, and process geomorphology can be investigated from new spatial perspectives. Such datasets also promote valuable inter-comparisons of sensor resolution and performance.

Joint sparse reconstruction of multi-contrast MRI images with graph based redundant wavelet transform.

PubMed

Lai, Zongying; Zhang, Xinlin; Guo, Di; Du, Xiaofeng; Yang, Yonggui; Guo, Gang; Chen, Zhong; Qu, Xiaobo

2018-05-03

Multi-contrast images in magnetic resonance imaging (MRI) provide abundant contrast information reflecting the characteristics of the internal tissues of human bodies, and thus have been widely utilized in clinical diagnosis. However, long acquisition time limits the application of multi-contrast MRI. One efficient way to accelerate data acquisition is to under-sample the k-space data and then reconstruct images with sparsity constraint. However, images are compromised at high acceleration factor if images are reconstructed individually. We aim to improve the images with a jointly sparse reconstruction and Graph-based redundant wavelet transform (GBRWT). First, a sparsifying transform, GBRWT, is trained to reflect the similarity of tissue structures in multi-contrast images. Second, joint multi-contrast image reconstruction is formulated as a ℓ 2, 1 norm optimization problem under GBRWT representations. Third, the optimization problem is numerically solved using a derived alternating direction method. Experimental results in synthetic and in vivo MRI data demonstrate that the proposed joint reconstruction method can achieve lower reconstruction errors and better preserve image structures than the compared joint reconstruction methods. Besides, the proposed method outperforms single image reconstruction with joint sparsity constraint of multi-contrast images. The proposed method explores the joint sparsity of multi-contrast MRI images under graph-based redundant wavelet transform and realizes joint sparse reconstruction of multi-contrast images. Experiment demonstrate that the proposed method outperforms the compared joint reconstruction methods as well as individual reconstructions. With this high quality image reconstruction method, it is possible to achieve the high acceleration factors by exploring the complementary information provided by multi-contrast MRI.

Application of separable parameter space techniques to multi-tracer PET compartment modeling.

PubMed

Zhang, Jeff L; Michael Morey, A; Kadrmas, Dan J

2016-02-07

Multi-tracer positron emission tomography (PET) can image two or more tracers in a single scan, characterizing multiple aspects of biological functions to provide new insights into many diseases. The technique uses dynamic imaging, resulting in time-activity curves that contain contributions from each tracer present. The process of separating and recovering separate images and/or imaging measures for each tracer requires the application of kinetic constraints, which are most commonly applied by fitting parallel compartment models for all tracers. Such multi-tracer compartment modeling presents challenging nonlinear fits in multiple dimensions. This work extends separable parameter space kinetic modeling techniques, previously developed for fitting single-tracer compartment models, to fitting multi-tracer compartment models. The multi-tracer compartment model solution equations were reformulated to maximally separate the linear and nonlinear aspects of the fitting problem, and separable least-squares techniques were applied to effectively reduce the dimensionality of the nonlinear fit. The benefits of the approach are then explored through a number of illustrative examples, including characterization of separable parameter space multi-tracer objective functions and demonstration of exhaustive search fits which guarantee the true global minimum to within arbitrary search precision. Iterative gradient-descent algorithms using Levenberg-Marquardt were also tested, demonstrating improved fitting speed and robustness as compared to corresponding fits using conventional model formulations. The proposed technique overcomes many of the challenges in fitting simultaneous multi-tracer PET compartment models.

Application of separable parameter space techniques to multi-tracer PET compartment modeling

NASA Astrophysics Data System (ADS)

Zhang, Jeff L.; Morey, A. Michael; Kadrmas, Dan J.

2016-02-01

Multi-tracer positron emission tomography (PET) can image two or more tracers in a single scan, characterizing multiple aspects of biological functions to provide new insights into many diseases. The technique uses dynamic imaging, resulting in time-activity curves that contain contributions from each tracer present. The process of separating and recovering separate images and/or imaging measures for each tracer requires the application of kinetic constraints, which are most commonly applied by fitting parallel compartment models for all tracers. Such multi-tracer compartment modeling presents challenging nonlinear fits in multiple dimensions. This work extends separable parameter space kinetic modeling techniques, previously developed for fitting single-tracer compartment models, to fitting multi-tracer compartment models. The multi-tracer compartment model solution equations were reformulated to maximally separate the linear and nonlinear aspects of the fitting problem, and separable least-squares techniques were applied to effectively reduce the dimensionality of the nonlinear fit. The benefits of the approach are then explored through a number of illustrative examples, including characterization of separable parameter space multi-tracer objective functions and demonstration of exhaustive search fits which guarantee the true global minimum to within arbitrary search precision. Iterative gradient-descent algorithms using Levenberg-Marquardt were also tested, demonstrating improved fitting speed and robustness as compared to corresponding fits using conventional model formulations. The proposed technique overcomes many of the challenges in fitting simultaneous multi-tracer PET compartment models.

Decoding Multiple Sound Categories in the Human Temporal Cortex Using High Resolution fMRI

PubMed Central

Zhang, Fengqing; Wang, Ji-Ping; Kim, Jieun; Parrish, Todd; Wong, Patrick C. M.

2015-01-01

Perception of sound categories is an important aspect of auditory perception. The extent to which the brain’s representation of sound categories is encoded in specialized subregions or distributed across the auditory cortex remains unclear. Recent studies using multivariate pattern analysis (MVPA) of brain activations have provided important insights into how the brain decodes perceptual information. In the large existing literature on brain decoding using MVPA methods, relatively few studies have been conducted on multi-class categorization in the auditory domain. Here, we investigated the representation and processing of auditory categories within the human temporal cortex using high resolution fMRI and MVPA methods. More importantly, we considered decoding multiple sound categories simultaneously through multi-class support vector machine-recursive feature elimination (MSVM-RFE) as our MVPA tool. Results show that for all classifications the model MSVM-RFE was able to learn the functional relation between the multiple sound categories and the corresponding evoked spatial patterns and classify the unlabeled sound-evoked patterns significantly above chance. This indicates the feasibility of decoding multiple sound categories not only within but across subjects. However, the across-subject variation affects classification performance more than the within-subject variation, as the across-subject analysis has significantly lower classification accuracies. Sound category-selective brain maps were identified based on multi-class classification and revealed distributed patterns of brain activity in the superior temporal gyrus and the middle temporal gyrus. This is in accordance with previous studies, indicating that information in the spatially distributed patterns may reflect a more abstract perceptual level of representation of sound categories. Further, we show that the across-subject classification performance can be significantly improved by averaging the fMRI images over items, because the irrelevant variations between different items of the same sound category are reduced and in turn the proportion of signals relevant to sound categorization increases. PMID:25692885

Decoding multiple sound categories in the human temporal cortex using high resolution fMRI.

PubMed

Zhang, Fengqing; Wang, Ji-Ping; Kim, Jieun; Parrish, Todd; Wong, Patrick C M

2015-01-01

Perception of sound categories is an important aspect of auditory perception. The extent to which the brain's representation of sound categories is encoded in specialized subregions or distributed across the auditory cortex remains unclear. Recent studies using multivariate pattern analysis (MVPA) of brain activations have provided important insights into how the brain decodes perceptual information. In the large existing literature on brain decoding using MVPA methods, relatively few studies have been conducted on multi-class categorization in the auditory domain. Here, we investigated the representation and processing of auditory categories within the human temporal cortex using high resolution fMRI and MVPA methods. More importantly, we considered decoding multiple sound categories simultaneously through multi-class support vector machine-recursive feature elimination (MSVM-RFE) as our MVPA tool. Results show that for all classifications the model MSVM-RFE was able to learn the functional relation between the multiple sound categories and the corresponding evoked spatial patterns and classify the unlabeled sound-evoked patterns significantly above chance. This indicates the feasibility of decoding multiple sound categories not only within but across subjects. However, the across-subject variation affects classification performance more than the within-subject variation, as the across-subject analysis has significantly lower classification accuracies. Sound category-selective brain maps were identified based on multi-class classification and revealed distributed patterns of brain activity in the superior temporal gyrus and the middle temporal gyrus. This is in accordance with previous studies, indicating that information in the spatially distributed patterns may reflect a more abstract perceptual level of representation of sound categories. Further, we show that the across-subject classification performance can be significantly improved by averaging the fMRI images over items, because the irrelevant variations between different items of the same sound category are reduced and in turn the proportion of signals relevant to sound categorization increases.

Learning Evaluation: blending quality improvement and implementation research methods to study healthcare innovations.

PubMed

Balasubramanian, Bijal A; Cohen, Deborah J; Davis, Melinda M; Gunn, Rose; Dickinson, L Miriam; Miller, William L; Crabtree, Benjamin F; Stange, Kurt C

2015-03-10

In healthcare change interventions, on-the-ground learning about the implementation process is often lost because of a primary focus on outcome improvements. This paper describes the Learning Evaluation, a methodological approach that blends quality improvement and implementation research methods to study healthcare innovations. Learning Evaluation is an approach to multi-organization assessment. Qualitative and quantitative data are collected to conduct real-time assessment of implementation processes while also assessing changes in context, facilitating quality improvement using run charts and audit and feedback, and generating transportable lessons. Five principles are the foundation of this approach: (1) gather data to describe changes made by healthcare organizations and how changes are implemented; (2) collect process and outcome data relevant to healthcare organizations and to the research team; (3) assess multi-level contextual factors that affect implementation, process, outcome, and transportability; (4) assist healthcare organizations in using data for continuous quality improvement; and (5) operationalize common measurement strategies to generate transportable results. Learning Evaluation principles are applied across organizations by the following: (1) establishing a detailed understanding of the baseline implementation plan; (2) identifying target populations and tracking relevant process measures; (3) collecting and analyzing real-time quantitative and qualitative data on important contextual factors; (4) synthesizing data and emerging findings and sharing with stakeholders on an ongoing basis; and (5) harmonizing and fostering learning from process and outcome data. Application to a multi-site program focused on primary care and behavioral health integration shows the feasibility and utility of Learning Evaluation for generating real-time insights into evolving implementation processes. Learning Evaluation generates systematic and rigorous cross-organizational findings about implementing healthcare innovations while also enhancing organizational capacity and accelerating translation of findings by facilitating continuous learning within individual sites. Researchers evaluating change initiatives and healthcare organizations implementing improvement initiatives may benefit from a Learning Evaluation approach.

Real-Time Multi-Target Localization from Unmanned Aerial Vehicles

PubMed Central

Wang, Xuan; Liu, Jinghong; Zhou, Qianfei

2016-01-01

In order to improve the reconnaissance efficiency of unmanned aerial vehicle (UAV) electro-optical stabilized imaging systems, a real-time multi-target localization scheme based on an UAV electro-optical stabilized imaging system is proposed. First, a target location model is studied. Then, the geodetic coordinates of multi-targets are calculated using the homogeneous coordinate transformation. On the basis of this, two methods which can improve the accuracy of the multi-target localization are proposed: (1) the real-time zoom lens distortion correction method; (2) a recursive least squares (RLS) filtering method based on UAV dead reckoning. The multi-target localization error model is established using Monte Carlo theory. In an actual flight, the UAV flight altitude is 1140 m. The multi-target localization results are within the range of allowable error. After we use a lens distortion correction method in a single image, the circular error probability (CEP) of the multi-target localization is reduced by 7%, and 50 targets can be located at the same time. The RLS algorithm can adaptively estimate the location data based on multiple images. Compared with multi-target localization based on a single image, CEP of the multi-target localization using RLS is reduced by 25%. The proposed method can be implemented on a small circuit board to operate in real time. This research is expected to significantly benefit small UAVs which need multi-target geo-location functions. PMID:28029145

Real-Time Multi-Target Localization from Unmanned Aerial Vehicles.

PubMed

Wang, Xuan; Liu, Jinghong; Zhou, Qianfei

2016-12-25

In order to improve the reconnaissance efficiency of unmanned aerial vehicle (UAV) electro-optical stabilized imaging systems, a real-time multi-target localization scheme based on an UAV electro-optical stabilized imaging system is proposed. First, a target location model is studied. Then, the geodetic coordinates of multi-targets are calculated using the homogeneous coordinate transformation. On the basis of this, two methods which can improve the accuracy of the multi-target localization are proposed: (1) the real-time zoom lens distortion correction method; (2) a recursive least squares (RLS) filtering method based on UAV dead reckoning. The multi-target localization error model is established using Monte Carlo theory. In an actual flight, the UAV flight altitude is 1140 m. The multi-target localization results are within the range of allowable error. After we use a lens distortion correction method in a single image, the circular error probability (CEP) of the multi-target localization is reduced by 7%, and 50 targets can be located at the same time. The RLS algorithm can adaptively estimate the location data based on multiple images. Compared with multi-target localization based on a single image, CEP of the multi-target localization using RLS is reduced by 25%. The proposed method can be implemented on a small circuit board to operate in real time. This research is expected to significantly benefit small UAVs which need multi-target geo-location functions.

Facilitating insights with a user adaptable dashboard, illustrated by airport connectivity data

NASA Astrophysics Data System (ADS)

Dobraja, Ieva; Kraak, Menno-Jan; Engelhardt, Yuri

2018-05-01

Since the movement data exist, there have been approaches to collect and analyze them to get insights. This kind of data is often heterogeneous, multiscale and multi-temporal. Those interested in spatio-temporal patterns of movement data do not gain insights from textual descriptions. Therefore, visualization is required. As spatio-temporal movement data can be complex because size and characteristics, it is even challenging to create an overview of it. Plotting all the data on the screen will not be the solution as it likely will result into cluttered images where no data exploration is possible. To ensure that users will receive the information they are interested in, it is important to provide a graphical data representation environment where exploration to gain insights are possible not only in the overall level but at sub-levels as well. A dashboard would be a solution the representation of heterogeneous spatio- temporal data. It provides an overview and helps to unravel the complexity of data by splitting data in multiple data representation views. The adaptability of dashboard will help to reveal the information which cannot be seen in the overview.

Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online

PubMed Central

Forsberg, Erica M; Huan, Tao; Rinehart, Duane; Benton, H Paul; Warth, Benedikt; Hilmers, Brian; Siuzdak, Gary

2018-01-01

Systems biology is the study of complex living organisms, and as such, analysis on a systems-wide scale involves the collection of information-dense data sets that are representative of an entire phenotype. To uncover dynamic biological mechanisms, bioinformatics tools have become essential to facilitating data interpretation in large-scale analyses. Global metabolomics is one such method for performing systems biology, as metabolites represent the downstream functional products of ongoing biological processes. We have developed XCMS Online, a platform that enables online metabolomics data processing and interpretation. A systems biology workflow recently implemented within XCMS Online enables rapid metabolic pathway mapping using raw metabolomics data for investigating dysregulated metabolic processes. In addition, this platform supports integration of multi-omic (such as genomic and proteomic) data to garner further systems-wide mechanistic insight. Here, we provide an in-depth procedure showing how to effectively navigate and use the systems biology workflow within XCMS Online without a priori knowledge of the platform, including uploading liquid chromatography (LCLC)–mass spectrometry (MS) data from metabolite-extracted biological samples, defining the job parameters to identify features, correcting for retention time deviations, conducting statistical analysis of features between sample classes and performing predictive metabolic pathway analysis. Additional multi-omics data can be uploaded and overlaid with previously identified pathways to enhance systems-wide analysis of the observed dysregulations. We also describe unique visualization tools to assist in elucidation of statistically significant dysregulated metabolic pathways. Parameter input takes 5–10 min, depending on user experience; data processing typically takes 1–3 h, and data analysis takes ~30 min. PMID:29494574

Theoretical study of the effect of an AlGaAs double heterostructure on metal-semiconductor-metal photodetector performance

NASA Technical Reports Server (NTRS)

Salem, Ali F.; Smith, Arlynn W.; Brennan, Kevin F.

1994-01-01

The sizing and efficiency of an aircraft is largely determined by the performance of its high-lift system. Subsonic civil transports most often use deployable multi-element airfoils to achieve the maximum-lift requirements for landing, as well as the high lift-to-drag ratios for take-off. However, these systems produce very complex flow fields which are not fully understood by the scientific community. In order to compete in today's market place, aircraft manufacturers will have to design better high-lift systems. Therefore, a more thorough understanding of the flows associated with these systems is desired. Flight and wind-tunnel experiments have been conducted on NASA Langley's B737-100 research aircraft to obtain detailed full-scale flow measurements on a multi-element high-lift system at various flight conditions. As part of this effort, computational aerodynamic tools are being used to provide preliminary flow-field information for instrumentation development, and to provide additional insight during the data analysis and interpretation process. The purpose of this paper is to demonstrate the ability and usefulness of a three-dimensional low-order potentialflow solver, PMARC, by comparing computational results with data obtained from 1/8 scale wind-tunnel tests. Overall, correlation of experimental and computational data reveals that the panel method is able to predict reasonably well the pressures of the aircraft's multi-element wing at several spanwise stations. PMARC's versatility and usefulness is also demonstrated by accurately predicting inviscid threedimensional flow features for several intricate geometrical regions.

Strategies for the structural analysis of multi-protein complexes: lessons from the 3D-Repertoire project.

PubMed

Collinet, B; Friberg, A; Brooks, M A; van den Elzen, T; Henriot, V; Dziembowski, A; Graille, M; Durand, D; Leulliot, N; Saint André, C; Lazar, N; Sattler, M; Séraphin, B; van Tilbeurgh, H

2011-08-01

Structural studies of multi-protein complexes, whether by X-ray diffraction, scattering, NMR spectroscopy or electron microscopy, require stringent quality control of the component samples. The inability to produce 'keystone' subunits in a soluble and correctly folded form is a serious impediment to the reconstitution of the complexes. Co-expression of the components offers a valuable alternative to the expression of single proteins as a route to obtain sufficient amounts of the sample of interest. Even in cases where milligram-scale quantities of purified complex of interest become available, there is still no guarantee that good quality crystals can be obtained. At this step, protein engineering of one or more components of the complex is frequently required to improve solubility, yield or the ability to crystallize the sample. Subsequent characterization of these constructs may be performed by solution techniques such as Small Angle X-ray Scattering and Nuclear Magnetic Resonance to identify 'well behaved' complexes. Herein, we recount our experiences gained at protein production and complex assembly during the European 3D Repertoire project (3DR). The goal of this consortium was to obtain structural information on multi-protein complexes from yeast by combining crystallography, electron microscopy, NMR and in silico modeling methods. We present here representative set case studies of complexes that were produced and analyzed within the 3DR project. Our experience provides useful insight into strategies that are more generally applicable for structural analysis of protein complexes. Copyright © 2011 Elsevier Inc. All rights reserved.

Multi-modal distraction: insights from children's limited attention.

PubMed

Matusz, Pawel J; Broadbent, Hannah; Ferrari, Jessica; Forrest, Benjamin; Merkley, Rebecca; Scerif, Gaia

2015-03-01

How does the multi-sensory nature of stimuli influence information processing? Cognitive systems with limited selective attention can elucidate these processes. Six-year-olds, 11-year-olds and 20-year-olds engaged in a visual search task that required them to detect a pre-defined coloured shape under conditions of low or high visual perceptual load. On each trial, a peripheral distractor that could be either compatible or incompatible with the current target colour was presented either visually, auditorily or audiovisually. Unlike unimodal distractors, audiovisual distractors elicited reliable compatibility effects across the two levels of load in adults and in the older children, but high visual load significantly reduced distraction for all children, especially the youngest participants. This study provides the first demonstration that multi-sensory distraction has powerful effects on selective attention: Adults and older children alike allocate attention to potentially relevant information across multiple senses. However, poorer attentional resources can, paradoxically, shield the youngest children from the deleterious effects of multi-sensory distraction. Furthermore, we highlight how developmental research can enrich the understanding of distinct mechanisms controlling adult selective attention in multi-sensory environments. Copyright © 2014 Elsevier B.V. All rights reserved.

A novel approach to study effects of asymmetric stiffness on parametric instabilities of multi-rotor-system

NASA Astrophysics Data System (ADS)

Jain, Anuj Kumar; Rastogi, Vikas; Agrawal, Atul Kumar

2018-01-01

The main focus of this paper is to study effects of asymmetric stiffness on parametric instabilities of multi-rotor-system through extended Lagrangian formalism, where symmetries are broken in terms of the rotor stiffness. The complete insight of dynamic behaviour of multi-rotor-system with asymmetries is evaluated through extension of Lagrangian equation with a case study. In this work, a dynamic mathematical model of a multi-rotor-system through a novel approach of extension of Lagrangian mechanics is developed, where the system is having asymmetries due to varying stiffness. The amplitude and the natural frequency of the rotor are obtained analytically through the proposed methodology. The bond graph modeling technique is used for modeling the asymmetric rotor. Symbol-shakti® software is used for the simulation of the model. The effects of the stiffness of multi-rotor-system on amplitude and frequencies are studied using numerical simulation. Simulation results show a considerable agreement with the theoretical results obtained through extended Lagrangian formalism. It is further shown that amplitude of the rotor increases inversely the stiffness of the rotor up to a certain limit, which is also affirmed theoretically.

Cluster-based analysis of multi-model climate ensembles

NASA Astrophysics Data System (ADS)

Hyde, Richard; Hossaini, Ryan; Leeson, Amber A.

2018-06-01

Clustering - the automated grouping of similar data - can provide powerful and unique insight into large and complex data sets, in a fast and computationally efficient manner. While clustering has been used in a variety of fields (from medical image processing to economics), its application within atmospheric science has been fairly limited to date, and the potential benefits of the application of advanced clustering techniques to climate data (both model output and observations) has yet to be fully realised. In this paper, we explore the specific application of clustering to a multi-model climate ensemble. We hypothesise that clustering techniques can provide (a) a flexible, data-driven method of testing model-observation agreement and (b) a mechanism with which to identify model development priorities. We focus our analysis on chemistry-climate model (CCM) output of tropospheric ozone - an important greenhouse gas - from the recent Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Tropospheric column ozone from the ACCMIP ensemble was clustered using the Data Density based Clustering (DDC) algorithm. We find that a multi-model mean (MMM) calculated using members of the most-populous cluster identified at each location offers a reduction of up to ˜ 20 % in the global absolute mean bias between the MMM and an observed satellite-based tropospheric ozone climatology, with respect to a simple, all-model MMM. On a spatial basis, the bias is reduced at ˜ 62 % of all locations, with the largest bias reductions occurring in the Northern Hemisphere - where ozone concentrations are relatively large. However, the bias is unchanged at 9 % of all locations and increases at 29 %, particularly in the Southern Hemisphere. The latter demonstrates that although cluster-based subsampling acts to remove outlier model data, such data may in fact be closer to observed values in some locations. We further demonstrate that clustering can provide a viable and useful framework in which to assess and visualise model spread, offering insight into geographical areas of agreement among models and a measure of diversity across an ensemble. Finally, we discuss caveats of the clustering techniques and note that while we have focused on tropospheric ozone, the principles underlying the cluster-based MMMs are applicable to other prognostic variables from climate models.

Multi-electrolyte-step anodic aluminum oxide method for the fabrication of self-organized nanochannel arrays

PubMed Central

2012-01-01

Nanochannel arrays were fabricated by the self-organized multi-electrolyte-step anodic aluminum oxide [AAO] method in this study. The anodization conditions used in the multi-electrolyte-step AAO method included a phosphoric acid solution as the electrolyte and an applied high voltage. There was a change in the phosphoric acid by the oxalic acid solution as the electrolyte and the applied low voltage. This method was used to produce self-organized nanochannel arrays with good regularity and circularity, meaning less power loss and processing time than with the multi-step AAO method. PMID:22333268

Multi-scale calculation based on dual domain material point method combined with molecular dynamics

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

Dhakal, Tilak Raj

This dissertation combines the dual domain material point method (DDMP) with molecular dynamics (MD) in an attempt to create a multi-scale numerical method to simulate materials undergoing large deformations with high strain rates. In these types of problems, the material is often in a thermodynamically non-equilibrium state, and conventional constitutive relations are often not available. In this method, the closure quantities, such as stress, at each material point are calculated from a MD simulation of a group of atoms surrounding the material point. Rather than restricting the multi-scale simulation in a small spatial region, such as phase interfaces, or crackmore » tips, this multi-scale method can be used to consider non-equilibrium thermodynamic e ects in a macroscopic domain. This method takes advantage that the material points only communicate with mesh nodes, not among themselves; therefore MD simulations for material points can be performed independently in parallel. First, using a one-dimensional shock problem as an example, the numerical properties of the original material point method (MPM), the generalized interpolation material point (GIMP) method, the convected particle domain interpolation (CPDI) method, and the DDMP method are investigated. Among these methods, only the DDMP method converges as the number of particles increases, but the large number of particles needed for convergence makes the method very expensive especially in our multi-scale method where we calculate stress in each material point using MD simulation. To improve DDMP, the sub-point method is introduced in this dissertation, which provides high quality numerical solutions with a very small number of particles. The multi-scale method based on DDMP with sub-points is successfully implemented for a one dimensional problem of shock wave propagation in a cerium crystal. The MD simulation to calculate stress in each material point is performed in GPU using CUDA to accelerate the computation. The numerical properties of the multiscale method are investigated as well as the results from this multi-scale calculation are compared of particles needed for convergence makes the method very expensive especially in our multi-scale method where we calculate stress in each material point using MD simulation. To improve DDMP, the sub-point method is introduced in this dissertation, which provides high quality numerical solutions with a very small number of particles. The multi-scale method based on DDMP with sub-points is successfully implemented for a one dimensional problem of shock wave propagation in a cerium crystal. The MD simulation to calculate stress in each material point is performed in GPU using CUDA to accelerate the computation. The numerical properties of the multiscale method are investigated as well as the results from this multi-scale calculation are compared with direct MD simulation results to demonstrate the feasibility of the method. Also, the multi-scale method is applied for a two dimensional problem of jet formation around copper notch under a strong impact.« less

Electrically optical phase controlling for millimeter wave orbital angular momentum multi-modulation communication

NASA Astrophysics Data System (ADS)

Wu, Haotian; Tang, Jin; Yu, Zhenliang; Yi, Jun; Chen, Shuqing; Xiao, Jiangnan; Zhao, Chujun; Li, Ying; Chen, Lin; Wen, Shuangchun

2017-06-01

Orbital angular momentum (OAM), an emerging and fascinating degree of freedom, has highlighted an innovation in communication and optical manipulation field. The beams with different OAM state, which manifest as the phase front ;twisting; of electromagnetic waves, are mutually orthogonal, which is exactly what a new freedom applied to practical communication eagers for. Herein, we proposed a novel millimeter-wave OAM modulation technique by electrically optical phase controlling. By modulating OAM and phase of optical-millimeter-wave synchronously, the multi-modulation: quadrature orbital angular momentum modulation (QOM) communication system at W band is structured and simulated, allowing a 50 Gbit/s signal transmitting with bit-error rates less than 10-4. Our work might suggest that OAM could be compounded to more complex multi-modulation signal, and revealed a new insight into OAM based high capacity wireless and radio-over-fiber communication.

Multi-wavelength Raman spectroscopy study of supported vanadia catalysts: Structure identification and quantification

DOE PAGES

Wu, Zili

2014-10-20

Revealing the structure of supported metal oxide catalysts is a prerequisite for establishing the structure - catalysis relationship. Among a variety of characterization techniques, multi-wavelength Raman spectroscopy, combining resonance Raman and non-resonance Raman with different excitation wavelengths, has recently emerged as a particularly powerful tool in not only identifying but also quantifying the structure of supported metal oxide clusters. In our review, we make use of two supported vanadia systems, VO x/SiO 2 and VO x/CeO 2, as examples to showcase how one can employ this technique to investigate the heterogeneous structure of active oxide clusters and to understand themore » complex interaction between the oxide clusters and the support. Moreover, the qualitative and quantitative structural information gained from the multi-wavelength Raman spectroscopy can be utilized to provide fundamental insights for designing more efficient supported metal oxide catalysts.« less

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

Zhao, T; Ruan, D

Purpose: The growing size and heterogeneity in training atlas necessitates sophisticated schemes to identify only the most relevant atlases for the specific multi-atlas-based image segmentation problem. This study aims to develop a model to infer the inaccessible oracle geometric relevance metric from surrogate image similarity metrics, and based on such model, provide guidance to atlas selection in multi-atlas-based image segmentation. Methods: We relate the oracle geometric relevance metric in label space to the surrogate metric in image space, by a monotonically non-decreasing function with additive random perturbations. Subsequently, a surrogate’s ability to prognosticate the oracle order for atlas subset selectionmore » is quantified probabilistically. Finally, important insights and guidance are provided for the design of fusion set size, balancing the competing demands to include the most relevant atlases and to exclude the most irrelevant ones. A systematic solution is derived based on an optimization framework. Model verification and performance assessment is performed based on clinical prostate MR images. Results: The proposed surrogate model was exemplified by a linear map with normally distributed perturbation, and verified with several commonly-used surrogates, including MSD, NCC and (N)MI. The derived behaviors of different surrogates in atlas selection and their corresponding performance in ultimate label estimate were validated. The performance of NCC and (N)MI was similarly superior to MSD, with a 10% higher atlas selection probability and a segmentation performance increase in DSC by 0.10 with the first and third quartiles of (0.83, 0.89), compared to (0.81, 0.89). The derived optimal fusion set size, valued at 7/8/8/7 for MSD/NCC/MI/NMI, agreed well with the appropriate range [4, 9] from empirical observation. Conclusion: This work has developed an efficacious probabilistic model to characterize the image-based surrogate metric on atlas selection. Analytical insights lead to valid guiding principles on fusion set size design.« less

A New Method for Setting Calculation Sequence of Directional Relay Protection in Multi-Loop Networks

NASA Astrophysics Data System (ADS)

Haijun, Xiong; Qi, Zhang

2016-08-01

Workload of relay protection setting calculation in multi-loop networks may be reduced effectively by optimization setting calculation sequences. A new method of setting calculation sequences of directional distance relay protection in multi-loop networks based on minimum broken nodes cost vector (MBNCV) was proposed to solve the problem experienced in current methods. Existing methods based on minimum breakpoint set (MBPS) lead to more break edges when untying the loops in dependent relationships of relays leading to possibly more iterative calculation workloads in setting calculations. A model driven approach based on behavior trees (BT) was presented to improve adaptability of similar problems. After extending the BT model by adding real-time system characters, timed BT was derived and the dependency relationship in multi-loop networks was then modeled. The model was translated into communication sequence process (CSP) models and an optimization setting calculation sequence in multi-loop networks was finally calculated by tools. A 5-nodes multi-loop network was applied as an example to demonstrate effectiveness of the modeling and calculation method. Several examples were then calculated with results indicating the method effectively reduces the number of forced broken edges for protection setting calculation in multi-loop networks.

A label distance maximum-based classifier for multi-label learning.

PubMed

Liu, Xiaoli; Bao, Hang; Zhao, Dazhe; Cao, Peng

2015-01-01

Multi-label classification is useful in many bioinformatics tasks such as gene function prediction and protein site localization. This paper presents an improved neural network algorithm, Max Label Distance Back Propagation Algorithm for Multi-Label Classification. The method was formulated by modifying the total error function of the standard BP by adding a penalty term, which was realized by maximizing the distance between the positive and negative labels. Extensive experiments were conducted to compare this method against state-of-the-art multi-label methods on three popular bioinformatic benchmark datasets. The results illustrated that this proposed method is more effective for bioinformatic multi-label classification compared to commonly used techniques.

On-Line Multi-Damage Scanning Spatial-Wavenumber Filter Based Imaging Method for Aircraft Composite Structure.

PubMed

Ren, Yuanqiang; Qiu, Lei; Yuan, Shenfang; Bao, Qiao

2017-05-11

Structural health monitoring (SHM) of aircraft composite structure is helpful to increase reliability and reduce maintenance costs. Due to the great effectiveness in distinguishing particular guided wave modes and identifying the propagation direction, the spatial-wavenumber filter technique has emerged as an interesting SHM topic. In this paper, a new scanning spatial-wavenumber filter (SSWF) based imaging method for multiple damages is proposed to conduct on-line monitoring of aircraft composite structures. Firstly, an on-line multi-damage SSWF is established, including the fundamental principle of SSWF for multiple damages based on a linear piezoelectric (PZT) sensor array, and a corresponding wavenumber-time imaging mechanism by using the multi-damage scattering signal. Secondly, through combining the on-line multi-damage SSWF and a PZT 2D cross-shaped array, an image-mapping method is proposed to conduct wavenumber synthesis and convert the two wavenumber-time images obtained by the PZT 2D cross-shaped array to an angle-distance image, from which the multiple damages can be directly recognized and located. In the experimental validation, both simulated multi-damage and real multi-damage introduced by repeated impacts are performed on a composite plate structure. The maximum localization error is less than 2 cm, which shows good performance of the multi-damage imaging method. Compared with the existing spatial-wavenumber filter based damage evaluation methods, the proposed method requires no more than the multi-damage scattering signal and can be performed without depending on any wavenumber modeling or measuring. Besides, this method locates multiple damages by imaging instead of the geometric method, which helps to improve the signal-to-noise ratio. Thus, it can be easily applied to on-line multi-damage monitoring of aircraft composite structures.

On-Line Multi-Damage Scanning Spatial-Wavenumber Filter Based Imaging Method for Aircraft Composite Structure

PubMed Central

Ren, Yuanqiang; Qiu, Lei; Yuan, Shenfang; Bao, Qiao

2017-01-01

Structural health monitoring (SHM) of aircraft composite structure is helpful to increase reliability and reduce maintenance costs. Due to the great effectiveness in distinguishing particular guided wave modes and identifying the propagation direction, the spatial-wavenumber filter technique has emerged as an interesting SHM topic. In this paper, a new scanning spatial-wavenumber filter (SSWF) based imaging method for multiple damages is proposed to conduct on-line monitoring of aircraft composite structures. Firstly, an on-line multi-damage SSWF is established, including the fundamental principle of SSWF for multiple damages based on a linear piezoelectric (PZT) sensor array, and a corresponding wavenumber-time imaging mechanism by using the multi-damage scattering signal. Secondly, through combining the on-line multi-damage SSWF and a PZT 2D cross-shaped array, an image-mapping method is proposed to conduct wavenumber synthesis and convert the two wavenumber-time images obtained by the PZT 2D cross-shaped array to an angle-distance image, from which the multiple damages can be directly recognized and located. In the experimental validation, both simulated multi-damage and real multi-damage introduced by repeated impacts are performed on a composite plate structure. The maximum localization error is less than 2 cm, which shows good performance of the multi-damage imaging method. Compared with the existing spatial-wavenumber filter based damage evaluation methods, the proposed method requires no more than the multi-damage scattering signal and can be performed without depending on any wavenumber modeling or measuring. Besides, this method locates multiple damages by imaging instead of the geometric method, which helps to improve the signal-to-noise ratio. Thus, it can be easily applied to on-line multi-damage monitoring of aircraft composite structures. PMID:28772879

Noise Suppression Based on Multi-Model Compositions Using Multi-Pass Search with Multi-Label N-gram Models

NASA Astrophysics Data System (ADS)

Jitsuhiro, Takatoshi; Toriyama, Tomoji; Kogure, Kiyoshi

We propose a noise suppression method based on multi-model compositions and multi-pass search. In real environments, input speech for speech recognition includes many kinds of noise signals. To obtain good recognized candidates, suppressing many kinds of noise signals at once and finding target speech is important. Before noise suppression, to find speech and noise label sequences, we introduce multi-pass search with acoustic models including many kinds of noise models and their compositions, their n-gram models, and their lexicon. Noise suppression is frame-synchronously performed using the multiple models selected by recognized label sequences with time alignments. We evaluated this method using the E-Nightingale task, which contains voice memoranda spoken by nurses during actual work at hospitals. The proposed method obtained higher performance than the conventional method.

The eyes have it: Using eye tracking to inform information processing strategies in multi-attributes choices.

PubMed

Ryan, Mandy; Krucien, Nicolas; Hermens, Frouke

2018-04-01

Although choice experiments (CEs) are widely applied in economics to study choice behaviour, understanding of how individuals process attribute information remains limited. We show how eye-tracking methods can provide insight into how decisions are made. Participants completed a CE, while their eye movements were recorded. Results show that although the information presented guided participants' decisions, there were also several processing biases at work. Evidence was found of (a) top-to-bottom, (b) left-to-right, and (c) first-to-last order biases. Experimental factors-whether attributes are defined as "best" or "worst," choice task complexity, and attribute ordering-also influence information processing. How individuals visually process attribute information was shown to be related to their choices. Implications for the design and analysis of CEs and future research are discussed. Copyright © 2017 John Wiley & Sons, Ltd.

Visualization and analysis of flow structures in an open cavity

NASA Astrophysics Data System (ADS)

Liu, Jun; Cai, Jinsheng; Yang, Dangguo; Wu, Junqiang; Wang, Xiansheng

2018-05-01

A numerical study is performed on the supersonic flow over an open cavity at Mach number of 1.5. A newly developed visualization method is employed to visualize the complicated flow structures, which provide an insight into major flow physics. Four types of shock/compressive waves which existed in experimental schlieren are observed in numerical visualization results. Furthermore, other flow structures such as multi-scale vortices are also obtained in the numerical results. And a new type of shocklet which is beneath large vortices is found. The shocklet beneath the vortex originates from leading edge, then, is strengthened by successive interactions between feedback compressive waves and its attached vortex. Finally, it collides against the trailing surface and generates a large number of feedback compressive waves and intensive pressure fluctuations. It is suggested that the shocklets beneath vortex play an important role of cavity self-sustained oscillation.

Aging, training, and the brain: A review and future directions

PubMed Central

Lustig, Cindy; Shah, Priti; Seidler, Rachael; Reuter-Lorenz, Patricia A.

2010-01-01

As the population ages, the need for effective methods to maintain or even improve older adults’ cognitive performance becomes increasingly pressing. Here we provide a brief review of the major intervention approaches that have been the focus of past research with healthy older adults (strategy training, multi-modal interventions, cardiovascular exercise, and process-based training), and new approaches that incorporate neuroimaging. As outcome measures, neuroimaging data on intervention-related changes in volume, structural integrity, and functional activation can provide important insights into the nature and duration of an intervention's effects. Perhaps even more intriguingly, several recent studies have used neuroimaging data as a guide to identify core cognitive processes that can be trained in one task with effective transfer to other tasks that share the same underlying processes. Although many open questions remain, this research has greatly increased our understanding of how to promote successful aging of cognition and the brain. PMID:19876740

Mediating Effects of Working Memory in the Relation Between Rapid Automatized Naming and Chinese Reading Comprehension.

PubMed

Weng, Xiaoqian; Li, Guangze; Li, Rongbao

2016-08-01

This study examined the mediating role of working memory (WM) in the relation between rapid automatized naming (RAN) and Chinese reading comprehension. Three tasks assessing differentially visual and verbal components of WM were programmed by E-prime 2.0. Data collected from 55 Chinese college students were analyzed using correlations and hierarchical regression methods to determine the connection among RAN, reading comprehension, and WM components. Results showed that WM played a significant mediating role in the RAN-reading relation and that auditory WM made stronger contributions than visual WM. Taking into account of the multi-component nature of WM and the specificity of Chinese reading processing, this study discussed the mediating powers of the WM components, particularly auditory WM, further clarifying the possible components involved in the RAN-reading relation and thus providing some insight into the complicated Chinese reading process.

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

Meyers, D.; Liu, Jian; Freeland, J. W.

We observed complex materials in electronic phases and transitions between them often involve coupling between many degrees of freedom whose entanglement convolutes understanding of the instigating mechanism. Metal-insulator transitions are one such problem where coupling to the structural, orbital, charge, and magnetic order parameters frequently obscures the underlying physics. We demonstrate a way to unravel this conundrum by heterostructuring a prototypical multi-ordered complex oxide NdNiO3 in ultra thin geometry, which preserves the metal-to-insulator transition and bulk-like magnetic order parameter, but entirely suppresses the symmetry lowering and long-range charge order parameter. Furthermore, these findings illustrate the utility of heterointerfaces as amore » powerful method for removing competing order parameters to gain greater insight into the nature of the transition, here revealing that the magnetic order generates the transition independently, leading to an exceptionally rare purely electronic metal-insulator transition with no symmetry change.« less

Computer simulations of phase field drops on super-hydrophobic surfaces

NASA Astrophysics Data System (ADS)

Fedeli, Livio

2017-09-01

We present a novel quasi-Newton continuation procedure that efficiently solves the system of nonlinear equations arising from the discretization of a phase field model for wetting phenomena. We perform a comparative numerical analysis that shows the improved speed of convergence gained with respect to other numerical schemes. Moreover, we discuss the conditions that, on a theoretical level, guarantee the convergence of this method. At each iterative step, a suitable continuation procedure develops and passes to the nonlinear solver an accurate initial guess. Discretization performs through cell-centered finite differences. The resulting system of equations is solved on a composite grid that uses dynamic mesh refinement and multi-grid techniques. The final code achieves three-dimensional, realistic computer experiments comparable to those produced in laboratory settings. This code offers not only new insights into the phenomenology of super-hydrophobicity, but also serves as a reliable predictive tool for the study of hydrophobic surfaces.

Dynamic labelling of neural connections in multiple colours by trans-synaptic fluorescence complementation

PubMed Central

Macpherson, Lindsey J.; Zaharieva, Emanuela E.; Kearney, Patrick J.; Alpert, Michael H.; Lin, Tzu-Yang; Turan, Zeynep; Lee, Chi-Hon; Gallio, Marco

2015-01-01

Determining the pattern of activity of individual connections within a neural circuit could provide insights into the computational processes that underlie brain function. Here, we develop new strategies to label active synapses by trans-synaptic fluorescence complementation in Drosophila. First, we demonstrate that a synaptobrevin-GRASP chimera functions as a powerful activity-dependent marker for synapses in vivo. Next, we create cyan and yellow variants, achieving activity-dependent, multi-colour fluorescence reconstitution across synapses (X-RASP). Our system allows for the first time retrospective labelling of synapses (rather than whole neurons) based on their activity, in multiple colours, in the same animal. As individual synapses often act as computational units in the brain, our method will promote the design of experiments that are not possible using existing techniques. Moreover, our strategies are easily adaptable to circuit mapping in any genetic system. PMID:26635273

Development of borderline personality disorder in adolescence and young adulthood: introduction to the special section.

PubMed

Stepp, Stephanie D

2012-01-01

Recognizable symptoms and features of borderline personality disorder (BPD) appear during adolescence. However, there has been resistance to diagnose or research this disorder prior to adulthood because of clinical lore that BPD is a long-standing illness and that personality traits are not stable until adulthood. This has resulted in little information regarding the development of and risk factors for BPD in youth. The goal of this special section is to examine the development of BPD in adolescence and young adulthood using a broad collection of approaches, including a theoretical review paper, two prospective studies, and a multi-method cross-sectional study. This body of work provides new insights into vulnerabilities that may transact with early attachment relationships and experiences to predict the emergence of BPD in adolescence and young adulthood. These papers also point to future research that is needed to better understand the etiology, development, and course of BPD.

Cesium and Strontium Retentions Governed by Aluminosilicate Gel in Alkali-Activated Cements

PubMed Central

Jang, Jeong Gook; Park, Sol Moi; Lee, Haeng Ki

2017-01-01

The present study investigates the retention mechanisms of cesium and strontium for alkali-activated cements. Retention mechanisms such as adsorption and precipitation were examined in light of chemical interactions. Batch adsorption experiments and multi-technical characterizations by using X-ray diffraction, zeta potential measurements, and the N2 gas adsorption/desorption methods were conducted for this purpose. Strontium was found to crystalize in alkali-activated cements, while no cesium-bearing crystalline phases were detected. The adsorption kinetics of alkali-activated cements having relatively high adsorption capacities were compatible with pseudo-second-order kinetic model, thereby suggesting that it is governed by complex multistep adsorption. The results provide new insight, demonstrating that characteristics of aluminosilicate gel with a highly negatively charged surface and high micropore surface area facilitated more effective immobilization of cesium and strontium in comparison with calcium silicate hydrates. PMID:28772803

Insights into the hierarchical structure and digestion rate of alkali-modulated starches with different amylose contents.

PubMed

Qiao, Dongling; Yu, Long; Liu, Hongsheng; Zou, Wei; Xie, Fengwei; Simon, George; Petinakis, Eustathios; Shen, Zhiqi; Chen, Ling

2016-06-25

Combined analytical techniques were used to explore the effects of alkali treatment on the multi-scale structure and digestion behavior of starches with different amylose/amylopectin ratios. Alkali treatment disrupted the amorphous matrix, and partial lamellae and crystallites, which weakened starch molecular packing and eventually enhanced the susceptibility of starch to alkali. Stronger alkali treatment (0.5% w/w) made this effect more prominent and even transformed the dual-phase digestion of starch into a triple-phase pattern. Compared with high-amylose starch, regular maize starch, which possesses some unique structure characteristics typically as pores and crystallite weak points, showed evident changes of hierarchical structure and in digestion rate. Thus, alkali treatment has been demonstrated as a simple method to modulate starch hierarchical structure and thus to realize the rational development of starch-based food products with desired digestibility. Copyright © 2016 Elsevier Ltd. All rights reserved.

Simplification of femtosecond transient absorption microscopy data from CH3NH3PbI3 perovskite thin films into decay associated amplitude maps

NASA Astrophysics Data System (ADS)

Doughty, Benjamin; Simpson, Mary Jane; Yang, Bin; Xiao, Kai; Ma, Ying-Zhong

2016-03-01

This work aims to simplify multi-dimensional femtosecond transient absorption microscopy (TAM) data into decay associated amplitude maps (DAAMs) that describe the spatial distributions of dynamical processes occurring on various characteristic timescales. Application of this method to TAM data obtained from a model methyl-ammonium lead iodide (CH3NH3PbI3) perovskite thin film allows us to simplify the data set comprising 68 time-resolved images into four DAAMs. These maps offer a simple means to visualize the complex electronic excited-state dynamics in this system by separating distinct dynamical processes evolving on characteristic timescales into individual spatial images. This approach provides new insight into subtle aspects of ultrafast relaxation dynamics associated with excitons and charge carriers in the perovskite thin film, which have recently been found to coexist at spatially distinct locations.

TCA precipitation and ethanol/HCl single-step purification evaluation: One-dimensional gel electrophoresis, bradford assays, spectrofluorometry and Raman spectroscopy data on HSA, Rnase, lysozyme - Mascots and Skyline data.

PubMed

Eddhif, Balkis; Guignard, Nadia; Batonneau, Yann; Clarhaut, Jonathan; Papot, Sébastien; Geffroy-Rodier, Claude; Poinot, Pauline

2018-04-01

The data presented here are related to the research paper entitled "Study of a Novel Agent for TCA Precipitated Proteins Washing - Comprehensive Insights into the Role of Ethanol/HCl on Molten Globule State by Multi-Spectroscopic Analyses" (Eddhif et al., submitted for publication) [1]. The suitability of ethanol/HCl for the washing of TCA-precipitated proteins was first investigated on standard solution of HSA, cellulase, ribonuclease and lysozyme. Recoveries were assessed by one-dimensional gel electrophoresis, Bradford assays and UPLC-HRMS. The mechanistic that triggers protein conformational changes at each purification stage was then investigated by Raman spectroscopy and spectrofluorometry. Finally, the efficiency of the method was evaluated on three different complex samples (mouse liver, river biofilm, loamy soil surface). Proteins profiling was assessed by gel electrophoresis and by UPLC-HRMS.

Physiology, anatomy, and plasticity of the cerebral cortex in relation to musical instrument performance

NASA Astrophysics Data System (ADS)

Tramo, Mark Jude

2004-05-01

The acquisition and maintenance of fine-motor skills underlying musical instrument performance rely on the development, integration, and plasticity of neural systems localized within specific subregions of the cerebral cortex. Cortical representations of a motor sequence, such as a sequence of finger movements along the keys of a saxophone, take shape before the figure sequence occurs. The temporal pattern and spatial coordinates are computed by networks of neurons before and during the movements. When a finger sequence is practiced over and over, performance gets faster and more accurate, probably because cortical neurons generating the sequence increase in spatial extent, their electrical discharges become more synchronous, or both. By combining experimental methods such as single- and multi-neuron recordings, focal stimulation, microanatomical tracers, gross morphometry, evoked potentials, and functional imaging in humans and nonhuman primates, neuroscientists are gaining insights into the cortical physiology, anatomy, and plasticity of musical instrument performance.

Pure electronic metal-insulator transition at the interface of complex oxides

DOE PAGES

Meyers, D.; Liu, Jian; Freeland, J. W.; ...

2016-06-21

We observed complex materials in electronic phases and transitions between them often involve coupling between many degrees of freedom whose entanglement convolutes understanding of the instigating mechanism. Metal-insulator transitions are one such problem where coupling to the structural, orbital, charge, and magnetic order parameters frequently obscures the underlying physics. We demonstrate a way to unravel this conundrum by heterostructuring a prototypical multi-ordered complex oxide NdNiO3 in ultra thin geometry, which preserves the metal-to-insulator transition and bulk-like magnetic order parameter, but entirely suppresses the symmetry lowering and long-range charge order parameter. Furthermore, these findings illustrate the utility of heterointerfaces as amore » powerful method for removing competing order parameters to gain greater insight into the nature of the transition, here revealing that the magnetic order generates the transition independently, leading to an exceptionally rare purely electronic metal-insulator transition with no symmetry change.« less

Educative Experiences of Rural Junior High History Fair Participants Seeking and Evaluating Online Primary Sources

ERIC Educational Resources Information Center

Johnson, Riley Todd

2012-01-01

This phenomenological ethnographic multi-case study's purpose was to gain insight into experiences of rural junior high History Fair participants as they searched for and evaluated online primary sources. Drawing on the theories of Dewey and Kuhlthau, the study examined how the participants searched the Internet, what strategies they used to…

Historic fire regimes of eastern Great Basin (USA) mountains reconstructed from tree rings

Treesearch

Stanley G. Kitchen

2010-01-01

Management of natural landscapes requires knowledge of key disturbance processes and their effects. Fire and forest histories provide valuable insight into how fire and vegetation varied and interacted in the past. I constructed multi-century fire chronologies for 10 sites on six mountain ranges representative of the eastern Great Basin (USA), a region in which...

Creativity in Early and Established Career: Insights into Multi-Level Drivers from Nobel Prize Winners

ERIC Educational Resources Information Center

Eubanks, Dawn L.; Palanski, Michael E.; Swart, Juani; Hammond, Michelle M.; Oguntebi, Joy

2016-01-01

The freedom to try new things plays a vital role for employees engaging in creative endeavors. This freedom can be influenced by one's relationship with her supervisor, relationship with her team, and various work pressures. One of the first steps to reaching creative output is to have a playful attitude toward work where there is encouragement…

First Large-Scale Proteogenomic Study of Breast Cancer Provides Insight into Potential Therapeutic Targets | Office of Cancer Clinical Proteomics Research

Cancer.gov

News Release: May 25, 2016 — Building on data from The Cancer Genome Atlas (TCGA) project, a multi-institutional team of scientists has completed the first large-scale “proteogenomic” study of breast cancer, linking DNA mutations to protein signaling and helping pinpoint the genes that drive cancer.

Exercise Attenuates the Major Hallmarks of Aging

PubMed Central

Garatachea, Nuria; Pareja-Galeano, Helios; Santos-Lozano, Alejandro; Fiuza-Luces, Carmen; Morán, María; Emanuele, Enzo; Joyner, Michael J.; Lucia, Alejandro

2015-01-01

Abstract Regular exercise has multi-system anti-aging effects. Here we summarize how exercise impacts the major hallmarks of aging. We propose that, besides searching for novel pharmaceutical targets of the aging process, more research efforts should be devoted to gaining insights into the molecular mediators of the benefits of exercise and to implement effective exercise interventions for elderly people. PMID:25431878

An Investigation of Western Australian Pre-Service Primary Teachers' Experiences and Self-Efficacy in the Arts

ERIC Educational Resources Information Center

Lummis, Geoff W.; Morris, Julia; Paolino, Annamaria

2014-01-01

The arts are crucial in developing our multi-sensory interpretation of culture. With the introduction of the Australian National Curriculum in the arts, there is cause to reflect on teacher education courses, and pre-service teachers' ability to deliver the new curriculum. Reflection on students' experiences in the arts may provide insight into…

Connecting Satellite-Based Precipitation Estimates to Users

NASA Technical Reports Server (NTRS)

Huffman, George J.; Bolvin, David T.; Nelkin, Eric

2018-01-01

Beginning in 1997, the Merged Precipitation Group at NASA Goddard has distributed gridded global precipitation products built by combining satellite and surface gauge data. This started with the Global Precipitation Climatology Project (GPCP), then the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), and recently the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG). This 20+-year (and on-going) activity has yielded an important set of insights and lessons learned for making state-of-the-art precipitation data accessible to the diverse communities of users. Merged-data products critically depend on the input sensors and the retrieval algorithms providing accurate, reliable estimates, but it is also important to provide ancillary information that helps users determine suitability for their application. We typically provide fields of estimated random error, and recently reintroduced the quality index concept at user request. Also at user request we have added a (diagnostic) field of estimated precipitation phase. Over time, increasingly more ancillary fields have been introduced for intermediate products that give expert users insight into the detailed performance of the combination algorithm, such as individual merged microwave and microwave-calibrated infrared estimates, the contributing microwave sensor types, and the relative influence of the infrared estimate.

The Reconstruction Toolkit (RTK), an open-source cone-beam CT reconstruction toolkit based on the Insight Toolkit (ITK)

NASA Astrophysics Data System (ADS)

Rit, S.; Vila Oliva, M.; Brousmiche, S.; Labarbe, R.; Sarrut, D.; Sharp, G. C.

2014-03-01

We propose the Reconstruction Toolkit (RTK, http://www.openrtk.org), an open-source toolkit for fast cone-beam CT reconstruction, based on the Insight Toolkit (ITK) and using GPU code extracted from Plastimatch. RTK is developed by an open consortium (see affiliations) under the non-contaminating Apache 2.0 license. The quality of the platform is daily checked with regression tests in partnership with Kitware, the company supporting ITK. Several features are already available: Elekta, Varian and IBA inputs, multi-threaded Feldkamp-David-Kress reconstruction on CPU and GPU, Parker short scan weighting, multi-threaded CPU and GPU forward projectors, etc. Each feature is either accessible through command line tools or C++ classes that can be included in independent software. A MIDAS community has been opened to share CatPhan datasets of several vendors (Elekta, Varian and IBA). RTK will be used in the upcoming cone-beam CT scanner developed by IBA for proton therapy rooms. Many features are under development: new input format support, iterative reconstruction, hybrid Monte Carlo / deterministic CBCT simulation, etc. RTK has been built to freely share tomographic reconstruction developments between researchers and is open for new contributions.

Interactive natural language acquisition in a multi-modal recurrent neural architecture

NASA Astrophysics Data System (ADS)

Heinrich, Stefan; Wermter, Stefan

2018-01-01

For the complex human brain that enables us to communicate in natural language, we gathered good understandings of principles underlying language acquisition and processing, knowledge about sociocultural conditions, and insights into activity patterns in the brain. However, we were not yet able to understand the behavioural and mechanistic characteristics for natural language and how mechanisms in the brain allow to acquire and process language. In bridging the insights from behavioural psychology and neuroscience, the goal of this paper is to contribute a computational understanding of appropriate characteristics that favour language acquisition. Accordingly, we provide concepts and refinements in cognitive modelling regarding principles and mechanisms in the brain and propose a neurocognitively plausible model for embodied language acquisition from real-world interaction of a humanoid robot with its environment. In particular, the architecture consists of a continuous time recurrent neural network, where parts have different leakage characteristics and thus operate on multiple timescales for every modality and the association of the higher level nodes of all modalities into cell assemblies. The model is capable of learning language production grounded in both, temporal dynamic somatosensation and vision, and features hierarchical concept abstraction, concept decomposition, multi-modal integration, and self-organisation of latent representations.

The pearl oyster Pinctada fucata martensii genome and multi-omic analyses provide insights into biomineralization

PubMed Central

Fan, Guangyi; Jiao, Yu; Zhang, He; Huang, Ronglian; Zheng, Zhe; Bian, Chao; Deng, Yuewen; Wang, Qingheng; Wang, Zhongduo; Liang, Xinming; Liang, Haiying; Shi, Chengcheng; Zhao, Xiaoxia; Sun, Fengming; Hao, Ruijuan; Bai, Jie; Liu, Jialiang; Chen, Wenbin; Liang, Jinlian; Liu, Weiqing; Xu, Zhe; Shi, Qiong; Xu, Xun

2017-01-01

Abstract Nacre, the iridescent material found in pearls and shells of molluscs, is formed through an extraordinary process of matrix-assisted biomineralization. Despite recent advances, many aspects of the biomineralization process and its evolutionary origin remain unknown. The pearl oyster Pinctada fucata martensii is a well-known master of biomineralization, but the molecular mechanisms that underlie its production of shells and pearls are not fully understood. We sequenced the highly polymorphic genome of the pearl oyster and conducted multi-omic and biochemical studies to probe nacre formation. We identified a large set of novel proteins participating in matrix-framework formation, many in expanded families, including components similar to that found in vertebrate bones such as collagen-related VWA-containing proteins, chondroitin sulfotransferases, and regulatory elements. Considering that there are only collagen-based matrices in vertebrate bones and chitin-based matrices in most invertebrate skeletons, the presence of both chitin and elements of collagen-based matrices in nacre suggests that elements of chitin- and collagen-based matrices have deep roots and might be part of an ancient biomineralizing matrix. Our results expand the current shell matrix-framework model and provide new insights into the evolution of diverse biomineralization systems. PMID:28873964

Neural Substrate of Group Mental Health: Insights from Multi-Brain Reference Frame in Functional Neuroimaging.

PubMed

Ray, Dipanjan; Roy, Dipanjan; Sindhu, Brahmdeep; Sharan, Pratap; Banerjee, Arpan

2017-01-01

Contemporary mental health practice primarily centers around the neurobiological and psychological processes at the individual level. However, a more careful consideration of interpersonal and other group-level attributes (e.g., interpersonal relationship, mutual trust/hostility, interdependence, and cooperation) and a better grasp of their pathology can add a crucial dimension to our understanding of mental health problems. A few recent studies have delved into the interpersonal behavioral processes in the context of different psychiatric abnormalities. Neuroimaging can supplement these approaches by providing insight into the neurobiology of interpersonal functioning. Keeping this view in mind, we discuss a recently developed approach in functional neuroimaging that calls for a shift from a focus on neural information contained within brain space to a multi-brain framework exploring degree of similarity/dissimilarity of neural signals between multiple interacting brains. We hypothesize novel applications of quantitative neuroimaging markers like inter-subject correlation that might be able to evaluate the role of interpersonal attributes affecting an individual or a group. Empirical evidences of the usage of these markers in understanding the neurobiology of social interactions are provided to argue for their application in future mental health research.

Neural Substrate of Group Mental Health: Insights from Multi-Brain Reference Frame in Functional Neuroimaging

PubMed Central

Ray, Dipanjan; Roy, Dipanjan; Sindhu, Brahmdeep; Sharan, Pratap; Banerjee, Arpan

2017-01-01

Contemporary mental health practice primarily centers around the neurobiological and psychological processes at the individual level. However, a more careful consideration of interpersonal and other group-level attributes (e.g., interpersonal relationship, mutual trust/hostility, interdependence, and cooperation) and a better grasp of their pathology can add a crucial dimension to our understanding of mental health problems. A few recent studies have delved into the interpersonal behavioral processes in the context of different psychiatric abnormalities. Neuroimaging can supplement these approaches by providing insight into the neurobiology of interpersonal functioning. Keeping this view in mind, we discuss a recently developed approach in functional neuroimaging that calls for a shift from a focus on neural information contained within brain space to a multi-brain framework exploring degree of similarity/dissimilarity of neural signals between multiple interacting brains. We hypothesize novel applications of quantitative neuroimaging markers like inter-subject correlation that might be able to evaluate the role of interpersonal attributes affecting an individual or a group. Empirical evidences of the usage of these markers in understanding the neurobiology of social interactions are provided to argue for their application in future mental health research. PMID:29033866

Multi-Domain Transfer Learning for Early Diagnosis of Alzheimer's Disease.

PubMed

Cheng, Bo; Liu, Mingxia; Shen, Dinggang; Li, Zuoyong; Zhang, Daoqiang

2017-04-01

Recently, transfer learning has been successfully applied in early diagnosis of Alzheimer's Disease (AD) based on multi-domain data. However, most of existing methods only use data from a single auxiliary domain, and thus cannot utilize the intrinsic useful correlation information from multiple domains. Accordingly, in this paper, we consider the joint learning of tasks in multi-auxiliary domains and the target domain, and propose a novel Multi-Domain Transfer Learning (MDTL) framework for early diagnosis of AD. Specifically, the proposed MDTL framework consists of two key components: 1) a multi-domain transfer feature selection (MDTFS) model that selects the most informative feature subset from multi-domain data, and 2) a multi-domain transfer classification (MDTC) model that can identify disease status for early AD detection. We evaluate our method on 807 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database using baseline magnetic resonance imaging (MRI) data. The experimental results show that the proposed MDTL method can effectively utilize multi-auxiliary domain data for improving the learning performance in the target domain, compared with several state-of-the-art methods.

NUMERICAL METHODS FOR SOLVING THE MULTI-TERM TIME-FRACTIONAL WAVE-DIFFUSION EQUATION.

PubMed

Liu, F; Meerschaert, M M; McGough, R J; Zhuang, P; Liu, Q

2013-03-01

In this paper, the multi-term time-fractional wave-diffusion equations are considered. The multi-term time fractional derivatives are defined in the Caputo sense, whose orders belong to the intervals [0,1], [1,2), [0,2), [0,3), [2,3) and [2,4), respectively. Some computationally effective numerical methods are proposed for simulating the multi-term time-fractional wave-diffusion equations. The numerical results demonstrate the effectiveness of theoretical analysis. These methods and techniques can also be extended to other kinds of the multi-term fractional time-space models with fractional Laplacian.

NUMERICAL METHODS FOR SOLVING THE MULTI-TERM TIME-FRACTIONAL WAVE-DIFFUSION EQUATION

PubMed Central

Liu, F.; Meerschaert, M.M.; McGough, R.J.; Zhuang, P.; Liu, Q.

2013-01-01

In this paper, the multi-term time-fractional wave-diffusion equations are considered. The multi-term time fractional derivatives are defined in the Caputo sense, whose orders belong to the intervals [0,1], [1,2), [0,2), [0,3), [2,3) and [2,4), respectively. Some computationally effective numerical methods are proposed for simulating the multi-term time-fractional wave-diffusion equations. The numerical results demonstrate the effectiveness of theoretical analysis. These methods and techniques can also be extended to other kinds of the multi-term fractional time-space models with fractional Laplacian. PMID:23772179

Categorical prototyping: incorporating molecular mechanisms into 3D printing.

PubMed

Brommer, Dieter B; Giesa, Tristan; Spivak, David I; Buehler, Markus J

2016-01-15

We apply the mathematical framework of category theory to articulate the precise relation between the structure and mechanics of a nanoscale system in a macroscopic domain. We maintain the chosen molecular mechanical properties from the nanoscale to the continuum scale. Therein we demonstrate a procedure to 'protoype a model', as category theory enables us to maintain certain information across disparate fields of study, distinct scales, or physical realizations. This process fits naturally with prototyping, as a prototype is not a complete product but rather a reduction to test a subset of properties. To illustrate this point, we use large-scale multi-material printing to examine the scaling of the elastic modulus of 2D carbon allotropes at the macroscale and validate our printed model using experimental testing. The resulting hand-held materials can be examined more readily, and yield insights beyond those available in the original digital representations. We demonstrate this concept by twisting the material, a test beyond the scope of the original model. The method developed can be extended to other methods of additive manufacturing.

Uncovered secret of a Vasseur-Tramond wax model.

PubMed

Pastor, J F; Gutiérrez, B; Montes, J M; Ballestriero, R

2016-01-01

The technique of anatomical wax modelling reached its heyday in Italy during the 18th century, through a fruitful collaboration between sculptors and anatomists. It soon spread to other countries, and prestigious schools were created in England, France, Spain and Austria. Paris subsequently replaced Italy as the major centre of manufacture, and anatomical waxes were created there from the mid-19th century in workshops such as that of Vasseur-Tramond. This workshop began to sell waxes to European Faculties of Medicine and Schools of Surgery around 1880. Little is known of the technique employed in the creation of such artefacts as this was deemed a professional secret. To gain some insight into the methods of construction, we have studied a Vasseur-Tramond wax model in the Valladolid University Anatomy Museum, Spain, by means of multi-slice computerised tomography and X-ray analysis by means of environmental scanning electron microscopy. Scanning electron microscopy was used to examine the hair. These results have revealed some of the methods used to make these anatomical models and the materials employed. © 2015 Anatomical Society.

Health promotion and sustainability programmes in Australia: barriers and enablers to evaluation.

PubMed

Patrick, Rebecca; Kingsley, Jonathan

2017-08-01

In an era characterised by the adverse impacts of climate change and environmental degradation, health promotion programmes are beginning to actively link human health with environmental sustainability imperatives. This paper draws on a study of health promotion and sustainability programmes in Australia, providing insights to evaluation approaches being used and barriers and enablers to these evaluations. The study was based on a multi-strategy research involving both quantitative and qualitative methods. Health promotion practitioners explained through surveys and semi-structured interviews that they focused on five overarching health and sustainability programme types (healthy and sustainable food, active transport, energy efficiency, contact with nature, and capacity building). Various evaluation methods and indicators (health, social, environmental, economic and demographic) were identified as being valuable for monitoring and evaluating health and sustainability programmes. Findings identified several evaluation enablers such as successful community engagement, knowledge of health and sustainability issues and programme champions, whereas barriers included resource constraints and competing interests. This paper highlights the need for ecological models and evaluation tools to support the design and monitoring of health promotion and sustainability programmes.

A New Self-Consistent Field Model of Polymer/Nanoparticle Mixture

NASA Astrophysics Data System (ADS)

Chen, Kang; Li, Hui-Shu; Zhang, Bo-Kai; Li, Jian; Tian, Wen-De

2016-02-01

Field-theoretical method is efficient in predicting assembling structures of polymeric systems. However, it’s challenging to generalize this method to study the polymer/nanoparticle mixture due to its multi-scale nature. Here, we develop a new field-based model which unifies the nanoparticle description with the polymer field within the self-consistent field theory. Instead of being “ensemble-averaged” continuous distribution, the particle density in the final morphology can represent individual particles located at preferred positions. The discreteness of particle density allows our model to properly address the polymer-particle interface and the excluded-volume interaction. We use this model to study the simplest system of nanoparticles immersed in the dense homopolymer solution. The flexibility of tuning the interfacial details allows our model to capture the rich phenomena such as bridging aggregation and depletion attraction. Insights are obtained on the enthalpic and/or entropic origin of the structural variation due to the competition between depletion and interfacial interaction. This approach is readily extendable to the study of more complex polymer-based nanocomposites or biology-related systems, such as dendrimer/drug encapsulation and membrane/particle assembly.

Binding interaction of atorvastatin with bovine serum albumin: Spectroscopic methods and molecular docking

NASA Astrophysics Data System (ADS)

Wang, Qi; Huang, Chuan-ren; Jiang, Min; Zhu, Ying-yao; Wang, Jing; Chen, Jun; Shi, Jie-hua

2016-03-01

The interaction of atorvastatin with bovine serum albumin (BSA) was investigated using multi-spectroscopic methods and molecular docking technique for providing important insight into further elucidating the store and transport process of atorvastatin in the body and the mechanism of action and pharmacokinetics. The experimental results revealed that the fluorescence quenching mechanism of BSA induced atorvastatin was a combined dynamic and static quenching. The binding constant and number of binding site of atorvastatin with BSA under simulated physiological conditions (pH = 7.4) were 1.41 × 105 M- 1 and about 1 at 310 K, respectively. The values of the enthalpic change (ΔH0), entropic change (ΔS0) and Gibbs free energy (ΔG0) in the binding process of atorvastatin with BSA at 310 K were negative, suggesting that the binding process of atorvastatin and BSA was spontaneous and the main interaction forces were van der Waals force and hydrogen bonding interaction. Moreover, atorvastatin was bound into the subdomain IIA (site I) of BSA, resulting in a slight change of the conformation of BSA.

Asymmetric flow field-flow fractionation (AF4) for the quantification of nanoparticle release from tablets during dissolution testing.

PubMed

Engel, A; Plöger, M; Mulac, D; Langer, K

2014-01-30

Nanoparticles composed of poly(DL-lactide-co-glycolide) (PLGA) represent promising colloidal drug carriers for improved drug targeting. Although most research activities are focused on intravenous application of these carriers the peroral administration is described to improve bioavailability of poorly soluble drugs. Based on these insights the manuscript describes a model tablet formulation for PLGA-nanoparticles and especially its analytical characterisation with regard to a nanosized drug carrier. Besides physico-chemical tablet characterisation according to pharmacopoeias the main goal of the study was the development of a suitable analytical method for the quantification of nanoparticle release from tablets. An analytical flow field-flow fractionation (AF4) method was established and validated which enables determination of nanoparticle content in solid dosage forms as well as quantification of particle release during dissolution testing. For particle detection a multi-angle light scattering (MALS) detector was coupled to the AF4-system. After dissolution testing, the presence of unaltered PLGA-nanoparticles was successfully proved by dynamic light scattering and scanning electron microscopy. Copyright © 2013 Elsevier B.V. All rights reserved.

The Expanding Diversity of Mycobacterium tuberculosis Drug Targets.

PubMed

Wellington, Samantha; Hung, Deborah T

2018-05-11

After decades of relative inactivity, a large increase in efforts to discover antitubercular therapeutics has brought insights into the biology of Mycobacterium tuberculosis (Mtb) and promising new drugs such as bedaquiline, which inhibits ATP synthase, and the nitroimidazoles delamanid and pretomanid, which inhibit both mycolic acid synthesis and energy production. Despite these advances, the drug discovery pipeline remains underpopulated. The field desperately needs compounds with novel mechanisms of action capable of inhibiting multi- and extensively drug -resistant Mtb (M/XDR-TB) and, potentially, nonreplicating Mtb with the hope of shortening the duration of required therapy. New knowledge about Mtb, along with new methods and technologies, has driven exploration into novel target areas, such as energy production and central metabolism, that diverge from the classical targets in macromolecular synthesis. Here, we review new small molecule drug candidates that act on these novel targets to highlight the methods and perspectives advancing the field. These new targets bring with them the aspiration of shortening treatment duration as well as a pipeline of effective regimens against XDR-TB, positioning Mtb drug discovery to become a model for anti-infective discovery.

The multi-layer multi-configuration time-dependent Hartree method for bosons: theory, implementation, and applications.

PubMed

Cao, Lushuai; Krönke, Sven; Vendrell, Oriol; Schmelcher, Peter

2013-10-07

We develop the multi-layer multi-configuration time-dependent Hartree method for bosons (ML-MCTDHB), a variational numerically exact ab initio method for studying the quantum dynamics and stationary properties of general bosonic systems. ML-MCTDHB takes advantage of the permutation symmetry of identical bosons, which allows for investigations of the quantum dynamics from few to many-body systems. Moreover, the multi-layer feature enables ML-MCTDHB to describe mixed bosonic systems consisting of arbitrary many species. Multi-dimensional as well as mixed-dimensional systems can be accurately and efficiently simulated via the multi-layer expansion scheme. We provide a detailed account of the underlying theory and the corresponding implementation. We also demonstrate the superior performance by applying the method to the tunneling dynamics of bosonic ensembles in a one-dimensional double well potential, where a single-species bosonic ensemble of various correlation strengths and a weakly interacting two-species bosonic ensemble are considered.

Forecast horizon of multi-item dynamic lot size model with perishable inventory.

PubMed

Jing, Fuying; Lan, Zirui

2017-01-01

This paper studies a multi-item dynamic lot size problem for perishable products where stock deterioration rates and inventory costs are age-dependent. We explore structural properties in an optimal solution under two cost structures and develop a dynamic programming algorithm to solve the problem in polynomial time when the number of products is fixed. We establish forecast horizon results that can help the operation manager to decide the precise forecast horizon in a rolling decision-making process. Finally, based on a detailed test bed of instance, we obtain useful managerial insights on the impact of deterioration rate and lifetime of products on the length of forecast horizon.

Direct writing of tunable multi-wavelength polymer lasers on a flexible substrate.

PubMed

Zhai, Tianrui; Wang, Yonglu; Chen, Li; Zhang, Xinping

2015-08-07

Tunable multi-wavelength polymer lasers based on two-dimensional distributed feedback structures are fabricated on a transparent flexible substrate using interference ablation. A scalene triangular lattice structure was designed to support stable tri-wavelength lasing emission and was achieved through multiple exposure processes. Three wavelengths were controlled by three periods of the compound cavity. Mode competition among different cavity modes was observed by changing the pump fluence. Both a redshift and blueshift of the laser wavelength could be achieved by bending the soft substrate. These results not only provide insight into the physical mechanisms behind co-cavity polymer lasers but also introduce new laser sources and laser designs for white light lasers.

Forecast horizon of multi-item dynamic lot size model with perishable inventory

PubMed Central

Jing, Fuying

2017-01-01

This paper studies a multi-item dynamic lot size problem for perishable products where stock deterioration rates and inventory costs are age-dependent. We explore structural properties in an optimal solution under two cost structures and develop a dynamic programming algorithm to solve the problem in polynomial time when the number of products is fixed. We establish forecast horizon results that can help the operation manager to decide the precise forecast horizon in a rolling decision-making process. Finally, based on a detailed test bed of instance, we obtain useful managerial insights on the impact of deterioration rate and lifetime of products on the length of forecast horizon. PMID:29125856

Bridging simulations and experiment in shock and ramp induced phenomena

NASA Astrophysics Data System (ADS)

Flicker, Dawn

2014-03-01

The high pressure materials physics program at Sandia's Z facility includes strong collaboration between theory, simulations and experiments. This multi-disciplinary approach has led to new insights in many cases. Several examples will be discussed to illustrate the benefits of bridging simulations and experiments. Results will be chosen from recent work on the xenon equation of state, phase change in MgO, shock induced chemistry in CO2 and tantalum strength. Sandia National Laboratories is a multi-program laboratory operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Measurement of in situ sulfur isotopes by laser ablation multi-collector ICPMS: opening Pandora’s Box

USGS Publications Warehouse

Ridley, William I.; Pribil, Michael; Koenig, Alan E.; Slack, John F.

2015-01-01

Laser ablation multi-collector ICPMS is a modern tool for in situ measurement of S isotopes. Advantages of the technique are speed of analysis and relatively minor matrix effects combined with spatial resolution sufficient for many applications. The main disadvantage is a more destructive sampling mechanism relative to the ion microprobe technique. Recent advances in instrumentation allow precise measurement with spatial resolutions down to 25 microns. We describe specific examples from economic geology where increased spatial resolution has greatly expanded insights into the sources and evolution of fluids that cause mineralization and illuminated genetic relations between individual deposits in single mineral districts.

A MIMO radar quadrature and multi-channel amplitude-phase error combined correction method based on cross-correlation

NASA Astrophysics Data System (ADS)

Yun, Lingtong; Zhao, Hongzhong; Du, Mengyuan

2018-04-01

Quadrature and multi-channel amplitude-phase error have to be compensated in the I/Q quadrature sampling and signal through multi-channel. A new method that it doesn't need filter and standard signal is presented in this paper. And it can combined estimate quadrature and multi-channel amplitude-phase error. The method uses cross-correlation and amplitude ratio between the signal to estimate the two amplitude-phase errors simply and effectively. And the advantages of this method are verified by computer simulation. Finally, the superiority of the method is also verified by measure data of outfield experiments.

Advantages of a multi-state approach in surgical research: how intermediate events and risk factor profile affect the prognosis of a patient with locally advanced rectal cancer.

PubMed

Manzini, G; Ettrich, T J; Kremer, M; Kornmann, M; Henne-Bruns, D; Eikema, D A; Schlattmann, P; de Wreede, L C

2018-02-13

Standard survival analysis fails to give insight into what happens to a patient after a first outcome event (like first relapse of a disease). Multi-state models are a useful tool for analyzing survival data when different treatments and results (intermediate events) can occur. Aim of this study was to implement a multi-state model on data of patients with rectal cancer to illustrate the advantages of multi-state analysis in comparison to standard survival analysis. We re-analyzed data from the RCT FOGT-2 study by using a multi-state model. Based on the results we defined a high and low risk reference patient. Using dynamic prediction, we estimated how the survival probability changes as more information about the clinical history of the patient becomes available. A patient with stage UICC IIIc (vs UICC II) has a higher risk to develop distant metastasis (DM) or both DM and local recurrence (LR) if he/she discontinues chemotherapy within 6 months or between 6 and 12 months, as well as after the completion of 12 months CTx with HR 3.55 (p = 0.026), 5.33 (p = 0.001) and 3.37 (p < 0.001), respectively. He/she also has a higher risk to die after the development of DM (HR 1.72, p = 0.023). Anterior resection vs. abdominoperineal amputation means 63% risk reduction to develop DM or both DM and LR (HR 0.37, p = 0.003) after discontinuation of chemotherapy between 6 and 12 months. After development of LR, a woman has a 4.62 times higher risk to die (p = 0.006). A high risk reference patient has an estimated 43% 5-year survival probability at start of CTx, whereas for a low risk patient this is 79%. After the development of DM 1 year later, the high risk patient has an estimated 5-year survival probability of 11% and the low risk patient one of 21%. Multi-state models help to gain additional insight into the complex events after start of treatment. Dynamic prediction shows how survival probabilities change by progression of the clinical history.

White-Nose Syndrome Disease Severity and a Comparison of Diagnostic Methods.

PubMed

McGuire, Liam P; Turner, James M; Warnecke, Lisa; McGregor, Glenna; Bollinger, Trent K; Misra, Vikram; Foster, Jeffrey T; Frick, Winifred F; Kilpatrick, A Marm; Willis, Craig K R

2016-03-01

White-nose syndrome is caused by the fungus Pseudogymnoascus destructans and has killed millions of hibernating bats in North America but the pathophysiology of the disease remains poorly understood. Our objectives were to (1) assess non-destructive diagnostic methods for P. destructans infection compared to histopathology, the current gold-standard, and (2) to evaluate potential metrics of disease severity. We used data from three captive inoculation experiments involving 181 little brown bats (Myotis lucifugus) to compare histopathology, quantitative PCR (qPCR), and ultraviolet fluorescence as diagnostic methods of P. destructans infection. To assess disease severity, we considered two histology metrics (wing area with fungal hyphae, area of dermal necrosis), P. destructans fungal load (qPCR), ultraviolet fluorescence, and blood chemistry (hematocrit, sodium, glucose, pCO2, and bicarbonate). Quantitative PCR was most effective for early detection of P. destructans, while all three methods were comparable in severe infections. Correlations among hyphae and necrosis scores, qPCR, ultraviolet fluorescence, blood chemistry, and hibernation duration indicate a multi-stage pattern of disease. Disruptions of homeostasis occurred rapidly in late hibernation. Our results provide valuable information about the use of non-destructive techniques for monitoring, and provide novel insight into the pathophysiology of white-nose syndrome, with implications for developing and implementing potential mitigation strategies.

Strategies to Support Recruitment of Patients with Life-limiting illness for Research: The Palliative Care Research Cooperative Group

PubMed Central

Hanson, Laura C.; Bull, Janet; Wessell, Kathryn; Massie, Lisa; Bennett, Rachael E.; Kutner, Jean S.; Aziz, Noreen M.; Abernethy, Amy

2014-01-01

Context The Palliative Care Research Cooperative group (PCRC) is the first clinical trials cooperative for palliative care in the United States. Objectives To describe barriers and strategies for recruitment during the inaugural PCRC clinical trial. Methods The parent study was a multi-site randomized controlled trial enrolling adults with life expectancy anticipated to be 1–6 months, randomized to discontinue statins (intervention) vs. to continue on statins (control). To study recruitment best practices, we conducted semi-structured interviews with 18 site Principal Investigators (PI) and Clinical Research Coordinators (CRC), and reviewed recruitment rates. Interviews covered 3 topics – 1) successful strategies for recruitment, 2) barriers to recruitment, and 3) optimal roles of the PI and CRC. Results All eligible site PIs and CRCs completed interviews and provided data on statin protocol recruitment. The parent study completed recruitment of n=381 patients. Site enrollment ranged from 1–109 participants, with an average of 25 enrolled per site. Five major barriers included difficulty locating eligible patients, severity of illness, family and provider protectiveness, seeking patients in multiple settings, and lack of resources for recruitment activities. Five effective recruitment strategies included systematic screening of patient lists, thoughtful messaging to make research relevant, flexible protocols to accommodate patients’ needs, support from clinical champions, and the additional resources of a trials cooperative group. Conclusion The recruitment experience from the multi-site PCRC yields new insights into methods for effective recruitment to palliative care clinical trials. These results will inform training materials for the PCRC and may assist other investigators in the field. PMID:24863152

What can artefact analysis tell us about patient transitions between the hospital and primary care? Lessons from the HANDOVER project.

PubMed

Johnson, Julie K; Arora, Vineet M; Barach, Paul R

2013-09-01

Hospital discharge often faces breakdowns in information, communication, and coordination. The European Union FP7 Health Research Programme commissioned the European HANDOVER Project in 2008, a three year, 3.5 million Euro programme to examine transitions of patient care from the hospital to the community care settings. Six European countries--Italy, the Netherlands, Poland, United Kingdom, Spain, and Sweden--participated in this collaborative study. This paper highlights a multi-centre, multi-national research programme. We describe how HANDOVER participants conducted an 'artefact analysis' as one element of the mixed methods study to inform opportunities to make patient handovers between hospital and community care more effective. The artefact analysis consisted of a four-step process to assess different tools used in communication and treatment and their effects on the communication processes between the hospital and general practice settings. Four themes emerged from our analysis: (a) The inpatient care of a patient is 'hospital centric' whereby the hospital 'pulls' information regarding a patient's family physician (b) There are rich cognitive artefacts that support the patient clinician encounter; c) The use of information technology does not necessarily improve the communication process; and (d) There is a role for the patient, albeit not particularly well-defined or explicit, as a conduit for essential information communication. Cognitive artefact analysis is an innovative method to provide insights into transitions of patient care. It may be most useful to think about interventions at both the individual patient and the system levels that more fully address and overcome the system issues at work.

Curricular initiatives that enhance student knowledge and perceptions of sexual and gender minority groups: a critical interpretive synthesis

PubMed Central

Desrosiers, Jennifer; Wilkinson, Tim; Abel, Gillian; Pitama, Suzanne

2016-01-01

Background There is no accepted best practice for optimizing tertiary student knowledge, perceptions, and skills to care for sexual and gender diverse groups. The objective of this research was to synthesize the relevant literature regarding effective curricular initiatives designed to enhance tertiary level student knowledge, perceptions, and skills to care for sexual and gender diverse populations. Methods A modified Critical Interpretive Synthesis using a systematic search strategy was conducted in 2015. This method was chosen to synthesize the relevant qualitative and quantitative literature as it allows for the depth and breadth of information to be captured and new constructs to be illuminated. Databases searched include AMED, CINAHL EBM Reviews, ERIC, Ovid MEDLINE, Ovid Nursing Database, PsychInfo, and Google Scholar. Results Thirty-one articles were included in this review. Curricular initiatives ranging from discrete to multimodal approaches have been implemented. Successful initiatives included discrete sessions with time for processing, and multi-modal strategies. Multi-modal approaches that encouraged awareness of one’s lens and privilege in conjunction with facilitated communication seemed the most effective. Conclusions The literature is limited to the evaluation of explicit curricula. The wider cultural competence literature offers further insight by highlighting the importance of broad and embedded forces including social influences, the institutional climate, and the implicit, or hidden, curriculum. A combined interpretation of the complementary cultural competence and sexual and gender diversity literature provides a novel understanding of the optimal content and context for the delivery of a successful curricular initiative. PMID:28344699

Summarising climate and air quality (ozone) data on self-organising maps: a Sydney case study.

PubMed

Jiang, Ningbo; Betts, Alan; Riley, Matt

2016-02-01

This paper explores the classification and visualisation utility of the self-organising map (SOM) method in the context of New South Wales (NSW), Australia, using gridded NCEP/NCAR geopotential height reanalysis for east Australia, together with multi-site meteorological and air quality data for Sydney from the NSW Office of Environment and Heritage Air Quality Monitoring Network. A twice-daily synoptic classification has been derived for east Australia for the period of 1958-2012. The classification has not only reproduced the typical synoptic patterns previously identified in the literature but also provided an opportunity to visualise the subtle, non-linear change in the eastward-migrating synoptic systems influencing NSW (including Sydney). The summarisation of long-term, multi-site air quality/meteorological data from the Sydney basin on the SOM plane has identified a set of typical air pollution/meteorological spatial patterns in the region. Importantly, the examination of these patterns in relation to synoptic weather types has provided important visual insights into how local and synoptic meteorological conditions interact with each other and affect the variability of air quality in tandem. The study illustrates that while synoptic circulation types are influential, the within-type variability in mesoscale flows plays a critical role in determining local ozone levels in Sydney. These results indicate that the SOM can be a useful tool for assessing the impact of weather and climatic conditions on air quality in the regional airshed. This study further promotes the use of the SOM method in environmental research.

Multi-parametric centrality method for graph network models

NASA Astrophysics Data System (ADS)

Ivanov, Sergei Evgenievich; Gorlushkina, Natalia Nikolaevna; Ivanova, Lubov Nikolaevna

2018-04-01

The graph model networks are investigated to determine centrality, weights and the significance of vertices. For centrality analysis appliesa typical method that includesany one of the properties of graph vertices. In graph theory, methods of analyzing centrality are used: in terms by degree, closeness, betweenness, radiality, eccentricity, page-rank, status, Katz and eigenvector. We have proposed a new method of multi-parametric centrality, which includes a number of basic properties of the network member. The mathematical model of multi-parametric centrality method is developed. Comparison of results for the presented method with the centrality methods is carried out. For evaluate the results for the multi-parametric centrality methodthe graph model with hundreds of vertices is analyzed. The comparative analysis showed the accuracy of presented method, includes simultaneously a number of basic properties of vertices.

Retrofit of a MultiFamily Mass Masonry Building in New England

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

Ueno, K.; Kerrigan, P.; Wytrykowska, H.

2013-08-01

Merrimack Valley Habitat for Humanity (MVHfH) has partnered with Building Science Corporation to provide high performance affordable housing for 10 families in the retrofit of an existing brick building (a former convent) into condominiums. The research performed for this project provides information regarding advanced retrofit packages for multi-family masonry buildings in Cold climates. In particular, this project demonstrates safe, durable, and cost-effective solutions that will potentially benefit millions of multi-family brick buildings throughout the East Coast and Midwest (Cold climates). The retrofit packages provide insight on the opportunities for and constraints on retrofitting multifamily buildings with ambitious energy performance goalsmore » but a limited budget. The condominium conversion project will contribute to several areas of research on enclosures, space conditioning, and water heating. Enclosure items include insulation of mass masonry building on the interior, airtightness of these types of retrofits, multi-unit building compartmentalization, window selection, and roof insulation strategies. Mechanical system items include combined hydronic and space heating systems with hydronic distribution in small (low load) units, and ventilation system retrofits for multifamily buildings.« less

Failures of metacognition and lack of insight in neuropsychiatric disorders

PubMed Central

David, Anthony S.; Bedford, Nicholas; Wiffen, Ben; Gilleen, James

2012-01-01

Lack of insight or unawareness of illness are the hallmarks of many psychiatric disorders, especially schizophrenia (SCZ) and other psychoses and could be conceived of as a failure in metacognition. Research in this area in the mental health field h as burgeoned with the development and widespread use of standard assessment instruments and the mapping out of the clinical and neuropsychological correlates of insight and its loss. There has been a growing appreciation of the multi-faceted nature of the concept and of the different ‘objects’ of insight, such as the general awareness that one is ill, to more specific metacognitive awareness of individual symptoms, impairments and performance. This in turn has led to the notion that insight may show modularity and may fractionate across different domains and disorders, supported by work that directly compares metacognition of memory deficits and illness awareness in patients with SCZ, Alzheimer's disease and brain injury. The focus of this paper will be on the varieties of metacognitive failure in psychiatry, particularly the psychoses. We explore cognitive models based on self-reflectiveness and their possible social and neurological bases, including data from structural and functional MRI. The medial frontal cortex appears to play an important role in self-appraisal in health and disease. PMID:22492754

Model Based Optimal Control, Estimation, and Validation of Lithium-Ion Batteries

NASA Astrophysics Data System (ADS)

Perez, Hector Eduardo

This dissertation focuses on developing and experimentally validating model based control techniques to enhance the operation of lithium ion batteries, safely. An overview of the contributions to address the challenges that arise are provided below. Chapter 1: This chapter provides an introduction to battery fundamentals, models, and control and estimation techniques. Additionally, it provides motivation for the contributions of this dissertation. Chapter 2: This chapter examines reference governor (RG) methods for satisfying state constraints in Li-ion batteries. Mathematically, these constraints are formulated from a first principles electrochemical model. Consequently, the constraints explicitly model specific degradation mechanisms, such as lithium plating, lithium depletion, and overheating. This contrasts with the present paradigm of limiting measured voltage, current, and/or temperature. The critical challenges, however, are that (i) the electrochemical states evolve according to a system of nonlinear partial differential equations, and (ii) the states are not physically measurable. Assuming available state and parameter estimates, this chapter develops RGs for electrochemical battery models. The results demonstrate how electrochemical model state information can be utilized to ensure safe operation, while simultaneously enhancing energy capacity, power, and charge speeds in Li-ion batteries. Chapter 3: Complex multi-partial differential equation (PDE) electrochemical battery models are characterized by parameters that are often difficult to measure or identify. This parametric uncertainty influences the state estimates of electrochemical model-based observers for applications such as state-of-charge (SOC) estimation. This chapter develops two sensitivity-based interval observers that map bounded parameter uncertainty to state estimation intervals, within the context of electrochemical PDE models and SOC estimation. Theoretically, this chapter extends the notion of interval observers to PDE models using a sensitivity-based approach. Practically, this chapter quantifies the sensitivity of battery state estimates to parameter variations, enabling robust battery management schemes. The effectiveness of the proposed sensitivity-based interval observers is verified via a numerical study for the range of uncertain parameters. Chapter 4: This chapter seeks to derive insight on battery charging control using electrochemistry models. Directly using full order complex multi-partial differential equation (PDE) electrochemical battery models is difficult and sometimes impossible to implement. This chapter develops an approach for obtaining optimal charge control schemes, while ensuring safety through constraint satisfaction. An optimal charge control problem is mathematically formulated via a coupled reduced order electrochemical-thermal model which conserves key electrochemical and thermal state information. The Legendre-Gauss-Radau (LGR) pseudo-spectral method with adaptive multi-mesh-interval collocation is employed to solve the resulting nonlinear multi-state optimal control problem. Minimum time charge protocols are analyzed in detail subject to solid and electrolyte phase concentration constraints, as well as temperature constraints. The optimization scheme is examined using different input current bounds, and an insight on battery design for fast charging is provided. Experimental results are provided to compare the tradeoffs between an electrochemical-thermal model based optimal charge protocol and a traditional charge protocol. Chapter 5: Fast and safe charging protocols are crucial for enhancing the practicality of batteries, especially for mobile applications such as smartphones and electric vehicles. This chapter proposes an innovative approach to devising optimally health-conscious fast-safe charge protocols. A multi-objective optimal control problem is mathematically formulated via a coupled electro-thermal-aging battery model, where electrical and aging sub-models depend upon the core temperature captured by a two-state thermal sub-model. The Legendre-Gauss-Radau (LGR) pseudo-spectral method with adaptive multi-mesh-interval collocation is employed to solve the resulting highly nonlinear six-state optimal control problem. Charge time and health degradation are therefore optimally traded off, subject to both electrical and thermal constraints. Minimum-time, minimum-aging, and balanced charge scenarios are examined in detail. Sensitivities to the upper voltage bound, ambient temperature, and cooling convection resistance are investigated as well. Experimental results are provided to compare the tradeoffs between a balanced and traditional charge protocol. Chapter 6: This chapter provides concluding remarks on the findings of this dissertation and a discussion of future work.

Multi-off-grid methods in multi-step integration of ordinary differential equations

NASA Technical Reports Server (NTRS)

Beaudet, P. R.

1974-01-01

Description of methods of solving first- and second-order systems of differential equations in which all derivatives are evaluated at off-grid locations in order to circumvent the Dahlquist stability limitation on the order of on-grid methods. The proposed multi-off-grid methods require off-grid state predictors for the evaluation of the n derivatives at each step. Progressing forward in time, the off-grid states are predicted using a linear combination of back on-grid state values and off-grid derivative evaluations. A comparison is made between the proposed multi-off-grid methods and the corresponding Adams and Cowell on-grid integration techniques in integrating systems of ordinary differential equations, showing a significant reduction in the error at larger step sizes in the case of the multi-off-grid integrator.

Initial insights on the performances and management of dairy cattle herds combining two breeds with contrasting features.

PubMed

Magne, M A; Thénard, V; Mihout, S

2016-05-01

Finding ways of increasing animal production with low external inputs and without compromising reproductive performances is a key issue of livestock systems sustainability. One way is to take advantage of the diversity and interactions among components within livestock systems. Among studies that investigate the influence of differences in animals' individual abilities in a herd, few focus on combinations of cow breeds with contrasting features in dairy cattle herds. This study aimed to analyse the performances and management of such multi-breed dairy cattle herds. These herds were composed of two types of dairy breeds: 'specialist' (Holstein) and 'generalist' (e.g. Montbeliarde, Simmental, etc.). Based on recorded milk data in southern French region, we performed (i) to compare the performances of dairy herds according to breed-type composition: multi-breed, single specialist breed or single generalist breed and (ii) to test the difference of milk performances of specialist and generalist breed cows (n = 10 682) per multi-breed dairy herd within a sample of 22 farms. The sampled farmers were also interviewed to characterise herd management through multivariate analysis. Multi-breed dairy herds had a better trade-off among milk yield, milk fat and protein contents, herd reproduction and concentrate-conversion efficiency than single-breed herds. Conversely, they did not offer advantages in terms of milk prices and udder health. Compared to specialist dairy herds, they produce less milk with the same concentrate-conversion efficiency but have better reproductive performances. Compared to generalist dairy herds, they produce more milk with better concentrate-conversion efficiency but have worse reproductive performances. Within herds, specialist and generalist breed cows significantly differed in milk performances, showing their complementarity. The former produced more milk for a longer lactation length while the latter produced milk with higher protein and fat contents and had a slightly longer lactation rank. Our results also focus on the farmers' management of multi-breed dairy herds underlying herd performances. Three strategies of management were identified and structured along two main axes. The first differentiates farmers according to their animal-selection practices in relation with their objectives of production: adapting animal to produce milk with low-feeding inputs v. focussing on milk yield trait to intensify milk production. The second refers to the purpose farmers give to multi-breed dairy herds: milk v. milk/meat production. These initial insights on the performances and management of multi-breed dairy herds contribute to better understanding the functioning of ruminant livestock systems based on individual variability.

A novel method for 3D measurement of RFID multi-tag network based on matching vision and wavelet

NASA Astrophysics Data System (ADS)

Zhuang, Xiao; Yu, Xiaolei; Zhao, Zhimin; Wang, Donghua; Zhang, Wenjie; Liu, Zhenlu; Lu, Dongsheng; Dong, Dingbang

2018-07-01

In the field of radio frequency identification (RFID), the three-dimensional (3D) distribution of RFID multi-tag networks has a significant impact on their reading performance. At the same time, in order to realize the anti-collision of RFID multi-tag networks in practical engineering applications, the 3D distribution of RFID multi-tag networks must be measured. In this paper, a novel method for the 3D measurement of RFID multi-tag networks is proposed. A dual-CCD system (vertical and horizontal cameras) is used to obtain images of RFID multi-tag networks from different angles. Then, the wavelet threshold denoising method is used to remove noise in the obtained images. The template matching method is used to determine the two-dimensional coordinates and vertical coordinate of each tag. The 3D coordinates of each tag are obtained subsequently. Finally, a model of the nonlinear relation between the 3D coordinate distribution of the RFID multi-tag network and the corresponding reading distance is established using the wavelet neural network. The experiment results show that the average prediction relative error is 0.71% and the time cost is 2.17 s. The values of the average prediction relative error and time cost are smaller than those of the particle swarm optimization neural network and genetic algorithm–back propagation neural network. The time cost of the wavelet neural network is about 1% of that of the other two methods. The method proposed in this paper has a smaller relative error. The proposed method can improve the real-time performance of RFID multi-tag networks and the overall dynamic performance of multi-tag networks.

Aircraft Conflict Analysis and Real-Time Conflict Probing Using Probabilistic Trajectory Modeling

NASA Technical Reports Server (NTRS)

Yang, Lee C.; Kuchar, James K.

2000-01-01

Methods for maintaining separation between aircraft in the current airspace system have been built from a foundation of structured routes and evolved procedures. However, as the airspace becomes more congested and the chance of failures or operational error become more problematic, automated conflict alerting systems have been proposed to help provide decision support and to serve as traffic monitoring aids. The problem of conflict detection and resolution has been tackled from a number of different ways, but in this thesis, it is recast as a problem of prediction in the presence of uncertainties. Much of the focus is concentrated on the errors and uncertainties from the working trajectory model used to estimate future aircraft positions. The more accurate the prediction, the more likely an ideal (no false alarms, no missed detections) alerting system can be designed. Additional insights into the problem were brought forth by a review of current operational and developmental approaches found in the literature. An iterative, trial and error approach to threshold design was identified. When examined from a probabilistic perspective, the threshold parameters were found to be a surrogate to probabilistic performance measures. To overcome the limitations in the current iterative design method, a new direct approach is presented where the performance measures are directly computed and used to perform the alerting decisions. The methodology is shown to handle complex encounter situations (3-D, multi-aircraft, multi-intent, with uncertainties) with relative ease. Utilizing a Monte Carlo approach, a method was devised to perform the probabilistic computations in near realtime. Not only does this greatly increase the method's potential as an analytical tool, but it also opens up the possibility for use as a real-time conflict alerting probe. A prototype alerting logic was developed and has been utilized in several NASA Ames Research Center experimental studies.

New methods for indexing multi-lattice diffraction data

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

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

2014-10-01

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

Multiple network alignment via multiMAGNA+.

PubMed

Vijayan, Vipin; Milenkovic, Tijana

2017-08-21

Network alignment (NA) aims to find a node mapping that identifies topologically or functionally similar network regions between molecular networks of different species. Analogous to genomic sequence alignment, NA can be used to transfer biological knowledge from well- to poorly-studied species between aligned network regions. Pairwise NA (PNA) finds similar regions between two networks while multiple NA (MNA) can align more than two networks. We focus on MNA. Existing MNA methods aim to maximize total similarity over all aligned nodes (node conservation). Then, they evaluate alignment quality by measuring the amount of conserved edges, but only after the alignment is constructed. Directly optimizing edge conservation during alignment construction in addition to node conservation may result in superior alignments. Thus, we present a novel MNA method called multiMAGNA++ that can achieve this. Indeed, multiMAGNA++ outperforms or is on par with existing MNA methods, while often completing faster than existing methods. That is, multiMAGNA++ scales well to larger network data and can be parallelized effectively. During method evaluation, we also introduce new MNA quality measures to allow for more fair MNA method comparison compared to the existing alignment quality measures. MultiMAGNA++ code is available on the method's web page at http://nd.edu/~cone/multiMAGNA++/.

Multi-Model Ensemble Wake Vortex Prediction

NASA Technical Reports Server (NTRS)

Koerner, Stephan; Holzaepfel, Frank; Ahmad, Nash'at N.

2015-01-01

Several multi-model ensemble methods are investigated for predicting wake vortex transport and decay. This study is a joint effort between National Aeronautics and Space Administration and Deutsches Zentrum fuer Luft- und Raumfahrt to develop a multi-model ensemble capability using their wake models. An overview of different multi-model ensemble methods and their feasibility for wake applications is presented. The methods include Reliability Ensemble Averaging, Bayesian Model Averaging, and Monte Carlo Simulations. The methodologies are evaluated using data from wake vortex field experiments.

Spanning maternal, newborn and child health (MNCH) and health systems research boundaries: conducive and limiting health systems factors to improving MNCH outcomes in West Africa.

PubMed

Agyepong, Irene Akua; Kwamie, Aku; Frimpong, Edith; Defor, Selina; Ibrahim, Abdallah; Aryeetey, Genevieve C; Lokossou, Virgil; Sombie, Issiaka

2017-07-12

Despite improvements over time, West Africa lags behind global as well as sub-Saharan averages in its maternal, newborn and child health (MNCH) outcomes. This is despite the availability of an increasing body of knowledge on interventions that improve such outcomes. Beyond our knowledge of what interventions work, insights are needed on others factors that facilitate or inhibit MNCH outcome improvement. This study aimed to explore health system factors conducive or limiting to MNCH policy and programme implementation and outcomes in West Africa, and how and why they work in context. We conducted a mixed methods multi-country case study focusing predominantly, but not exclusively, on the six West African countries (Burkina Faso, Benin, Mali, Senegal, Nigeria and Ghana) of the Innovating for Maternal and Child Health in Africa initiative. Data collection involved non-exhaustive review of grey and published literature, and 48 key informant interviews. We validated our findings and conclusions at two separate multi-stakeholder meetings organised by the West African Health Organization. To guide our data collection and analysis, we developed a unique theoretical framework of the link between health systems and MNCH, in which we conceptualised health systems as the foundations, pillars and roofing of a shelter for MNCH, and context as the ground on which the foundation is laid. A multitude of MNCH policies and interventions were being piloted, researched or implemented at scale in the sub-region, most of which faced multiple interacting conducive and limiting health system factors to effective implementation, as well as contextual challenges. Context acted through its effect on health system factors as well as on the social determinants of health. To accelerate and sustain improvements in MNCH outcomes in West Africa, an integrated approach to research and practice of simultaneously addressing health systems and contextual factors alongside MNCH service delivery interventions is needed. This requires multi-level, multi-sectoral and multi-stakeholder engagement approaches that span current geographical, language, research and practice community boundaries in West Africa, and effectively link the efforts of actors interested in health systems strengthening with those of actors interested in MNCH outcome improvement.

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.

Estimation of canopy carotenoid content of winter wheat using multi-angle hyperspectral data

NASA Astrophysics Data System (ADS)

Kong, Weiping; Huang, Wenjiang; Liu, Jiangui; Chen, Pengfei; Qin, Qiming; Ye, Huichun; Peng, Dailiang; Dong, Yingying; Mortimer, A. Hugh

2017-11-01

Precise estimation of carotenoid (Car) content in crops, using remote sensing data, could be helpful for agricultural resources management. Conventional methods for Car content estimation were mostly based on reflectance data acquired from nadir direction. However, reflectance acquired at this direction is highly influenced by canopy structure and soil background reflectance. Off-nadir observation is less impacted, and multi-angle viewing data are proven to contain additional information rarely exploited for crop Car content estimation. The objective of this study was to explore the potential of multi-angle observation data for winter wheat canopy Car content estimation. Canopy spectral reflectance was measured from nadir as well as from a series of off-nadir directions during different growing stages of winter wheat, with concurrent canopy Car content measurements. Correlation analyses were performed between Car content and the original and continuum removed spectral reflectance. Spectral features and previously published indices were derived from data obtained at different viewing angles and were tested for Car content estimation. Results showed that spectral features and indices obtained from backscattering directions between 20° and 40° view zenith angle had a stronger correlation with Car content than that from the nadir direction, and the strongest correlation was observed from about 30° backscattering direction. Spectral absorption depth at 500 nm derived from spectral data obtained from 30° backscattering direction was found to reduce the difference induced by plant cultivars greatly. It was the most suitable for winter wheat canopy Car estimation, with a coefficient of determination 0.79 and a root mean square error of 19.03 mg/m2. This work indicates the importance of taking viewing geometry effect into account when using spectral features/indices and provides new insight in the application of multi-angle remote sensing for the estimation of crop physiology.

Application of Multi-Model CMIP5 Analysis in Future Drought Adaptation Strategies

NASA Astrophysics Data System (ADS)

Casey, M.; Luo, L.; Lang, Y.

2014-12-01

Drought influences the efficacy of numerous natural and artificial systems including species diversity, agriculture, and infrastructure. Global climate change raises concerns that extend well beyond atmospheric and hydrological disciplines - as climate changes with time, the need for system adaptation becomes apparent. Drought, as a natural phenomenon, is typically defined relative to the climate in which it occurs. Typically a 30-year reference time frame (RTF) is used to determine the severity of a drought event. This study investigates the projected future droughts over North America with different RTFs. Confidence in future hydroclimate projection is characterized by the agreement of long term (2005-2100) multi-model precipitation (P) and temperature (T) projections within the Coupled model Intercomparison Project Phase 5 (CMIP5). Drought severity and the propensity of extreme conditions are measured by the multi-scalar, probabilistic, RTF-based Standard Precipitation Index (SPI) and Standard Precipitation Evapotranspiration Index (SPEI). SPI considers only P while SPEI incorporates Evapotranspiration (E) via T; comparing the two reveals the role of temperature change in future hydroclimate change. Future hydroclimate conditions, hydroclimate extremity, and CMIP5 model agreement are assessed for each Representative Concentration Pathway (RCP 2.6, 4.5, 6.0, 8.5) in regions throughout North America for the entire year and for the boreal seasons. In addition, multiple time scales of SPI and SPEI are calculated to characterize drought at time scales ranging from short to long term. The study explores a simple, standardized method for considering adaptation in future drought assessment, which provides a novel perspective to incorporate adaptation with climate change. The result of the analysis is a multi-dimension, probabilistic summary of the hydrological (P, E) environment a natural or artificial system must adapt to over time. Studies similar to this with specified criteria (SPI/SPEI value, time scale, RCP, etc.) can provide professionals in a variety of disciplines with necessary climatic insight to develop adaptation strategies.

Single Cell Force Spectroscopy for Quantification of Cellular Adhesion on Surfaces

NASA Astrophysics Data System (ADS)

Christenson, Wayne B.

Cell adhesion is an important aspect of many biological processes. The atomic force microscope (AFM) has made it possible to quantify the forces involved in cellular adhesion using a technique called single cell force spectroscopy (SCFS). AFM based SCFS offers versatile control over experimental conditions for probing directly the interaction between specific cell types and specific proteins, surfaces, or other cells. Transmembrane integrins are the primary proteins involved in cellular adhesion to the extra cellular matix (ECM). One of the chief integrins involved in the adhesion of leukocyte cells is alpha Mbeta2 (Mac-1). The experiments in this dissertation quantify the adhesion of Mac-1 expressing human embryonic kidney (HEK Mac-1), platelets, and neutrophils cells on substrates with different concentrations of fibrinogen and on fibrin gels and multi-layered fibrinogen coated fibrin gels. It was shown that multi-layered fibrinogen reduces the adhesion force of these cells considerably. A novel method was developed as part of this research combining total internal reflection microscopy (TIRFM) with SCFS allowing for optical microscopy of HEK Mac-1 cells interacting with bovine serum albumin (BSA) coated glass after interacting with multi-layered fibrinogen. HEK Mac-1 cells are able to remove fibrinogen molecules from the multi-layered fibrinogen matrix. An analysis methodology for quantifying the kinetic parameters of integrin-ligand interactions from SCFS experiments is proposed, and the kinetic parameters of the Mac-1 fibrinogen bond are quantified. Additional SCFS experiments quantify the adhesion of macrophages and HEK Mac-1 cells on functionalized glass surfaces and normal glass surfaces. Both cell types show highest adhesion on a novel functionalized glass surface that was prepared to induce macrophage fusion. These experiments demonstrate the versatility of AFM based SCFS, and how it can be applied to address many questions in cellular biology offering quantitative insights.

On Multifunctional Collaborative Methods in Engineering Science

NASA Technical Reports Server (NTRS)

Ransom, Jonathan B.

2001-01-01

Multifunctional methodologies and analysis procedures are formulated for interfacing diverse subdomain idealizations including multi-fidelity modeling methods and multi-discipline analysis methods. These methods, based on the method of weighted residuals, ensure accurate compatibility of primary and secondary variables across the subdomain interfaces. Methods are developed using diverse mathematical modeling (i.e., finite difference and finite element methods) and multi-fidelity modeling among the subdomains. Several benchmark scalar-field and vector-field problems in engineering science are presented with extensions to multidisciplinary problems. Results for all problems presented are in overall good agreement with the exact analytical solution or the reference numerical solution. Based on the results, the integrated modeling approach using the finite element method for multi-fidelity discretization among the subdomains is identified as most robust. The multiple method approach is advantageous when interfacing diverse disciplines in which each of the method's strengths are utilized.

Probabilistic Multi-Scale, Multi-Level, Multi-Disciplinary Analysis and Optimization of Engine Structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2000-01-01

Aircraft engines are assemblies of dynamically interacting components. Engine updates to keep present aircraft flying safely and engines for new aircraft are progressively required to operate in more demanding technological and environmental requirements. Designs to effectively meet those requirements are necessarily collections of multi-scale, multi-level, multi-disciplinary analysis and optimization methods and probabilistic methods are necessary to quantify respective uncertainties. These types of methods are the only ones that can formally evaluate advanced composite designs which satisfy those progressively demanding requirements while assuring minimum cost, maximum reliability and maximum durability. Recent research activities at NASA Glenn Research Center have focused on developing multi-scale, multi-level, multidisciplinary analysis and optimization methods. Multi-scale refers to formal methods which describe complex material behavior metal or composite; multi-level refers to integration of participating disciplines to describe a structural response at the scale of interest; multidisciplinary refers to open-ended for various existing and yet to be developed discipline constructs required to formally predict/describe a structural response in engine operating environments. For example, these include but are not limited to: multi-factor models for material behavior, multi-scale composite mechanics, general purpose structural analysis, progressive structural fracture for evaluating durability and integrity, noise and acoustic fatigue, emission requirements, hot fluid mechanics, heat-transfer and probabilistic simulations. Many of these, as well as others, are encompassed in an integrated computer code identified as Engine Structures Technology Benefits Estimator (EST/BEST) or Multi-faceted/Engine Structures Optimization (MP/ESTOP). The discipline modules integrated in MP/ESTOP include: engine cycle (thermodynamics), engine weights, internal fluid mechanics, cost, mission and coupled structural/thermal, various composite property simulators and probabilistic methods to evaluate uncertainty effects (scatter ranges) in all the design parameters. The objective of the proposed paper is to briefly describe a multi-faceted design analysis and optimization capability for coupled multi-discipline engine structures optimization. Results are presented for engine and aircraft type metrics to illustrate the versatility of that capability. Results are also presented for reliability, noise and fatigue to illustrate its inclusiveness. For example, replacing metal rotors with composites reduces the engine weight by 20 percent, 15 percent noise reduction, and an order of magnitude improvement in reliability. Composite designs exist to increase fatigue life by at least two orders of magnitude compared to state-of-the-art metals.

Application of separable parameter space techniques to multi-tracer PET compartment modeling

PubMed Central

Zhang, Jeff L; Morey, A Michael; Kadrmas, Dan J

2016-01-01

Multi-tracer positron emission tomography (PET) can image two or more tracers in a single scan, characterizing multiple aspects of biological functions to provide new insights into many diseases. The technique uses dynamic imaging, resulting in time-activity curves that contain contributions from each tracer present. The process of separating and recovering separate images and/or imaging measures for each tracer requires the application of kinetic constraints, which are most commonly applied by fitting parallel compartment models for all tracers. Such multi-tracer compartment modeling presents challenging nonlinear fits in multiple dimensions. This work extends separable parameter space kinetic modeling techniques, previously developed for fitting single-tracer compartment models, to fitting multi-tracer compartment models. The multi-tracer compartment model solution equations were reformulated to maximally separate the linear and nonlinear aspects of the fitting problem, and separable least-squares techniques were applied to effectively reduce the dimensionality of the nonlinear fit. The benefits of the approach are then explored through a number of illustrative examples, including characterization of separable parameter space multi-tracer objective functions and demonstration of exhaustive search fits which guarantee the true global minimum to within arbitrary search precision. Iterative gradient-descent algorithms using Levenberg–Marquardt were also tested, demonstrating improved fitting speed and robustness as compared to corresponding fits using conventional model formulations. The proposed technique overcomes many of the challenges in fitting simultaneous multi-tracer PET compartment models. PMID:26788888

Multi-Layer E-Textile Circuits

NASA Technical Reports Server (NTRS)

Dunne, Lucy E.; Bibeau, Kaila; Mulligan, Lucie; Frith, Ashton; Simon, Cory

2012-01-01

Stitched e-textile circuits facilitate wearable, flexible, comfortable wearable technology. However, while stitched methods of e-textile circuits are common, multi-layer circuit creation remains a challenge. Here, we present methods of stitched multi-layer circuit creation using accessible tools and techniques.

Investigating the effect of mental set on insight problem solving.

PubMed

Ollinger, Michael; Jones, Gary; Knoblich, Günther

2008-01-01

Mental set is the tendency to solve certain problems in a fixed way based on previous solutions to similar problems. The moment of insight occurs when a problem cannot be solved using solution methods suggested by prior experience and the problem solver suddenly realizes that the solution requires different solution methods. Mental set and insight have often been linked together and yet no attempt thus far has systematically examined the interplay between the two. Three experiments are presented that examine the extent to which sets of noninsight and insight problems affect the subsequent solutions of insight test problems. The results indicate a subtle interplay between mental set and insight: when the set involves noninsight problems, no mental set effects are shown for the insight test problems, yet when the set involves insight problems, both facilitation and inhibition can be seen depending on the type of insight problem presented in the set. A two process model is detailed to explain these findings that combines the representational change mechanism with that of proceduralization.

Multi-channel EEG-based sleep stage classification with joint collaborative representation and multiple kernel learning.

PubMed

Shi, Jun; Liu, Xiao; Li, Yan; Zhang, Qi; Li, Yingjie; Ying, Shihui

2015-10-30

Electroencephalography (EEG) based sleep staging is commonly used in clinical routine. Feature extraction and representation plays a crucial role in EEG-based automatic classification of sleep stages. Sparse representation (SR) is a state-of-the-art unsupervised feature learning method suitable for EEG feature representation. Collaborative representation (CR) is an effective data coding method used as a classifier. Here we use CR as a data representation method to learn features from the EEG signal. A joint collaboration model is established to develop a multi-view learning algorithm, and generate joint CR (JCR) codes to fuse and represent multi-channel EEG signals. A two-stage multi-view learning-based sleep staging framework is then constructed, in which JCR and joint sparse representation (JSR) algorithms first fuse and learning the feature representation from multi-channel EEG signals, respectively. Multi-view JCR and JSR features are then integrated and sleep stages recognized by a multiple kernel extreme learning machine (MK-ELM) algorithm with grid search. The proposed two-stage multi-view learning algorithm achieves superior performance for sleep staging. With a K-means clustering based dictionary, the mean classification accuracy, sensitivity and specificity are 81.10 ± 0.15%, 71.42 ± 0.66% and 94.57 ± 0.07%, respectively; while with the dictionary learned using the submodular optimization method, they are 80.29 ± 0.22%, 71.26 ± 0.78% and 94.38 ± 0.10%, respectively. The two-stage multi-view learning based sleep staging framework outperforms all other classification methods compared in this work, while JCR is superior to JSR. The proposed multi-view learning framework has the potential for sleep staging based on multi-channel or multi-modality polysomnography signals. Copyright © 2015 Elsevier B.V. All rights reserved.

'Micro-hole' optical dating of quartz from HOTRAX-05 Arctic Ocean cores

NASA Astrophysics Data System (ADS)

Berger, G. W.; Polyak, L. V.

2011-12-01

For Quaternary Arctic Ocean cores, numeric dating methods are needed spanning and exceeding the age range of the widely used radiocarbon (C-14) method. Previously, luminescence sediment dating of 4-11 μm diameter quartz and feldspar grains from core tops has often produced large burial-age overestimates (e.g., by >7 kyr) due to failure to resolve mixed-age histories. However, application of micro-focused-laser ('micro-hole') photon-stimulated-luminescence (PSL) applied to quartz grains of 11-90 μm diameters from the tops (upper 2 cm) of high-sedimentation- rate HOTRAX-05 multi-cores at the Alaska margin provides expected near zero ages (0-200 a), thus overcoming the earlier problem of large PSL age over-estimation. This micro-hole PSL dating approach has also been applied to >11 μm quartz grains from multi-cores at two sites on the central Lomonosov Ridge. For a core top within a perched basin, a burial-age estimate of ~2 ka for 11-62 μm quartz was obtained, in accord with published C-14 age estimates from foraminifera, demonstrating the efficacy of the micro-hole approach to this ridge area. At a nearby 'erosive' ridge-top site, the micro-hole PSL approach paradoxically produces two different burial-age estimates from the same core-top horizon. The >90 μm quartz grains yield a burial age of ~25 ka, in accord with a C-14 age estimate of ~26 ka from >250 μm foraminifers from the same horizon. However, the 11-90 μm quartz produces a burial-age estimate of ~9 ka, indicating a differently preserved burial history for the medium silt grains than for the sand grains within a single horizon. This unexpected result provides a unique insight into past, complicated, depositional processes on this ridge top over a time range spanning the LGM. These results from the micro-hole PSL approach thus indicate a clear potential for dating times of detrital quartz deposition at other ridge tops in the Arctic Ocean, and for providing perhaps new insights into local preservation of burial ages. These PSL procedures are being applied also to sediment above and below a diamicton in a HOTRAX-05 core from the Northwind Ridge, with the aim of dating indirectly the diamicton. Preliminary results from this core will be presented.

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

Hydrodynamic Stability Analysis of Multi-jet Effects in Swirling Jet Combustors

NASA Astrophysics Data System (ADS)

Emerson, Benjamin; Lieuwen, Tim

2016-11-01

Many practical combustion devices use multiple swirling jets to stabilize flames. However, much of the understanding of swirling jet dynamics has been generated from experimental and computational studies of single reacting, swirling jets. A smaller body of literature has begun to explore the effects of multi-jet systems and the role of jet-jet interactions on the macro-system dynamics. This work uses local temporal and spatio-temporal stability analyses to isolate the hydrodynamic interactions of multiple reacting, swirling jets, characterized by jet diameter, D, and spacing, L. The results first identify the familiar helical modes in the single jet. Comparison to the multi-jet configuration reveals these same familiar modes simultaneously oscillating in each of the jets. Jet-jet interaction is mostly limited to a spatial synchronization of each jet's oscillations at the jet spacing values analyzed here (L/D =3.5). The presence of multiple jets vs a single jet has little influence on the temporal and absolute growth rates. The biggest difference between the single and multi-jet configurations is the presence of nearly degenerate pairs of hydrodynamic modes in the multi-jet case, with one mode dominated by oscillations in the inner jet, and the other in the outer jets. The close similarity between the single and multi-jet hydrodynamics lends insight into experiments from our group.

Three-Dimensional Surface Parameters and Multi-Fractal Spectrum of Corroded Steel

PubMed Central

Shanhua, Xu; Songbo, Ren; Youde, Wang

2015-01-01

To study multi-fractal behavior of corroded steel surface, a range of fractal surfaces of corroded surfaces of Q235 steel were constructed by using the Weierstrass-Mandelbrot method under a high total accuracy. The multi-fractal spectrum of fractal surface of corroded steel was calculated to study the multi-fractal characteristics of the W-M corroded surface. Based on the shape feature of the multi-fractal spectrum of corroded steel surface, the least squares method was applied to the quadratic fitting of the multi-fractal spectrum of corroded surface. The fitting function was quantitatively analyzed to simplify the calculation of multi-fractal characteristics of corroded surface. The results showed that the multi-fractal spectrum of corroded surface was fitted well with the method using quadratic curve fitting, and the evolution rules and trends were forecasted accurately. The findings can be applied to research on the mechanisms of corroded surface formation of steel and provide a new approach for the establishment of corrosion damage constitutive models of steel. PMID:26121468

Three-Dimensional Surface Parameters and Multi-Fractal Spectrum of Corroded Steel.

PubMed

Shanhua, Xu; Songbo, Ren; Youde, Wang

2015-01-01

To study multi-fractal behavior of corroded steel surface, a range of fractal surfaces of corroded surfaces of Q235 steel were constructed by using the Weierstrass-Mandelbrot method under a high total accuracy. The multi-fractal spectrum of fractal surface of corroded steel was calculated to study the multi-fractal characteristics of the W-M corroded surface. Based on the shape feature of the multi-fractal spectrum of corroded steel surface, the least squares method was applied to the quadratic fitting of the multi-fractal spectrum of corroded surface. The fitting function was quantitatively analyzed to simplify the calculation of multi-fractal characteristics of corroded surface. The results showed that the multi-fractal spectrum of corroded surface was fitted well with the method using quadratic curve fitting, and the evolution rules and trends were forecasted accurately. The findings can be applied to research on the mechanisms of corroded surface formation of steel and provide a new approach for the establishment of corrosion damage constitutive models of steel.

multiDE: a dimension reduced model based statistical method for differential expression analysis using RNA-sequencing data with multiple treatment conditions.

PubMed

Kang, Guangliang; Du, Li; Zhang, Hong

2016-06-22

The growing complexity of biological experiment design based on high-throughput RNA sequencing (RNA-seq) is calling for more accommodative statistical tools. We focus on differential expression (DE) analysis using RNA-seq data in the presence of multiple treatment conditions. We propose a novel method, multiDE, for facilitating DE analysis using RNA-seq read count data with multiple treatment conditions. The read count is assumed to follow a log-linear model incorporating two factors (i.e., condition and gene), where an interaction term is used to quantify the association between gene and condition. The number of the degrees of freedom is reduced to one through the first order decomposition of the interaction, leading to a dramatically power improvement in testing DE genes when the number of conditions is greater than two. In our simulation situations, multiDE outperformed the benchmark methods (i.e. edgeR and DESeq2) even if the underlying model was severely misspecified, and the power gain was increasing in the number of conditions. In the application to two real datasets, multiDE identified more biologically meaningful DE genes than the benchmark methods. An R package implementing multiDE is available publicly at http://homepage.fudan.edu.cn/zhangh/softwares/multiDE . When the number of conditions is two, multiDE performs comparably with the benchmark methods. When the number of conditions is greater than two, multiDE outperforms the benchmark methods.

A fractional calculus perspective of distributed propeller design

NASA Astrophysics Data System (ADS)

Tenreiro Machado, J.; Galhano, Alexandra M.

2018-02-01

A new generation of aircraft with distributed propellers leads to operational performances superior to those exhibited by standard designs. Computational simulations and experimental tests show a reduction of fuel consumption and noise. This paper proposes an analogy between aerodynamics and electrical circuits. The model reveals properties similar to those of fractional-order systems and gives a deeper insight into the dynamics of multi-propeller coupling.

Multi-Objective Optimization for Trustworthy Tactical Networks: A Survey and Insights

DTIC Science & Technology

2013-06-01

existing data sources, gathering and maintaining the data needed , and completing and reviewing the collection of information. Send comments regarding...problems: using repeated cooperative games [12], hedonic games [25], and nontransferable utility cooperative games [27]. It should be noted that trust...examined an optimal task allocation problem in a distributed computing system where program modules need to be allocated to different processors to

Serving the Cause: Duty Concepts and Combat Effectiveness in War

DTIC Science & Technology

2010-06-01

War II.10 Like moral factors, the notion of military effectiveness is complex and multi-faceted. Murray and Millet argue that military...The insights derived from this synthesis will provide the common reference point for analysis of the historical examples. Alan Millet and...1988). 4 Allan Millet and Williamson Murray, Military Effectiveness, Vol I, 2. 9 This dynamic interaction is particularly pronounced at the

Transport Imaging of Multi-Junction and CIGS Solar Cell Materials

DTIC Science & Technology

2011-12-01

solar cells start with the material charge transport parameters, namely the charge mobility, lifetime and diffusion length . It is the goal of...every solar cell manufacturer to maintain high carrier lifetime so as to realize long diffusion lengths . Long diffusion lengths ensure that the charges...Thus, being able to accurately determine the diffusion length of any solar cell material proves advantageous by providing insights

Balancing the Values of Ethnic Studies and Academe: Exploring Efforts to Advance the Organizational Stability of American Indian and Asian American Studies

ERIC Educational Resources Information Center

Kimura-Walsh, Erin Fukiko

2009-01-01

This study examines Ethnic Studies' efforts to gain institutional stability at the university. The issue is explored through a qualitative, multi-case study of Ethnic Studies units, specifically American Indian and Asian American Studies at San Francisco State University and University of California, Los Angeles. To gain insight into their…

A Multi-Case Study of Research Using Mobile Imaging, Sensing and Tracking Technologies to Objectively Measure Behavior: Ethical Issues and Insights to Guide Responsible Research Practice

ERIC Educational Resources Information Center

Nebeker, Camille; Linares-Orozco, Rubi; Crist, Katie

2015-01-01

Introduction: The increased availability of mobile sensing technologies is creating a paradigm shift for health research by creating new opportunities for measuring and monitoring behavior. For example, researchers can now collect objective information about a participant's daily activity using wearable devices that have: 1- Global Positioning…

Self-balanced modulation and magnetic rebalancing method for parallel multilevel inverters

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

Li, Hui; Shi, Yanjun

A self-balanced modulation method and a closed-loop magnetic flux rebalancing control method for parallel multilevel inverters. The combination of the two methods provides for balancing of the magnetic flux of the inter-cell transformers (ICTs) of the parallel multilevel inverters without deteriorating the quality of the output voltage. In various embodiments a parallel multi-level inverter modulator is provide including a multi-channel comparator to generate a multiplexed digitized ideal waveform for a parallel multi-level inverter and a finite state machine (FSM) module coupled to the parallel multi-channel comparator, the FSM module to receive the multiplexed digitized ideal waveform and to generate amore » pulse width modulated gate-drive signal for each switching device of the parallel multi-level inverter. The system and method provides for optimization of the output voltage spectrum without influence the magnetic balancing.« less

Adaptive multi-view clustering based on nonnegative matrix factorization and pairwise co-regularization

NASA Astrophysics Data System (ADS)

Zhang, Tianzhen; Wang, Xiumei; Gao, Xinbo

2018-04-01

Nowadays, several datasets are demonstrated by multi-view, which usually include shared and complementary information. Multi-view clustering methods integrate the information of multi-view to obtain better clustering results. Nonnegative matrix factorization has become an essential and popular tool in clustering methods because of its interpretation. However, existing nonnegative matrix factorization based multi-view clustering algorithms do not consider the disagreement between views and neglects the fact that different views will have different contributions to the data distribution. In this paper, we propose a new multi-view clustering method, named adaptive multi-view clustering based on nonnegative matrix factorization and pairwise co-regularization. The proposed algorithm can obtain the parts-based representation of multi-view data by nonnegative matrix factorization. Then, pairwise co-regularization is used to measure the disagreement between views. There is only one parameter to auto learning the weight values according to the contribution of each view to data distribution. Experimental results show that the proposed algorithm outperforms several state-of-the-arts algorithms for multi-view clustering.

Multi-fidelity stochastic collocation method for computation of statistical moments

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

Zhu, Xueyu, E-mail: xueyu-zhu@uiowa.edu; Linebarger, Erin M., E-mail: aerinline@sci.utah.edu; Xiu, Dongbin, E-mail: xiu.16@osu.edu

We present an efficient numerical algorithm to approximate the statistical moments of stochastic problems, in the presence of models with different fidelities. The method extends the multi-fidelity approximation method developed in . By combining the efficiency of low-fidelity models and the accuracy of high-fidelity models, our method exhibits fast convergence with a limited number of high-fidelity simulations. We establish an error bound of the method and present several numerical examples to demonstrate the efficiency and applicability of the multi-fidelity algorithm.

Viscous-Inviscid Methods in Unsteady Aerodynamic Analysis of Bio-Inspired Morphing Wings

NASA Astrophysics Data System (ADS)

Dhruv, Akash V.

Flight has been one of the greatest realizations of human imagination, revolutionizing communication and transportation over the years. This has greatly influenced the growth of technology itself, enabling researchers to communicate and share their ideas more effectively, extending the human potential to create more sophisticated systems. While the end product of a sophisticated technology makes our lives easier, its development process presents an array of challenges in itself. In last decade, scientists and engineers have turned towards bio-inspiration to design more efficient and robust aerodynamic systems to enhance the ability of Unmanned Aerial Vehicles (UAVs) to be operated in cluttered environments, where tight maneuverability and controllability are necessary. Effective use of UAVs in domestic airspace will mark the beginning of a new age in communication and transportation. The design of such complex systems necessitates the need for faster and more effective tools to perform preliminary investigations in design, thereby streamlining the design process. This thesis explores the implementation of numerical panel methods for aerodynamic analysis of bio-inspired morphing wings. Numerical panel methods have been one of the earliest forms of computational methods for aerodynamic analysis to be developed. Although the early editions of this method performed only inviscid analysis, the algorithm has matured over the years as a result of contributions made by prominent aerodynamicists. The method discussed in this thesis is influenced by recent advancements in panel methods and incorporates both viscous and inviscid analysis of multi-flap wings. The surface calculation of aerodynamic coefficients makes this method less computationally expensive than traditional Computational Fluid Dynamics (CFD) solvers available, and thus is effective when both speed and accuracy are desired. The morphing wing design, which consists of sequential feather-like flaps installed over the upper and lower surfaces of a standard airfoil, proves to be an effective alternative to standard control surfaces by increasing the flight capability of bird-scale UAVs. The results obtained for this wing design under various flight and flap configurations provide insight into its aerodynamic behavior, which enhance the maneuverability and controllability. The overall method acts as an important tool to create an aerodynamic database to develop a distributed control system for autonomous operation of the multi-flap morphing wing, supporting the use of viscous-inviscid methods as a tool in rapid aerodynamic analysis.

Multi-Domain Transfer Learning for Early Diagnosis of Alzheimer’s Disease

PubMed Central

Cheng, Bo; Liu, Mingxia; Li, Zuoyong

2017-01-01

Recently, transfer learning has been successfully applied in early diagnosis of Alzheimer’s Disease (AD) based on multi-domain data. However, most of existing methods only use data from a single auxiliary domain, and thus cannot utilize the intrinsic useful correlation information from multiple domains. Accordingly, in this paper, we consider the joint learning of tasks in multi-auxiliary domains and the target domain, and propose a novel Multi-Domain Transfer Learning (MDTL) framework for early diagnosis of AD. Specifically, the proposed MDTL framework consists of two key components: 1) a multi-domain transfer feature selection (MDTFS) model that selects the most informative feature subset from multi-domain data, and 2) a multidomain transfer classification (MDTC) model that can identify disease status for early AD detection. We evaluate our method on 807 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database using baseline magnetic resonance imaging (MRI) data. The experimental results show that the proposed MDTL method can effectively utilize multi-auxiliary domain data for improving the learning performance in the target domain, compared with several state-of-the-art methods. PMID:27928657

New Insights in Tropospheric Ozone and its Variability

NASA Technical Reports Server (NTRS)

Oman, Luke D.; Douglass, Anne R.; Ziemke, Jerry R.; Rodriquez, Jose M.

2011-01-01

We have produced time-slice simulations using the Goddard Earth Observing System Version 5 (GEOS-5) coupled to a comprehensive stratospheric and tropospheric chemical mechanism. These simulations are forced with observed sea surface temperatures over the past 25 years and use constant specified surface emissions, thereby providing a measure of the dynamically controlled ozone response. We examine the model performance in simulating tropospheric ozone and its variability. Here we show targeted comparisons results from our simulations with a multi-decadal tropical tropospheric column ozone dataset obtained from satellite observations of total column ozone. We use SHADOZ ozonesondes to gain insight into the observed vertical response and compare with the simulated vertical structure. This work includes but is not limited to ENSO related variability.

Accelerated Stress Testing of Multi-Source LED Products: Horticulture Lamps and Tunable-White Modules

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

Davis, Lynn; Rountree, Kelley; Mills, Karmann

This report discusses the use of accelerated stress testing (AST) to provide insights into the long-term behavior of commercial products utilizing different types of mid-power LEDs (MP-LEDs) integrated into the same LED module. Test results are presented from two commercial lamps intended for use in horticulture applications and one tunable-white LED module intended for use in educational and office lighting applications. Each of these products is designed to provide a custom spectrum for their targeted applications and each achieves this goal in different ways. Consequently, a comparison of the long-term stability of these devices will provide insights regarding approaches thatmore » could be used to possibly lengthen the lifetime of SSL products.« less

Proceedings of the First NASA Formal Methods Symposium

NASA Technical Reports Server (NTRS)

Denney, Ewen (Editor); Giannakopoulou, Dimitra (Editor); Pasareanu, Corina S. (Editor)

2009-01-01

Topics covered include: Model Checking - My 27-Year Quest to Overcome the State Explosion Problem; Applying Formal Methods to NASA Projects: Transition from Research to Practice; TLA+: Whence, Wherefore, and Whither; Formal Methods Applications in Air Transportation; Theorem Proving in Intel Hardware Design; Building a Formal Model of a Human-Interactive System: Insights into the Integration of Formal Methods and Human Factors Engineering; Model Checking for Autonomic Systems Specified with ASSL; A Game-Theoretic Approach to Branching Time Abstract-Check-Refine Process; Software Model Checking Without Source Code; Generalized Abstract Symbolic Summaries; A Comparative Study of Randomized Constraint Solvers for Random-Symbolic Testing; Component-Oriented Behavior Extraction for Autonomic System Design; Automated Verification of Design Patterns with LePUS3; A Module Language for Typing by Contracts; From Goal-Oriented Requirements to Event-B Specifications; Introduction of Virtualization Technology to Multi-Process Model Checking; Comparing Techniques for Certified Static Analysis; Towards a Framework for Generating Tests to Satisfy Complex Code Coverage in Java Pathfinder; jFuzz: A Concolic Whitebox Fuzzer for Java; Machine-Checkable Timed CSP; Stochastic Formal Correctness of Numerical Algorithms; Deductive Verification of Cryptographic Software; Coloured Petri Net Refinement Specification and Correctness Proof with Coq; Modeling Guidelines for Code Generation in the Railway Signaling Context; Tactical Synthesis Of Efficient Global Search Algorithms; Towards Co-Engineering Communicating Autonomous Cyber-Physical Systems; and Formal Methods for Automated Diagnosis of Autosub 6000.

Joint reconstruction via coupled Bregman iterations with applications to PET-MR imaging

NASA Astrophysics Data System (ADS)

Rasch, Julian; Brinkmann, Eva-Maria; Burger, Martin

2018-01-01

Joint reconstruction has recently attracted a lot of attention, especially in the field of medical multi-modality imaging such as PET-MRI. Most of the developed methods rely on the comparison of image gradients, or more precisely their location, direction and magnitude, to make use of structural similarities between the images. A challenge and still an open issue for most of the methods is to handle images in entirely different scales, i.e. different magnitudes of gradients that cannot be dealt with by a global scaling of the data. We propose the use of generalized Bregman distances and infimal convolutions thereof with regard to the well-known total variation functional. The use of a total variation subgradient respectively the involved vector field rather than an image gradient naturally excludes the magnitudes of gradients, which in particular solves the scaling behavior. Additionally, the presented method features a weighting that allows to control the amount of interaction between channels. We give insights into the general behavior of the method, before we further tailor it to a particular application, namely PET-MRI joint reconstruction. To do so, we compute joint reconstruction results from blurry Poisson data for PET and undersampled Fourier data from MRI and show that we can gain a mutual benefit for both modalities. In particular, the results are superior to the respective separate reconstructions and other joint reconstruction methods.

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.

Coupled numerical approach combining finite volume and lattice Boltzmann methods for multi-scale multi-physicochemical processes

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

Chen, Li; He, Ya-Ling; Kang, Qinjun

2013-12-15

A coupled (hybrid) simulation strategy spatially combining the finite volume method (FVM) and the lattice Boltzmann method (LBM), called CFVLBM, is developed to simulate coupled multi-scale multi-physicochemical processes. In the CFVLBM, computational domain of multi-scale problems is divided into two sub-domains, i.e., an open, free fluid region and a region filled with porous materials. The FVM and LBM are used for these two regions, respectively, with information exchanged at the interface between the two sub-domains. A general reconstruction operator (RO) is proposed to derive the distribution functions in the LBM from the corresponding macro scalar, the governing equation of whichmore » obeys the convection–diffusion equation. The CFVLBM and the RO are validated in several typical physicochemical problems and then are applied to simulate complex multi-scale coupled fluid flow, heat transfer, mass transport, and chemical reaction in a wall-coated micro reactor. The maximum ratio of the grid size between the FVM and LBM regions is explored and discussed. -- Highlights: •A coupled simulation strategy for simulating multi-scale phenomena is developed. •Finite volume method and lattice Boltzmann method are coupled. •A reconstruction operator is derived to transfer information at the sub-domains interface. •Coupled multi-scale multiple physicochemical processes in micro reactor are simulated. •Techniques to save computational resources and improve the efficiency are discussed.« less

High-throughput hyperpolarized 13C metabolic investigations using a multi-channel acquisition system

NASA Astrophysics Data System (ADS)

Lee, Jaehyuk; Ramirez, Marc S.; Walker, Christopher M.; Chen, Yunyun; Yi, Stacey; Sandulache, Vlad C.; Lai, Stephen Y.; Bankson, James A.

2015-11-01

Magnetic resonance imaging and spectroscopy of hyperpolarized (HP) compounds such as [1-13C]-pyruvate have shown tremendous potential for offering new insight into disease and response to therapy. New applications of this technology in clinical research and care will require extensive validation in cells and animal models, a process that may be limited by the high cost and modest throughput associated with dynamic nuclear polarization. Relatively wide spectral separation between [1-13C]-pyruvate and its chemical endpoints in vivo are conducive to simultaneous multi-sample measurements, even in the presence of a suboptimal global shim. Multi-channel acquisitions could conserve costs and accelerate experiments by allowing acquisition from multiple independent samples following a single dissolution. Unfortunately, many existing preclinical MRI systems are equipped with only a single channel for broadband acquisitions. In this work, we examine the feasibility of this concept using a broadband multi-channel digital receiver extension and detector arrays that allow concurrent measurement of dynamic spectroscopic data from ex vivo enzyme phantoms, in vitro anaplastic thyroid carcinoma cells, and in vivo in tumor-bearing mice. Throughput and the cost of consumables were improved by up to a factor of four. These preliminary results demonstrate the potential for efficient multi-sample studies employing hyperpolarized agents.

Fluidic origami with embedded pressure dependent multi-stability: a plant inspired innovation

PubMed Central

Li, Suyi; Wang, K. W.

2015-01-01

Inspired by the impulsive movements in plants, this research investigates the physics of a novel fluidic origami concept for its pressure-dependent multi-stability. In this innovation, fluid-filled tubular cells are synthesized by integrating different Miura-Ori sheets into a three-dimensional topological system, where the internal pressures are strategically controlled similar to the motor cells in plants. Fluidic origami incorporates two crucial physiological features observed in nature: one is distributed, pressurized cellular organization, and the other is embedded multi-stability. For a single fluidic origami cell, two stable folding configurations can coexist due to the nonlinear relationships among folding, crease material deformation and internal volume change. When multiple origami cells are integrated, additional multi-stability characteristics could occur via the interactions between pressurized cells. Changes in the fluid pressure can tailor the existence and shapes of these stable folding configurations. As a result, fluidic origami can switch between being mono-stable, bistable and multi-stable with pressure control, and provide a rapid ‘snap-through’ type of shape change based on the similar principles as in plants. The outcomes of this research could lead to the development of new adaptive materials or structures, and provide insights for future plant physiology studies at the cellular level. PMID:26400197

Fluidic origami with embedded pressure dependent multi-stability: a plant inspired innovation.

PubMed

Li, Suyi; Wang, K W

2015-10-06

Inspired by the impulsive movements in plants, this research investigates the physics of a novel fluidic origami concept for its pressure-dependent multi-stability. In this innovation, fluid-filled tubular cells are synthesized by integrating different Miura-Ori sheets into a three-dimensional topological system, where the internal pressures are strategically controlled similar to the motor cells in plants. Fluidic origami incorporates two crucial physiological features observed in nature: one is distributed, pressurized cellular organization, and the other is embedded multi-stability. For a single fluidic origami cell, two stable folding configurations can coexist due to the nonlinear relationships among folding, crease material deformation and internal volume change. When multiple origami cells are integrated, additional multi-stability characteristics could occur via the interactions between pressurized cells. Changes in the fluid pressure can tailor the existence and shapes of these stable folding configurations. As a result, fluidic origami can switch between being mono-stable, bistable and multi-stable with pressure control, and provide a rapid 'snap-through' type of shape change based on the similar principles as in plants. The outcomes of this research could lead to the development of new adaptive materials or structures, and provide insights for future plant physiology studies at the cellular level. © 2015 The Author(s).

A multi-scale and multi-field coupling nonlinear constitutive theory for the layered magnetoelectric composites

NASA Astrophysics Data System (ADS)

Xu, Hao; Pei, Yongmao; Li, Faxin; Fang, Daining

2018-05-01

The magnetic, electric and mechanical behaviors are strongly coupled in magnetoelectric (ME) materials, making them great promising in the application of functional devices. In this paper, the magneto-electro-mechanical fully coupled constitutive behaviors of ME laminates are systematically studied both theoretically and experimentally. A new probabilistic domain switching function considering the surface ferromagnetic anisotropy and the interface charge-mediated effect is proposed. Then a multi-scale multi-field coupling nonlinear constitutive model for layered ME composites is developed with physical measureable parameters. The experiments were performed to compare the theoretical predictions with the experimental data. The theoretical predictions have a good agreement with experimental results. The proposed constitutive relation can be used to describe the nonlinear multi-field coupling properties of both ME laminates and thin films. Several novel coupling experimental phenomena such as the electric-field control of magnetization, and the magnetic-field tuning of polarization are observed and analyzed. Furthermore, the size-effect of the electric tuning behavior of magnetization is predicted, which demonstrates a competition mechanism between the interface strain-mediated effect and the charge-driven effect. Our study offers deep insight into the coupling microscopic mechanism and macroscopic properties of ME layered composites, which is benefit for the design of electromagnetic functional devices.

Multi-scale signed envelope inversion

NASA Astrophysics Data System (ADS)

Chen, Guo-Xin; Wu, Ru-Shan; Wang, Yu-Qing; Chen, Sheng-Chang

2018-06-01

Envelope inversion based on modulation signal mode was proposed to reconstruct large-scale structures of underground media. In order to solve the shortcomings of conventional envelope inversion, multi-scale envelope inversion was proposed using new envelope Fréchet derivative and multi-scale inversion strategy to invert strong contrast models. In multi-scale envelope inversion, amplitude demodulation was used to extract the low frequency information from envelope data. However, only to use amplitude demodulation method will cause the loss of wavefield polarity information, thus increasing the possibility of inversion to obtain multiple solutions. In this paper we proposed a new demodulation method which can contain both the amplitude and polarity information of the envelope data. Then we introduced this demodulation method into multi-scale envelope inversion, and proposed a new misfit functional: multi-scale signed envelope inversion. In the numerical tests, we applied the new inversion method to the salt layer model and SEG/EAGE 2-D Salt model using low-cut source (frequency components below 4 Hz were truncated). The results of numerical test demonstrated the effectiveness of this method.

Exploiting target amplitude information to improve multi-target tracking

NASA Astrophysics Data System (ADS)

Ehrman, Lisa M.; Blair, W. Dale

2006-05-01

Closely-spaced (but resolved) targets pose a challenge for measurement-to-track data association algorithms. Since the Mahalanobis distances between measurements collected on closely-spaced targets and tracks are similar, several elements of the corresponding kinematic measurement-to-track cost matrix are also similar. Lacking any other information on which to base assignments, it is not surprising that data association algorithms make mistakes. One ad hoc approach for mitigating this problem is to multiply the kinematic measurement-to-track likelihoods by amplitude likelihoods. However, this can actually be detrimental to the measurement-to-track association process. With that in mind, this paper pursues a rigorous treatment of the hypothesis probabilities for kinematic measurements and features. Three simple scenarios are used to demonstrate the impact of basing data association decisions on these hypothesis probabilities for Rayleigh, fixed-amplitude, and Rician targets. The first scenario assumes that the tracker carries two tracks but only one measurement is collected. This provides insight into more complex scenarios in which there are fewer measurements than tracks. The second scenario includes two measurements and one track. This extends naturally to the case with more measurements than tracks. Two measurements and two tracks are present in the third scenario, which provides insight into the performance of this method when the number of measurements equals the number of tracks. In all cases, basing data association decisions on the hypothesis probabilities leads to good results.

Effects of phone versus mail survey methods on the measurement of health-related quality of life and emotional and behavioural problems in adolescents.

PubMed

Erhart, Michael; Wetzel, Ralf M; Krügel, André; Ravens-Sieberer, Ulrike

2009-12-30

Telephone interviews have become established as an alternative to traditional mail surveys for collecting epidemiological data in public health research. However, the use of telephone and mail surveys raises the question of to what extent the results of different data collection methods deviate from one another. We therefore set out to study possible differences in using telephone and mail survey methods to measure health-related quality of life and emotional and behavioural problems in children and adolescents. A total of 1700 German children aged 8-18 years and their parents were interviewed randomly either by telephone or by mail. Health-related Quality of Life (HRQoL) and mental health problems (MHP) were assessed using the KINDL-R Quality of Life instrument and the Strengths and Difficulties Questionnaire (SDQ) children's self-report and parent proxy report versions. Mean Differences ("d" effect size) and differences in Cronbach alpha were examined across modes of administration. Pearson correlation between children's and parents' scores was calculated within a multi-trait-multi-method (MTMM) analysis and compared across survey modes using Fisher-Z transformation. Telephone and mail survey methods resulted in similar completion rates and similar socio-demographic and socio-economic makeups of the samples. Telephone methods resulted in more positive self- and parent proxy reports of children's HRQoL (SMD < or = 0.27) and MHP (SMD < or = 0.32) on many scales. For the phone administered KINDL, lower Cronbach alpha values (self/proxy Total: 0.79/0.84) were observed (mail survey self/proxy Total: 0.84/0.87). KINDL MTMM results were weaker for the phone surveys: mono-trait-multi-method mean r = 0.31 (mail: r = 0.45); multi-trait-mono-method mean (self/parents) r = 0.29/0.36 (mail: r = 0.34/0.40); multi-trait-multi-method mean r = 0.14 (mail: r = 0.21). Weaker MTMM results were also observed for the phone administered SDQ: mono-trait-multi-method mean r = 0.32 (mail: r = 0.40); multi-trait-mono-method mean (self/parents) r = 0.24/0.30 (mail: r = 0.20/0.32); multi-trait-multi-method mean r = 0.14 (mail = 0.14). The SDQ classification into borderline and abnormal for some scales was affected by the method (OR = 0.36-1.55). The observed differences between phone and mail surveys are small but should be regarded as relevant in certain settings. Therefore, while both methods are valid, some changes are necessary. The weaker reliability and MTMM validity associated with phone methods necessitates improved phone adaptations of paper and pencil questionnaires. The effects of phone versus mail survey modes are partly different across constructs/measures.

Quantum channel for the transmission of information

DOEpatents

Dress, William B.; Kisner, Roger A.; Richards, Roger K.

2004-01-13

Systems and methods are described for a quantum channel for the transmission of information. A method includes: down converting a beam of coherent energy to provide a beam of multi-color entangled photons; converging two spatially resolved portions of the beam of multi-color entangled photons into a converged multi-color entangled photon beam; changing a phase of at least a portion of the converged multi-color entangled photon beam to generate a first interferometric multi-color entangled photon beam; combining the first interferometric multi-color entangled photon beam with a second interferometric multi-color entangled photon beam within a single beam splitter; wherein combining includes erasing energy and momentum characteristics from both the first interferometric multi-color entangled photon beam and the second interferometric multi-color entangled photon beam; splitting the first interferometric multi-color entangled photon beam and the second interferometric multi-color entangled photon beam within the single beam splitter, wherein splitting yields a first output beam of multi-color entangled photons and a second output beam of multi-color entangled photons; and modulating the first output beam of multi-color entangled photons.

Terascale Visualization: Multi-resolution Aspirin for Big-Data Headaches

NASA Astrophysics Data System (ADS)

Duchaineau, Mark

2001-06-01

Recent experience on the Accelerated Strategic Computing Initiative (ASCI) computers shows that computational physicists are successfully producing a prodigious collection of numbers on several thousand processors. But with this wealth of numbers comes an unprecedented difficulty in processing and moving them to provide useful insight and analysis. In this talk, a few simulations are highlighted where recent advancements in multiple-resolution mathematical representations and algorithms have provided some hope of seeing most of the physics of interest while keeping within the practical limits of the post-simulation storage and interactive data-exploration resources. A whole host of visualization research activities was spawned by the 1999 Gordon Bell Prize-winning computation of a shock-tube experiment showing Richtmyer-Meshkov turbulent instabilities. This includes efforts for the entire data pipeline from running simulation to interactive display: wavelet compression of field data, multi-resolution volume rendering and slice planes, out-of-core extraction and simplification of mixing-interface surfaces, shrink-wrapping to semi-regularize the surfaces, semi-structured surface wavelet compression, and view-dependent display-mesh optimization. More recently on the 12 TeraOps ASCI platform, initial results from a 5120-processor, billion-atom molecular dynamics simulation showed that 30-to-1 reductions in storage size can be achieved with no human-observable errors for the analysis required in simulations of supersonic crack propagation. This made it possible to store the 25 trillion bytes worth of simulation numbers in the available storage, which was under 1 trillion bytes. While multi-resolution methods and related systems are still in their infancy, for the largest-scale simulations there is often no other choice should the science require detailed exploration of the results.

Validity and reliability of an application review process using dedicated reviewers in one stage of a multi-stage admissions model.

PubMed

Zeeman, Jacqueline M; McLaughlin, Jacqueline E; Cox, Wendy C

2017-11-01

With increased emphasis placed on non-academic skills in the workplace, a need exists to identify an admissions process that evaluates these skills. This study assessed the validity and reliability of an application review process involving three dedicated application reviewers in a multi-stage admissions model. A multi-stage admissions model was utilized during the 2014-2015 admissions cycle. After advancing through the academic review, each application was independently reviewed by two dedicated application reviewers utilizing a six-construct rubric (written communication, extracurricular and community service activities, leadership experience, pharmacy career appreciation, research experience, and resiliency). Rubric scores were extrapolated to a three-tier ranking to select candidates for on-site interviews. Kappa statistics were used to assess interrater reliability. A three-facet Many-Facet Rasch Model (MFRM) determined reviewer severity, candidate suitability, and rubric construct difficulty. The kappa statistic for candidates' tier rank score (n = 388 candidates) was 0.692 with a perfect agreement frequency of 84.3%. There was substantial interrater reliability between reviewers for the tier ranking (kappa: 0.654-0.710). Highest construct agreement occurred in written communication (kappa: 0.924-0.984). A three-facet MFRM analysis explained 36.9% of variance in the ratings, with 0.06% reflecting application reviewer scoring patterns (i.e., severity or leniency), 22.8% reflecting candidate suitability, and 14.1% reflecting construct difficulty. Utilization of dedicated application reviewers and a defined tiered rubric provided a valid and reliable method to effectively evaluate candidates during the application review process. These analyses provide insight into opportunities for improving the application review process among schools and colleges of pharmacy. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparison of the Prognostic Utility of the Diverse Molecular Data among lncRNA, DNA Methylation, microRNA, and mRNA across Five Human Cancers

PubMed Central

Xu, Li; Fengji, Liang; Changning, Liu; Liangcai, Zhang; Yinghui, Li; Yu, Li; Shanguang, Chen; Jianghui, Xiong

2015-01-01

Introduction Advances in high-throughput technologies have generated diverse informative molecular markers for cancer outcome prediction. Long non-coding RNA (lncRNA) and DNA methylation as new classes of promising markers are emerging as key molecules in human cancers; however, the prognostic utility of such diverse molecular data remains to be explored. Materials and Methods We proposed a computational pipeline (IDFO) to predict patient survival by identifying prognosis-related biomarkers using multi-type molecular data (mRNA, microRNA, DNA methylation, and lncRNA) from 3198 samples of five cancer types. We assessed the predictive performance of both single molecular data and integrated multi-type molecular data in patient survival stratification, and compared their relative importance in each type of cancer, respectively. Survival analysis using multivariate Cox regression was performed to investigate the impact of the IDFO-identified markers and traditional variables on clinical outcome. Results Using the IDFO approach, we obtained good predictive performance of the molecular datasets (bootstrap accuracy: 0.71–0.97) in five cancer types. Impressively, lncRNA was identified as the best prognostic predictor in the validated cohorts of four cancer types, followed by DNA methylation, mRNA, and then microRNA. We found the incorporating of multi-type molecular data showed similar predictive power to single-type molecular data, but with the exception of the lncRNA + DNA methylation combinations in two cancers. Survival analysis of proportional hazard models confirmed a high robustness for lncRNA and DNA methylation as prognosis factors independent of traditional clinical variables. Conclusion Our study provides insight into systematically understanding the prognostic performance of diverse molecular data in both single and aggregate patterns, which may have specific reference to subsequent related studies. PMID:26606135

In silico predicted reproductive endocrine transcriptional regulatory networks during zebrafish (Danio rerio) development.

PubMed

Hala, D

2017-03-21

The interconnected topology of transcriptional regulatory networks (TRNs) readily lends to mathematical (or in silico) representation and analysis as a stoichiometric matrix. Such a matrix can be 'solved' using the mathematical method of extreme pathway (ExPa) analysis, which identifies uniquely activated genes subject to transcription factor (TF) availability. In this manuscript, in silico multi-tissue TRN models of brain, liver and gonad were used to study reproductive endocrine developmental programming in zebrafish (Danio rerio) from 0.25h post fertilization (hpf; zygote) to 90 days post fertilization (dpf; adult life stage). First, properties of TRN models were studied by sequentially activating all genes in multi-tissue models. This analysis showed the brain to exhibit lowest proportion of co-regulated genes (19%) relative to liver (23%) and gonad (32%). This was surprising given that the brain comprised 75% and 25% more TFs than liver and gonad respectively. Such 'hierarchy' of co-regulatory capability (brain

Public perceptions and attitudes toward thalassaemia: Influencing factors in a multi-racial population

PubMed Central

2011-01-01

Background Thalassaemia is a common public health problem in Malaysia and about 4.5 to 6% of the Malays and Chinese are carriers of this genetic disorder. The major forms of thalassaemia result in death in utero of affected foetuses (α-thalassaemia) or life-long blood transfusions for survival in β-thalassaemia. This study, the first nationwide population based survey of thalassaemia in Malaysia, aimed to determine differences in public awareness, perceptions and attitudes toward thalassaemia in the multi-racial population in Malaysia. Methods A cross-sectional computer-assisted telephone interview survey of a representative sample of multi-racial Malaysians aged 18 years and above was conducted between July and December 2009. Results Of a total of 3723 responding households, 2846 (76.4%) have heard of thalassaemia. Mean knowledge score was 11.85 (SD ± 4.03), out of a maximum of 21, with higher scores indicating better knowledge. Statistically significant differences (P < 0.05) in total knowledge score by age groups, education attainment, employment status, and average household income were observed. Although the majority expressed very positive attitudes toward screening for thalassaemia, only 13.6% of married participants interviewed have been screened for thalassaemia. The majority (63.4%) were unsupportive of selective termination of foetuses diagnosed with thalassaemia major. Conclusion Study shows that carrier and premarital screening programs for thalassaemia may be more effective and culturally acceptable in the reduction of pregnancies with thalassaemia major. The findings provide insights into culturally congruent educational interventions to reach out diverse socio-demographic and ethnic communities to increase knowledge and cultivate positive attitudes toward prevention of thalassaemia. PMID:21447191

Uncertainty analysis for effluent trading planning using a Bayesian estimation-based simulation-optimization modeling approach.

PubMed

Zhang, J L; Li, Y P; Huang, G H; Baetz, B W; Liu, J

2017-06-01

In this study, a Bayesian estimation-based simulation-optimization modeling approach (BESMA) is developed for identifying effluent trading strategies. BESMA incorporates nutrient fate modeling with soil and water assessment tool (SWAT), Bayesian estimation, and probabilistic-possibilistic interval programming with fuzzy random coefficients (PPI-FRC) within a general framework. Based on the water quality protocols provided by SWAT, posterior distributions of parameters can be analyzed through Bayesian estimation; stochastic characteristic of nutrient loading can be investigated which provides the inputs for the decision making. PPI-FRC can address multiple uncertainties in the form of intervals with fuzzy random boundaries and the associated system risk through incorporating the concept of possibility and necessity measures. The possibility and necessity measures are suitable for optimistic and pessimistic decision making, respectively. BESMA is applied to a real case of effluent trading planning in the Xiangxihe watershed, China. A number of decision alternatives can be obtained under different trading ratios and treatment rates. The results can not only facilitate identification of optimal effluent-trading schemes, but also gain insight into the effects of trading ratio and treatment rate on decision making. The results also reveal that decision maker's preference towards risk would affect decision alternatives on trading scheme as well as system benefit. Compared with the conventional optimization methods, it is proved that BESMA is advantageous in (i) dealing with multiple uncertainties associated with randomness and fuzziness in effluent-trading planning within a multi-source, multi-reach and multi-period context; (ii) reflecting uncertainties existing in nutrient transport behaviors to improve the accuracy in water quality prediction; and (iii) supporting pessimistic and optimistic decision making for effluent trading as well as promoting diversity of decision alternatives. Copyright © 2017 Elsevier Ltd. All rights reserved.

Research on Multi - Person Parallel Modeling Method Based on Integrated Model Persistent Storage

NASA Astrophysics Data System (ADS)

Qu, MingCheng; Wu, XiangHu; Tao, YongChao; Liu, Ying

2018-03-01

This paper mainly studies the multi-person parallel modeling method based on the integrated model persistence storage. The integrated model refers to a set of MDDT modeling graphics system, which can carry out multi-angle, multi-level and multi-stage description of aerospace general embedded software. Persistent storage refers to converting the data model in memory into a storage model and converting the storage model into a data model in memory, where the data model refers to the object model and the storage model is a binary stream. And multi-person parallel modeling refers to the need for multi-person collaboration, the role of separation, and even real-time remote synchronization modeling.

Extended depth of field integral imaging using multi-focus fusion

NASA Astrophysics Data System (ADS)

Piao, Yongri; Zhang, Miao; Wang, Xiaohui; Li, Peihua

2018-03-01

In this paper, we propose a new method for depth of field extension in integral imaging by realizing the image fusion method on the multi-focus elemental images. In the proposed method, a camera is translated on a 2D grid to take multi-focus elemental images by sweeping the focus plane across the scene. Simply applying an image fusion method on the elemental images holding rich parallax information does not work effectively because registration accuracy of images is the prerequisite for image fusion. To solve this problem an elemental image generalization method is proposed. The aim of this generalization process is to geometrically align the objects in all elemental images so that the correct regions of multi-focus elemental images can be exacted. The all-in focus elemental images are then generated by fusing the generalized elemental images using the block based fusion method. The experimental results demonstrate that the depth of field of synthetic aperture integral imaging system has been extended by realizing the generation method combined with the image fusion on multi-focus elemental images in synthetic aperture integral imaging system.

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.

On shifted Jacobi spectral method for high-order multi-point boundary value problems

NASA Astrophysics Data System (ADS)

Doha, E. H.; Bhrawy, A. H.; Hafez, R. M.

2012-10-01

This paper reports a spectral tau method for numerically solving multi-point boundary value problems (BVPs) of linear high-order ordinary differential equations. The construction of the shifted Jacobi tau approximation is based on conventional differentiation. This use of differentiation allows the imposition of the governing equation at the whole set of grid points and the straight forward implementation of multiple boundary conditions. Extension of the tau method for high-order multi-point BVPs with variable coefficients is treated using the shifted Jacobi Gauss-Lobatto quadrature. Shifted Jacobi collocation method is developed for solving nonlinear high-order multi-point BVPs. The performance of the proposed methods is investigated by considering several examples. Accurate results and high convergence rates are achieved.

Multi-label literature classification based on the Gene Ontology graph.

PubMed

Jin, Bo; Muller, Brian; Zhai, Chengxiang; Lu, Xinghua

2008-12-08

The Gene Ontology is a controlled vocabulary for representing knowledge related to genes and proteins in a computable form. The current effort of manually annotating proteins with the Gene Ontology is outpaced by the rate of accumulation of biomedical knowledge in literature, which urges the development of text mining approaches to facilitate the process by automatically extracting the Gene Ontology annotation from literature. The task is usually cast as a text classification problem, and contemporary methods are confronted with unbalanced training data and the difficulties associated with multi-label classification. In this research, we investigated the methods of enhancing automatic multi-label classification of biomedical literature by utilizing the structure of the Gene Ontology graph. We have studied three graph-based multi-label classification algorithms, including a novel stochastic algorithm and two top-down hierarchical classification methods for multi-label literature classification. We systematically evaluated and compared these graph-based classification algorithms to a conventional flat multi-label algorithm. The results indicate that, through utilizing the information from the structure of the Gene Ontology graph, the graph-based multi-label classification methods can significantly improve predictions of the Gene Ontology terms implied by the analyzed text. Furthermore, the graph-based multi-label classifiers are capable of suggesting Gene Ontology annotations (to curators) that are closely related to the true annotations even if they fail to predict the true ones directly. A software package implementing the studied algorithms is available for the research community. Through utilizing the information from the structure of the Gene Ontology graph, the graph-based multi-label classification methods have better potential than the conventional flat multi-label classification approach to facilitate protein annotation based on the literature.

Multi-task Gaussian process for imputing missing data in multi-trait and multi-environment trials.

PubMed

Hori, Tomoaki; Montcho, David; Agbangla, Clement; Ebana, Kaworu; Futakuchi, Koichi; Iwata, Hiroyoshi

2016-11-01

A method based on a multi-task Gaussian process using self-measuring similarity gave increased accuracy for imputing missing phenotypic data in multi-trait and multi-environment trials. Multi-environmental trial (MET) data often encounter the problem of missing data. Accurate imputation of missing data makes subsequent analysis more effective and the results easier to understand. Moreover, accurate imputation may help to reduce the cost of phenotyping for thinned-out lines tested in METs. METs are generally performed for multiple traits that are correlated to each other. Correlation among traits can be useful information for imputation, but single-trait-based methods cannot utilize information shared by traits that are correlated. In this paper, we propose imputation methods based on a multi-task Gaussian process (MTGP) using self-measuring similarity kernels reflecting relationships among traits, genotypes, and environments. This framework allows us to use genetic correlation among multi-trait multi-environment data and also to combine MET data and marker genotype data. We compared the accuracy of three MTGP methods and iterative regularized PCA using rice MET data. Two scenarios for the generation of missing data at various missing rates were considered. The MTGP performed a better imputation accuracy than regularized PCA, especially at high missing rates. Under the 'uniform' scenario, in which missing data arise randomly, inclusion of marker genotype data in the imputation increased the imputation accuracy at high missing rates. Under the 'fiber' scenario, in which missing data arise in all traits for some combinations between genotypes and environments, the inclusion of marker genotype data decreased the imputation accuracy for most traits while increasing the accuracy in a few traits remarkably. The proposed methods will be useful for solving the missing data problem in MET data.

Multi-criteria Analysis of Factors for Application of Concrete Composites Considering Their Environmental Harmfulness

NASA Astrophysics Data System (ADS)

Paulikova, A.; Estokova, A.; Mitterpach, J.

2017-10-01

The analysis of factors is important in insight of the selection of proper building material with environmental added value. A comprehensive solution is possible if at the beginning there are all the relevant factors in detail characterized predominately that have got a major impact on the area in terms of environmentalharmfulness prevention. There are many groups of environmental factors. In this article only four factors are considered, i.e. contain of CrVI (mg/kg) and index of mass activity for radionuclides (Ra, Th, K) which are the most harmful. These factors can be evaluated by means of a supplementary tool, e.g. multi-criteriaanalysis, which improves and supports decision processes in the framework of construction bybuilding management, etc.

Thermodynamics and Kinetics of Prenucleation Clusters, Classical and Non-Classical Nucleation

PubMed Central

Zahn, Dirk

2015-01-01

Recent observations of prenucleation species and multi-stage crystal nucleation processes challenge the long-established view on the thermodynamics of crystal formation. Here, we review and generalize extensions to classical nucleation theory. Going beyond the conventional implementation as has been used for more than a century now, nucleation inhibitors, precursor clusters and non-classical nucleation processes are rationalized as well by analogous concepts based on competing interface and bulk energy terms. This is illustrated by recent examples of species formed prior to/instead of crystal nucleation and multi-step nucleation processes. Much of the discussed insights were obtained from molecular simulation using advanced sampling techniques, briefly summarized herein for both nucleation-controlled and diffusion-controlled aggregate formation. PMID:25914369

New Equations for Calculating Principal and Fine-Structure Atomic Spectra for Single and Multi-Electron Atoms

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

Surdoval, Wayne A.; Berry, David A.; Shultz, Travis R.

A set of equations are presented for calculating atomic principal spectral lines and fine-structure energy splits for single and multi-electron atoms. Calculated results are presented and compared to the National Institute of Science and Technology database demonstrating very good accuracy. The equations do not require fitted parameters. The only experimental parameter required is the Ionization energy for the electron of interest. The equations have comparable accuracy and broader applicability than the single electron Dirac equation. Three Appendices discuss the origin of the new equations and present calculated results. New insights into the special relativistic nature of the Dirac equation andmore » its relationship to the new equations are presented.« less

Simulation analysis of impulse characteristics of space debris irradiated by multi-pulse laser

NASA Astrophysics Data System (ADS)

Lin, Zhengguo; Jin, Xing; Chang, Hao; You, Xiangyu

2018-02-01

Cleaning space debris with laser is a hot topic in the field of space security research. Impulse characteristics are the basis of cleaning space debris with laser. In order to study the impulse characteristics of rotating irregular space debris irradiated by multi-pulse laser, the impulse calculation method of rotating space debris irradiated by multi-pulse laser is established based on the area matrix method. The calculation method of impulse and impulsive moment under multi-pulse irradiation is given. The calculation process of total impulse under multi-pulse irradiation is analyzed. With a typical non-planar space debris (cube) as example, the impulse characteristics of space debris irradiated by multi-pulse laser are simulated and analyzed. The effects of initial angular velocity, spot size and pulse frequency on impulse characteristics are investigated.

Distributed Multihoming Routing Method by Crossing Control MIPv6 with SCTP

NASA Astrophysics Data System (ADS)

Shi, Hongbo; Hamagami, Tomoki

There are various wireless communication technologies, such as 3G, WiFi, used widely in the world. Recently, not only the laptop but also the smart phones can be equipped with multiple wireless devices. The communication terminals which are implemented with multiple interfaces are usually called multi-homed nodes. Meanwhile, a multi-homed node with multiple interfaces can also be regarded as multiple single-homed nodes. For example, when a person who is using smart phone and laptop to connect to the Internet concurrently, we may regard the person as a multi-homed node in the Internet. This paper proposes a new routing method, Multi-homed Mobile Cross-layer Control to handle multi-homed mobile nodes. Our suggestion can provide a distributed end-to-end routing method for handling the communications among multi-homed nodes at the fundamental network layer.

Flexible Multi-Shock Shield

NASA Technical Reports Server (NTRS)

Christiansen, Eric L. (Inventor); Crews, Jeanne L. (Inventor)

2005-01-01

Flexible multi-shock shield system and method are disclosed for defending against hypervelocity particles. The flexible multi-shock shield system and method may include a number of flexible bumpers or shield layers spaced apart by one or more resilient support layers, all of which may be encapsulated in a protective cover. Fasteners associated with the protective cover allow the flexible multi-shock shield to be secured to the surface of a structure to be protected.

Methods for making a multi-layer seal for electrochemical devices

DOEpatents

Chou, Yeong-Shyung [Richland, WA; Meinhardt, Kerry D [Kennewick, WA; Stevenson, Jeffry W [Richland, WA

2007-05-29

Multi-layer seals are provided that find advantageous use for reducing leakage of gases between adjacent components of electrochemical devices. Multi-layer seals of the invention include a gasket body defining first and second opposing surfaces and a compliant interlayer positioned adjacent each of the first and second surfaces. Also provided are methods for making and using the multi-layer seals, and electrochemical devices including said seals.

Structural ensembles reveal intrinsic disorder for the multi-stimuli responsive bio-mimetic protein Rec1-resilin

PubMed Central

Balu, Rajkamal; Knott, Robert; Cowieson, Nathan P.; Elvin, Christopher M.; Hill, Anita J.; Choudhury, Namita R.; Dutta, Naba K.

2015-01-01

Rec1-resilin is the first recombinant resilin-mimetic protein polymer, synthesized from exon-1 of the Drosophila melanogaster gene CG15920 that has demonstrated unusual multi-stimuli responsiveness in aqueous solution. Crosslinked hydrogels of Rec1-resilin have also displayed remarkable mechanical properties including near-perfect rubber-like elasticity. The structural basis of these extraordinary properties is not clearly understood. Here we combine a computational and experimental investigation to examine structural ensembles of Rec1-resilin in aqueous solution. The structure of Rec1-resilin in aqueous solutions is investigated experimentally using circular dichroism (CD) spectroscopy and small angle X-ray scattering (SAXS). Both bench-top and synchrotron SAXS are employed to extract structural data sets of Rec1-resilin and to confirm their validity. Computational approaches have been applied to these experimental data sets in order to extract quantitative information about structural ensembles including radius of gyration, pair-distance distribution function, and the fractal dimension. The present work confirms that Rec1-resilin is an intrinsically disordered protein (IDP) that displays equilibrium structural qualities between those of a structured globular protein and a denatured protein. The ensemble optimization method (EOM) analysis reveals a single conformational population with partial compactness. This work provides new insight into the structural ensembles of Rec1-resilin in solution. PMID:26042819

Optimal performance of single-column chromatography and simulated moving bed processes for the separation of optical isomers

NASA Astrophysics Data System (ADS)

Medi, Bijan; Kazi, Monzure-Khoda; Amanullah, Mohammad

2013-06-01

Chromatography has been established as the method of choice for the separation and purification of optically pure drugs which has a market size of about 250 billion USD. Single column chromatography (SCC) is commonly used in the development and testing phase of drug development while multi-column Simulated Moving Bed (SMB) chromatography is more suitable for large scale production due to its continuous nature. In this study, optimal performance of SCC and SMB processes for the separation of optical isomers under linear and overloaded separation conditions has been investigated. The performance indicators, namely productivity and desorbent requirement have been compared under geometric similarity for the separation of a mixture of guaifenesin, and Tröger's base enantiomers. SCC process has been analyzed under equilibrium assumption i.e., assuming infinite column efficiency, and zero dispersion, and its optimal performance parameters are compared with the optimal prediction of an SMB process by triangle theory. Simulation results obtained using actual experimental data indicate that SCC may compete with SMB in terms of productivity depending on the molecules to be separated. Besides, insights into the process performances in terms of degree of freedom and relationship between the optimal operating point and solubility limit of the optical isomers have been ascertained. This investigation enables appropriate selection of single or multi-column chromatographic processes based on column packing properties and isotherm parameters.

Genome-wide association study of ancestry-specific TB risk in the South African Coloured population

PubMed Central

Chimusa, Emile R.; Zaitlen, Noah; Daya, Michelle; Möller, Marlo; van Helden, Paul D.; Mulder, Nicola J.; Price, Alkes L.; Hoal, Eileen G.

2014-01-01

The worldwide burden of tuberculosis (TB) remains an enormous problem, and is particularly severe in the admixed South African Coloured (SAC) population residing in the Western Cape. Despite evidence from twin studies suggesting a strong genetic component to TB resistance, only a few loci have been identified to date. In this work, we conduct a genome-wide association study (GWAS), meta-analysis and trans-ethnic fine mapping to attempt the replication of previously identified TB susceptibility loci. Our GWAS results confirm the WT1 chr11 susceptibility locus (rs2057178: odds ratio = 0.62, P = 2.71e−06) previously identified by Thye et al., but fail to replicate previously identified polymorphisms in the TLR8 gene and locus 18q11.2. Our study demonstrates that the genetic contribution to TB risk varies between continental populations, and illustrates the value of including admixed populations in studies of TB risk and other complex phenotypes. Our evaluation of local ancestry based on the real and simulated data demonstrates that case-only admixture mapping is currently impractical in multi-way admixed populations, such as the SAC, due to spurious deviations in average local ancestry generated by current local ancestry inference methods. This study provides insights into identifying disease genes and ancestry-specific disease risk in multi-way admixed populations. PMID:24057671

Multi-relaxation-time lattice Boltzmann modeling of the acoustic field generated by focused transducer

NASA Astrophysics Data System (ADS)

Shan, Feng; Guo, Xiasheng; Tu, Juan; Cheng, Jianchun; Zhang, Dong

The high-intensity focused ultrasound (HIFU) has become an attractive therapeutic tool for the noninvasive tumor treatment. The ultrasonic transducer is the key component in HIFU treatment to generate the HIFU energy. The dimension of focal region generated by the transducer is closely relevant to the safety of HIFU treatment. Therefore, it is essential to numerically investigate the focal region of the transducer. Although the conventional acoustic wave equations have been used successfully to describe the acoustic field, there still exist some inherent drawbacks. In this work, we presented an axisymmetric isothermal multi-relaxation-time lattice Boltzmann method (MRT-LBM) model with the Bouzidi-Firdaouss-Lallemand (BFL) boundary condition in cylindrical coordinate system. With this model, some preliminary simulations were firstly conducted to determine a reasonable value of the relaxation parameter. Then, the validity of the model was examined by comparing the results obtained with the LBM results with the Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation and the Spheroidal beam equation (SBE) for the focused transducers with different aperture angles, respectively. In addition, the influences of the aperture angle on the focal region were investigated. The proposed model in this work will provide significant references for the parameter optimization of the focused transducer for applications in the HIFU treatment or other fields, and provide new insights into the conventional acoustic numerical simulations.

Structural ensembles reveal intrinsic disorder for the multi-stimuli responsive bio-mimetic protein Rec1-resilin.

PubMed

Balu, Rajkamal; Knott, Robert; Cowieson, Nathan P; Elvin, Christopher M; Hill, Anita J; Choudhury, Namita R; Dutta, Naba K

2015-06-04

Rec1-resilin is the first recombinant resilin-mimetic protein polymer, synthesized from exon-1 of the Drosophila melanogaster gene CG15920 that has demonstrated unusual multi-stimuli responsiveness in aqueous solution. Crosslinked hydrogels of Rec1-resilin have also displayed remarkable mechanical properties including near-perfect rubber-like elasticity. The structural basis of these extraordinary properties is not clearly understood. Here we combine a computational and experimental investigation to examine structural ensembles of Rec1-resilin in aqueous solution. The structure of Rec1-resilin in aqueous solutions is investigated experimentally using circular dichroism (CD) spectroscopy and small angle X-ray scattering (SAXS). Both bench-top and synchrotron SAXS are employed to extract structural data sets of Rec1-resilin and to confirm their validity. Computational approaches have been applied to these experimental data sets in order to extract quantitative information about structural ensembles including radius of gyration, pair-distance distribution function, and the fractal dimension. The present work confirms that Rec1-resilin is an intrinsically disordered protein (IDP) that displays equilibrium structural qualities between those of a structured globular protein and a denatured protein. The ensemble optimization method (EOM) analysis reveals a single conformational population with partial compactness. This work provides new insight into the structural ensembles of Rec1-resilin in solution.

Seasonal and Diel Vocalization Patterns of Antarctic Blue Whale (Balaenoptera musculus intermedia) in the Southern Indian Ocean: A Multi-Year and Multi-Site Study.

PubMed

Leroy, Emmanuelle C; Samaran, Flore; Bonnel, Julien; Royer, Jean-Yves

2016-01-01

Passive acoustic monitoring is an efficient way to provide insights on the ecology of large whales. This approach allows for long-term and species-specific monitoring over large areas. In this study, we examined six years (2010 to 2015) of continuous acoustic recordings at up to seven different locations in the Central and Southern Indian Basin to assess the peak periods of presence, seasonality and migration movements of Antarctic blue whales (Balaenoptera musculus intermedia). An automated method is used to detect the Antarctic blue whale stereotyped call, known as Z-call. Detection results are analyzed in terms of distribution, seasonal presence and diel pattern of emission at each site. Z-calls are detected year-round at each site, except for one located in the equatorial Indian Ocean, and display highly seasonal distribution. This seasonality is stable across years for every site, but varies between sites. Z-calls are mainly detected during autumn and spring at the subantarctic locations, suggesting that these sites are on the Antarctic blue whale migration routes, and mostly during winter at the subtropical sites. In addition to these seasonal trends, there is a significant diel pattern in Z-call emission, with more Z-calls in daytime than in nighttime. This diel pattern may be related to the blue whale feeding ecology.

Ontological function annotation of long non-coding RNAs through hierarchical multi-label classification.

PubMed

Zhang, Jingpu; Zhang, Zuping; Wang, Zixiang; Liu, Yuting; Deng, Lei

2018-05-15

Long non-coding RNAs (lncRNAs) are an enormous collection of functional non-coding RNAs. Over the past decades, a large number of novel lncRNA genes have been identified. However, most of the lncRNAs remain function uncharacterized at present. Computational approaches provide a new insight to understand the potential functional implications of lncRNAs. Considering that each lncRNA may have multiple functions and a function may be further specialized into sub-functions, here we describe NeuraNetL2GO, a computational ontological function prediction approach for lncRNAs using hierarchical multi-label classification strategy based on multiple neural networks. The neural networks are incrementally trained level by level, each performing the prediction of gene ontology (GO) terms belonging to a given level. In NeuraNetL2GO, we use topological features of the lncRNA similarity network as the input of the neural networks and employ the output results to annotate the lncRNAs. We show that NeuraNetL2GO achieves the best performance and the overall advantage in maximum F-measure and coverage on the manually annotated lncRNA2GO-55 dataset compared to other state-of-the-art methods. The source code and data are available at http://denglab.org/NeuraNetL2GO/. leideng@csu.edu.cn. Supplementary data are available at Bioinformatics online.

Muver, a computational framework for accurately calling accumulated mutations.

PubMed

Burkholder, Adam B; Lujan, Scott A; Lavender, Christopher A; Grimm, Sara A; Kunkel, Thomas A; Fargo, David C

2018-05-09

Identification of mutations from next-generation sequencing data typically requires a balance between sensitivity and accuracy. This is particularly true of DNA insertions and deletions (indels), that can impart significant phenotypic consequences on cells but are harder to call than substitution mutations from whole genome mutation accumulation experiments. To overcome these difficulties, we present muver, a computational framework that integrates established bioinformatics tools with novel analytical methods to generate mutation calls with the extremely low false positive rates and high sensitivity required for accurate mutation rate determination and comparison. Muver uses statistical comparison of ancestral and descendant allelic frequencies to identify variant loci and assigns genotypes with models that include per-sample assessments of sequencing errors by mutation type and repeat context. Muver identifies maximally parsimonious mutation pathways that connect these genotypes, differentiating potential allelic conversion events and delineating ambiguities in mutation location, type, and size. Benchmarking with a human gold standard father-son pair demonstrates muver's sensitivity and low false positive rates. In DNA mismatch repair (MMR) deficient Saccharomyces cerevisiae, muver detects multi-base deletions in homopolymers longer than the replicative polymerase footprint at rates greater than predicted for sequential single-base deletions, implying a novel multi-repeat-unit slippage mechanism. Benchmarking results demonstrate the high accuracy and sensitivity achieved with muver, particularly for indels, relative to available tools. Applied to an MMR-deficient Saccharomyces cerevisiae system, muver mutation calls facilitate mechanistic insights into DNA replication fidelity.

EMD-regression for modelling multi-scale relationships, and application to weather-related cardiovascular mortality

NASA Astrophysics Data System (ADS)

Masselot, Pierre; Chebana, Fateh; Bélanger, Diane; St-Hilaire, André; Abdous, Belkacem; Gosselin, Pierre; Ouarda, Taha B. M. J.

2018-01-01

In a number of environmental studies, relationships between natural processes are often assessed through regression analyses, using time series data. Such data are often multi-scale and non-stationary, leading to a poor accuracy of the resulting regression models and therefore to results with moderate reliability. To deal with this issue, the present paper introduces the EMD-regression methodology consisting in applying the empirical mode decomposition (EMD) algorithm on data series and then using the resulting components in regression models. The proposed methodology presents a number of advantages. First, it accounts of the issues of non-stationarity associated to the data series. Second, this approach acts as a scan for the relationship between a response variable and the predictors at different time scales, providing new insights about this relationship. To illustrate the proposed methodology it is applied to study the relationship between weather and cardiovascular mortality in Montreal, Canada. The results shed new knowledge concerning the studied relationship. For instance, they show that the humidity can cause excess mortality at the monthly time scale, which is a scale not visible in classical models. A comparison is also conducted with state of the art methods which are the generalized additive models and distributed lag models, both widely used in weather-related health studies. The comparison shows that EMD-regression achieves better prediction performances and provides more details than classical models concerning the relationship.

Structural ensembles reveal intrinsic disorder for the multi-stimuli responsive bio-mimetic protein Rec1-resilin

NASA Astrophysics Data System (ADS)

Balu, Rajkamal; Knott, Robert; Cowieson, Nathan P.; Elvin, Christopher M.; Hill, Anita J.; Choudhury, Namita R.; Dutta, Naba K.

2015-06-01

Rec1-resilin is the first recombinant resilin-mimetic protein polymer, synthesized from exon-1 of the Drosophila melanogaster gene CG15920 that has demonstrated unusual multi-stimuli responsiveness in aqueous solution. Crosslinked hydrogels of Rec1-resilin have also displayed remarkable mechanical properties including near-perfect rubber-like elasticity. The structural basis of these extraordinary properties is not clearly understood. Here we combine a computational and experimental investigation to examine structural ensembles of Rec1-resilin in aqueous solution. The structure of Rec1-resilin in aqueous solutions is investigated experimentally using circular dichroism (CD) spectroscopy and small angle X-ray scattering (SAXS). Both bench-top and synchrotron SAXS are employed to extract structural data sets of Rec1-resilin and to confirm their validity. Computational approaches have been applied to these experimental data sets in order to extract quantitative information about structural ensembles including radius of gyration, pair-distance distribution function, and the fractal dimension. The present work confirms that Rec1-resilin is an intrinsically disordered protein (IDP) that displays equilibrium structural qualities between those of a structured globular protein and a denatured protein. The ensemble optimization method (EOM) analysis reveals a single conformational population with partial compactness. This work provides new insight into the structural ensembles of Rec1-resilin in solution.

Seasonal and Diel Vocalization Patterns of Antarctic Blue Whale (Balaenoptera musculus intermedia) in the Southern Indian Ocean: A Multi-Year and Multi-Site Study

PubMed Central

Leroy, Emmanuelle C.; Samaran, Flore; Bonnel, Julien; Royer, Jean-Yves

2016-01-01

Passive acoustic monitoring is an efficient way to provide insights on the ecology of large whales. This approach allows for long-term and species-specific monitoring over large areas. In this study, we examined six years (2010 to 2015) of continuous acoustic recordings at up to seven different locations in the Central and Southern Indian Basin to assess the peak periods of presence, seasonality and migration movements of Antarctic blue whales (Balaenoptera musculus intermedia). An automated method is used to detect the Antarctic blue whale stereotyped call, known as Z-call. Detection results are analyzed in terms of distribution, seasonal presence and diel pattern of emission at each site. Z-calls are detected year-round at each site, except for one located in the equatorial Indian Ocean, and display highly seasonal distribution. This seasonality is stable across years for every site, but varies between sites. Z-calls are mainly detected during autumn and spring at the subantarctic locations, suggesting that these sites are on the Antarctic blue whale migration routes, and mostly during winter at the subtropical sites. In addition to these seasonal trends, there is a significant diel pattern in Z-call emission, with more Z-calls in daytime than in nighttime. This diel pattern may be related to the blue whale feeding ecology. PMID:27828976

Analysis of multi lobe journal bearings with surface roughness using finite difference method

NASA Astrophysics Data System (ADS)

PhaniRaja Kumar, K.; Bhaskar, SUdaya; Manzoor Hussain, M.

2018-04-01

Multi lobe journal bearings are used for high operating speeds and high loads in machines. In this paper symmetrical multi lobe journal bearings are analyzed to find out the effect of surface roughnessduring non linear loading. Using the fourth order RungeKutta method, time transient analysis was performed to calculate and plot the journal centre trajectories. Flow factor method is used to evaluate the roughness and the finite difference method (FDM) is used to predict the pressure distribution over the bearing surface. The Transient analysis is done on the multi lobe journal bearings for threedifferent surface roughness orientations. Longitudinal surface roughness is more effective when compared with isotopic and traverse surface roughness.

Nonlinear Conservation Laws and Finite Volume Methods

NASA Astrophysics Data System (ADS)

Leveque, Randall J.

Introduction Software Notation Classification of Differential Equations Derivation of Conservation Laws The Euler Equations of Gas Dynamics Dissipative Fluxes Source Terms Radiative Transfer and Isothermal Equations Multi-dimensional Conservation Laws The Shock Tube Problem Mathematical Theory of Hyperbolic Systems Scalar Equations Linear Hyperbolic Systems Nonlinear Systems The Riemann Problem for the Euler Equations Numerical Methods in One Dimension Finite Difference Theory Finite Volume Methods Importance of Conservation Form - Incorrect Shock Speeds Numerical Flux Functions Godunov's Method Approximate Riemann Solvers High-Resolution Methods Other Approaches Boundary Conditions Source Terms and Fractional Steps Unsplit Methods Fractional Step Methods General Formulation of Fractional Step Methods Stiff Source Terms Quasi-stationary Flow and Gravity Multi-dimensional Problems Dimensional Splitting Multi-dimensional Finite Volume Methods Grids and Adaptive Refinement Computational Difficulties Low-Density Flows Discrete Shocks and Viscous Profiles Start-Up Errors Wall Heating Slow-Moving Shocks Grid Orientation Effects Grid-Aligned Shocks Magnetohydrodynamics The MHD Equations One-Dimensional MHD Solving the Riemann Problem Nonstrict Hyperbolicity Stiffness The Divergence of B Riemann Problems in Multi-dimensional MHD Staggered Grids The 8-Wave Riemann Solver Relativistic Hydrodynamics Conservation Laws in Spacetime The Continuity Equation The 4-Momentum of a Particle The Stress-Energy Tensor Finite Volume Methods Multi-dimensional Relativistic Flow Gravitation and General Relativity References

Nonlinear oscillations and waves in multi-species cold plasmas

NASA Astrophysics Data System (ADS)

Verma, Prabal Singh

2016-12-01

The spatio-temporal evolution of nonlinear oscillations in multi-species plasma is revisited to provide more insight into the physics of phase mixing by constructing two sets of nonlinear solutions up to the second order. The first solution exhibits perfect oscillations in the linear regime and phase mixing appears only nonlinearly in the second order as a response to the ponderomotive forces. This response can be both direct and indirect. The indirect contribution of the ponderomotive forces appears through self-consistently generated low frequency fields. Furthermore, the direct and indirect contributions of the ponderomotive forces on the phase mixing process is explored and it is found that the indirect contribution is negligible in an electron-ion plasma and it disappears in the case of electron-positron plasma, yet represents an equal contribution in the electron-positron-ion plasma. However, the second solution does not exhibit any phase mixing due to the absence of ponderomotive forces but results in an undistorted nonlinear traveling wave. These investigations have relevance for laboratory/astrophysical multi-species plasma.

New insights for mesospheric OH: multi-quantum vibrational relaxation as a driver for non-local thermodynamic equilibrium

PubMed Central

Kalogerakis, Konstantinos S.; Matsiev, Daniel; Cosby, Philip C.; Dodd, James A.; Falcinelli, Stefano; Hedin, Jonas; Kutepov, Alexander A.; Noll, Stefan; Panka, Peter A.; Romanescu, Constantin; Thiebaud, Jérôme E.

2018-01-01

The question of whether mesospheric OH(υ) rotational population distributions are in equilibrium with the local kinetic temperature has been debated over several decades. Despite several indications for the existence of non-equilibrium effects, the general consensus has been that emissions originating from low rotational levels are thermalized. Sky spectra simultaneously observing several vibrational levels demonstrated reproducible trends in the extracted OH(υ) rotational temperatures as a function of vibrational excitation. Laboratory experiments provided information on rotational energy transfer and direct evidence for fast multi-quantum OH(high-υ) vibrational relaxation by O atoms. We examine the relationship of the new relaxation pathways with the behavior exhibited by OH(υ) rotational population distributions. Rapid OH(high-υ) + O multi-quantum vibrational relaxation connects high and low vibrational levels and enhances the hot tail of the OH(low-υ) rotational distributions. The effective rotational temperatures of mesospheric OH(υ) are found to deviate from local thermodynamic equilibrium for all observed vibrational levels. PMID:29503514

An analytic-geometric model of the effect of spherically distributed injection errors for Galileo and Ulysses spacecraft - The multi-stage problem

NASA Technical Reports Server (NTRS)

Longuski, James M.; Mcronald, Angus D.

1988-01-01

In previous work the problem of injecting the Galileo and Ulysses spacecraft from low earth orbit into their respective interplanetary trajectories has been discussed for the single stage (Centaur) vehicle. The central issue, in the event of spherically distributed injection errors, is what happens to the vehicle? The difficulties addressed in this paper involve the multi-stage problem since both Galileo and Ulysses will be utilizing the two-stage IUS system. Ulysses will also include a third stage: the PAM-S. The solution is expressed in terms of probabilities for total percentage of escape, orbit decay and reentry trajectories. Analytic solutions are found for Hill's Equations of Relative Motion (more recently called Clohessy-Wiltshire Equations) for multi-stage injections. These solutions are interpreted geometrically on the injection sphere. The analytic-geometric models compare well with numerical solutions, provide insight into the behavior of trajectories mapped on the injection sphere and simplify the numerical two-dimensional search for trajectory families.

Metacognition of Multi-Tasking: How Well Do We Predict the Costs of Divided Attention?

PubMed Central

Finley, Jason R.; Benjamin, Aaron S.; McCarley, Jason S.

2014-01-01

Risky multi-tasking, such as texting while driving, may occur because people misestimate the costs of divided attention. In two experiments, participants performed a computerized visual-manual tracking task in which they attempted to keep a mouse cursor within a small target that moved erratically around a circular track. They then separately performed an auditory n-back task. After practicing both tasks separately, participants received feedback on their single-task tracking performance and predicted their dual-task tracking performance before finally performing the two tasks simultaneously. Most participants correctly predicted reductions in tracking performance under dual-task conditions, with a majority overestimating the costs of dual-tasking. However, the between-subjects correlation between predicted and actual performance decrements was near zero. This combination of results suggests that people do anticipate costs of multi-tasking, but have little metacognitive insight on the extent to which they are personally vulnerable to the risks of divided attention, relative to other people. PMID:24490818

Multi-frequency complex network from time series for uncovering oil-water flow structure.

PubMed

Gao, Zhong-Ke; Yang, Yu-Xuan; Fang, Peng-Cheng; Jin, Ning-De; Xia, Cheng-Yi; Hu, Li-Dan

2015-02-04

Uncovering complex oil-water flow structure represents a challenge in diverse scientific disciplines. This challenge stimulates us to develop a new distributed conductance sensor for measuring local flow signals at different positions and then propose a novel approach based on multi-frequency complex network to uncover the flow structures from experimental multivariate measurements. In particular, based on the Fast Fourier transform, we demonstrate how to derive multi-frequency complex network from multivariate time series. We construct complex networks at different frequencies and then detect community structures. Our results indicate that the community structures faithfully represent the structural features of oil-water flow patterns. Furthermore, we investigate the network statistic at different frequencies for each derived network and find that the frequency clustering coefficient enables to uncover the evolution of flow patterns and yield deep insights into the formation of flow structures. Current results present a first step towards a network visualization of complex flow patterns from a community structure perspective.

Integration of a photocatalytic multi-tube reactor for indoor air purification in HVAC systems: a feasibility study.

PubMed

van Walsem, Jeroen; Roegiers, Jelle; Modde, Bart; Lenaerts, Silvia; Denys, Siegfried

2018-04-24

This work is focused on an in-depth experimental characterization of multi-tube reactors for indoor air purification integrated in ventilation systems. Glass tubes were selected as an excellent photocatalyst substrate to meet the challenging requirements of the operating conditions in a ventilation system in which high flow rates are typical. Glass tubes show a low-pressure drop which reduces the energy demand of the ventilator, and additionally, they provide a large exposed surface area to allow interaction between indoor air contaminants and the photocatalyst. Furthermore, the performance of a range of P25-loaded sol-gel coatings was investigated, based on their adhesion properties and photocatalytic activities. Moreover, the UV light transmission and photocatalytic reactor performance under various operating conditions were studied. These results provide vital insights for the further development and scaling up of multi-tube reactors in ventilation systems which can provide a better comfort, improved air quality in indoor environments, and reduced human exposure to harmful pollutants.

Multi-temporal RADARSAT-1 and ERS backscattering signatures of coastal wetlands in southeastern Louisiana

USGS Publications Warehouse

Kwoun, Oh-Ig; Lu, Z.

2009-01-01

Using multi-temporal European Remote-sensing Satellites (ERS-1/-2) and Canadian Radar Satellite (RADARSAT-1) synthetic aperture radar (SAR) data over the Louisiana coastal zone, we characterize seasonal variations of radar backscat-tering according to vegetation type. Our main findings are as follows. First, ERS-1/-2 and RADARSAT-1 require careful radiometric calibration to perform multi-temporal backscattering analysis for wetland mapping. We use SAR backscattering signals from cities for the relative calibration. Second, using seasonally averaged backscattering coefficients from ERS-1/-2 and RADARSAT-1, we can differentiate most forests (bottomland and swamp forests) and marshes (freshwater, intermediate, brackish, and saline marshes) in coastal wetlands. The student t-test results support the usefulness of season-averaged backscatter data for classification. Third, combining SAR backscattering coefficients and an optical-sensor-based normalized difference vegetation index can provide further insight into vegetation type and enhance the separation between forests and marshes. Our study demonstrates that SAR can provide necessary information to characterize coastal wetlands and monitor their changes.

Multi-Valued Logic, Neutrosophy, and Schrödinger Equation

NASA Astrophysics Data System (ADS)

Smarandache, Florentin; Christianto, Victor

2017-04-01

Discussing some paradoxes in Quantum Mechanics from the viewpoint of Multi-Valued-logic pioneered by Lukasiewicz, and the recent concept Neutrosophic Logic. Essentially, this new concept offers new insights on the idea of `identity', which too often it has been accepted as given. Neutrosophy itself was developed in attempt to generalize Fuzzy-Logic introduced by L. Zadeh. The discussion is motivated by observation that despite almost eight decades, there is indication that some of those paradoxes known in Quantum Physics are not yet solved. In our knowledge, this is because the solution of those paradoxes requires re-examination of the foundations of logic itself, in particular on the notion of identity and multi-valuedness of entity. The discussion is also intended for young physicist fellows who think that somewhere there should be a `complete' explanation of these paradoxes in Quantum Mechanics. If this it doesn't answer all of their questions, it is our hope that at least it offers a new alternative viewpoint for these old questions.

Generation of Multi-band Chorus by Lower Band Cascade in the Earth's Magnetosphere

NASA Astrophysics Data System (ADS)

Gao, X.; Lu, Q.; Chen, L.; Bortnik, J.; Li, W.; Wang, S.

2016-12-01

Chorus waves are intense electromagnetic whistler-mode emissions in the magnetosphere, typically falling into two distinct frequency bands: a lower band (0.1-0.5fce) and an upper band (0.5-0.8fce) with a power gap at about 0.5fce. In this letter, with the THEMIS satellite, we observed two special chorus events, which are called as multi-band chorus because upper band chorus is located at harmonics of lower band chorus. We propose a new potential generation mechanism for multi-band chorus, which is called as lower band cascade. In this scenario, a density mode with a frequency equal to that of lower band chorus is caused by the ponderomotive effect (inhomogeneity of the electric amplitude) along the wave vector, and then upper band chorus with the frequency twice that of lower band chorus is generated through wave-wave couplings between lower band chorus and the density mode. The mechanism provides a new insight into the evolution of whistler-mode chorus in the Earth's magnetosphere.

Investigating the multi-causal and complex nature of the accident causal influence of construction project features.

PubMed

Manu, Patrick A; Ankrah, Nii A; Proverbs, David G; Suresh, Subashini

2012-09-01

Construction project features (CPFs) are organisational, physical and operational attributes that characterise construction projects. Although previous studies have examined the accident causal influence of CPFs, the multi-causal attribute of this causal phenomenon still remain elusive and thus requires further investigation. Aiming to shed light on this facet of the accident causal phenomenon of CPFs, this study examines relevant literature and crystallises the attained insight of the multi-causal attribute by a graphical model which is subsequently operationalised by a derived mathematical risk expression that offers a systematic approach for evaluating the potential of CPFs to cause harm and consequently their health and safety (H&S) risk implications. The graphical model and the risk expression put forth by the study thus advance current understanding of the accident causal phenomenon of CPFs and they present an opportunity for project participants to manage the H&S risk associated with CPFs from the early stages of project procurement. Copyright © 2011 Elsevier Ltd. All rights reserved.

A comprehensive reconstruction of Alaskan Arctic fire history over the last 30,000 years as inferred from a novel multi-proxy suite of organic geochemical and paleoecological methodology.

NASA Astrophysics Data System (ADS)

Vachula, R. S.; Longo, W. M.; Reinert, S. T.; Russell, J. M.; Huang, Y.

2016-12-01

The frequency and spatial extent of tundra fires have increased contemporaneously with anthropogenic climate change in the Arctic. These fires threaten the stability of permafrost carbon stores, subsistence resources, and ecosystem nutrient cycling and are thus important components of rapidly changing Arctic systems. Future projections of tundra fire rely upon reconstructions of fire regime and ecosystem response to climatic variations of the past. High resolution lake sediment records from Northern Alaska have facilitated important insights into the dynamic relationships between fire, climate, and vegetation throughout the Holocene. However, our understanding of how fire regimes in this region have responded to climate on glacial-interglacial timescales remains speculative. We present a 30,000 year fire history reconstruction from Lake E5, a small lake in the northern foothills of the Brooks Range. Our reconstruction, inferred from sedimentary charcoal particles, polycyclic aromatic hydrocarbons (PAHs), and bulk sediment Black Carbon (BC) content, offers unique insights into how Arctic terrestrial ecosystems of the past and present have interacted with climate on glacial-interglacial time scales via the mechanism of fire. This unique approach pairs traditional (charcoal) and novel (PAHs and BC) proxies and thereby (1) allows for a simultaneous interpretation of local and regional fire history (2) quantifies the abundance of all sizes of all byproducts of incomplete combustion and (3) gains insights into relative changes in combustion temperature, fire severity, and fuel type. While traditional methods would focus on a narrow range of the size spectrum of the physical and chemical byproducts of fire (charcoal particles >0.15 mm), the suite of methods used in this study facilitates a more holistic and comprehensive fire history reconstruction from the E5 sediment record. Results indicate that moisture and vegetation variations were likely the primary drivers of fire in this region over the last 30,000 years. Furthermore, sea level changes and related shifts in atmospheric circulation likely influenced fire regimes in this area prior to the Holocene.

Potential of Iraqi Local Councils to facilitate Iraqi National Unity

DTIC Science & Technology

2009-06-12

U.S. forces to form a multi-tribal grassroots council involving both sects. Abu Ahmed currently serves as a local contractor in Baghdad. He has...worked with local councils and supported their efforts in reconstruction. Abu Ahmed offers insight into local councils from a unique third...responded on average in agreement when asked whether reform was more effective if local leaders sought to achieve it. Abu Ahmed , a prominent

Advanced Multi-Photon Chromophores for Broad-Band Ultra-Fast Optical Limiting

DTIC Science & Technology

2014-11-04

for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data ...sources, gathering and maintaining the data needed, and completing and reviewing this collection of information. Send comments regarding this...with expanded -system. This data provides crucial insight into the push-pull 2PA-enhancement mechanism. Following systems were studied in detail: i

Nanosecond Plasma Enhanced H2/O2/N2 Premixed Flat Flames

DTIC Science & Technology

2014-01-01

Simulations are conducted with a one-dimensional, multi-scale, pulsed -discharge model with detailed plasma-combustion kinetics to develop additional insight... model framework. The reduced electric field, E/N, during each pulse varies inversely with number density. A significant portion of the input energy is...dimensional numerical model [4, 12] capable of resolving electric field transients over nanosecond timescales (during each discharge pulse ) and radical

Multi-scale controls of historical forest-fire regimes: new insights from fire-scar networks

Treesearch

Donald A. Falk; Emily K. Heyerdahl; Peter M. Brown; Calvin Farris; Peter Z. Fule; Donald McKenzie; Thomas W. Swetnam; Alan H. Taylor; Megan L. Van Horne

2011-01-01

Anticipating future forest-fire regimes under changing climate requires that scientists and natural resource managers understand the factors that control fire across space and time. Fire scars—proxy records of fires, formed in the growth rings of long-lived trees—provide an annually accurate window into past low-severity fire regimes. In western North America, networks...

Advances in Induced Pluripotent Stem Cells, Genomics, Biomarkers, and Antiplatelet Therapy

PubMed Central

Barbato, Emanuele; Lara-Pezzi, Enrique; Stolen, Craig; Taylor, Angela; Barton, Paul J.; Bartunek, Jozef; Iaizzo, Paul; Judge, Daniel P.; Kirshenbaum, Lorrie; Blaxall, Burns C.; Terzic, Andre; Hall, Jennifer L.

2014-01-01

The Journal provides the clinician and scientist with the latest advances in discovery research, emerging technologies, pre-clinical research design and testing, and clinical trials. We highlight advances in areas of induced pluripotent stem cells, genomics, biomarkers, multi-modality imaging and antiplatelet biology and therapy. The top publications are critically discussed and presented along with anatomical reviews and FDA insight to provide context. PMID:24659088

Ocean Variability Effects on Underwater Acoustic Communications

DTIC Science & Technology

2007-09-30

sea surface was rougher. To recover the transmitted symbols which have been passed through the time-varying multi-path acoustic channels, a new ...B is about 6 dB higher than that during enviromental case A. Due to the large aperture and deployment range of the MPL array, the channel impulse...environmental fluctuations and the performance of coherent underwater acoustic communications presents new insights into the operational effectiveness of

Psychosexual Functioning of Cognitively-Able Adolescents with Autism Spectrum Disorder Compared to Typically Developing Peers: The Development and Testing of the Teen Transition Inventory--A Self- and Parent Report Questionnaire on Psychosexual Functioning

ERIC Educational Resources Information Center

Dekker, Linda P.; van der Vegt, Esther J. M.; van der Ende, Jan; Tick, Nouchka; Louwerse, Anneke; Maras, Athanasios; Verhulst, Frank C.; Greaves-Lord, Kirstin

2017-01-01

To gain further insight into psychosexual functioning, including behaviors, intrapersonal and interpersonal aspects, in adolescents with Autism Spectrum Disorder (ASD), comprehensive, multi-informant measures are needed. This study describes (1) the development of a new measure of psychosexual functioning in both parent- and self-reports (Teen…

Loners, Groupies, and Long-term Eccentricity (and Inclination) Behavior: Insights from Secular Theory

NASA Astrophysics Data System (ADS)

Van Laerhoven, Christa L.

2015-05-01

Considering the secular dynamics of multi-planet systems provides substantial insight into the interactions between planets in those systems. Secular interactions are those that don't involve knowing where a planet is along its orbit, and they dominate when planets are not involved in mean motion resonances. These interactions exchange angular momentum among the planets, evolving their eccentricities and inclinations. To second order in the planets' eccentricities and inclinations, the eccentricity and inclination perturbations are decoupled. Given the right variable choice, the relevant differential equations are linear and thus the eccentricity and inclination behaviors can be described as a sum of eigenmodes. Since the underlying structure of the secular eigenmodes can be calculated using only the planets' masses and semi-major axes, one can elucidate the eccentricity and inclination behavior of planets in exoplanet systems even without knowing the planets' current eccentricities and inclinations. I have calculated both the eccentricity and inclination secular eigenmodes for the population of known multi-planet systems whose planets have well determined masses and periods. Using this catalog of secular character, I will discuss the prevalence of dynamically grouped planets ('groupies') versus dynamically uncoupled planets ('loners') and how this relates to the exoplanets' long-term eccentricity and inclination behavior. I will also touch on the distribution of the secular eigenfreqiencies.

Comparative Study of Lectin Domains in Model Species: New Insights into Evolutionary Dynamics

PubMed Central

Van Holle, Sofie; De Schutter, Kristof; Eggermont, Lore; Tsaneva, Mariya; Dang, Liuyi; Van Damme, Els J. M.

2017-01-01

Lectins are present throughout the plant kingdom and are reported to be involved in diverse biological processes. In this study, we provide a comparative analysis of the lectin families from model species in a phylogenetic framework. The analysis focuses on the different plant lectin domains identified in five representative core angiosperm genomes (Arabidopsis thaliana, Glycine max, Cucumis sativus, Oryza sativa ssp. japonica and Oryza sativa ssp. indica). The genomes were screened for genes encoding lectin domains using a combination of Basic Local Alignment Search Tool (BLAST), hidden Markov models, and InterProScan analysis. Additionally, phylogenetic relationships were investigated by constructing maximum likelihood phylogenetic trees. The results demonstrate that the majority of the lectin families are present in each of the species under study. Domain organization analysis showed that most identified proteins are multi-domain proteins, owing to the modular rearrangement of protein domains during evolution. Most of these multi-domain proteins are widespread, while others display a lineage-specific distribution. Furthermore, the phylogenetic analyses reveal that some lectin families evolved to be similar to the phylogeny of the plant species, while others share a closer evolutionary history based on the corresponding protein domain architecture. Our results yield insights into the evolutionary relationships and functional divergence of plant lectins. PMID:28587095