Practical use of a framework for network science experimentation

NASA Astrophysics Data System (ADS)

Toth, Andrew; Bergamaschi, Flavio

2014-06-01

In 2006, the US Army Research Laboratory (ARL) and the UK Ministry of Defence (MoD) established a collaborative research alliance with academia and industry, called the International Technology Alliance (ITA)1 In Network and Information Sciences, to address fundamental issues concerning Network and Information Sciences that will enhance decision making for coalition operations and enable rapid, secure formation of ad hoc teams in coalition environments and enhance US and UK capabilities to conduct coalition warfare. Research conducted under the ITA was extended through collaboration between ARL and IBM UK to characterize and dene a software stack and tooling that has become the reference framework for network science experimentation in support for validation of theoretical research. This paper discusses the composition of the reference framework for experimentation resulting from the ARL/IBM UK collaboration and its use, by the Network Science Collaborative Technology Alliance (NS CTA)2 , in a recent network science experiment conducted at ARL. It also discusses how the experiment was modeled using the reference framework, the integration of two new components, the Apollo Fact-Finder3 tool and the Medusa Crowd Sensing4 application, the limitations identified and how they shall be addressed in future work.

An Experimental Framework for Executing Applications in Dynamic Grid Environments

NASA Technical Reports Server (NTRS)

Huedo, Eduardo; Montero, Ruben S.; Llorente, Ignacio M.; Bushnell, Dennis M. (Technical Monitor)

2002-01-01

The Grid opens up opportunities for resource-starved scientists and engineers to harness highly distributed computing resources. A number of Grid middleware projects are currently available to support the simultaneous exploitation of heterogeneous resources distributed in different administrative domains. However, efficient job submission and management continue being far from accessible to ordinary scientists and engineers due to the dynamic and complex nature of the Grid. This report describes a new Globus framework that allows an easier and more efficient execution of jobs in a 'submit and forget' fashion. Adaptation to dynamic Grid conditions is achieved by supporting automatic application migration following performance degradation, 'better' resource discovery, requirement change, owner decision or remote resource failure. The report also includes experimental results of the behavior of our framework on the TRGP testbed.

US Army Research Laboratory Visualization Framework Architecture Document

DTIC Science & Technology

2018-01-11

this report are not to be construed as an official Department of the Army position unless so designated by other authorized documents. Citation of...release; distribution is unlimited. 14. ABSTRACT Visualization of network science experimentation results is generally achieved using stovepipe...report documents the ARL Visualization Framework system design and specific details of its implementation. 15. SUBJECT TERMS visualization

A review of event processing frameworks used in HEP

DOE PAGES

Sexton-Kennedy, E.

2015-12-23

Today there are many different experimental event processing frameworks in use by running or about to be running experiments. This talk will discuss the different components of these frameworks. In the past there have been attempts at shared framework projects for example the collaborations on the BaBar framework (between BaBar, CDF, and CLEO), on the Gaudi framework (between LHCb and ATLAS), on AliROOT/FairROOT (between Alice and GSI/Fair), and in some ways on art (Fermilab based experiments) and CMS’ framework. However, for reasons that will be discussed, these collaborations did not result in common frameworks shared among the intended experiments. Thoughmore » importantly, two of the resulting projects have succeeded in providing frameworks that are shared among many customer experiments: Fermilab's art framework and GSI/Fair's FairROOT. Interestingly, several projects are considering remerging their frameworks after many years apart. I'll report on an investigation and analysis of these realities. In addition, with the advent of the need for multi-threaded frameworks and the scarce available manpower, it is important to collaborate in the future, however it is also important to understand why previous attempts at multi-experiment frameworks either worked or didn't work.« less

Dynamically analyzing cell interactions in biological environments using multiagent social learning framework.

PubMed

Zhang, Chengwei; Li, Xiaohong; Li, Shuxin; Feng, Zhiyong

2017-09-20

Biological environment is uncertain and its dynamic is similar to the multiagent environment, thus the research results of the multiagent system area can provide valuable insights to the understanding of biology and are of great significance for the study of biology. Learning in a multiagent environment is highly dynamic since the environment is not stationary anymore and each agent's behavior changes adaptively in response to other coexisting learners, and vice versa. The dynamics becomes more unpredictable when we move from fixed-agent interaction environments to multiagent social learning framework. Analytical understanding of the underlying dynamics is important and challenging. In this work, we present a social learning framework with homogeneous learners (e.g., Policy Hill Climbing (PHC) learners), and model the behavior of players in the social learning framework as a hybrid dynamical system. By analyzing the dynamical system, we obtain some conditions about convergence or non-convergence. We experimentally verify the predictive power of our model using a number of representative games. Experimental results confirm the theoretical analysis. Under multiagent social learning framework, we modeled the behavior of agent in biologic environment, and theoretically analyzed the dynamics of the model. We present some sufficient conditions about convergence or non-convergence and prove them theoretically. It can be used to predict the convergence of the system.

Theoretical verification of experimentally obtained conformation-dependent electronic conductance in a biphenyl molecule

NASA Astrophysics Data System (ADS)

Maiti, Santanu K.

2014-07-01

The experimentally obtained (Venkataraman et al. [1]) cosine squared relation of electronic conductance in a biphenyl molecule is verified theoretically within a tight-binding framework. Using Green's function formalism we numerically calculate two-terminal conductance as a function of relative twist angle among the molecular rings and find that the results are in good agreement with the experimental observation.

Linking water age and solute dynamics in streamflow at the Hubbard Brook Experimental Forest, NH, USA

Treesearch

Paolo Benettin; Scott W. Bailey; John L. Campbell; Mark B. Green; Andrea Rinaldo; Gene E. Likens; Kevin J. McGuire; Gianluca Botter

2015-01-01

We combine experimental and modeling results from a headwater catchment at the Hubbard Brook Experimental Forest (HBEF), New Hampshire, USA, to explore the link between stream solute dynamics and water age. A theoretical framework based on water age dynamics, which represents a general basis for characterizing solute transport at the catchment scale, is here applied to...

A comprehensive combined experimental and computational framework for pre-clinical wear simulation of total knee replacements.

PubMed

Abdelgaied, A; Fisher, J; Jennings, L M

2018-02-01

A more robust pre-clinical wear simulation framework is required in order to simulate wider and higher ranges of activities, observed in different patient populations such as younger more active patients. Such a framework will help to understand and address the reported higher failure rates for younger and more active patients (National_Joint_Registry, 2016). The current study has developed and validated a comprehensive combined experimental and computational framework for pre-clinical wear simulation of total knee replacements (TKR). The input mechanical (elastic modulus and Poisson's ratio) and wear parameters of the moderately cross-linked ultra-high molecular weight polyethylene (UHMWPE) bearing material were independently measured from experimental studies under realistic test conditions, similar to the loading conditions found in the total knee replacements. The wear predictions from the computational wear simulation were validated against the direct experimental wear measurements for size 3 Sigma curved total knee replacements (DePuy, UK) in an independent experimental wear simulation study under three different daily activities; walking, deep squat, and stairs ascending kinematic conditions. The measured compressive mechanical properties of the moderately cross-linked UHMWPE material were more than 20% lower than that reported in the literature under tensile test conditions. The pin-on-plate wear coefficient of moderately cross-linked UHMWPE was significantly dependant of the contact stress and the degree of cross-shear at the articulating surfaces. The computational wear predictions for the TKR from the current framework were consistent and in a good agreement with the independent full TKR experimental wear simulation measurements, with 0.94 coefficient of determination of the framework. In addition, the comprehensive combined experimental and computational framework was able to explain the complex experimental wear trends from the three different daily activities investigated. Therefore, such a framework can be adopted as a pre-clinical simulation approach to optimise different designs, materials, as well as patient's specific total knee replacements for a range of activities. Copyright © 2017. Published by Elsevier Ltd.

Towards adaptive, streaming analysis of x-ray tomography data

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

Thomas, Mathew; Kleese van Dam, Kerstin; Marshall, Matthew J.

2015-03-04

Temporal and spatial resolution of chemical imaging methodologies such as x-ray tomography are rapidly increasing, leading to more complex experimental procedures and fast growing data volumes. Automated analysis pipelines and big data analytics are becoming essential to effectively evaluate the results of such experiments. Offering those data techniques in an adaptive, streaming environment can further substantially improve the scientific discovery process, by enabling experimental control and steering based on the evaluation of emerging phenomena as they are observed by the experiment. Pacific Northwest National Laboratory (PNNL)’ Chemical Imaging Initiative (CII - http://imaging.pnnl.gov/ ) has worked since 2011 towards developing amore » framework that allows users to rapidly compose and customize high throughput experimental analysis pipelines for multiple instrument types. The framework, named ‘Rapid Experimental Analysis’ (REXAN) Framework [1], is based on the idea of reusable component libraries and utilizes the PNNL developed collaborative data management and analysis environment ‘Velo’, to provide a user friendly analysis and data management environment for experimental facilities. This article will, discuss the capabilities established for X-Ray tomography, discuss lessons learned, and provide an overview of our more recent work in the Analysis in Motion Initiative (AIM - http://aim.pnnl.gov/ ) at PNNL to provide REXAN capabilities in a streaming environment.« less

An Integrated Qualitative and Quantitative Biochemical Model Learning Framework Using Evolutionary Strategy and Simulated Annealing.

PubMed

Wu, Zujian; Pang, Wei; Coghill, George M

2015-01-01

Both qualitative and quantitative model learning frameworks for biochemical systems have been studied in computational systems biology. In this research, after introducing two forms of pre-defined component patterns to represent biochemical models, we propose an integrative qualitative and quantitative modelling framework for inferring biochemical systems. In the proposed framework, interactions between reactants in the candidate models for a target biochemical system are evolved and eventually identified by the application of a qualitative model learning approach with an evolution strategy. Kinetic rates of the models generated from qualitative model learning are then further optimised by employing a quantitative approach with simulated annealing. Experimental results indicate that our proposed integrative framework is feasible to learn the relationships between biochemical reactants qualitatively and to make the model replicate the behaviours of the target system by optimising the kinetic rates quantitatively. Moreover, potential reactants of a target biochemical system can be discovered by hypothesising complex reactants in the synthetic models. Based on the biochemical models learned from the proposed framework, biologists can further perform experimental study in wet laboratory. In this way, natural biochemical systems can be better understood.

Atomic layer deposition in a metal–organic framework: Synthesis, characterization, and performance of a solid acid

DOE PAGES

Rimoldi, Martino; Bernales, Varinia; Borycz, Joshua; ...

2017-01-05

NU-1000, a zirconium-based metal-organic framework featuring mesoporous channels, has been post-synthetically metalated via atomic layer deposition in MOF (AIM) employing dimethylaluminum iso-propoxide ([AlMe 2 iOPr] 2 – DMAI), a milder precursor than widely used trimethylaluminum (AlMe 3 - TMA). The aluminum-modified NU-1000 (Al-NU-1000) has been characterized with a comprehensive suite of techniques that points to the formation of aluminum oxide clusters well dispersed through the framework and stabilized by confinement within small pores intrinsic to the NU-1000 structure. Experimental evidence allows for identification of spectroscopic similarities between Al-NU-1000 and γ-Al 2O 3. Density functional theory modeling provides structures and simulatedmore » spectra the relevance of which can be assessed via comparison to experimental IR and EXAFS data. As a result, the catalytic performance of Al-NU-1000 has been benchmarked against γ-Al 2O 3, with promising results in terms of selectivity.« less

Coherent evolution of parahydrogen induced polarisation using laser pump, NMR probe spectroscopy: Theoretical framework and experimental observation.

PubMed

Halse, Meghan E; Procacci, Barbara; Henshaw, Sarah-Louise; Perutz, Robin N; Duckett, Simon B

2017-05-01

We recently reported a pump-probe method that uses a single laser pulse to introduce parahydrogen (p-H 2 ) into a metal dihydride complex and then follows the time-evolution of the p-H 2 -derived nuclear spin states by NMR. We present here a theoretical framework to describe the oscillatory behaviour of the resultant hyperpolarised NMR signals using a product operator formalism. We consider the cases where the p-H 2 -derived protons form part of an AX, AXY, AXYZ or AA'XX' spin system in the product molecule. We use this framework to predict the patterns for 2D pump-probe NMR spectra, where the indirect dimension represents the evolution during the pump-probe delay and the positions of the cross-peaks depend on the difference in chemical shift of the p-H 2 -derived protons and the difference in their couplings to other nuclei. The evolution of the NMR signals of the p-H 2 -derived protons, as well as the transfer of hyperpolarisation to other NMR-active nuclei in the product, is described. The theoretical framework is tested experimentally for a set of ruthenium dihydride complexes representing the different spin systems. Theoretical predictions and experimental results agree to within experimental error for all features of the hyperpolarised 1 H and 31 P pump-probe NMR spectra. Thus we establish the laser pump, NMR probe approach as a robust way to directly observe and quantitatively analyse the coherent evolution of p-H 2 -derived spin order over micro-to-millisecond timescales. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Computations of Combustion-Powered Actuation for Dynamic Stall Suppression

NASA Technical Reports Server (NTRS)

Jee, Solkeun; Bowles, Patrick O.; Matalanis, Claude G.; Min, Byung-Young; Wake, Brian E.; Crittenden, Tom; Glezer, Ari

2016-01-01

A computational framework for the simulation of dynamic stall suppression with combustion-powered actuation (COMPACT) is validated against wind tunnel experimental results on a VR-12 airfoil. COMPACT slots are located at 10% chord from the leading edge of the airfoil and directed tangentially along the suction-side surface. Helicopter rotor-relevant flow conditions are used in the study. A computationally efficient two-dimensional approach, based on unsteady Reynolds-averaged Navier-Stokes (RANS), is compared in detail against the baseline and the modified airfoil with COMPACT, using aerodynamic forces, pressure profiles, and flow-field data. The two-dimensional RANS approach predicts baseline static and dynamic stall very well. Most of the differences between the computational and experimental results are within two standard deviations of the experimental data. The current framework demonstrates an ability to predict COMPACT efficacy across the experimental dataset. Enhanced aerodynamic lift on the downstroke of the pitching cycle due to COMPACT is well predicted, and the cycleaveraged lift enhancement computed is within 3% of the test data. Differences with experimental data are discussed with a focus on three-dimensional features not included in the simulations and the limited computational model for COMPACT.

Understanding Leadership: An Experimental-Experiential Model

ERIC Educational Resources Information Center

Hole, George T.

2014-01-01

Books about leadership are dangerous to readers who fantasize about being leaders or apply leadership ideas as if they were proven formulas. As an antidote, I offer an experimental framework in which any leadership-management model can be tested to gain experiential understanding of the model. As a result one can gain reality-based insights about…

Range Finding with a Plenoptic Camera

DTIC Science & Technology

2014-03-27

92 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Simulated Camera Analysis...Varying Lens Diameter . . . . . . . . . . . . . . . . 95 Simulated Camera Analysis: Varying Detector Size . . . . . . . . . . . . . . . . . 98 Simulated ...Matching Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 37 Simulated Camera Performance with SIFT

A novel framework of tissue membrane systems for image fusion.

PubMed

Zhang, Zulin; Yi, Xinzhong; Peng, Hong

2014-01-01

This paper proposes a tissue membrane system-based framework to deal with the optimal image fusion problem. A spatial domain fusion algorithm is given, and a tissue membrane system of multiple cells is used as its computing framework. Based on the multicellular structure and inherent communication mechanism of the tissue membrane system, an improved velocity-position model is developed. The performance of the fusion framework is studied with comparison of several traditional fusion methods as well as genetic algorithm (GA)-based and differential evolution (DE)-based spatial domain fusion methods. Experimental results show that the proposed fusion framework is superior or comparable to the other methods and can be efficiently used for image fusion.

eXframe: reusable framework for storage, analysis and visualization of genomics experiments

PubMed Central

2011-01-01

Background Genome-wide experiments are routinely conducted to measure gene expression, DNA-protein interactions and epigenetic status. Structured metadata for these experiments is imperative for a complete understanding of experimental conditions, to enable consistent data processing and to allow retrieval, comparison, and integration of experimental results. Even though several repositories have been developed for genomics data, only a few provide annotation of samples and assays using controlled vocabularies. Moreover, many of them are tailored for a single type of technology or measurement and do not support the integration of multiple data types. Results We have developed eXframe - a reusable web-based framework for genomics experiments that provides 1) the ability to publish structured data compliant with accepted standards 2) support for multiple data types including microarrays and next generation sequencing 3) query, analysis and visualization integration tools (enabled by consistent processing of the raw data and annotation of samples) and is available as open-source software. We present two case studies where this software is currently being used to build repositories of genomics experiments - one contains data from hematopoietic stem cells and another from Parkinson's disease patients. Conclusion The web-based framework eXframe offers structured annotation of experiments as well as uniform processing and storage of molecular data from microarray and next generation sequencing platforms. The framework allows users to query and integrate information across species, technologies, measurement types and experimental conditions. Our framework is reusable and freely modifiable - other groups or institutions can deploy their own custom web-based repositories based on this software. It is interoperable with the most important data formats in this domain. We hope that other groups will not only use eXframe, but also contribute their own useful modifications. PMID:22103807

Sensor-Based Human Activity Recognition in a Multi-user Scenario

NASA Astrophysics Data System (ADS)

Wang, Liang; Gu, Tao; Tao, Xianping; Lu, Jian

Existing work on sensor-based activity recognition focuses mainly on single-user activities. However, in real life, activities are often performed by multiple users involving interactions between them. In this paper, we propose Coupled Hidden Markov Models (CHMMs) to recognize multi-user activities from sensor readings in a smart home environment. We develop a multimodal sensing platform and present a theoretical framework to recognize both single-user and multi-user activities. We conduct our trace collection done in a smart home, and evaluate our framework through experimental studies. Our experimental result shows that we achieve an average accuracy of 85.46% with CHMMs.

Tile prediction schemes for wide area motion imagery maps in GIS

NASA Astrophysics Data System (ADS)

Michael, Chris J.; Lin, Bruce Y.

2017-11-01

Wide-area surveillance, traffic monitoring, and emergency management are just several of many applications benefiting from the incorporation of Wide-Area Motion Imagery (WAMI) maps into geographic information systems. Though the use of motion imagery as a GIS base map via the Web Map Service (WMS) standard is not a new concept, effectively streaming imagery is particularly challenging due to its large scale and the multidimensionally interactive nature of clients that use WMS. Ineffective streaming from a server to one or more clients can unnecessarily overwhelm network bandwidth and cause frustratingly large amounts of latency in visualization to the user. Seamlessly streaming WAMI through GIS requires good prediction to accurately guess the tiles of the video that will be traversed in the near future. In this study, we present an experimental framework for such prediction schemes by presenting a stochastic interaction model that represents a human user's interaction with a GIS video map. We then propose several algorithms by which the tiles of the stream may be predicted. Results collected both within the experimental framework and using human analyst trajectories show that, though each algorithm thrives under certain constraints, the novel Markovian algorithm yields the best results overall. Furthermore, we make the argument that the proposed experimental framework is sufficient for the study of these prediction schemes.

Semi-NLO production of Higgs bosons in the framework of kt-factorization using KMR unintegrated parton distributions

NASA Astrophysics Data System (ADS)

Modarres, M.; Masouminia, M. R.; Aminzadeh Nik, R.; Hosseinkhani, H.; Olanj, N.

2018-01-01

The cross-section for the production of the Standard Model Higgs boson has been calculated using a mixture of LO and NLO partonic diagrams and the unintegrated parton distribution functions (UPDF) of the Kimber-Martin-Ryskin (KMR) from the kt-factorization framework. The UPDF are prepared using the phenomenological libraries of Martin-Motylinski-Harland Lang-Thorne (MMHT 2014). The results are compared against the existing experimental data from the CMS and the ATLAS collaborations and available pQCD calculation. It is shown that, while the present calculation is in agreement with the experimental data, it is comparable with the pQCD results. It is also concluded that the K-factor approximation is comparable with the semi-NLOkt-factorization predictions.

Questioning and Experimentation

ERIC Educational Resources Information Center

Mutanen, Arto

2014-01-01

The paper is a philosophical analysis of experimentation. The philosophical framework of the analysis is the interrogative model of inquiry developed by Hintikka. The basis of the model is explicit and well-formed logic of questions and answers. The framework allows us to formulate a flexible logic of experimentation. In particular, the formulated…

Plasma Model V&V of Collisionless Electrostatic Shock

NASA Astrophysics Data System (ADS)

Martin, Robert; Le, Hai; Bilyeu, David; Gildea, Stephen

2014-10-01

A simple 1D electrostatic collisionless shock was selected as an initial validation and verification test case for a new plasma modeling framework under development at the Air Force Research Laboratory's In-Space Propulsion branch (AFRL/RQRS). Cross verification between PIC, Vlasov, and Fluid plasma models within the framework along with expected theoretical results will be shown. The non-equilibrium velocity distributions (VDF) captured by PIC and Vlasov will be compared to each other and the assumed VDF of the fluid model at selected points. Validation against experimental data from the University of California, Los Angeles double-plasma device will also be presented along with current work in progress at AFRL/RQRS towards reproducing the experimental results using higher fidelity diagnostics to help elucidate differences between model results and between the models and original experiment. DISTRIBUTION A: Approved for public release; unlimited distribution; PA (Public Affairs) Clearance Number 14332.

Experimental Non-Violation of the Bell Inequality

NASA Astrophysics Data System (ADS)

Palmer, Tim

2018-05-01

A finite non-classical framework for physical theory is described which challenges the conclusion that the Bell Inequality has been shown to have been violated experimentally, even approximately. This framework postulates the universe as a deterministic locally causal system evolving on a measure-zero fractal-like geometry $I_U$ in cosmological state space. Consistent with the assumed primacy of $I_U$, and $p$-adic number theory, a non-Euclidean (and hence non-classical) metric $g_p$ is defined on cosmological state space, where $p$ is a large but finite Pythagorean prime. Using number-theoretic properties of spherical triangles, the inequalities violated experimentally are shown to be $g_p$-distant from the CHSH inequality, whose violation would rule out local realism. This result fails in the singular limit $p=\\infty$, at which $g_p$ is Euclidean. Broader implications are discussed.

Biologically driven neural platform invoking parallel electrophoretic separation and urinary metabolite screening.

PubMed

Page, Tessa; Nguyen, Huong Thi Huynh; Hilts, Lindsey; Ramos, Lorena; Hanrahan, Grady

2012-06-01

This work reveals a computational framework for parallel electrophoretic separation of complex biological macromolecules and model urinary metabolites. More specifically, the implementation of a particle swarm optimization (PSO) algorithm on a neural network platform for multiparameter optimization of multiplexed 24-capillary electrophoresis technology with UV detection is highlighted. Two experimental systems were examined: (1) separation of purified rabbit metallothioneins and (2) separation of model toluene urinary metabolites and selected organic acids. Results proved superior to the use of neural networks employing standard back propagation when examining training error, fitting response, and predictive abilities. Simulation runs were obtained as a result of metaheuristic examination of the global search space with experimental responses in good agreement with predicted values. Full separation of selected analytes was realized after employing optimal model conditions. This framework provides guidance for the application of metaheuristic computational tools to aid in future studies involving parallel chemical separation and screening. Adaptable pseudo-code is provided to enable users of varied software packages and modeling framework to implement the PSO algorithm for their desired use.

A Temporal Mining Framework for Classifying Un-Evenly Spaced Clinical Data: An Approach for Building Effective Clinical Decision-Making System.

PubMed

Jane, Nancy Yesudhas; Nehemiah, Khanna Harichandran; Arputharaj, Kannan

2016-01-01

Clinical time-series data acquired from electronic health records (EHR) are liable to temporal complexities such as irregular observations, missing values and time constrained attributes that make the knowledge discovery process challenging. This paper presents a temporal rough set induced neuro-fuzzy (TRiNF) mining framework that handles these complexities and builds an effective clinical decision-making system. TRiNF provides two functionalities namely temporal data acquisition (TDA) and temporal classification. In TDA, a time-series forecasting model is constructed by adopting an improved double exponential smoothing method. The forecasting model is used in missing value imputation and temporal pattern extraction. The relevant attributes are selected using a temporal pattern based rough set approach. In temporal classification, a classification model is built with the selected attributes using a temporal pattern induced neuro-fuzzy classifier. For experimentation, this work uses two clinical time series dataset of hepatitis and thrombosis patients. The experimental result shows that with the proposed TRiNF framework, there is a significant reduction in the error rate, thereby obtaining the classification accuracy on an average of 92.59% for hepatitis and 91.69% for thrombosis dataset. The obtained classification results prove the efficiency of the proposed framework in terms of its improved classification accuracy.

Experimentation in software engineering

NASA Technical Reports Server (NTRS)

Basili, V. R.; Selby, R. W.; Hutchens, D. H.

1986-01-01

Experimentation in software engineering supports the advancement of the field through an iterative learning process. In this paper, a framework for analyzing most of the experimental work performed in software engineering over the past several years is presented. A variety of experiments in the framework is described and their contribution to the software engineering discipline is discussed. Some useful recommendations for the application of the experimental process in software engineering are included.

Predicting the 3D fatigue crack growth rate of small cracks using multimodal data via Bayesian networks: In-situ experiments and crystal plasticity simulations

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

Rovinelli, Andrea; Sangid, Michael D.; Proudhon, Henry

Small crack propagation accounts for most of the fatigue life of engineering structures subject to high cycle fatigue loading conditions. Determining the fatigue crack growth rate of small cracks propagating into polycrystalline engineering alloys is critical to improving fatigue life predictions, thus lowering cost and increasing safety. In this work, cycle-by-cycle data of a small crack propagating in a beta metastable titanium alloy is available via phase and diffraction contrast tomography. Crystal plasticity simulations are used to supplement experimental data regarding the micromechanical fields ahead of the crack tip. Experimental and numerical results are combined into a multimodal dataset andmore » sampled utilizing a non-local data mining procedure. Furthermore, to capture the propensity of body-centered cubic metals to deform according to the pencil-glide model, a non-local driving force is postulated. The proposed driving force serves as the basis to construct a data-driven probabilistic crack propagation framework using Bayesian networks as building blocks. The spatial correlation between the postulated driving force and experimental observations is obtained by analyzing the results of the proposed framework. Results show that the above correlation increases proportionally to the distance from the crack front until the edge of the plastic zone. Moreover, the predictions of the propagation framework show good agreement with experimental observations. Finally, we studied the interaction of a small crack with grain boundaries (GBs) utilizing various slip transmission criteria, revealing the tendency of a crack to cross a GB by propagating along the slip directions minimizing the residual Burgers vector within the GB.« less

Predicting the 3D fatigue crack growth rate of small cracks using multimodal data via Bayesian networks: In-situ experiments and crystal plasticity simulations

NASA Astrophysics Data System (ADS)

Rovinelli, Andrea; Sangid, Michael D.; Proudhon, Henry; Guilhem, Yoann; Lebensohn, Ricardo A.; Ludwig, Wolfgang

2018-06-01

Small crack propagation accounts for most of the fatigue life of engineering structures subject to high cycle fatigue loading conditions. Determining the fatigue crack growth rate of small cracks propagating into polycrystalline engineering alloys is critical to improving fatigue life predictions, thus lowering cost and increasing safety. In this work, cycle-by-cycle data of a small crack propagating in a beta metastable titanium alloy is available via phase and diffraction contrast tomography. Crystal plasticity simulations are used to supplement experimental data regarding the micromechanical fields ahead of the crack tip. Experimental and numerical results are combined into a multimodal dataset and sampled utilizing a non-local data mining procedure. Furthermore, to capture the propensity of body-centered cubic metals to deform according to the pencil-glide model, a non-local driving force is postulated. The proposed driving force serves as the basis to construct a data-driven probabilistic crack propagation framework using Bayesian networks as building blocks. The spatial correlation between the postulated driving force and experimental observations is obtained by analyzing the results of the proposed framework. Results show that the above correlation increases proportionally to the distance from the crack front until the edge of the plastic zone. Moreover, the predictions of the propagation framework show good agreement with experimental observations. Finally, we studied the interaction of a small crack with grain boundaries (GBs) utilizing various slip transmission criteria, revealing the tendency of a crack to cross a GB by propagating along the slip directions minimizing the residual Burgers vector within the GB.

Predicting the 3D fatigue crack growth rate of small cracks using multimodal data via Bayesian networks: In-situ experiments and crystal plasticity simulations

DOE PAGES

Rovinelli, Andrea; Sangid, Michael D.; Proudhon, Henry; ...

2018-03-11

Small crack propagation accounts for most of the fatigue life of engineering structures subject to high cycle fatigue loading conditions. Determining the fatigue crack growth rate of small cracks propagating into polycrystalline engineering alloys is critical to improving fatigue life predictions, thus lowering cost and increasing safety. In this work, cycle-by-cycle data of a small crack propagating in a beta metastable titanium alloy is available via phase and diffraction contrast tomography. Crystal plasticity simulations are used to supplement experimental data regarding the micromechanical fields ahead of the crack tip. Experimental and numerical results are combined into a multimodal dataset andmore » sampled utilizing a non-local data mining procedure. Furthermore, to capture the propensity of body-centered cubic metals to deform according to the pencil-glide model, a non-local driving force is postulated. The proposed driving force serves as the basis to construct a data-driven probabilistic crack propagation framework using Bayesian networks as building blocks. The spatial correlation between the postulated driving force and experimental observations is obtained by analyzing the results of the proposed framework. Results show that the above correlation increases proportionally to the distance from the crack front until the edge of the plastic zone. Moreover, the predictions of the propagation framework show good agreement with experimental observations. Finally, we studied the interaction of a small crack with grain boundaries (GBs) utilizing various slip transmission criteria, revealing the tendency of a crack to cross a GB by propagating along the slip directions minimizing the residual Burgers vector within the GB.« less

Framework for assessing key variable dependencies in loose-abrasive grinding and polishing

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

Taylor, J.S.; Aikens, D.M.; Brown, N.J.

1995-12-01

This memo describes a framework for identifying all key variables that determine the figuring performance of loose-abrasive lapping and polishing machines. This framework is intended as a tool for prioritizing R&D issues, assessing the completeness of process models and experimental data, and for providing a mechanism to identify any assumptions in analytical models or experimental procedures. Future plans for preparing analytical models or performing experiments can refer to this framework in establishing the context of the work.

Digital evaluation of sitting posture comfort in human-vehicle system under Industry 4.0 framework

NASA Astrophysics Data System (ADS)

Tao, Qing; Kang, Jinsheng; Sun, Wenlei; Li, Zhaobo; Huo, Xiao

2016-09-01

Most of the previous studies on the vibration ride comfort of the human-vehicle system were focused only on one or two aspects of the investigation. A hybrid approach which integrates all kinds of investigation methods in real environment and virtual environment is described. The real experimental environment includes the WBV(whole body vibration) test, questionnaires for human subjective sensation and motion capture. The virtual experimental environment includes the theoretical calculation on simplified 5-DOF human body vibration model, the vibration simulation and analysis within ADAMS/VibrationTM module, and the digital human biomechanics and occupational health analysis in Jack software. While the real experimental environment provides realistic and accurate test results, it also serves as core and validation for the virtual experimental environment. The virtual experimental environment takes full advantages of current available vibration simulation and digital human modelling software, and makes it possible to evaluate the sitting posture comfort in a human-vehicle system with various human anthropometric parameters. How this digital evaluation system for car seat comfort design is fitted in the Industry 4.0 framework is also proposed.

Evaluating the role of coherent delocalized phonon-like modes in DNA cyclization

DOE PAGES

Alexandrov, Ludmil B.; Rasmussen, Kim Ø.; Bishop, Alan R.; ...

2017-08-29

The innate flexibility of a DNA sequence is quantified by the Jacobson-Stockmayer’s J-factor, which measures the propensity for DNA loop formation. Recent studies of ultra-short DNA sequences revealed a discrepancy of up to six orders of magnitude between experimentally measured and theoretically predicted J-factors. These large differences suggest that, in addition to the elastic moduli of the double helix, other factors contribute to loop formation. We develop a new theoretical model that explores how coherent delocalized phonon-like modes in DNA provide single-stranded ”flexible hinges” to assist in loop formation. We also combine the Czapla-Swigon-Olson structural model of DNA with ourmore » extended Peyrard-Bishop-Dauxois model and, without changing any of the parameters of the two models, apply this new computational framework to 86 experimentally characterized DNA sequences. Our results demonstrate that the new computational framework can predict J-factors within an order of magnitude of experimental measurements for most ultra-short DNA sequences, while continuing to accurately describe the J-factors of longer sequences. Furthermore, we demonstrate that our computational framework can be used to describe the cyclization of DNA sequences that contain a base pair mismatch. Overall, our results support the conclusion that coherent delocalized phonon-like modes play an important role in DNA cyclization.« less

Evaluating the role of coherent delocalized phonon-like modes in DNA cyclization

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

Alexandrov, Ludmil B.; Rasmussen, Kim Ø.; Bishop, Alan R.

The innate flexibility of a DNA sequence is quantified by the Jacobson-Stockmayer’s J-factor, which measures the propensity for DNA loop formation. Recent studies of ultra-short DNA sequences revealed a discrepancy of up to six orders of magnitude between experimentally measured and theoretically predicted J-factors. These large differences suggest that, in addition to the elastic moduli of the double helix, other factors contribute to loop formation. We develop a new theoretical model that explores how coherent delocalized phonon-like modes in DNA provide single-stranded ”flexible hinges” to assist in loop formation. We also combine the Czapla-Swigon-Olson structural model of DNA with ourmore » extended Peyrard-Bishop-Dauxois model and, without changing any of the parameters of the two models, apply this new computational framework to 86 experimentally characterized DNA sequences. Our results demonstrate that the new computational framework can predict J-factors within an order of magnitude of experimental measurements for most ultra-short DNA sequences, while continuing to accurately describe the J-factors of longer sequences. Furthermore, we demonstrate that our computational framework can be used to describe the cyclization of DNA sequences that contain a base pair mismatch. Overall, our results support the conclusion that coherent delocalized phonon-like modes play an important role in DNA cyclization.« less

Analysis and characterization of graphene-on-substrate devices

NASA Astrophysics Data System (ADS)

Berdebes, Dionisis

The purpose of this MS Thesis is the analysis and characterization of graphene on substrate structures prepared at the Birck Nanotechnology Center-Purdue University/IBM Watson Research Center-N.Y., and characterized under low-field transport conditions. First, a literature survey is conducted, both in theoretical and experimental work on graphene transport phenomena, and the open issues are reported. Next, the theory of low-field transport in graphene is reviewed within a Landauer framework. Experimental results of back-gated graphene-on-substrate devices, prepared by the Appenzeller group, are then presented, followed by an extraction of an energy/temperature dependent backscattering mean free path as the main characterization parameter. A key conclusion is the critical role of contacts in two-probe measurements. In this framework, a non-self-consistent Non Equilibrium Green's Function method is employed for the calculation of the odd and even metal-graphene ballistic interfacial resistance. A good agreement with the relevant experimental work is observed.

Human-assisted sound event recognition for home service robots.

PubMed

Do, Ha Manh; Sheng, Weihua; Liu, Meiqin

This paper proposes and implements an open framework of active auditory learning for a home service robot to serve the elderly living alone at home. The framework was developed to realize the various auditory perception capabilities while enabling a remote human operator to involve in the sound event recognition process for elderly care. The home service robot is able to estimate the sound source position and collaborate with the human operator in sound event recognition while protecting the privacy of the elderly. Our experimental results validated the proposed framework and evaluated auditory perception capabilities and human-robot collaboration in sound event recognition.

A framework for testing and comparing binaural models.

PubMed

Dietz, Mathias; Lestang, Jean-Hugues; Majdak, Piotr; Stern, Richard M; Marquardt, Torsten; Ewert, Stephan D; Hartmann, William M; Goodman, Dan F M

2018-03-01

Auditory research has a rich history of combining experimental evidence with computational simulations of auditory processing in order to deepen our theoretical understanding of how sound is processed in the ears and in the brain. Despite significant progress in the amount of detail and breadth covered by auditory models, for many components of the auditory pathway there are still different model approaches that are often not equivalent but rather in conflict with each other. Similarly, some experimental studies yield conflicting results which has led to controversies. This can be best resolved by a systematic comparison of multiple experimental data sets and model approaches. Binaural processing is a prominent example of how the development of quantitative theories can advance our understanding of the phenomena, but there remain several unresolved questions for which competing model approaches exist. This article discusses a number of current unresolved or disputed issues in binaural modelling, as well as some of the significant challenges in comparing binaural models with each other and with the experimental data. We introduce an auditory model framework, which we believe can become a useful infrastructure for resolving some of the current controversies. It operates models over the same paradigms that are used experimentally. The core of the proposed framework is an interface that connects three components irrespective of their underlying programming language: The experiment software, an auditory pathway model, and task-dependent decision stages called artificial observers that provide the same output format as the test subject. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Komppula, J., E-mail: jani.komppula@jyu.fi; Tarvainen, O.

A theoretical framework for power dissipation in low temperature plasmas in corona equilibrium is developed. The framework is based on fundamental conservation laws and reaction cross sections and is only weakly sensitive to plasma parameters, e.g., electron temperature and density. The theory is applied to low temperature atomic and molecular hydrogen laboratory plasmas for which the plasma heating power dissipation to photon emission, ionization, and chemical potential is calculated. The calculated photon emission is compared to recent experimental results.

Development, Validation, and Application of OSSEs at NASA/GMAO

NASA Technical Reports Server (NTRS)

Errico, Ronald; Prive, Nikki

2015-01-01

During the past several years, NASA Goddard's Global Modeling and Assimilation Office (GMAO) has been developing a framework for conducting Observing System Simulation Experiments (OSSEs). The motivation and design of that framework will be described and a sample of validation results presented. Fundamentals issues will be highlighted, particularly the critical importance of appropriately simulating system errors. Some problems that have just arisen in the newest experimental system will also be mentioned.

Distributed memory parallel Markov random fields using graph partitioning

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

Heinemann, C.; Perciano, T.; Ushizima, D.

Markov random fields (MRF) based algorithms have attracted a large amount of interest in image analysis due to their ability to exploit contextual information about data. Image data generated by experimental facilities, though, continues to grow larger and more complex, making it more difficult to analyze in a reasonable amount of time. Applying image processing algorithms to large datasets requires alternative approaches to circumvent performance problems. Aiming to provide scientists with a new tool to recover valuable information from such datasets, we developed a general purpose distributed memory parallel MRF-based image analysis framework (MPI-PMRF). MPI-PMRF overcomes performance and memory limitationsmore » by distributing data and computations across processors. The proposed approach was successfully tested with synthetic and experimental datasets. Additionally, the performance of the MPI-PMRF framework is analyzed through a detailed scalability study. We show that a performance increase is obtained while maintaining an accuracy of the segmentation results higher than 98%. The contributions of this paper are: (a) development of a distributed memory MRF framework; (b) measurement of the performance increase of the proposed approach; (c) verification of segmentation accuracy in both synthetic and experimental, real-world datasets« less

A simple theoretical framework for understanding heterogeneous differentiation of CD4+ T cells

PubMed Central

2012-01-01

Background CD4+ T cells have several subsets of functional phenotypes, which play critical yet diverse roles in the immune system. Pathogen-driven differentiation of these subsets of cells is often heterogeneous in terms of the induced phenotypic diversity. In vitro recapitulation of heterogeneous differentiation under homogeneous experimental conditions indicates some highly regulated mechanisms by which multiple phenotypes of CD4+ T cells can be generated from a single population of naïve CD4+ T cells. Therefore, conceptual understanding of induced heterogeneous differentiation will shed light on the mechanisms controlling the response of populations of CD4+ T cells under physiological conditions. Results We present a simple theoretical framework to show how heterogeneous differentiation in a two-master-regulator paradigm can be governed by a signaling network motif common to all subsets of CD4+ T cells. With this motif, a population of naïve CD4+ T cells can integrate the signals from their environment to generate a functionally diverse population with robust commitment of individual cells. Notably, two positive feedback loops in this network motif govern three bistable switches, which in turn, give rise to three types of heterogeneous differentiated states, depending upon particular combinations of input signals. We provide three prototype models illustrating how to use this framework to explain experimental observations and make specific testable predictions. Conclusions The process in which several types of T helper cells are generated simultaneously to mount complex immune responses upon pathogenic challenges can be highly regulated, and a simple signaling network motif can be responsible for generating all possible types of heterogeneous populations with respect to a pair of master regulators controlling CD4+ T cell differentiation. The framework provides a mathematical basis for understanding the decision-making mechanisms of CD4+ T cells, and it can be helpful for interpreting experimental results. Mathematical models based on the framework make specific testable predictions that may improve our understanding of this differentiation system. PMID:22697466

On the dynamics of disobedience: experimental investigations of defying unjust authority

PubMed Central

Bocchiaro, Piero; Zimbardo, Philip

2017-01-01

Across six Experimental conditions with university student participants (N=600), we examined some of the dynamics underlying expressed defiance to unjust authority. Results revealed disobedience was best enacted by participants low in right-wing authoritarianism and was more likely to occur when: 1) in physical proximity of other rebels, 2) the authority made two demanding requests instead of one, and 3) there had been an earlier opposition to injustice. Results are discussed within the theoretical framework of bounded rationality. PMID:28761383

On the dynamics of disobedience: experimental investigations of defying unjust authority.

PubMed

Bocchiaro, Piero; Zimbardo, Philip

2017-01-01

Across six Experimental conditions with university student participants (N=600), we examined some of the dynamics underlying expressed defiance to unjust authority. Results revealed disobedience was best enacted by participants low in right-wing authoritarianism and was more likely to occur when: 1) in physical proximity of other rebels, 2) the authority made two demanding requests instead of one, and 3) there had been an earlier opposition to injustice. Results are discussed within the theoretical framework of bounded rationality.

A simple and accurate rule-based modeling framework for simulation of autocrine/paracrine stimulation of glioblastoma cell motility and proliferation by L1CAM in 2-D culture.

PubMed

Caccavale, Justin; Fiumara, David; Stapf, Michael; Sweitzer, Liedeke; Anderson, Hannah J; Gorky, Jonathan; Dhurjati, Prasad; Galileo, Deni S

2017-12-11

Glioblastoma multiforme (GBM) is a devastating brain cancer for which there is no known cure. Its malignancy is due to rapid cell division along with high motility and invasiveness of cells into the brain tissue. Simple 2-dimensional laboratory assays (e.g., a scratch assay) commonly are used to measure the effects of various experimental perturbations, such as treatment with chemical inhibitors. Several mathematical models have been developed to aid the understanding of the motile behavior and proliferation of GBM cells. However, many are mathematically complicated, look at multiple interdependent phenomena, and/or use modeling software not freely available to the research community. These attributes make the adoption of models and simulations of even simple 2-dimensional cell behavior an uncommon practice by cancer cell biologists. Herein, we developed an accurate, yet simple, rule-based modeling framework to describe the in vitro behavior of GBM cells that are stimulated by the L1CAM protein using freely available NetLogo software. In our model L1CAM is released by cells to act through two cell surface receptors and a point of signaling convergence to increase cell motility and proliferation. A simple graphical interface is provided so that changes can be made easily to several parameters controlling cell behavior, and behavior of the cells is viewed both pictorially and with dedicated graphs. We fully describe the hierarchical rule-based modeling framework, show simulation results under several settings, describe the accuracy compared to experimental data, and discuss the potential usefulness for predicting future experimental outcomes and for use as a teaching tool for cell biology students. It is concluded that this simple modeling framework and its simulations accurately reflect much of the GBM cell motility behavior observed experimentally in vitro in the laboratory. Our framework can be modified easily to suit the needs of investigators interested in other similar intrinsic or extrinsic stimuli that influence cancer or other cell behavior. This modeling framework of a commonly used experimental motility assay (scratch assay) should be useful to both researchers of cell motility and students in a cell biology teaching laboratory.

An Experimental Study of Medical Error Explanations: Do Apology, Empathy, Corrective Action, and Compensation Alter Intentions and Attitudes?

PubMed

Nazione, Samantha; Pace, Kristin

2015-01-01

Medical malpractice lawsuits are a growing problem in the United States, and there is much controversy regarding how to best address this problem. The medical error disclosure framework suggests that apologizing, expressing empathy, engaging in corrective action, and offering compensation after a medical error may improve the provider-patient relationship and ultimately help reduce the number of medical malpractice lawsuits patients bring to medical providers. This study provides an experimental examination of the medical error disclosure framework and its effect on amount of money requested in a lawsuit, negative intentions, attitudes, and anger toward the provider after a medical error. Results suggest empathy may play a large role in providing positive outcomes after a medical error.

The pressure and entropy of a unitary Fermi gas with particle-hole fluctuation

NASA Astrophysics Data System (ADS)

Gong, Hao; Ruan, Xiao-Xia; Zong, Hong-Shi

2018-01-01

We calculate the pressure and entropy of a unitary Fermi gas based on universal relations combined with our previous prediction of energy which was calculated within the framework of the non-self-consistent T-matrix approximation with particle-hole fluctuation. The resulting entropy and pressure are compared with the experimental data and the theoretical results without induced interaction. For entropy, we find good agreement between our results with particle-hole fluctuation and the experimental measurements reported by ENS group and MIT experiment. For pressure, our results suffer from a systematic upshift compared to MIT data.

First principle investigation of structural and optical properties of cubic titanium dioxide

NASA Astrophysics Data System (ADS)

Dash, Debashish; Chaudhury, Saurabh; Tripathy, Susanta K.

2018-05-01

This paper presents an analysis of structural and optical properties of cubic titanium dioxide (TiO2) using Orthogonalzed Linear Combinations of Atomic Orbitals (OLCAO) basis set under the framework of Density Functional Theory (DFT). The structural property, specially the lattice constant `a' and the optical properties such as refractive index, extinction coefficient, and reflectivity are investigated and discussed in the energy range of 0-16 eV. Further, the results have compared with previous theoretical as well as with experimental results. It was found that DFT based simulation results are approximation to experimental results.

First-principles analysis of structural and opto-electronic properties of indium tin oxide

NASA Astrophysics Data System (ADS)

Tripathi, Madhvendra Nath; Shida, Kazuhito; Sahara, Ryoji; Mizuseki, Hiroshi; Kawazoe, Yoshiyuki

2012-05-01

Density functional theory (DFT) and DFT + U (DFT with on-site Coulomb repulsion corrections) calculations have been carried out to study the structural and opto-electronic properties of indium tin oxide (ITO) for both the oxidized and reduced environment conditions. Some of the results obtained by DFT calculations differ from the experimental observations, such as uncertain indication for the site preference of tin atom to replace indium atom at b-site or d-site, underestimation of local inward relaxation in the first oxygen polyhedra around tin atom, and also the improper estimation of electronic density of states and hence resulting in an inappropriate optical spectra of ITO. These discrepancies of theoretical outcomes with experimental observations in ITO arise mainly due to the underestimation of the cationic 4d levels within standard DFT calculations. Henceforth, the inclusion of on-site corrections within DFT + U framework significantly modifies the theoretical results in better agreement to the experimental observations. Within this framework, our calculations show that the indium b-site is preferential site over d-site for tin atom substitution in indium oxide under both the oxidized and reduced conditions. Moreover, the calculated average inward relaxation value of 0.16 Å around tin atom is in good agreement with the experimental value of 0.18 Å. Furthermore, DFT + U significantly modify the electronic structure and consequently induce modifications in the calculated optical spectra of ITO.

Non-Markovian quantum processes: Complete framework and efficient characterization

NASA Astrophysics Data System (ADS)

Pollock, Felix A.; Rodríguez-Rosario, César; Frauenheim, Thomas; Paternostro, Mauro; Modi, Kavan

2018-01-01

Currently, there is no systematic way to describe a quantum process with memory solely in terms of experimentally accessible quantities. However, recent technological advances mean we have control over systems at scales where memory effects are non-negligible. The lack of such an operational description has hindered advances in understanding physical, chemical, and biological processes, where often unjustified theoretical assumptions are made to render a dynamical description tractable. This has led to theories plagued with unphysical results and no consensus on what a quantum Markov (memoryless) process is. Here, we develop a universal framework to characterize arbitrary non-Markovian quantum processes. We show how a multitime non-Markovian process can be reconstructed experimentally, and that it has a natural representation as a many-body quantum state, where temporal correlations are mapped to spatial ones. Moreover, this state is expected to have an efficient matrix-product-operator form in many cases. Our framework constitutes a systematic tool for the effective description of memory-bearing open-system evolutions.

A super resolution framework for low resolution document image OCR

NASA Astrophysics Data System (ADS)

Ma, Di; Agam, Gady

2013-01-01

Optical character recognition is widely used for converting document images into digital media. Existing OCR algorithms and tools produce good results from high resolution, good quality, document images. In this paper, we propose a machine learning based super resolution framework for low resolution document image OCR. Two main techniques are used in our proposed approach: a document page segmentation algorithm and a modified K-means clustering algorithm. Using this approach, by exploiting coherence in the document, we reconstruct from a low resolution document image a better resolution image and improve OCR results. Experimental results show substantial gain in low resolution documents such as the ones captured from video.

Some Aspects of Self-Field Effects in Large Vanadium-Based Josephson Junctions

NASA Astrophysics Data System (ADS)

Cristiano, R.; Russo, M.; Di Chiara, A.; Huang, Hesheng; Peluso, G.

1984-03-01

Experiments concerning large V-VxOy-Pb Josephson junctions have been performed. Structures having an overlap-type geometry have been considered. Preliminary experimental results are justified in the framework of the linearized current-phase model.

High energy nucleus-nucleus collisions

NASA Technical Reports Server (NTRS)

Wosiek, B.

1986-01-01

Experimental results on high energy nucleus-nucleus interactions are presented. The data are discussed within the framework of standard super-position models and from the point-of-view of the possible formation of new states of matter in heavy ion collisions.

Understanding of visual attention by adult humans (Homo sapiens): a partial replication of Povinelli, Bierschwale, and Cech (1999).

PubMed

Thomas, Emily; Murphy, Mary; Pitt, Rebecca; Rivers, Angela; Leavens, David A

2008-11-01

Povinelli, Bierschwale, and Cech (1999) reported that when tested on a visual attention task, the behavior of juvenile chimpanzees did not support a high-level understanding of visual attention. This study replicates their research using adult humans and aims to investigate the validity of their experimental design. Participants were trained to respond to pointing cues given by an experimenter, and then tested on their ability to locate hidden objects from visual cues. Povinelli et al.'s assertion that the generalization of pointing to gaze is indicative of a high-level framework was not supported by our findings: Training improved performance only on initial probe trials when the experimenter's gaze was not directed at the baited cup. Furthermore, participants performed above chance on such trials, the same result exhibited by chimpanzees and used as evidence by Povinelli et al. to support a low-level framework. These findings, together with the high performance of participants in an incongruent condition, in which the experimenter pointed to or gazed at an unbaited container, challenge the validity of their experimental design. (PsycINFO Database Record (c) 2008 APA, all rights reserved).

Combining Cryptography with EEG Biometrics

PubMed Central

Kazanavičius, Egidijus; Woźniak, Marcin

2018-01-01

Cryptographic frameworks depend on key sharing for ensuring security of data. While the keys in cryptographic frameworks must be correctly reproducible and not unequivocally connected to the identity of a user, in biometric frameworks this is different. Joining cryptography techniques with biometrics can solve these issues. We present a biometric authentication method based on the discrete logarithm problem and Bose-Chaudhuri-Hocquenghem (BCH) codes, perform its security analysis, and demonstrate its security characteristics. We evaluate a biometric cryptosystem using our own dataset of electroencephalography (EEG) data collected from 42 subjects. The experimental results show that the described biometric user authentication system is effective, achieving an Equal Error Rate (ERR) of 0.024.

Combining Cryptography with EEG Biometrics.

PubMed

Damaševičius, Robertas; Maskeliūnas, Rytis; Kazanavičius, Egidijus; Woźniak, Marcin

2018-01-01

Cryptographic frameworks depend on key sharing for ensuring security of data. While the keys in cryptographic frameworks must be correctly reproducible and not unequivocally connected to the identity of a user, in biometric frameworks this is different. Joining cryptography techniques with biometrics can solve these issues. We present a biometric authentication method based on the discrete logarithm problem and Bose-Chaudhuri-Hocquenghem (BCH) codes, perform its security analysis, and demonstrate its security characteristics. We evaluate a biometric cryptosystem using our own dataset of electroencephalography (EEG) data collected from 42 subjects. The experimental results show that the described biometric user authentication system is effective, achieving an Equal Error Rate (ERR) of 0.024.

Water-Stable Metal-Organic Framework with Three Hydrogen-Bond Acceptors: Versatile Theoretical and Experimental Insights into Adsorption Ability and Thermo-Hydrolytic Stability.

PubMed

Roztocki, Kornel; Lupa, Magdalena; Sławek, Andrzej; Makowski, Wacław; Senkovska, Irena; Kaskel, Stefan; Matoga, Dariusz

2018-03-19

A new microporous cadmium metal-organic framework was synthesized both mechanochemically and in solution by using a sulfonyl-functionalized dicarboxylate linker and an acylhydrazone colinker. The three-dimensional framework is highly stable upon heating to 300 °C as well as in aqueous solutions at elevated temperatures or acidic conditions. The thermally activated material exhibits steep water vapor uptake at low relative pressures at 298 K and excellent recyclability up to 260 °C as confirmed by both quasi-equilibrated temperature-programmed desorption and adsorption (QE-TPDA) method as well as adsorption isotherm measurements. Reversible isotherms and hysteretic isobars recorded for the desorption-adsorption cycles indicate the maximum uptake of 0.19 g/g (at 298 K, up to p/p 0 = 1) or 0.18 g/g (at 1 bar, within 295-375 K range), respectively. The experimental isosteric heat of adsorption (48.9 kJ/mol) indicates noncoordinative interactions of water molecules with the framework. Exchange of the solvent molecules in the as-made material with water, performed in the single-crystal to single-crystal manner, allows direct comparison of both X-ray crystal structures. The single-crystal X-ray diffraction for the water-loaded framework demonstrates the orientation of water clusters in the framework cavities and reveals their strong hydrogen bonding with sulfonyl, acyl, and carboxylate groups of the two linkers. The grand canonical Monte Carlo (GCMC) simulations of H 2 O adsorption corroborate the experimental findings and reveal preferable locations of guest molecules in the framework voids at various pressures. Additionally, both experimental and GCMC simulation insights into the adsorption of CO 2 (at 195 K) on the activated framework are presented.

Toll-like receptor signaling in vertebrates: testing the integration of protein, complex, and pathway data in the protein ontology framework.

PubMed

Arighi, Cecilia; Shamovsky, Veronica; Masci, Anna Maria; Ruttenberg, Alan; Smith, Barry; Natale, Darren A; Wu, Cathy; D'Eustachio, Peter

2015-01-01

The Protein Ontology (PRO) provides terms for and supports annotation of species-specific protein complexes in an ontology framework that relates them both to their components and to species-independent families of complexes. Comprehensive curation of experimentally known forms and annotations thereof is expected to expose discrepancies, differences, and gaps in our knowledge. We have annotated the early events of innate immune signaling mediated by Toll-Like Receptor 3 and 4 complexes in human, mouse, and chicken. The resulting ontology and annotation data set has allowed us to identify species-specific gaps in experimental data and possible functional differences between species, and to employ inferred structural and functional relationships to suggest plausible resolutions of these discrepancies and gaps.

Quantum interval-valued probability: Contextuality and the Born rule

NASA Astrophysics Data System (ADS)

Tai, Yu-Tsung; Hanson, Andrew J.; Ortiz, Gerardo; Sabry, Amr

2018-05-01

We present a mathematical framework based on quantum interval-valued probability measures to study the effect of experimental imperfections and finite precision measurements on defining aspects of quantum mechanics such as contextuality and the Born rule. While foundational results such as the Kochen-Specker and Gleason theorems are valid in the context of infinite precision, they fail to hold in general in a world with limited resources. Here we employ an interval-valued framework to establish bounds on the validity of those theorems in realistic experimental environments. In this way, not only can we quantify the idea of finite-precision measurement within our theory, but we can also suggest a possible resolution of the Meyer-Mermin debate on the impact of finite-precision measurement on the Kochen-Specker theorem.

Photocatalytic degradation of organic dyes by a stable and biocompatible Zn(II) MOF having ferulic acid: Experimental findings and theoretical correlation

NASA Astrophysics Data System (ADS)

Zhou, En-Hong; Li, Bao-Hong; Chen, Wei-Xin; Luo, Zhidong; Liu, Jianqiang; Singh, Amita; Kumar, Abhinav; Jin, Jun-Cheng

2017-12-01

The photocatalytic properties of d10-based metal-organic frameworks (MOFs) have been developed as a potential technology in the photo-degradation of organic dyes. Herein, a biocompatible metal-organic framework (MOF) {[Zn2(fer)2]•0.5H2O}n (1) (fer = ferulic acid) has been selected which shows photocatalytic activity for the degradation of methyl violet (MV) and Rhodamine B (Rh B) in aqueous solution under UV irradiation. The photocatalytic results indicated the 1 exhibit 88% photocatalytic efficiency against Rh B in 100 min, while its against MV was only 54% under the identical experimental conditions. Moreover, a possible mechanism for the photocatalytic activity has proposed by density of states (DOS) calculations.

Neutrino Oscillations with the MINOS, MINOS+, T2K, and NOvA Experiments

DOE PAGES

Nakaya, Tsuyoshi; Plunkett, Robert K.

2016-01-18

Our paper discusses results and near-term prospects of the long-baseline neutrino experiments MINOS, MONOS+, T2K and NOvA. The non-zero value of the third neutrino mixing angle θ 13 allows experimental analysis in a manner which explicitly exhibits appearance and disappearance dependencies on additional parameters associated with mass-hierarchy, CP violation, and any non-maximal θ 23. Our current and near-future experiments begin the era of precision accelerator long-baseline measurements and lay the framework within which future experimental results will be interpreted.

Left Ventricular Endocardium Tracking by Fusion of Biomechanical and Deformable Models

PubMed Central

Gu, Jason

2014-01-01

This paper presents a framework for tracking left ventricular (LV) endocardium through 2D echocardiography image sequence. The framework is based on fusion of biomechanical (BM) model of the heart with the parametric deformable model. The BM model constitutive equation consists of passive and active strain energy functions. The deformations of the LV are obtained by solving the constitutive equations using ABAQUS FEM in each frame in the cardiac cycle. The strain energy functions are defined in two user subroutines for active and passive phases. Average fusion technique is used to fuse the BM and deformable model contours. Experimental results are conducted to verify the detected contours and the results are evaluated by comparing themto a created gold standard. The results and the evaluation proved that the framework has the tremendous potential to track and segment the LV through the whole cardiac cycle. PMID:24587814

Fuzzy entropy thresholding and multi-scale morphological approach for microscopic image enhancement

NASA Astrophysics Data System (ADS)

Zhou, Jiancan; Li, Yuexiang; Shen, Linlin

2017-07-01

Microscopic images provide lots of useful information for modern diagnosis and biological research. However, due to the unstable lighting condition during image capturing, two main problems, i.e., high-level noises and low image contrast, occurred in the generated cell images. In this paper, a simple but efficient enhancement framework is proposed to address the problems. The framework removes image noises using a hybrid method based on wavelet transform and fuzzy-entropy, and enhances the image contrast with an adaptive morphological approach. Experiments on real cell dataset were made to assess the performance of proposed framework. The experimental results demonstrate that our proposed enhancement framework increases the cell tracking accuracy to an average of 74.49%, which outperforms the benchmark algorithm, i.e., 46.18%.

Bose-Einstein correlation within the framework of hadronic mechanics

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

Burande, Chandrakant S.

The Bose-Einstein correlation is the phenomenon in which protons and antiprotons collide at extremely high energies; coalesce one into the other resulting into the fireball of finite dimension. They annihilate each other and produces large number of mesons that remain correlated at distances very large compared to the size of the fireball. It was believed that Einstein’s special relativity and relativistic quantum mechanics are the valid frameworks to represent this phenomenon. Although, these frameworks are incomplete and require arbitrary parameters (chaoticity) to fit the experimental data which are prohibited by the basic axioms of relativistic quantum mechanics, such as thatmore » for the vacuum expectation values. Moreover, correlated mesons can not be treated as a finite set of isolated point-like particles because it is non-local event due to overlapping of wavepackets. Therefore, the Bose-Einstein correlation is incompatible with the axiom of expectation values of quantum mechanics. In contrary, relativistic hadronic mechanics constructed by Santilli allows an exact representation of the experimental data of the Bose-Einstein correlation and restore the validity of the Lorentz and Poincare symmetries under nonlocal and non-Hamiltonian internal effects. Further, F. Cardone and R. Mignani observed that the Bose-Einstein two-point correlation function derived by Santilli is perfectly matched with experimental data at high energy.« less

Model based inference from microvascular measurements: Combining experimental measurements and model predictions using a Bayesian probabilistic approach

PubMed Central

Rasmussen, Peter M.; Smith, Amy F.; Sakadžić, Sava; Boas, David A.; Pries, Axel R.; Secomb, Timothy W.; Østergaard, Leif

2017-01-01

Objective In vivo imaging of the microcirculation and network-oriented modeling have emerged as powerful means of studying microvascular function and understanding its physiological significance. Network-oriented modeling may provide the means of summarizing vast amounts of data produced by high-throughput imaging techniques in terms of key, physiological indices. To estimate such indices with sufficient certainty, however, network-oriented analysis must be robust to the inevitable presence of uncertainty due to measurement errors as well as model errors. Methods We propose the Bayesian probabilistic data analysis framework as a means of integrating experimental measurements and network model simulations into a combined and statistically coherent analysis. The framework naturally handles noisy measurements and provides posterior distributions of model parameters as well as physiological indices associated with uncertainty. Results We applied the analysis framework to experimental data from three rat mesentery networks and one mouse brain cortex network. We inferred distributions for more than five hundred unknown pressure and hematocrit boundary conditions. Model predictions were consistent with previous analyses, and remained robust when measurements were omitted from model calibration. Conclusion Our Bayesian probabilistic approach may be suitable for optimizing data acquisition and for analyzing and reporting large datasets acquired as part of microvascular imaging studies. PMID:27987383

Comparison of hand-craft feature based SVM and CNN based deep learning framework for automatic polyp classification.

PubMed

Younghak Shin; Balasingham, Ilangko

2017-07-01

Colonoscopy is a standard method for screening polyps by highly trained physicians. Miss-detected polyps in colonoscopy are potential risk factor for colorectal cancer. In this study, we investigate an automatic polyp classification framework. We aim to compare two different approaches named hand-craft feature method and convolutional neural network (CNN) based deep learning method. Combined shape and color features are used for hand craft feature extraction and support vector machine (SVM) method is adopted for classification. For CNN approach, three convolution and pooling based deep learning framework is used for classification purpose. The proposed framework is evaluated using three public polyp databases. From the experimental results, we have shown that the CNN based deep learning framework shows better classification performance than the hand-craft feature based methods. It achieves over 90% of classification accuracy, sensitivity, specificity and precision.

A Novel Framework Based on FastICA for High Density Surface EMG Decomposition

PubMed Central

Chen, Maoqi; Zhou, Ping

2015-01-01

This study presents a progressive FastICA peel-off (PFP) framework for high density surface electromyogram (EMG) decomposition. The novel framework is based on a shift-invariant model for describing surface EMG. The decomposition process can be viewed as progressively expanding the set of motor unit spike trains, which is primarily based on FastICA. To overcome the local convergence of FastICA, a “peel off” strategy (i.e. removal of the estimated motor unit action potential (MUAP) trains from the previous step) is used to mitigate the effects of the already identified motor units, so more motor units can be extracted. Moreover, a constrained FastICA is applied to assess the extracted spike trains and correct possible erroneous or missed spikes. These procedures work together to improve the decomposition performance. The proposed framework was validated using simulated surface EMG signals with different motor unit numbers (30, 70, 91) and signal to noise ratios (SNRs) (20, 10, 0 dB). The results demonstrated relatively large numbers of extracted motor units and high accuracies (high F1-scores). The framework was also tested with 111 trials of 64-channel electrode array experimental surface EMG signals during the first dorsal interosseous (FDI) muscle contraction at different intensities. On average 14.1 ± 5.0 motor units were identified from each trial of experimental surface EMG signals. PMID:25775496

Modelling the strength of an aluminium-steel nailed joint

NASA Astrophysics Data System (ADS)

Goldspiegel, Fabien; Mocellin, Katia; Michel, Philippe

2018-05-01

For multi-material applications in automotive industry, a cast aluminium (upper layer) and dual-phase steel (lower layer) superposition joined with High-Speed Nailing process is investigated through an experimental vs numerical framework. Using FORGE® finite-element software, results from joining simulations have been inserted into models in charge of nailed-joint mechanical testings. Numerical Shear and Cross-tensile tests are compared to experimental ones to discuss discrepancy and possible improvements.

Influence of field dependent critical current density on flux profiles in high Tc superconductors

NASA Technical Reports Server (NTRS)

Takacs, S.

1990-01-01

The field distribution for superconducting cylinders and slabs with field dependent critical current densities in combined DC and AC magnetic fields and the corresponding magnetic fluxes are calculated. It is shown that all features of experimental magnetic-field profile measurements can be explained in the framework of field dependent critical current density. Even the quantitative agreement between the experimental and theoretical results using Kim's model is very good.

A geometrical approach to control and controllability of nonlinear dynamical networks

PubMed Central

Wang, Le-Zhi; Su, Ri-Qi; Huang, Zi-Gang; Wang, Xiao; Wang, Wen-Xu; Grebogi, Celso; Lai, Ying-Cheng

2016-01-01

In spite of the recent interest and advances in linear controllability of complex networks, controlling nonlinear network dynamics remains an outstanding problem. Here we develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another, assuming that the former is undesired and the latter is desired. To make our framework practically meaningful, we consider restricted parameter perturbation by imposing two constraints: it must be experimentally realizable and applied only temporarily. We introduce the concept of attractor network, which allows us to formulate a quantifiable controllability framework for nonlinear dynamical networks: a network is more controllable if the attractor network is more strongly connected. We test our control framework using examples from various models of experimental gene regulatory networks and demonstrate the beneficial role of noise in facilitating control. PMID:27076273

A Microfluidics and Agent-Based Modeling Framework for Investigating Spatial Organization in Bacterial Colonies: The Case of Pseudomonas Aeruginosa and H1-Type VI Secretion Interactions.

PubMed

Wilmoth, Jared L; Doak, Peter W; Timm, Andrea; Halsted, Michelle; Anderson, John D; Ginovart, Marta; Prats, Clara; Portell, Xavier; Retterer, Scott T; Fuentes-Cabrera, Miguel

2018-01-01

The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P . aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density and local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models.

A Microfluidics and Agent-Based Modeling Framework for Investigating Spatial Organization in Bacterial Colonies: The Case of Pseudomonas Aeruginosa and H1-Type VI Secretion Interactions

PubMed Central

Wilmoth, Jared L.; Doak, Peter W.; Timm, Andrea; Halsted, Michelle; Anderson, John D.; Ginovart, Marta; Prats, Clara; Portell, Xavier; Retterer, Scott T.; Fuentes-Cabrera, Miguel

2018-01-01

The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P. aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density and local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models. PMID:29467721

Water age and stream solute dynamics at the Hubbard Brook Experimental Forest (US)

NASA Astrophysics Data System (ADS)

Botter, Gianluca; Benettin, Paolo; McGuire, Kevin; Rinaldo, Andrea

2016-04-01

The contribution discusses experimental and modeling results from a headwater catchment at the Hubbard Brook Experimental Forest (New Hampshire, USA) to explore the link between stream solute dynamics and water age. A theoretical framework based on water age dynamics, which represents a general basis for characterizing solute transport at the catchment scale, is used to model both conservative and weathering-derived solutes. Based on the available information about the hydrology of the site, an integrated transport model was developed and used to estimate the relevant hydrochemical fluxes. The model was designed to reproduce the deuterium content of streamflow and allowed for the estimate of catchment water storage and dynamic travel time distributions (TTDs). Within this framework, dissolved silicon and sodium concentration in streamflow were simulated by implementing first-order chemical kinetics based explicitly on dynamic TTD, thus upscaling local geochemical processes to catchment scale. Our results highlight the key role of water stored within the subsoil glacial material in both the short-term and long-term solute circulation at Hubbard Brook. The analysis of the results provided by the calibrated model allowed a robust estimate of the emerging concentration-discharge relationship, streamflow age distributions (including the fraction of event water) and storage size, and their evolution in time due to hydrologic variability.

Transonic Blunt Body Aerodynamic Coefficients Computation

NASA Astrophysics Data System (ADS)

Sancho, Jorge; Vargas, M.; Gonzalez, Ezequiel; Rodriguez, Manuel

2011-05-01

In the framework of EXPERT (European Experimental Re-entry Test-bed) accurate transonic aerodynamic coefficients are of paramount importance for the correct trajectory assessment and parachute deployment. A combined CFD (Computational Fluid Dynamics) modelling and experimental campaign strategy was selected to obtain accurate coefficients. A preliminary set of coefficients were obtained by CFD Euler inviscid computation. Then experimental campaign was performed at DNW facilities at NLR. A profound review of the CFD modelling was done lighten up by WTT results, aimed to obtain reliable values of the coefficients in the future (specially the pitching moment). Study includes different turbulence modelling and mesh sensitivity analysis. Comparison with the WTT results is explored, and lessons learnt are collected.

Characterisation of the LMS propagation channel at L- and S-bands: Narrowband experimental data and channel modelling

NASA Technical Reports Server (NTRS)

Sforza, Mario; Buonomo, Sergio

1993-01-01

During the period 1983-1992 the European Space Agency (ESA) carried out several experimental campaigns to investigate the propagation impairments of the Land Mobile Satellite (LMS) communication channel. A substantial amount of data covering quite a large range of elevation angles, environments, and frequencies was obtained. Results from the data analyses are currently used for system planning and design applications within the framework of the future ESA LMS projects. This comprehensive experimental data base is presently utilized also for channel modeling purposes and preliminary results are given. Cumulative Distribution Functions (PDF) and Duration of Fades (DoF) statistics at different elevation angles and environments were also included.

Automatic Organ Segmentation for CT Scans Based on Super-Pixel and Convolutional Neural Networks.

PubMed

Liu, Xiaoming; Guo, Shuxu; Yang, Bingtao; Ma, Shuzhi; Zhang, Huimao; Li, Jing; Sun, Changjian; Jin, Lanyi; Li, Xueyan; Yang, Qi; Fu, Yu

2018-04-20

Accurate segmentation of specific organ from computed tomography (CT) scans is a basic and crucial task for accurate diagnosis and treatment. To avoid time-consuming manual optimization and to help physicians distinguish diseases, an automatic organ segmentation framework is presented. The framework utilized convolution neural networks (CNN) to classify pixels. To reduce the redundant inputs, the simple linear iterative clustering (SLIC) of super-pixels and the support vector machine (SVM) classifier are introduced. To establish the perfect boundary of organs in one-pixel-level, the pixels need to be classified step-by-step. First, the SLIC is used to cut an image into grids and extract respective digital signatures. Next, the signature is classified by the SVM, and the rough edges are acquired. Finally, a precise boundary is obtained by the CNN, which is based on patches around each pixel-point. The framework is applied to abdominal CT scans of livers and high-resolution computed tomography (HRCT) scans of lungs. The experimental CT scans are derived from two public datasets (Sliver 07 and a Chinese local dataset). Experimental results show that the proposed method can precisely and efficiently detect the organs. This method consumes 38 s/slice for liver segmentation. The Dice coefficient of the liver segmentation results reaches to 97.43%. For lung segmentation, the Dice coefficient is 97.93%. This finding demonstrates that the proposed framework is a favorable method for lung segmentation of HRCT scans.

Like Hercules and the Hydra: Trade-offs and strategies in ecological model-building and experimental design.

PubMed

Inkpen, S Andrew

2016-06-01

Experimental ecologists often invoke trade-offs to describe the constraints they encounter when choosing between alternative experimental designs, such as between laboratory, field, and natural experiments. In making these claims, they tend to rely on Richard Levins' analysis of trade-offs in theoretical model-building. But does Levins' framework apply to experiments? In this paper, I focus this question on one desideratum widely invoked in the modelling literature: generality. Using the case of generality, I assess whether Levins-style treatments of modelling provide workable resources for assessing trade-offs in experimental design. I argue that, of four strategies modellers employ to increase generality, only one may be unproblematically applied to experimental design. Furthermore, modelling desiderata do not have obvious correlates in experimental design, and when we define these desiderata in a way that seem consistent with ecologists' usage, the trade-off framework falls apart. I conclude that a Levins-inspired framework for modelling does not provide the content for a similar approach to experimental practice; this does not, however, mean that it cannot provide the form. Copyright © 2016 Elsevier Ltd. All rights reserved.

Nonlinear and non-Gaussian Bayesian based handwriting beautification

NASA Astrophysics Data System (ADS)

Shi, Cao; Xiao, Jianguo; Xu, Canhui; Jia, Wenhua

2013-03-01

A framework is proposed in this paper to effectively and efficiently beautify handwriting by means of a novel nonlinear and non-Gaussian Bayesian algorithm. In the proposed framework, format and size of handwriting image are firstly normalized, and then typeface in computer system is applied to optimize vision effect of handwriting. The Bayesian statistics is exploited to characterize the handwriting beautification process as a Bayesian dynamic model. The model parameters to translate, rotate and scale typeface in computer system are controlled by state equation, and the matching optimization between handwriting and transformed typeface is employed by measurement equation. Finally, the new typeface, which is transformed from the original one and gains the best nonlinear and non-Gaussian optimization, is the beautification result of handwriting. Experimental results demonstrate the proposed framework provides a creative handwriting beautification methodology to improve visual acceptance.

Active Learning Using Hint Information.

PubMed

Li, Chun-Liang; Ferng, Chun-Sung; Lin, Hsuan-Tien

2015-08-01

The abundance of real-world data and limited labeling budget calls for active learning, an important learning paradigm for reducing human labeling efforts. Many recently developed active learning algorithms consider both uncertainty and representativeness when making querying decisions. However, exploiting representativeness with uncertainty concurrently usually requires tackling sophisticated and challenging learning tasks, such as clustering. In this letter, we propose a new active learning framework, called hinted sampling, which takes both uncertainty and representativeness into account in a simpler way. We design a novel active learning algorithm within the hinted sampling framework with an extended support vector machine. Experimental results validate that the novel active learning algorithm can result in a better and more stable performance than that achieved by state-of-the-art algorithms. We also show that the hinted sampling framework allows improving another active learning algorithm designed from the transductive support vector machine.

M(II)-dipyridylamide-based coordination frameworks (M=Mn, Co, Ni): Structural transformation

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

Tzeng, Biing-Chiau; Selvam, TamilSelvi; Tsai, Miao-Hsin

2016-11-15

A series of 1-D double-zigzag (([M(papx){sub 2}(H{sub 2}O){sub 2}](ClO{sub 4}){sub 2}){sub n}; M=Mn, x=s (1), x=o (3); M=Co, x=s (4), x=o (5); M=Ni, x=s (6), x=o (7)) and 2-D polyrotaxane ([Mn(paps){sub 2}(ClO{sub 4}){sub 2}]{sub n} (2)) frameworks were synthesized by reactions of M(ClO{sub 4}){sub 2} (M=Mn, Co, and Ni) with papx (paps, N,N’-bis(pyridylcarbonyl)-4,4’-diaminodiphenylthioether; papo, N,N’-bis(pyridylcarbonyl)-4,4’-diaminodiphenyl ether), which have been isolated and structurally characterized by X-ray diffraction. Based on powder X-ray diffraction (PXRD) experiments, heating the double-zigzag frameworks underwent structural transformation to give the respective polyrotaxane ones. Moreover, grinding the solid samples of the respective polyrotaxanes in the presence of moisturemore » also resulted in the total conversion to the original double-zigzag frameworks. In this study, we have successfully extended studies to Mn{sup II}, Co{sup II}, and Ni{sup II} frameworks from the previous Zn{sup II}, Cd{sup II}, and Cu{sup II} ones, and interestingly such structural transformation is able to be proven experimentally by powder and single-crystal X-ray diffraction studies as well. - Graphical abstract: 1-D double-zigzag and 2-D polyrotaxane frameworks of M(II)-papx (x=s, o; M=Mn, Co, Ni) frameworks can be interconverted by heating and grinding in the presence of moiture, and such structural transformation has be proven experimentally by powder and single-crystal X-ray diffraction studies.« less

Simultaneous-Fault Diagnosis of Gearboxes Using Probabilistic Committee Machine

PubMed Central

Zhong, Jian-Hua; Wong, Pak Kin; Yang, Zhi-Xin

2016-01-01

This study combines signal de-noising, feature extraction, two pairwise-coupled relevance vector machines (PCRVMs) and particle swarm optimization (PSO) for parameter optimization to form an intelligent diagnostic framework for gearbox fault detection. Firstly, the noises of sensor signals are de-noised by using the wavelet threshold method to lower the noise level. Then, the Hilbert-Huang transform (HHT) and energy pattern calculation are applied to extract the fault features from de-noised signals. After that, an eleven-dimension vector, which consists of the energies of nine intrinsic mode functions (IMFs), maximum value of HHT marginal spectrum and its corresponding frequency component, is obtained to represent the features of each gearbox fault. The two PCRVMs serve as two different fault detection committee members, and they are trained by using vibration and sound signals, respectively. The individual diagnostic result from each committee member is then combined by applying a new probabilistic ensemble method, which can improve the overall diagnostic accuracy and increase the number of detectable faults as compared to individual classifiers acting alone. The effectiveness of the proposed framework is experimentally verified by using test cases. The experimental results show the proposed framework is superior to existing single classifiers in terms of diagnostic accuracies for both single- and simultaneous-faults in the gearbox. PMID:26848665

Simultaneous-Fault Diagnosis of Gearboxes Using Probabilistic Committee Machine.

PubMed

Zhong, Jian-Hua; Wong, Pak Kin; Yang, Zhi-Xin

2016-02-02

This study combines signal de-noising, feature extraction, two pairwise-coupled relevance vector machines (PCRVMs) and particle swarm optimization (PSO) for parameter optimization to form an intelligent diagnostic framework for gearbox fault detection. Firstly, the noises of sensor signals are de-noised by using the wavelet threshold method to lower the noise level. Then, the Hilbert-Huang transform (HHT) and energy pattern calculation are applied to extract the fault features from de-noised signals. After that, an eleven-dimension vector, which consists of the energies of nine intrinsic mode functions (IMFs), maximum value of HHT marginal spectrum and its corresponding frequency component, is obtained to represent the features of each gearbox fault. The two PCRVMs serve as two different fault detection committee members, and they are trained by using vibration and sound signals, respectively. The individual diagnostic result from each committee member is then combined by applying a new probabilistic ensemble method, which can improve the overall diagnostic accuracy and increase the number of detectable faults as compared to individual classifiers acting alone. The effectiveness of the proposed framework is experimentally verified by using test cases. The experimental results show the proposed framework is superior to existing single classifiers in terms of diagnostic accuracies for both single- and simultaneous-faults in the gearbox.

Face liveness detection using shearlet-based feature descriptors

NASA Astrophysics Data System (ADS)

Feng, Litong; Po, Lai-Man; Li, Yuming; Yuan, Fang

2016-07-01

Face recognition is a widely used biometric technology due to its convenience but it is vulnerable to spoofing attacks made by nonreal faces such as photographs or videos of valid users. The antispoof problem must be well resolved before widely applying face recognition in our daily life. Face liveness detection is a core technology to make sure that the input face is a live person. However, this is still very challenging using conventional liveness detection approaches of texture analysis and motion detection. The aim of this paper is to propose a feature descriptor and an efficient framework that can be used to effectively deal with the face liveness detection problem. In this framework, new feature descriptors are defined using a multiscale directional transform (shearlet transform). Then, stacked autoencoders and a softmax classifier are concatenated to detect face liveness. We evaluated this approach using the CASIA Face antispoofing database and replay-attack database. The experimental results show that our approach performs better than the state-of-the-art techniques following the provided protocols of these databases, and it is possible to significantly enhance the security of the face recognition biometric system. In addition, the experimental results also demonstrate that this framework can be easily extended to classify different spoofing attacks.

A Quantitative Theoretical Framework For Protein-Induced Fluorescence Enhancement-Förster-Type Resonance Energy Transfer (PIFE-FRET).

PubMed

Lerner, Eitan; Ploetz, Evelyn; Hohlbein, Johannes; Cordes, Thorben; Weiss, Shimon

2016-07-07

Single-molecule, protein-induced fluorescence enhancement (PIFE) serves as a molecular ruler at molecular distances inaccessible to other spectroscopic rulers such as Förster-type resonance energy transfer (FRET) or photoinduced electron transfer. In order to provide two simultaneous measurements of two distances on different molecular length scales for the analysis of macromolecular complexes, we and others recently combined measurements of PIFE and FRET (PIFE-FRET) on the single molecule level. PIFE relies on steric hindrance of the fluorophore Cy3, which is covalently attached to a biomolecule of interest, to rotate out of an excited-state trans isomer to the cis isomer through a 90° intermediate. In this work, we provide a theoretical framework that accounts for relevant photophysical and kinetic parameters of PIFE-FRET, show how this framework allows the extraction of the fold-decrease in isomerization mobility from experimental data, and show how these results provide information on changes in the accessible volume of Cy3. The utility of this model is then demonstrated for experimental results on PIFE-FRET measurement of different protein-DNA interactions. The proposed model and extracted parameters could serve as a benchmark to allow quantitative comparison of PIFE effects in different biological systems.

Protein solubility modeling

NASA Technical Reports Server (NTRS)

Agena, S. M.; Pusey, M. L.; Bogle, I. D.

1999-01-01

A thermodynamic framework (UNIQUAC model with temperature dependent parameters) is applied to model the salt-induced protein crystallization equilibrium, i.e., protein solubility. The framework introduces a term for the solubility product describing protein transfer between the liquid and solid phase and a term for the solution behavior describing deviation from ideal solution. Protein solubility is modeled as a function of salt concentration and temperature for a four-component system consisting of a protein, pseudo solvent (water and buffer), cation, and anion (salt). Two different systems, lysozyme with sodium chloride and concanavalin A with ammonium sulfate, are investigated. Comparison of the modeled and experimental protein solubility data results in an average root mean square deviation of 5.8%, demonstrating that the model closely follows the experimental behavior. Model calculations and model parameters are reviewed to examine the model and protein crystallization process. Copyright 1999 John Wiley & Sons, Inc.

Statistical Mechanics of Viral Entry

NASA Astrophysics Data System (ADS)

Zhang, Yaojun; Dudko, Olga K.

2015-01-01

Viruses that have lipid-membrane envelopes infect cells by fusing with the cell membrane to release viral genes. Membrane fusion is known to be hindered by high kinetic barriers associated with drastic structural rearrangements—yet viral infection, which occurs by fusion, proceeds on remarkably short time scales. Here, we present a quantitative framework that captures the principles behind the invasion strategy shared by all enveloped viruses. The key to this strategy—ligand-triggered conformational changes in the viral proteins that pull the membranes together—is treated as a set of concurrent, bias field-induced activated rate processes. The framework results in analytical solutions for experimentally measurable characteristics of virus-cell fusion and enables us to express the efficiency of the viral strategy in quantitative terms. The predictive value of the theory is validated through simulations and illustrated through recent experimental data on influenza virus infection.

Liquid 4He at Zero Temperature and the STLS Scheme

NASA Astrophysics Data System (ADS)

Doroudi, A.

2007-07-01

Within the framework of the self-consistent scheme proposed by Singwi, Tosi, Land and Sjölander (STLS) for an interacting system we study the properties of superfluid liquid 4He. By employing the Aziz potential (HFD-B) as the interaction potential between helium atoms, we have calculated the static structure factor, the pair-correlation function, the elementary excitation spectrum and the effective two-body interaction as a function of wave-vector, for different densities. Our results show considerable improvement over the Ng-Singwi’s model potential of a hard core plus an attractive tail and are comparable with experimental data. We have compared our results with experimental data and with the results of some theoretical models. Agreement between our results and the experimental data for the static structure factor for the small k values is fairly good.

A framework for accelerated phototrophic bioprocess development: integration of parallelized microscale cultivation, laboratory automation and Kriging-assisted experimental design.

PubMed

Morschett, Holger; Freier, Lars; Rohde, Jannis; Wiechert, Wolfgang; von Lieres, Eric; Oldiges, Marco

2017-01-01

Even though microalgae-derived biodiesel has regained interest within the last decade, industrial production is still challenging for economic reasons. Besides reactor design, as well as value chain and strain engineering, laborious and slow early-stage parameter optimization represents a major drawback. The present study introduces a framework for the accelerated development of phototrophic bioprocesses. A state-of-the-art micro-photobioreactor supported by a liquid-handling robot for automated medium preparation and product quantification was used. To take full advantage of the technology's experimental capacity, Kriging-assisted experimental design was integrated to enable highly efficient execution of screening applications. The resulting platform was used for medium optimization of a lipid production process using Chlorella vulgaris toward maximum volumetric productivity. Within only four experimental rounds, lipid production was increased approximately threefold to 212 ± 11 mg L -1  d -1 . Besides nitrogen availability as a key parameter, magnesium, calcium and various trace elements were shown to be of crucial importance. Here, synergistic multi-parameter interactions as revealed by the experimental design introduced significant further optimization potential. The integration of parallelized microscale cultivation, laboratory automation and Kriging-assisted experimental design proved to be a fruitful tool for the accelerated development of phototrophic bioprocesses. By means of the proposed technology, the targeted optimization task was conducted in a very timely and material-efficient manner.

A novel speckle pattern—Adaptive digital image correlation approach with robust strain calculation

NASA Astrophysics Data System (ADS)

Cofaru, Corneliu; Philips, Wilfried; Van Paepegem, Wim

2012-02-01

Digital image correlation (DIC) has seen widespread acceptance and usage as a non-contact method for the determination of full-field displacements and strains in experimental mechanics. The advances of imaging hardware in the last decades led to high resolution and speed cameras being more affordable than in the past making large amounts of data image available for typical DIC experimental scenarios. The work presented in this paper is aimed at maximizing both the accuracy and speed of DIC methods when employed with such images. A low-level framework for speckle image partitioning which replaces regularly shaped blocks with image-adaptive cells in the displacement calculation is introduced. The Newton-Raphson DIC method is modified to use the image pixels of the cells and to perform adaptive regularization to increase the spatial consistency of the displacements. Furthermore, a novel robust framework for strain calculation based also on the Newton-Raphson algorithm is introduced. The proposed methods are evaluated in five experimental scenarios, out of which four use numerically deformed images and one uses real experimental data. Results indicate that, as the desired strain density increases, significant computational gains can be obtained while maintaining or improving accuracy and rigid-body rotation sensitivity.

FRAN and RBF-PSO as two components of a hyper framework to recognize protein folds.

PubMed

Abbasi, Elham; Ghatee, Mehdi; Shiri, M E

2013-09-01

In this paper, an intelligent hyper framework is proposed to recognize protein folds from its amino acid sequence which is a fundamental problem in bioinformatics. This framework includes some statistical and intelligent algorithms for proteins classification. The main components of the proposed framework are the Fuzzy Resource-Allocating Network (FRAN) and the Radial Bases Function based on Particle Swarm Optimization (RBF-PSO). FRAN applies a dynamic method to tune up the RBF network parameters. Due to the patterns complexity captured in protein dataset, FRAN classifies the proteins under fuzzy conditions. Also, RBF-PSO applies PSO to tune up the RBF classifier. Experimental results demonstrate that FRAN improves prediction accuracy up to 51% and achieves acceptable multi-class results for protein fold prediction. Although RBF-PSO provides reasonable results for protein fold recognition up to 48%, it is weaker than FRAN in some cases. However the proposed hyper framework provides an opportunity to use a great range of intelligent methods and can learn from previous experiences. Thus it can avoid the weakness of some intelligent methods in terms of memory, computational time and static structure. Furthermore, the performance of this system can be enhanced throughout the system life-cycle. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Microfluidics and Agent-Based Modeling Framework for Investigating Spatial Organization in Bacterial Colonies: The Case of Pseudomonas Aeruginosa and H1-Type VI Secretion Interactions

DOE PAGES

Wilmoth, Jared L.; Doak, Peter W.; Timm, Andrea; ...

2018-02-06

The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P. aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density andmore » local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models.« less

A Microfluidics and Agent-Based Modeling Framework for Investigating Spatial Organization in Bacterial Colonies: The Case of Pseudomonas Aeruginosa and H1-Type VI Secretion Interactions

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

Wilmoth, Jared L.; Doak, Peter W.; Timm, Andrea

The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P. aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density andmore » local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models.« less

The Design and Analysis of Transposon-Insertion Sequencing Experiments

PubMed Central

Chao, Michael C.; Abel, Sören; Davis, Brigid M.; Waldor, Matthew K.

2016-01-01

Preface Transposon-insertion sequencing (TIS) is a powerful approach that can be widely applied to genome-wide definition of loci that are required for growth in diverse conditions. However, experimental design choices and stochastic biological processes can heavily influence the results of TIS experiments and affect downstream statistical analysis. Here, we discuss TIS experimental parameters and how these factors relate to the benefits and limitations of the various statistical frameworks that can be applied to computational analysis of TIS data. PMID:26775926

Decay properties of charm and beauty open flavour mesons

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

Kumar Rai, Ajay; Vinodkumar, P. C.

The masses of S and P states, pseudoscalar and vector decay constants, leptonic, semileptonic decay widths of charm (D) and beauty (B) open flavour mesons have been computed in the framework of Coulomb and power potential of the form V(r) = -({alpha}{sub c}/r)+Ar{sup v}. The results are compared with other theoretical as well as experimental results.

A motion deblurring method with long/short exposure image pairs

NASA Astrophysics Data System (ADS)

Cui, Guangmang; Hua, Weiping; Zhao, Jufeng; Gong, Xiaoli; Zhu, Liyao

2018-01-01

In this paper, a motion deblurring method with long/short exposure image pairs is presented. The long/short exposure image pairs are captured for the same scene under different exposure time. The image pairs are treated as the input of the deblurring method and more information could be used to obtain a deblurring result with high image quality. Firstly, the luminance equalization process is carried out to the short exposure image. And the blur kernel is estimated with the image pair under the maximum a posteriori (MAP) framework using conjugate gradient algorithm. Then a L0 image smoothing based denoising method is applied to the luminance equalized image. And the final deblurring result is obtained with the gain controlled residual image deconvolution process with the edge map as the gain map. Furthermore, a real experimental optical system is built to capture the image pair in order to demonstrate the effectiveness of the proposed deblurring framework. The long/short image pairs are obtained under different exposure time and camera gain control. Experimental results show that the proposed method could provide a superior deblurring result in both subjective and objective assessment compared with other deblurring approaches.

Structural evolution of 2D microporous covalent triazine-based framework toward the study of high-performance supercapacitors.

PubMed

Hao, Long; Ning, Jing; Luo, Bin; Wang, Bin; Zhang, Yunbo; Tang, Zhihong; Yang, Junhe; Thomas, Arne; Zhi, Linjie

2015-01-14

A series of nitrogen-containing micropore-donimated materials, porous triazine-based frameworks (PTFs), are constructed through the structural evolution of a 2D microporous covalent triazine-based framework. The PTFs feature predictable and controllable nitrogen doping and pore structures, which serve as a model-like system to more deeply understand the heteroatom effect and micropore effect in ionic liquid-based supercapacitors. The experimental results reveal that the nitrogen doping can enhance the supercapacitor performance mainly through affecting the relative permittivity of the electrode materials. Although microspores' contribution is not as obvious as the doped nitrogen, the great performances of the micropore-dominated PTF suggest that micropore-dominated materials still have great potential in ionic liquid-based supercapacitors.

A Unified Framework for Complex Networks with Degree Trichotomy Based on Markov Chains.

PubMed

Hui, David Shui Wing; Chen, Yi-Chao; Zhang, Gong; Wu, Weijie; Chen, Guanrong; Lui, John C S; Li, Yingtao

2017-06-16

This paper establishes a Markov chain model as a unified framework for describing the evolution processes in complex networks. The unique feature of the proposed model is its capability in addressing the formation mechanism that can reflect the "trichotomy" observed in degree distributions, based on which closed-form solutions can be derived. Important special cases of the proposed unified framework are those classical models, including Poisson, Exponential, Power-law distributed networks. Both simulation and experimental results demonstrate a good match of the proposed model with real datasets, showing its superiority over the classical models. Implications of the model to various applications including citation analysis, online social networks, and vehicular networks design, are also discussed in the paper.

A Software Framework for Aircraft Simulation

NASA Technical Reports Server (NTRS)

Curlett, Brian P.

2008-01-01

The National Aeronautics and Space Administration Dryden Flight Research Center has a long history in developing simulations of experimental fixed-wing aircraft from gliders to suborbital vehicles on platforms ranging from desktop simulators to pilot-in-the-loop/aircraft-in-the-loop simulators. Regardless of the aircraft or simulator hardware, much of the software framework is common to all NASA Dryden simulators. Some of this software has withstood the test of time, but in recent years the push toward high-fidelity user-friendly simulations has resulted in some significant changes. This report presents an overview of the current NASA Dryden simulation software framework and capabilities with an emphasis on the new features that have permitted NASA to develop more capable simulations while maintaining the same staffing levels.

NoSQL Based 3D City Model Management System

NASA Astrophysics Data System (ADS)

Mao, B.; Harrie, L.; Cao, J.; Wu, Z.; Shen, J.

2014-04-01

To manage increasingly complicated 3D city models, a framework based on NoSQL database is proposed in this paper. The framework supports import and export of 3D city model according to international standards such as CityGML, KML/COLLADA and X3D. We also suggest and implement 3D model analysis and visualization in the framework. For city model analysis, 3D geometry data and semantic information (such as name, height, area, price and so on) are stored and processed separately. We use a Map-Reduce method to deal with the 3D geometry data since it is more complex, while the semantic analysis is mainly based on database query operation. For visualization, a multiple 3D city representation structure CityTree is implemented within the framework to support dynamic LODs based on user viewpoint. Also, the proposed framework is easily extensible and supports geoindexes to speed up the querying. Our experimental results show that the proposed 3D city management system can efficiently fulfil the analysis and visualization requirements.

A sampling framework for incorporating quantitative mass spectrometry data in protein interaction analysis.

PubMed

Tucker, George; Loh, Po-Ru; Berger, Bonnie

2013-10-04

Comprehensive protein-protein interaction (PPI) maps are a powerful resource for uncovering the molecular basis of genetic interactions and providing mechanistic insights. Over the past decade, high-throughput experimental techniques have been developed to generate PPI maps at proteome scale, first using yeast two-hybrid approaches and more recently via affinity purification combined with mass spectrometry (AP-MS). Unfortunately, data from both protocols are prone to both high false positive and false negative rates. To address these issues, many methods have been developed to post-process raw PPI data. However, with few exceptions, these methods only analyze binary experimental data (in which each potential interaction tested is deemed either observed or unobserved), neglecting quantitative information available from AP-MS such as spectral counts. We propose a novel method for incorporating quantitative information from AP-MS data into existing PPI inference methods that analyze binary interaction data. Our approach introduces a probabilistic framework that models the statistical noise inherent in observations of co-purifications. Using a sampling-based approach, we model the uncertainty of interactions with low spectral counts by generating an ensemble of possible alternative experimental outcomes. We then apply the existing method of choice to each alternative outcome and aggregate results over the ensemble. We validate our approach on three recent AP-MS data sets and demonstrate performance comparable to or better than state-of-the-art methods. Additionally, we provide an in-depth discussion comparing the theoretical bases of existing approaches and identify common aspects that may be key to their performance. Our sampling framework extends the existing body of work on PPI analysis using binary interaction data to apply to the richer quantitative data now commonly available through AP-MS assays. This framework is quite general, and many enhancements are likely possible. Fruitful future directions may include investigating more sophisticated schemes for converting spectral counts to probabilities and applying the framework to direct protein complex prediction methods.

A framework for learning and planning against switching strategies in repeated games

NASA Astrophysics Data System (ADS)

Hernandez-Leal, Pablo; Munoz de Cote, Enrique; Sucar, L. Enrique

2014-04-01

Intelligent agents, human or artificial, often change their behaviour as they interact with other agents. For an agent to optimise its performance when interacting with such agents, it must be capable of detecting and adapting according to such changes. This work presents an approach on how to effectively deal with non-stationary switching opponents in a repeated game context. Our main contribution is a framework for online learning and planning against opponents that switch strategies. We present how two opponent modelling techniques work within the framework and prove the usefulness of the approach experimentally in the iterated prisoner's dilemma, when the opponent is modelled as an agent that switches between different strategies (e.g. TFT, Pavlov and Bully). The results of both models were compared against each other and against a state-of-the-art non-stationary reinforcement learning technique. Results reflect that our approach obtains competitive results without needing an offline training phase, as opposed to the state-of-the-art techniques.

Template-Framework Interactions in Tetraethylammonium-Directed Zeolite Synthesis

DOE PAGES

Schmidt, Joel E.; Fu, Donglong; Deem, Michael W.; ...

2016-11-22

Zeolites, having widespread applications in chemical industries, are often synthesized using organic templates. These can be cost-prohibitive, motivating investigations into their role in promoting crystallization. Herein, the relationship between framework structure, chemical composition, synthesis conditions and the conformation of the occluded, economical template tetraethylammonium (TEA +) has been systematically examined by experimental and computational means. The results show two distinct regimes of occluded conformer tendencies: 1) In frameworks with a large stabilization energy difference, only a single conformer was found (BEA, LTA and MFI). 2) In the frameworks with small stabilization energy differences (AEI, AFI, CHA and MOR), less thanmore » the interconversion of TEA + in solution, a heteroatom-dependent (Al, B, Co, Mn, Ti, Zn) distribution of conformers was observed. Our findings demonstrate that host–guest chemistry principles, including electrostatic interactions and coordination chemistry, are as important as ideal pore-filling.« less

RIPOSTE: a framework for improving the design and analysis of laboratory-based research.

PubMed

Masca, Nicholas Gd; Hensor, Elizabeth Ma; Cornelius, Victoria R; Buffa, Francesca M; Marriott, Helen M; Eales, James M; Messenger, Michael P; Anderson, Amy E; Boot, Chris; Bunce, Catey; Goldin, Robert D; Harris, Jessica; Hinchliffe, Rod F; Junaid, Hiba; Kingston, Shaun; Martin-Ruiz, Carmen; Nelson, Christopher P; Peacock, Janet; Seed, Paul T; Shinkins, Bethany; Staples, Karl J; Toombs, Jamie; Wright, Adam Ka; Teare, M Dawn

2015-05-07

Lack of reproducibility is an ongoing problem in some areas of the biomedical sciences. Poor experimental design and a failure to engage with experienced statisticians at key stages in the design and analysis of experiments are two factors that contribute to this problem. The RIPOSTE (Reducing IrreProducibility in labOratory STudiEs) framework has been developed to support early and regular discussions between scientists and statisticians in order to improve the design, conduct and analysis of laboratory studies and, therefore, to reduce irreproducibility. This framework is intended for use during the early stages of a research project, when specific questions or hypotheses are proposed. The essential points within the framework are explained and illustrated using three examples (a medical equipment test, a macrophage study and a gene expression study). Sound study design minimises the possibility of bias being introduced into experiments and leads to higher quality research with more reproducible results.

Securing Real-Time Sessions in an IMS-Based Architecture

NASA Astrophysics Data System (ADS)

Cennamo, Paolo; Fresa, Antonio; Longo, Maurizio; Postiglione, Fabio; Robustelli, Anton Luca; Toro, Francesco

The emerging all-IP mobile network infrastructures based on 3rd Generation IP Multimedia Subsystem philosophy are characterised by radio access technology independence and ubiquitous connectivity for mobile users. Currently, great focus is being devoted to security issues since most of the security threats presently affecting the public Internet domain, and the upcoming ones as well, are going to be suffered by mobile users in the years to come. While a great deal of research activity, together with standardisation efforts and experimentations, is carried out on mechanisms for signalling protection, very few integrated frameworks for real-time multimedia data protection have been proposed in a context of IP Multimedia Subsystem, and even fewer experimental results based on testbeds are available. In this paper, after a general overview of the security issues arising in an advanced IP Multimedia Subsystem scenario, a comprehensive infrastructure for real-time multimedia data protection, based on the adoption of the Secure Real-Time Protocol, is proposed; then, the development of a testbed incorporating such functionalities, including mechanisms for key management and cryptographic context transfer, and allowing the setup of Secure Real-Time Protocol sessions is presented; finally, experimental results are provided together with quantitative assessments and comparisons of system performances for audio sessions with and without the adoption of the Secure Real-Time Protocol framework.

Experimental validation for thermal transmittances of window shading systems with perimeter gaps

DOE PAGES

Hart, Robert; Goudey, Howdy; Curcija, D. Charlie

2018-02-22

Virtually all residential and commercial windows in the U.S. have some form of window attachment, but few have been designed for energy savings. ISO 15099 presents a simulation framework to determine thermal performance of window attachments, but the model has not been validated for these products. This paper outlines a review and validation of the ISO 15099 centre-of-glass heat transfer correlations for perimeter gaps (top, bottom, and side) in naturally ventilated cavities through measurement and simulation. The thermal transmittance impact due to dimensional variations of these gaps is measured experimentally, simulated using computational fluid dynamics, and simulated utilizing simplified correlationsmore » from ISO 15099. Results show that the ISO 15099 correlations produce a mean error between measured and simulated heat flux of 2.5 ± 7%. These tolerances are similar to those obtained from sealed cavity comparisons and are deemed acceptable within the ISO 15099 framework.« less

Dynamic steady-state analysis of crack propagation in rubber-like solids using an extended finite element method

NASA Astrophysics Data System (ADS)

Kroon, Martin

2012-01-01

In the present study, a computational framework for studying high-speed crack growth in rubber-like solids under conditions of plane stress and steady-state is proposed. Effects of inertia, viscoelasticity and finite strains are included. The main purpose of the study is to examine the contribution of viscoelastic dissipation to the total work of fracture required to propagate a crack in a rubber-like solid. The computational framework builds upon a previous work by the present author (Kroon in Int J Fract 169:49-60, 2011). The model was fully able to predict experimental results in terms of the local surface energy at the crack tip and the total energy release rate at different crack speeds. The predicted distributions of stress and dissipation around the propagating crack tip are presented. The predicted crack tip profiles also agree qualitatively with experimental findings.

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

Sava Gallis, Dorina F.; Ermanoski, Ivan; Greathouse, Jeffrey A.

Here, we present a combined experimental and Grand Canonical Monte Carlo (GCMC) modeling study on the adsorption of iodine in three classes of nanoporous materials: activated charcoals, zeolites, and metal–organic frameworks (MOFs). Iodine adsorption profiles were measured for the first time in situ, with a uniquely designed sorption apparatus. It was determined that pore size and pore environment are responsible for a dynamic adsorption profile, correlated with distinct pressure ranges. At pressures below 0.3 atm, iodine adsorption is governed by a combination of small pores and extra-framework components (e.g., Ag+ ions in the zeolite mordenite). At regimes above 0.3 atm,more » the amount of iodine gas stored relates with an increase in pore size and specific surface area. GCMC results validate the trends noted experimentally and in addition provide a measure of the strength of the adsorbate–adsorbent interactions in these materials.« less

Improve Biomedical Information Retrieval using Modified Learning to Rank Methods.

PubMed

Xu, Bo; Lin, Hongfei; Lin, Yuan; Ma, Yunlong; Yang, Liang; Wang, Jian; Yang, Zhihao

2016-06-14

In these years, the number of biomedical articles has increased exponentially, which becomes a problem for biologists to capture all the needed information manually. Information retrieval technologies, as the core of search engines, can deal with the problem automatically, providing users with the needed information. However, it is a great challenge to apply these technologies directly for biomedical retrieval, because of the abundance of domain specific terminologies. To enhance biomedical retrieval, we propose a novel framework based on learning to rank. Learning to rank is a series of state-of-the-art information retrieval techniques, and has been proved effective in many information retrieval tasks. In the proposed framework, we attempt to tackle the problem of the abundance of terminologies by constructing ranking models, which focus on not only retrieving the most relevant documents, but also diversifying the searching results to increase the completeness of the resulting list for a given query. In the model training, we propose two novel document labeling strategies, and combine several traditional retrieval models as learning features. Besides, we also investigate the usefulness of different learning to rank approaches in our framework. Experimental results on TREC Genomics datasets demonstrate the effectiveness of our framework for biomedical information retrieval.

Gene Profiling in Experimental Models of Eye Growth: Clues to Myopia Pathogenesis

PubMed Central

Stone, Richard A.; Khurana, Tejvir S.

2010-01-01

To understand the complex regulatory pathways that underlie the development of refractive errors, expression profiling has evaluated gene expression in ocular tissues of well-characterized experimental models that alter postnatal eye growth and induce refractive errors. Derived from a variety of platforms (e.g. differential display, spotted microarrays or Affymetrix GeneChips), gene expression patterns are now being identified in species that include chicken, mouse and primate. Reconciling available results is hindered by varied experimental designs and analytical/statistical features. Continued application of these methods offers promise to provide the much-needed mechanistic framework to develop therapies to normalize refractive development in children. PMID:20363242

An Efficient Framework for Development of Task-Oriented Dialog Systems in a Smart Home Environment.

PubMed

Park, Youngmin; Kang, Sangwoo; Seo, Jungyun

2018-05-16

In recent times, with the increasing interest in conversational agents for smart homes, task-oriented dialog systems are being actively researched. However, most of these studies are focused on the individual modules of such a system, and there is an evident lack of research on a dialog framework that can integrate and manage the entire dialog system. Therefore, in this study, we propose a framework that enables the user to effectively develop an intelligent dialog system. The proposed framework ontologically expresses the knowledge required for the task-oriented dialog system's process and can build a dialog system by editing the dialog knowledge. In addition, the framework provides a module router that can indirectly run externally developed modules. Further, it enables a more intelligent conversation by providing a hierarchical argument structure (HAS) to manage the various argument representations included in natural language sentences. To verify the practicality of the framework, an experiment was conducted in which developers without any previous experience in developing a dialog system developed task-oriented dialog systems using the proposed framework. The experimental results show that even beginner dialog system developers can develop a high-level task-oriented dialog system.

An Efficient Framework for Development of Task-Oriented Dialog Systems in a Smart Home Environment

PubMed Central

Park, Youngmin; Kang, Sangwoo; Seo, Jungyun

2018-01-01

In recent times, with the increasing interest in conversational agents for smart homes, task-oriented dialog systems are being actively researched. However, most of these studies are focused on the individual modules of such a system, and there is an evident lack of research on a dialog framework that can integrate and manage the entire dialog system. Therefore, in this study, we propose a framework that enables the user to effectively develop an intelligent dialog system. The proposed framework ontologically expresses the knowledge required for the task-oriented dialog system’s process and can build a dialog system by editing the dialog knowledge. In addition, the framework provides a module router that can indirectly run externally developed modules. Further, it enables a more intelligent conversation by providing a hierarchical argument structure (HAS) to manage the various argument representations included in natural language sentences. To verify the practicality of the framework, an experiment was conducted in which developers without any previous experience in developing a dialog system developed task-oriented dialog systems using the proposed framework. The experimental results show that even beginner dialog system developers can develop a high-level task-oriented dialog system. PMID:29772668

Consideration of the Aluminum Distribution in Zeolites in Theoretical and Experimental Catalysis Research

DOE PAGES

Knott, Brandon C.; Nimlos, Claire T.; Robichaud, David J.; ...

2017-12-11

Research efforts in zeolite catalysis have become increasingly cognizant of the diversity in structure and function resulting from the distribution of framework aluminum atoms, through emerging reports of catalytic phenomena that fall outside those recognizable as the shape-selective ones emblematic of its earlier history. Molecular-level descriptions of how active-site distributions affect catalysis are an aspirational goal articulated frequently in experimental and theoretical research, yet they are limited by imprecise knowledge of the structure and behavior of the zeolite materials under interrogation. In experimental research, higher precision can result from more reliable control of structure during synthesis and from more robustmore » and quantitative structural and kinetic characterization probes. In theoretical research, construction of models with specific aluminum locations and distributions seldom capture the heterogeneity inherent to the materials studied by experiment. In this Perspective, we discuss research findings that appropriately frame the challenges in developing more predictive synthesis-structure-function relations for zeolites, highlighting studies on ZSM-5 zeolites that are among the most structurally complex molecular sieve frameworks and the most widely studied because of their versatility in commercial applications. We discuss research directions to address these challenges and forge stronger connections between zeolite structure, composition, and active sites to catalytic function. Such connections promise to aid in bridging the findings of theoretical and experimental catalysis research, and transforming zeolite active site design from an empirical endeavor into a more predictable science founded on validated models.« less

Consideration of the Aluminum Distribution in Zeolites in Theoretical and Experimental Catalysis Research

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

Knott, Brandon C.; Nimlos, Claire T.; Robichaud, David J.

Research efforts in zeolite catalysis have become increasingly cognizant of the diversity in structure and function resulting from the distribution of framework aluminum atoms, through emerging reports of catalytic phenomena that fall outside those recognizable as the shape-selective ones emblematic of its earlier history. Molecular-level descriptions of how active-site distributions affect catalysis are an aspirational goal articulated frequently in experimental and theoretical research, yet they are limited by imprecise knowledge of the structure and behavior of the zeolite materials under interrogation. In experimental research, higher precision can result from more reliable control of structure during synthesis and from more robustmore » and quantitative structural and kinetic characterization probes. In theoretical research, construction of models with specific aluminum locations and distributions seldom capture the heterogeneity inherent to the materials studied by experiment. In this Perspective, we discuss research findings that appropriately frame the challenges in developing more predictive synthesis-structure-function relations for zeolites, highlighting studies on ZSM-5 zeolites that are among the most structurally complex molecular sieve frameworks and the most widely studied because of their versatility in commercial applications. We discuss research directions to address these challenges and forge stronger connections between zeolite structure, composition, and active sites to catalytic function. Such connections promise to aid in bridging the findings of theoretical and experimental catalysis research, and transforming zeolite active site design from an empirical endeavor into a more predictable science founded on validated models.« less

Pyff - a pythonic framework for feedback applications and stimulus presentation in neuroscience.

PubMed

Venthur, Bastian; Scholler, Simon; Williamson, John; Dähne, Sven; Treder, Matthias S; Kramarek, Maria T; Müller, Klaus-Robert; Blankertz, Benjamin

2010-01-01

This paper introduces Pyff, the Pythonic feedback framework for feedback applications and stimulus presentation. Pyff provides a platform-independent framework that allows users to develop and run neuroscientific experiments in the programming language Python. Existing solutions have mostly been implemented in C++, which makes for a rather tedious programming task for non-computer-scientists, or in Matlab, which is not well suited for more advanced visual or auditory applications. Pyff was designed to make experimental paradigms (i.e., feedback and stimulus applications) easily programmable. It includes base classes for various types of common feedbacks and stimuli as well as useful libraries for external hardware such as eyetrackers. Pyff is also equipped with a steadily growing set of ready-to-use feedbacks and stimuli. It can be used as a standalone application, for instance providing stimulus presentation in psychophysics experiments, or within a closed loop such as in biofeedback or brain-computer interfacing experiments. Pyff communicates with other systems via a standardized communication protocol and is therefore suitable to be used with any system that may be adapted to send its data in the specified format. Having such a general, open-source framework will help foster a fruitful exchange of experimental paradigms between research groups. In particular, it will decrease the need of reprogramming standard paradigms, ease the reproducibility of published results, and naturally entail some standardization of stimulus presentation.

Pyff – A Pythonic Framework for Feedback Applications and Stimulus Presentation in Neuroscience

PubMed Central

Venthur, Bastian; Scholler, Simon; Williamson, John; Dähne, Sven; Treder, Matthias S.; Kramarek, Maria T.; Müller, Klaus-Robert; Blankertz, Benjamin

2010-01-01

This paper introduces Pyff, the Pythonic feedback framework for feedback applications and stimulus presentation. Pyff provides a platform-independent framework that allows users to develop and run neuroscientific experiments in the programming language Python. Existing solutions have mostly been implemented in C++, which makes for a rather tedious programming task for non-computer-scientists, or in Matlab, which is not well suited for more advanced visual or auditory applications. Pyff was designed to make experimental paradigms (i.e., feedback and stimulus applications) easily programmable. It includes base classes for various types of common feedbacks and stimuli as well as useful libraries for external hardware such as eyetrackers. Pyff is also equipped with a steadily growing set of ready-to-use feedbacks and stimuli. It can be used as a standalone application, for instance providing stimulus presentation in psychophysics experiments, or within a closed loop such as in biofeedback or brain–computer interfacing experiments. Pyff communicates with other systems via a standardized communication protocol and is therefore suitable to be used with any system that may be adapted to send its data in the specified format. Having such a general, open-source framework will help foster a fruitful exchange of experimental paradigms between research groups. In particular, it will decrease the need of reprogramming standard paradigms, ease the reproducibility of published results, and naturally entail some standardization of stimulus presentation. PMID:21160550

The Locus analytical framework for indoor localization and tracking applications

NASA Astrophysics Data System (ADS)

Segou, Olga E.; Thomopoulos, Stelios C. A.

2015-05-01

Obtaining location information can be of paramount importance in the context of pervasive and context-aware computing applications. Many systems have been proposed to date, e.g. GPS that has been proven to offer satisfying results in outdoor areas. The increased effect of large and small scale fading in indoor environments, however, makes localization a challenge. This is particularly reflected in the multitude of different systems that have been proposed in the context of indoor localization (e.g. RADAR, Cricket etc). The performance of such systems is often validated on vastly different test beds and conditions, making performance comparisons difficult and often irrelevant. The Locus analytical framework incorporates algorithms from multiple disciplines such as channel modeling, non-uniform random number generation, computational geometry, localization, tracking and probabilistic modeling etc. in order to provide: (a) fast and accurate signal propagation simulation, (b) fast experimentation with localization and tracking algorithms and (c) an in-depth analysis methodology for estimating the performance limits of any Received Signal Strength localization system. Simulation results for the well-known Fingerprinting and Trilateration algorithms are herein presented and validated with experimental data collected in real conditions using IEEE 802.15.4 ZigBee modules. The analysis shows that the Locus framework accurately predicts the underlying distribution of the localization error and produces further estimates of the system's performance limitations (in a best-case/worst-case scenario basis).

Theory and experimental results of transfer-NOE experiments. 1. The influence of the off rate versus cross-relaxation rates

NASA Astrophysics Data System (ADS)

Lippens, R. M.; Cerf, C.; Hallenga, K.

The theory of the transferred nuclear Overhauser effect is presented in the framework of an extended relaxation matrix representation. This matrix representation allows a coherent description of all one- and two-dimensional experiments. We present analytical solutions for the buildup of magnetization in the 2D transfer-NOE experiment, for all ratios of the off rate k to the cross-relaxation rates R involved. We show that systematic deviations in distance determination occur when the off rate becomes comparable to or smaller than the relaxation rates. Experimental results on the peptide/protein system oxytocin/neurophysin confirming this analysis are presented. The importance of residual mobility in the bound ligand, as demonstrated by the experimental data, is also discussed.

Connecting heterogeneous single slip to diffraction peak evolution in high-energy monochromatic X-ray experiments

PubMed Central

Pagan, Darren C.; Miller, Matthew P.

2014-01-01

A forward modeling diffraction framework is introduced and employed to identify slip system activity in high-energy diffraction microscopy (HEDM) experiments. In the framework, diffraction simulations are conducted on virtual mosaic crystals with orientation gradients consistent with Nye’s model of heterogeneous single slip. Simulated diffraction peaks are then compared against experimental measurements to identify slip system activity. Simulation results compared against diffraction data measured in situ from a silicon single-crystal specimen plastically deformed under single-slip conditions indicate that slip system activity can be identified during HEDM experiments. PMID:24904242

An ontology-based framework for bioinformatics workflows.

PubMed

Digiampietri, Luciano A; Perez-Alcazar, Jose de J; Medeiros, Claudia Bauzer

2007-01-01

The proliferation of bioinformatics activities brings new challenges - how to understand and organise these resources, how to exchange and reuse successful experimental procedures, and to provide interoperability among data and tools. This paper describes an effort toward these directions. It is based on combining research on ontology management, AI and scientific workflows to design, reuse and annotate bioinformatics experiments. The resulting framework supports automatic or interactive composition of tasks based on AI planning techniques and takes advantage of ontologies to support the specification and annotation of bioinformatics workflows. We validate our proposal with a prototype running on real data.

Simulation of creep effects in framework of a geometrically nonlinear endochronic theory of inelasticity

NASA Astrophysics Data System (ADS)

Zabavnikova, T. A.; Kadashevich, Yu. I.; Pomytkin, S. P.

2018-05-01

A geometric non-linear endochronic theory of inelasticity in tensor parametric form is considered. In the framework of this theory, the creep strains are modelled. The effect of various schemes of applying stresses and changing of material properties on the development of creep strains is studied. The constitutive equations of the model are represented by non-linear systems of ordinary differential equations which are solved in MATLAB environment by implicit difference method. Presented results demonstrate a good qualitative agreement of theoretical data and experimental observations including the description of the tertiary creep and pre-fracture of materials.

Screening metal-organic frameworks for selective noble gas adsorption in air: effect of pore size and framework topology.

PubMed

Parkes, Marie V; Staiger, Chad L; Perry, John J; Allendorf, Mark D; Greathouse, Jeffery A

2013-06-21

The adsorption of noble gases and nitrogen by sixteen metal-organic frameworks (MOFs) was investigated using grand canonical Monte Carlo simulation. The MOFs were chosen to represent a variety of net topologies, pore dimensions, and metal centers. Three commercially available MOFs (HKUST-1, AlMIL-53, and ZIF-8) and PCN-14 were also included for comparison. Experimental adsorption isotherms, obtained from volumetric and gravimetric methods, were used to compare krypton, argon, and nitrogen uptake with the simulation results. Simulated trends in gas adsorption and predicted selectivities among the commercially available MOFs are in good agreement with experiment. In the low pressure regime, the expected trend of increasing adsorption with increasing noble gas polarizabilty is seen. For each noble gas, low pressure adsorption correlates with several MOF properties, including free volume, topology, and metal center. Additionally, a strong correlation exists between the Henry's constant and the isosteric heat of adsorption for all gases and MOFs considered. Finally, we note that the simulated and experimental gas selectivities demonstrated by this small set of MOFs show improved performance compared to similar values reported for zeolites.

Comparison between phase field simulations and experimental data from intragranular bubble growth in UO{sub 2}

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

Tonks, M. R.; Biner, S. B.; Mille, P. C.

2013-07-01

In this work, we used the phase field method to simulate the post-irradiation annealing of UO{sub 2} described in the experimental work by Kashibe et al., 1993 [1]. The simulations were carried out in 2D and 3D using the MARMOT FEM-based phase-field modeling framework. The 2-D results compared fairly well with the experiments, in spite of the assumptions made in the model. The 3-D results compare even more favorably to experiments, indicating that diffusion in all three directions must be considered to accurate represent the bubble growth. (authors)

A Surrogate Approach to the Experimental Optimization of Multielement Airfoils

NASA Technical Reports Server (NTRS)

Otto, John C.; Landman, Drew; Patera, Anthony T.

1996-01-01

The incorporation of experimental test data into the optimization process is accomplished through the use of Bayesian-validated surrogates. In the surrogate approach, a surrogate for the experiment (e.g., a response surface) serves in the optimization process. The validation step of the framework provides a qualitative assessment of the surrogate quality, and bounds the surrogate-for-experiment error on designs "near" surrogate-predicted optimal designs. The utility of the framework is demonstrated through its application to the experimental selection of the trailing edge ap position to achieve a design lift coefficient for a three-element airfoil.

Validating a new methodology for strain estimation from cardiac cine MRI

NASA Astrophysics Data System (ADS)

Elnakib, Ahmed; Beache, Garth M.; Gimel'farb, Georgy; Inanc, Tamer; El-Baz, Ayman

2013-10-01

This paper focuses on validating a novel framework for estimating the functional strain from cine cardiac magnetic resonance imaging (CMRI). The framework consists of three processing steps. First, the left ventricle (LV) wall borders are segmented using a level-set based deformable model. Second, the points on the wall borders are tracked during the cardiac cycle based on solving the Laplace equation between the LV edges. Finally, the circumferential and radial strains are estimated at the inner, mid-wall, and outer borders of the LV wall. The proposed framework is validated using synthetic phantoms of the material strains that account for the physiological features and the LV response during the cardiac cycle. Experimental results on simulated phantom images confirm the accuracy and robustness of our method.

Protein loop modeling using a new hybrid energy function and its application to modeling in inaccurate structural environments.

PubMed

Park, Hahnbeom; Lee, Gyu Rie; Heo, Lim; Seok, Chaok

2014-01-01

Protein loop modeling is a tool for predicting protein local structures of particular interest, providing opportunities for applications involving protein structure prediction and de novo protein design. Until recently, the majority of loop modeling methods have been developed and tested by reconstructing loops in frameworks of experimentally resolved structures. In many practical applications, however, the protein loops to be modeled are located in inaccurate structural environments. These include loops in model structures, low-resolution experimental structures, or experimental structures of different functional forms. Accordingly, discrepancies in the accuracy of the structural environment assumed in development of the method and that in practical applications present additional challenges to modern loop modeling methods. This study demonstrates a new strategy for employing a hybrid energy function combining physics-based and knowledge-based components to help tackle this challenge. The hybrid energy function is designed to combine the strengths of each energy component, simultaneously maintaining accurate loop structure prediction in a high-resolution framework structure and tolerating minor environmental errors in low-resolution structures. A loop modeling method based on global optimization of this new energy function is tested on loop targets situated in different levels of environmental errors, ranging from experimental structures to structures perturbed in backbone as well as side chains and template-based model structures. The new method performs comparably to force field-based approaches in loop reconstruction in crystal structures and better in loop prediction in inaccurate framework structures. This result suggests that higher-accuracy predictions would be possible for a broader range of applications. The web server for this method is available at http://galaxy.seoklab.org/loop with the PS2 option for the scoring function.

Measurement of New Observables from the pi+pi- Electroproduction off the Proton

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

Trivedi, Arjun

Knowledge of the Universe as constructed by human beings, in order to tackle its complexity, can be thought to be organized at varying scales at which it is observed. Implicit in such an approach is the idea of a smooth evolution of knowledge between scales and, therefore, access to how Nature constructs the visible Universe beginning from its most fundamental constituents. New and, in a sense, fundamental phenomena may typically be emergent as the scale of observation changes. The study of the Strong Interaction, which is responsible for the construction of the bulk of the visible matter in the Universemore » (98% by mass), in this sense, is a labor of exploring evolutions and unifying aspects of its knowledge found at varying scales ranging from interaction of quarks and gluons as represented by the theory of Quantum Chromodynamics (QCD) at small space-time scale to emerging dressed quark and even meson-baryon degrees of freedom mostly described by effective models as the space-time scale increases. A direct effort to study the Strong Interaction over this scale forms the basis of an international collaborative effort often referred to as the N* program. The core work of this thesis is an experimental analysis prompted by the need to measure experimental observables that are of particular interest to the theory-experiment epistemological framework of this collaboration. While the core of this thesis, therefore, discusses the nature of the experimental analysis and presents its results which will serve as input to the N* program's epistemological framework, the particular nature of this framework in the context of not only the Strong Interaction, but also that of the physical science and human knowledge in general will be used to motivate and introduce the experimental analysis and its related observables.« less

Measurement of new observables from the pi+pi - electroproduction off the proton

NASA Astrophysics Data System (ADS)

Trivedi, Arjun

Knowledge of the Universe as constructed by human beings, in order to tackle its complexity, can be thought to be organized at varying scales at which it is observed. Implicit in such an approach is the idea of a smooth evolution of knowledge between scales and, therefore, access to how Nature constructs the visible Universe beginning from its most fundamental constituents. New and, in a sense, fundamental phenomena may typically be emergent as the scale of observation changes. The study of the Strong Interaction, which is responsible for the construction of the bulk of the visible matter in the Universe (98% by mass), in this sense, is a labor of exploring evolutions and unifying aspects of its knowledge found at varying scales ranging from interaction of quarks and gluons as represented by the theory of Quantum Chromodynamics (QCD) at small space-time scale to emerging dressed quark and even mesonbaryon degrees of freedom mostly described by effective models as the space-time scale increases. A direct effort to study the Strong Interaction over this scale forms the basis of an international collaborative effort often referred to as the N* program. The core work of this thesis is an experimental analysis prompted by the need to measure experimental observables that are of particular interest to the theory-experiment epistemological framework of this collaboration. While the core of this thesis, therefore, discusses the nature of the experimental analysis and presents its results which will serve as input to the N* program's epistemological framework, the particular nature of this framework in the context of not only the Strong Interaction, but also that of the physical science and human knowledge in general will be used to motivate and introduce the experimental analysis and its related observables.

Optimal bioprocess design through a gene regulatory network - growth kinetic hybrid model: Towards Replacing Monod kinetics.

PubMed

Tsipa, Argyro; Koutinas, Michalis; Usaku, Chonlatep; Mantalaris, Athanasios

2018-05-02

Currently, design and optimisation of biotechnological bioprocesses is performed either through exhaustive experimentation and/or with the use of empirical, unstructured growth kinetics models. Whereas, elaborate systems biology approaches have been recently explored, mixed-substrate utilisation is predominantly ignored despite its significance in enhancing bioprocess performance. Herein, bioprocess optimisation for an industrially-relevant bioremediation process involving a mixture of highly toxic substrates, m-xylene and toluene, was achieved through application of a novel experimental-modelling gene regulatory network - growth kinetic (GRN-GK) hybrid framework. The GRN model described the TOL and ortho-cleavage pathways in Pseudomonas putida mt-2 and captured the transcriptional kinetics expression patterns of the promoters. The GRN model informed the formulation of the growth kinetics model replacing the empirical and unstructured Monod kinetics. The GRN-GK framework's predictive capability and potential as a systematic optimal bioprocess design tool, was demonstrated by effectively predicting bioprocess performance, which was in agreement with experimental values, when compared to four commonly used models that deviated significantly from the experimental values. Significantly, a fed-batch biodegradation process was designed and optimised through the model-based control of TOL Pr promoter expression resulting in 61% and 60% enhanced pollutant removal and biomass formation, respectively, compared to the batch process. This provides strong evidence of model-based bioprocess optimisation at the gene level, rendering the GRN-GK framework as a novel and applicable approach to optimal bioprocess design. Finally, model analysis using global sensitivity analysis (GSA) suggests an alternative, systematic approach for model-driven strain modification for synthetic biology and metabolic engineering applications. Copyright © 2018. Published by Elsevier Inc.

EXACT2: the semantics of biomedical protocols

PubMed Central

2014-01-01

Background The reliability and reproducibility of experimental procedures is a cornerstone of scientific practice. There is a pressing technological need for the better representation of biomedical protocols to enable other agents (human or machine) to better reproduce results. A framework that ensures that all information required for the replication of experimental protocols is essential to achieve reproducibility. Methods We have developed the ontology EXACT2 (EXperimental ACTions) that is designed to capture the full semantics of biomedical protocols required for their reproducibility. To construct EXACT2 we manually inspected hundreds of published and commercial biomedical protocols from several areas of biomedicine. After establishing a clear pattern for extracting the required information we utilized text-mining tools to translate the protocols into a machine amenable format. We have verified the utility of EXACT2 through the successful processing of previously 'unseen' (not used for the construction of EXACT2) protocols. Results The paper reports on a fundamentally new version EXACT2 that supports the semantically-defined representation of biomedical protocols. The ability of EXACT2 to capture the semantics of biomedical procedures was verified through a text mining use case. In this EXACT2 is used as a reference model for text mining tools to identify terms pertinent to experimental actions, and their properties, in biomedical protocols expressed in natural language. An EXACT2-based framework for the translation of biomedical protocols to a machine amenable format is proposed. Conclusions The EXACT2 ontology is sufficient to record, in a machine processable form, the essential information about biomedical protocols. EXACT2 defines explicit semantics of experimental actions, and can be used by various computer applications. It can serve as a reference model for for the translation of biomedical protocols in natural language into a semantically-defined format. PMID:25472549

Calculation of the wetting parameter from a cluster model in the framework of nanothermodynamics.

PubMed

García-Morales, V; Cervera, J; Pellicer, J

2003-06-01

The critical wetting parameter omega(c) determines the strength of interfacial fluctuations in critical wetting transitions. In this Brief Report, we calculate omega(c) from considerations on critical liquid clusters inside a vapor phase. The starting point is a cluster model developed by Hill and Chamberlin in the framework of nanothermodynamics [Proc. Natl. Acad. Sci. USA 95, 12779 (1998)]. Our calculations yield results for omega(c) between 0.52 and 1.00, depending on the degrees of freedom considered. The findings are in agreement with previous experimental results and give an idea of the universal dynamical behavior of the clusters when approaching criticality. We suggest that this behavior is a combination of translation and vortex rotational motion (omega(c)=0.84).

Iterative deep convolutional encoder-decoder network for medical image segmentation.

PubMed

Jung Uk Kim; Hak Gu Kim; Yong Man Ro

2017-07-01

In this paper, we propose a novel medical image segmentation using iterative deep learning framework. We have combined an iterative learning approach and an encoder-decoder network to improve segmentation results, which enables to precisely localize the regions of interest (ROIs) including complex shapes or detailed textures of medical images in an iterative manner. The proposed iterative deep convolutional encoder-decoder network consists of two main paths: convolutional encoder path and convolutional decoder path with iterative learning. Experimental results show that the proposed iterative deep learning framework is able to yield excellent medical image segmentation performances for various medical images. The effectiveness of the proposed method has been proved by comparing with other state-of-the-art medical image segmentation methods.

Multilevel analysis of sports video sequences

NASA Astrophysics Data System (ADS)

Han, Jungong; Farin, Dirk; de With, Peter H. N.

2006-01-01

We propose a fully automatic and flexible framework for analysis and summarization of tennis broadcast video sequences, using visual features and specific game-context knowledge. Our framework can analyze a tennis video sequence at three levels, which provides a broad range of different analysis results. The proposed framework includes novel pixel-level and object-level tennis video processing algorithms, such as a moving-player detection taking both the color and the court (playing-field) information into account, and a player-position tracking algorithm based on a 3-D camera model. Additionally, we employ scene-level models for detecting events, like service, base-line rally and net-approach, based on a number real-world visual features. The system can summarize three forms of information: (1) all court-view playing frames in a game, (2) the moving trajectory and real-speed of each player, as well as relative position between the player and the court, (3) the semantic event segments in a game. The proposed framework is flexible in choosing the level of analysis that is desired. It is effective because the framework makes use of several visual cues obtained from the real-world domain to model important events like service, thereby increasing the accuracy of the scene-level analysis. The paper presents attractive experimental results highlighting the system efficiency and analysis capabilities.

ICADx: interpretable computer aided diagnosis of breast masses

NASA Astrophysics Data System (ADS)

Kim, Seong Tae; Lee, Hakmin; Kim, Hak Gu; Ro, Yong Man

2018-02-01

In this study, a novel computer aided diagnosis (CADx) framework is devised to investigate interpretability for classifying breast masses. Recently, a deep learning technology has been successfully applied to medical image analysis including CADx. Existing deep learning based CADx approaches, however, have a limitation in explaining the diagnostic decision. In real clinical practice, clinical decisions could be made with reasonable explanation. So current deep learning approaches in CADx are limited in real world deployment. In this paper, we investigate interpretability in CADx with the proposed interpretable CADx (ICADx) framework. The proposed framework is devised with a generative adversarial network, which consists of interpretable diagnosis network and synthetic lesion generative network to learn the relationship between malignancy and a standardized description (BI-RADS). The lesion generative network and the interpretable diagnosis network compete in an adversarial learning so that the two networks are improved. The effectiveness of the proposed method was validated on public mammogram database. Experimental results showed that the proposed ICADx framework could provide the interpretability of mass as well as mass classification. It was mainly attributed to the fact that the proposed method was effectively trained to find the relationship between malignancy and interpretations via the adversarial learning. These results imply that the proposed ICADx framework could be a promising approach to develop the CADx system.

Computational discovery of metal-organic frameworks with high gas deliverable capacity

NASA Astrophysics Data System (ADS)

Bao, Yi

Metal-organic frameworks (MOFs) are a rapidly emerging class of nanoporous materials with largely tunable chemistry and diverse applications in gas storage, gas purification, catalysis, sensing and drug delivery. Efforts have been made to develop new MOFs with desirable properties both experimentally and computationally for decades. To guide experimental synthesis, we here develop a computational methodology to explore MOFs with high gas deliverable capacity. This de novo design procedure applies known chemical reactions, considers synthesizability and geometric requirements of organic linkers, and efficiently evolves a population of MOFs to optimize a desirable property. We identify 48 MOFs with higher methane deliverable capacity at 65-5.8 bar condition than the MOF-5 reference in nine networks. In a more comprehensive work, we predict two sets of MOFs with high methane deliverable capacity at a 65-5.8 bar loading-delivery condition or a 35-5.8 bar loading-delivery condition. We also optimize a set of MOFs with high methane accessible internal surface area to investigate the relationship between deliverable capacities and internal surface area. This methodology can be extended to MOFs with multiple types of linkers and multiple SBUs. Flexibile MOFs may allow for sophisticated heat management strategies and also provide higher gas deliverable capacity than rigid frameworks. We investigate flexible MOFs, such as MIL-53 families, and Fe(bdp) and Co(bdp) analogs, to understand the structural phase transition of frameworks and the resulting influence on heat of adsorption. Challenges of simulating a system with a flexible host structure and incoming guest molecules are discussed. Preliminary results from isotherm simulation using the hybrid MC/MD simulation scheme on MIL-53(Cr) are presented. Suggestions for proceeding to understand the free energy profile of flexible MOFs are provided.

Constitutive formulations for the mechanical investigation of colonic tissues.

PubMed

Carniel, Emanuele Luigi; Gramigna, Vera; Fontanella, Chiara Giulia; Stefanini, Cesare; Natali, Arturo N

2014-05-01

A constitutive framework is provided for the characterization of the mechanical behavior of colonic tissues, as a fundamental tool for the development of numerical models of the colonic structures. The constitutive analysis is performed by a multidisciplinary approach that requires the cooperation between experimental and computational competences. The preliminary investigation pertains to the review of the tissues histology. The complex structural configuration of the tissues and the specific distributions of fibrous elements entail the nonlinear mechanical behavior and the anisotropic response. The identification of the mechanical properties requires to perform mechanical tests according to different loading situations, as different loading directions. Because of the typical functionality of colon structures, the tissues mechanics is investigated by tensile tests, which are performed on taenia coli and haustra specimens from fresh pig colons. Accounting for the histological investigation and the results from the mechanical tests, a specific hyperelastic framework is provided within the theory of fiber-reinforced composite materials. Preliminary analytical formulations are defined to identify the constitutive parameters by the inverse analysis of the experimental tests. Finite element models of the specimens are developed accounting for the actual configuration of the colon structures to verify the quality of the results. The good agreement between experimental and numerical model results suggests the reliability of the constitutive formulations and parameters. Finally, the developed constitutive analysis makes it possible to identify the mechanical behavior and properties of the different colonic tissues. Copyright © 2013 Wiley Periodicals, Inc.

Long term radiocesium contamination of fruit trees following the Chernobyl accident.

PubMed

Antonopoulos-Domis, M; Clouvas, A; Gagianas, A

1996-12-01

Radiocesium contamination from the Chernobyl accident of fruits and leaves from various fruit trees was systematically studied from 1990 to 1995 on two agricultural experimentation farms in Northern Greece. The results are discussed in the framework of a previously published model describing the long-term radiocesium contamination mechanism of deciduous fruit trees after a nuclear accident. The results of the present work qualitatively verify the model predictions.

Experimental observation of direct particle acceleration by stimulated emission of radiation.

PubMed

Banna, Samer; Berezovsky, Valery; Schächter, Levi

2006-09-29

We report the first experimental evidence for direct particle acceleration by stimulated emission of radiation. In the framework of this proof-of-principle experiment, a 45 MeV electron macrobunch was modulated by a high-power CO2 laser and then injected into an excited CO2 gas mixture. The emerging microbunches experienced a 0.15% relative change in the kinetic energy, in a less than 40 cm long interaction region. According to our experimental results, a fraction of these electrons have gained more than 200 keV each, implying that such an electron has undergone an order of magnitude of 2 x 10(6) collisions of the second kind.

TROIKA: a general framework for heart rate monitoring using wrist-type photoplethysmographic signals during intensive physical exercise.

PubMed

Zhang, Zhilin; Pi, Zhouyue; Liu, Benyuan

2015-02-01

Heart rate monitoring using wrist-type photoplethysmographic signals during subjects' intensive exercise is a difficult problem, since the signals are contaminated by extremely strong motion artifacts caused by subjects' hand movements. So far few works have studied this problem. In this study, a general framework, termed TROIKA, is proposed, which consists of signal decomposiTion for denoising, sparse signal RecOnstructIon for high-resolution spectrum estimation, and spectral peaK trAcking with verification. The TROIKA framework has high estimation accuracy and is robust to strong motion artifacts. Many variants can be straightforwardly derived from this framework. Experimental results on datasets recorded from 12 subjects during fast running at the peak speed of 15 km/h showed that the average absolute error of heart rate estimation was 2.34 beat per minute, and the Pearson correlation between the estimates and the ground truth of heart rate was 0.992. This framework is of great values to wearable devices such as smartwatches which use PPG signals to monitor heart rate for fitness.

The theoretical tools of experimental gravitation

NASA Technical Reports Server (NTRS)

Will, C. M.

1972-01-01

Theoretical frameworks for testing relativistic gravity are presented in terms of a system for analyzing theories of gravity invented as alternatives to Einstein. The parametrized post-Newtonian (PPN) formalism, based on the Dicke framework and the Eotvos-Dicke-Braginsky experiment, is discussed in detail. The metric theories of gravity, and their post-Newtonian limits are reviewed, and PPN equations of motion are derived. These equations are used to analyze specific effects and experimental tests in the solar system.

Constitutive modeling and structural analysis considering simultaneous phase transformation and plastic yield in shape memory alloys

NASA Astrophysics Data System (ADS)

Hartl, D. J.; Lagoudas, D. C.

2009-10-01

The new developments summarized in this work represent both theoretical and experimental investigations of the effects of plastic strain generation in shape memory alloys (SMAs). Based on the results of SMA experimental characterization described in the literature and additional testing described in this work, a new 3D constitutive model is proposed. This phenomenological model captures both the conventional shape memory effects of pseudoelasticity and thermal strain recovery, and additionally considers the initiation and evolution of plastic strains. The model is numerically implemented in a finite element framework using a return mapping algorithm to solve the constitutive equations at each material point. This combination of theory and implementation is unique in its ability to capture the simultaneous evolution of recoverable transformation strains and irrecoverable plastic strains. The consideration of isotropic and kinematic plastic hardening allows the derivation of a theoretical framework capturing the interactions between irrecoverable plastic strain and recoverable strain due to martensitic transformation. Further, the numerical integration of the constitutive equations is formulated such that objectivity is maintained for SMA structures undergoing moderate strains and large displacements. The implemented model has been used to perform 3D analysis of SMA structural components under uniaxial and bending loads, including a case of local buckling behavior. Experimentally validated results considering simultaneous transformation and plasticity in a bending member are provided, illustrating the predictive accuracy of the model and its implementation.

Head Start Classroom Teachers' and Assistant Teachers' Perceptions of Professional Development Using a Learn Framework

ERIC Educational Resources Information Center

Nasser, Ilham; Kidd, Julie K.; Burns, M. Susan; Campbell, Trina

2015-01-01

This study investigates early childhood education teachers' and assistant teachers' views about a year-long professional development model that focuses on developing intentional teaching. The study shares the results of interviews conducted with the teachers at the end of the implementation of a one-year experimental professional model in Head…

The Differentiation of Heat and Temperature: An Evaluation of the Effect of Microcomputer Models on Students' Misconceptions.

ERIC Educational Resources Information Center

Wiser, Marianne; Kipman, Daphna

This paper describes the characterization of a student's framework of heat and temperature, and the development of a microcomputer-based laboratories (MBL) intervention program for grade 9 and grade ll students. The report presents the results of classroom study, including interview questions and answers and pretest/posttest, from experimental and…

Observing System Simulation Experiments: An Overview

NASA Technical Reports Server (NTRS)

Prive, Nikki C.; Errico, Ronald M.

2016-01-01

An overview of Observing System Simulation Experiments (OSSEs) will be given, with focus on calibration and validation of OSSE frameworks. Pitfalls and practice will be discussed, including observation error characteristics, incestuousness, and experimental design. The potential use of OSSEs for investigation of the behaviour of data assimilation systems will be explored, including some results from experiments using the NASAGMAO OSSE.

An experimental and theoretical investigation into the electronically excited states of para-benzoquinone

NASA Astrophysics Data System (ADS)

Jones, D. B.; Limão-Vieira, P.; Mendes, M.; Jones, N. C.; Hoffmann, S. V.; da Costa, R. F.; Varella, M. T. do N.; Bettega, M. H. F.; Blanco, F.; García, G.; Ingólfsson, O.; Lima, M. A. P.; Brunger, M. J.

2017-05-01

We report on a combination of experimental and theoretical investigations into the structure of electronically excited para-benzoquinone (pBQ). Here synchrotron photoabsorption measurements are reported over the 4.0-10.8 eV range. The higher resolution obtained reveals previously unresolved pBQ spectral features. Time-dependent density functional theory calculations are used to interpret the spectrum and resolve discrepancies relating to the interpretation of the Rydberg progressions. Electron-impact energy loss experiments are also reported. These are combined with elastic electron scattering cross section calculations performed within the framework of the independent atom model-screening corrected additivity rule plus interference (IAM-SCAR + I) method to derive differential cross sections for electronic excitation of key spectral bands. A generalized oscillator strength analysis is also performed, with the obtained results demonstrating that a cohesive and reliable quantum chemical structure and cross section framework has been established. Within this context, we also discuss some issues associated with the development of a minimal orbital basis for the single configuration interaction strategy to be used for our high-level low-energy electron scattering calculations that will be carried out as a subsequent step in this joint experimental and theoretical investigation.

Multilevel modeling of single-case data: A comparison of maximum likelihood and Bayesian estimation.

PubMed

Moeyaert, Mariola; Rindskopf, David; Onghena, Patrick; Van den Noortgate, Wim

2017-12-01

The focus of this article is to describe Bayesian estimation, including construction of prior distributions, and to compare parameter recovery under the Bayesian framework (using weakly informative priors) and the maximum likelihood (ML) framework in the context of multilevel modeling of single-case experimental data. Bayesian estimation results were found similar to ML estimation results in terms of the treatment effect estimates, regardless of the functional form and degree of information included in the prior specification in the Bayesian framework. In terms of the variance component estimates, both the ML and Bayesian estimation procedures result in biased and less precise variance estimates when the number of participants is small (i.e., 3). By increasing the number of participants to 5 or 7, the relative bias is close to 5% and more precise estimates are obtained for all approaches, except for the inverse-Wishart prior using the identity matrix. When a more informative prior was added, more precise estimates for the fixed effects and random effects were obtained, even when only 3 participants were included. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Conducting Human Research

DTIC Science & Technology

2009-08-05

Socio-cultural data acquisition, extraction, and management.??? First the idea of a theoretical framework will be very briefly discussed as well as...SUBJECT TERMS human behavior, theoretical framework , hypothesis development, experimental design, ethical research, statistical power, human laboratory...who throw rocks? • How can we make them stay too far away to throw rocks? UNCLASSIFIED – Approved for Public Release Theoretical Framework / Conceptual

New phenomena in non-equilibrium quantum physics

NASA Astrophysics Data System (ADS)

Kitagawa, Takuya

From its beginning in the early 20th century, quantum theory has become progressively more important especially due to its contributions to the development of technologies. Quantum mechanics is crucial for current technology such as semiconductors, and also holds promise for future technologies such as superconductors and quantum computing. Despite of the success of quantum theory, its applications have been mostly limited to equilibrium or static systems due to 1. lack of experimental controllability of non-equilibrium quantum systems 2. lack of theoretical frameworks to understand non-equilibrium dynamics. Consequently, physicists have not yet discovered too many interesting phenomena in non-equilibrium quantum systems from both theoretical and experimental point of view and thus, non-equilibrium quantum physics did not attract too much attentions. The situation has recently changed due to the rapid development of experimental techniques in condensed matter as well as cold atom systems, which now enables a better control of non-equilibrium quantum systems. Motivated by this experimental progress, we constructed theoretical frameworks to study three different non-equilibrium regimes of transient dynamics, steady states and periodically drives. These frameworks provide new perspectives for dynamical quantum process, and help to discover new phenomena in these systems. In this thesis, we describe these frameworks through explicit examples and demonstrate their versatility. Some of these theoretical proposals have been realized in experiments, confirming the applicability of the theories to realistic experimental situations. These studies have led to not only the improved fundamental understanding of non-equilibrium processes in quantum systems, but also suggested entirely different venues for developing quantum technologies.

An Analytical Model for the Performance Analysis of Concurrent Transmission in IEEE 802.15.4

PubMed Central

Gezer, Cengiz; Zanella, Alberto; Verdone, Roberto

2014-01-01

Interference is a serious cause of performance degradation for IEEE802.15.4 devices. The effect of concurrent transmissions in IEEE 802.15.4 has been generally investigated by means of simulation or experimental activities. In this paper, a mathematical framework for the derivation of chip, symbol and packet error probability of a typical IEEE 802.15.4 receiver in the presence of interference is proposed. Both non-coherent and coherent demodulation schemes are considered by our model under the assumption of the absence of thermal noise. Simulation results are also added to assess the validity of the mathematical framework when the effect of thermal noise cannot be neglected. Numerical results show that the proposed analysis is in agreement with the measurement results on the literature under realistic working conditions. PMID:24658624

An analytical model for the performance analysis of concurrent transmission in IEEE 802.15.4.

PubMed

Gezer, Cengiz; Zanella, Alberto; Verdone, Roberto

2014-03-20

Interference is a serious cause of performance degradation for IEEE802.15.4 devices. The effect of concurrent transmissions in IEEE 802.15.4 has been generally investigated by means of simulation or experimental activities. In this paper, a mathematical framework for the derivation of chip, symbol and packet error probability of a typical IEEE 802.15.4 receiver in the presence of interference is proposed. Both non-coherent and coherent demodulation schemes are considered by our model under the assumption of the absence of thermal noise. Simulation results are also added to assess the validity of the mathematical framework when the effect of thermal noise cannot be neglected. Numerical results show that the proposed analysis is in agreement with the measurement results on the literature under realistic working conditions.

RIPOSTE: a framework for improving the design and analysis of laboratory-based research

PubMed Central

Masca, Nicholas GD; Hensor, Elizabeth MA; Cornelius, Victoria R; Buffa, Francesca M; Marriott, Helen M; Eales, James M; Messenger, Michael P; Anderson, Amy E; Boot, Chris; Bunce, Catey; Goldin, Robert D; Harris, Jessica; Hinchliffe, Rod F; Junaid, Hiba; Kingston, Shaun; Martin-Ruiz, Carmen; Nelson, Christopher P; Peacock, Janet; Seed, Paul T; Shinkins, Bethany; Staples, Karl J; Toombs, Jamie; Wright, Adam KA; Teare, M Dawn

2015-01-01

Lack of reproducibility is an ongoing problem in some areas of the biomedical sciences. Poor experimental design and a failure to engage with experienced statisticians at key stages in the design and analysis of experiments are two factors that contribute to this problem. The RIPOSTE (Reducing IrreProducibility in labOratory STudiEs) framework has been developed to support early and regular discussions between scientists and statisticians in order to improve the design, conduct and analysis of laboratory studies and, therefore, to reduce irreproducibility. This framework is intended for use during the early stages of a research project, when specific questions or hypotheses are proposed. The essential points within the framework are explained and illustrated using three examples (a medical equipment test, a macrophage study and a gene expression study). Sound study design minimises the possibility of bias being introduced into experiments and leads to higher quality research with more reproducible results. DOI: http://dx.doi.org/10.7554/eLife.05519.001 PMID:25951517

Audio-based queries for video retrieval over Java enabled mobile devices

NASA Astrophysics Data System (ADS)

Ahmad, Iftikhar; Cheikh, Faouzi Alaya; Kiranyaz, Serkan; Gabbouj, Moncef

2006-02-01

In this paper we propose a generic framework for efficient retrieval of audiovisual media based on its audio content. This framework is implemented in a client-server architecture where the client application is developed in Java to be platform independent whereas the server application is implemented for the PC platform. The client application adapts to the characteristics of the mobile device where it runs such as screen size and commands. The entire framework is designed to take advantage of the high-level segmentation and classification of audio content to improve speed and accuracy of audio-based media retrieval. Therefore, the primary objective of this framework is to provide an adaptive basis for performing efficient video retrieval operations based on the audio content and types (i.e. speech, music, fuzzy and silence). Experimental results approve that such an audio based video retrieval scheme can be used from mobile devices to search and retrieve video clips efficiently over wireless networks.

A constitutive model for magnetostriction based on thermodynamic framework

NASA Astrophysics Data System (ADS)

Ho, Kwangsoo

2016-08-01

This work presents a general framework for the continuum-based formulation of dissipative materials with magneto-mechanical coupling in the viewpoint of irreversible thermodynamics. The thermodynamically consistent model developed for the magnetic hysteresis is extended to include the magnetostrictive effect. The dissipative and hysteretic response of magnetostrictive materials is captured through the introduction of internal state variables. The evolution rate of magnetostrictive strain as well as magnetization is derived from thermodynamic and dissipative potentials in accordance with the general principles of thermodynamics. It is then demonstrated that the constitutive model is competent to describe the magneto-mechanical behavior by comparing simulation results with the experimental data reported in the literature.

Music video shot segmentation using independent component analysis and keyframe extraction based on image complexity

NASA Astrophysics Data System (ADS)

Li, Wei; Chen, Ting; Zhang, Wenjun; Shi, Yunyu; Li, Jun

2012-04-01

In recent years, Music video data is increasing at an astonishing speed. Shot segmentation and keyframe extraction constitute a fundamental unit in organizing, indexing, retrieving video content. In this paper a unified framework is proposed to detect the shot boundaries and extract the keyframe of a shot. Music video is first segmented to shots by illumination-invariant chromaticity histogram in independent component (IC) analysis feature space .Then we presents a new metric, image complexity, to extract keyframe in a shot which is computed by ICs. Experimental results show the framework is effective and has a good performance.

[Testing of the effect of classic conditioning stimuli in human experiment by means of the transfer of control paradigm].

PubMed

Wolter, J

1999-01-01

Pavlovian conditioning in animals is often evaluated by means of transfer of control experiments. With human subjects, however, only very few studies have been conducted and the outcomes were often not in accordance with theoretical explanations based on studies with animals. A theoretical framework is presented that tries to integrate the results of the human conditioning paradigm and the animal conditioning paradigm as well, with reference to the well-known Yerkes-Dodson law. The experimental study with human subjects (N = 24) confirmed the predictions out of this framework, when a procedure similar to animal research is applied.

Practical training framework for fitting a function and its derivatives.

PubMed

Pukrittayakamee, Arjpolson; Hagan, Martin; Raff, Lionel; Bukkapatnam, Satish T S; Komanduri, Ranga

2011-06-01

This paper describes a practical framework for using multilayer feedforward neural networks to simultaneously fit both a function and its first derivatives. This framework involves two steps. The first step is to train the network to optimize a performance index, which includes both the error in fitting the function and the error in fitting the derivatives. The second step is to prune the network by removing neurons that cause overfitting and then to retrain it. This paper describes two novel types of overfitting that are only observed when simultaneously fitting both a function and its first derivatives. A new pruning algorithm is proposed to eliminate these types of overfitting. Experimental results show that the pruning algorithm successfully eliminates the overfitting and produces the smoothest responses and the best generalization among all the training algorithms that we have tested.

ReaxFF molecular dynamics simulation of thermal stability of a Cu3(BTC)2 metal-organic framework.

PubMed

Huang, Liangliang; Joshi, Kaushik L; van Duin, Adri C T; Bandosz, Teresa J; Gubbins, Keith E

2012-08-28

The thermal stability of a dehydrated Cu(3)(BTC)(2) (copper(II) benzene 1,3,5-tricarboxylate) metal-organic framework was studied by molecular dynamics simulation with a ReaxFF reactive force field. The results show that Cu(3)(BTC)(2) is thermally stable up to 565 K. When the temperature increases between 600 K and 700 K, the framework starts to partially collapse. The RDF analysis shows that the long range correlations between Cu dimers disappear, indicating the loss of the main channels of Cu(3)(BTC)(2). When the temperature is above 800 K, we find the decomposition of the Cu(3)(BTC)(2) framework. CO is the major product, and we also observe the release of CO(2), O(2), 1,3,5-benzenetricarboxylate (C(6)H(3)(CO(2))(3), BTC) and glassy carbon. The Cu dimer is stable up to 1100 K, but we find the formation of new copper oxide clusters at 1100 K. These results are consistent with experimental findings, and provide valuable information for future theoretical investigations of Cu(3)(BTC)(2) and its application in adsorption, separation and catalytic processes.

The Distinction between Experimental and Historical Sciences as a Framework for Improving Classroom Inquiry

ERIC Educational Resources Information Center

Gray, Ron

2014-01-01

Inquiry experiences in secondary science classrooms are heavily weighted toward experimentation. We know, however, that many fields of science (e.g., evolutionary biology, cosmology, and paleontology), while they may utilize experiments, are not justified by experimental methodologies. With the focus on experimentation in schools, these fields of…

Robopedia: Leveraging Sensorpedia for Web-Enabled Robot Control

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

Resseguie, David R

There is a growing interest in building Internetscale sensor networks that integrate sensors from around the world into a single unified system. In contrast, robotics application development has primarily focused on building specialized systems. These specialized systems take scalability and reliability into consideration, but generally neglect exploring the key components required to build a large scale system. Integrating robotic applications with Internet-scale sensor networks will unify specialized robotics applications and provide answers to large scale implementation concerns. We focus on utilizing Internet-scale sensor network technology to construct a framework for unifying robotic systems. Our framework web-enables a surveillance robot smore » sensor observations and provides a webinterface to the robot s actuators. This lets robots seamlessly integrate into web applications. In addition, the framework eliminates most prerequisite robotics knowledge, allowing for the creation of general web-based robotics applications. The framework also provides mechanisms to create applications that can interface with any robot. Frameworks such as this one are key to solving large scale mobile robotics implementation problems. We provide an overview of previous Internetscale sensor networks, Sensorpedia (an ad-hoc Internet-scale sensor network), our framework for integrating robots with Sensorpedia, two applications which illustrate our frameworks ability to support general web-based robotic control, and offer experimental results that illustrate our framework s scalability, feasibility, and resource requirements.« less

Design and experimentation of an empirical multistructure framework for accurate, sharp and reliable hydrological ensembles

NASA Astrophysics Data System (ADS)

Seiller, G.; Anctil, F.; Roy, R.

2017-09-01

This paper outlines the design and experimentation of an Empirical Multistructure Framework (EMF) for lumped conceptual hydrological modeling. This concept is inspired from modular frameworks, empirical model development, and multimodel applications, and encompasses the overproduce and select paradigm. The EMF concept aims to reduce subjectivity in conceptual hydrological modeling practice and includes model selection in the optimisation steps, reducing initial assumptions on the prior perception of the dominant rainfall-runoff transformation processes. EMF generates thousands of new modeling options from, for now, twelve parent models that share their functional components and parameters. Optimisation resorts to ensemble calibration, ranking and selection of individual child time series based on optimal bias and reliability trade-offs, as well as accuracy and sharpness improvement of the ensemble. Results on 37 snow-dominated Canadian catchments and 20 climatically-diversified American catchments reveal the excellent potential of the EMF in generating new individual model alternatives, with high respective performance values, that may be pooled efficiently into ensembles of seven to sixty constitutive members, with low bias and high accuracy, sharpness, and reliability. A group of 1446 new models is highlighted to offer good potential on other catchments or applications, based on their individual and collective interests. An analysis of the preferred functional components reveals the importance of the production and total flow elements. Overall, results from this research confirm the added value of ensemble and flexible approaches for hydrological applications, especially in uncertain contexts, and open up new modeling possibilities.

Quantifying the Energy Landscape Statistics in Proteins - a Relaxation Mode Analysis

NASA Astrophysics Data System (ADS)

Cai, Zhikun; Zhang, Yang

Energy landscape, the hypersurface in the configurational space, has been a useful concept in describing complex processes that occur over a very long time scale, such as the multistep slow relaxations of supercooled liquids and folding of polypeptide chains into structured proteins. Despite extensive simulation studies, its experimental characterization still remains a challenge. To address this challenge, we developed a relaxation mode analysis (RMA) for liquids under a framework analogous to the normal mode analysis for solids. Using RMA, important statistics of the activation barriers of the energy landscape becomes accessible from experimentally measurable two-point correlation functions, e.g. using quasi-elastic and inelastic scattering experiments. We observed a prominent coarsening effect of the energy landscape. The results were further confirmed by direct sampling of the energy landscape using a metadynamics-like adaptive autonomous basin climbing computation. We first demonstrate RMA in a supercooled liquid when dynamical cooperativity emerges in the landscape-influenced regime. Then we show this framework reveals encouraging energy landscape statistics when applied to proteins.

Pattern production through a chiral chasing mechanism

NASA Astrophysics Data System (ADS)

Woolley, Thomas E.

2017-09-01

Recent experiments on zebrafish pigmentation suggests that their typical black and white striped skin pattern is made up of a number of interacting chromatophore families. Specifically, two of these cell families have been shown to interact through a nonlocal chasing mechanism, which has previously been modeled using integro-differential equations. We extend this framework to include the experimentally observed fact that the cells often exhibit chiral movement, in that the cells chase, and run away, at angles different to the line connecting their centers. This framework is simplified through the use of multiple small limits leading to a coupled set of partial differential equations which are amenable to Fourier analysis. This analysis results in the production of dispersion relations and necessary conditions for a patterning instability to occur. Beyond the theoretical development and the production of new pattern planiforms we are able to corroborate the experimental hypothesis that the global pigmentation patterns can be dependent on the chirality of the chromatophores.

Experimental and theoretical electron-scattering cross-section data for dichloromethane

NASA Astrophysics Data System (ADS)

Krupa, K.; Lange, E.; Blanco, F.; Barbosa, A. S.; Pastega, D. F.; Sanchez, S. d'A.; Bettega, M. H. F.; García, G.; Limão-Vieira, P.; Ferreira da Silva, F.

2018-04-01

We report on a combination of experimental and theoretical investigations into the elastic differential cross sections (DCSs) and integral cross sections for electron interactions with dichloromethane, C H2C l2 , in the incident electron energy over the 7.0-30 eV range. Elastic electron-scattering cross-section calculations have been performed within the framework of the Schwinger multichannel method implemented with pseudopotentials (SMCPP), and the independent-atom model with screening-corrected additivity rule including interference-effects correction (IAM-SCAR+I). The present elastic DCSs have been found to agree reasonably well with the results of IAM-SCAR+I calculations above 20 eV and also with the SMC calculations below 30 eV. Although some discrepancies were found for 7 eV, the agreement between the two theoretical methodologies is remarkable as the electron-impact energy increases. Calculated elastic DCSs are also reported up to 10000 eV for scattering angles from 0° to 180° together with total cross section within the IAM-SCAR+I framework.

Animal models in biological and biomedical research - experimental and ethical concerns.

PubMed

Andersen, Monica L; Winter, Lucile M F

2017-09-04

Animal models have been used in experimental research to increase human knowledge and contribute to finding solutions to biological and biomedical questions. However, increased concern for the welfare of the animals used, and a growing awareness of the concept of animal rights, has brought a greater focus on the related ethical issues. In this review, we intend to give examples on how animals are used in the health research related to some major health problems in Brazil, as well as to stimulate discussion about the application of ethics in the use of animals in research and education, highlighting the role of National Council for the Control of Animal Experimentation (Conselho Nacional de Controle de Experimentação Animal - CONCEA) in these areas. In 2008, Brazil emerged into a new era of animal research regulation, with the promulgation of Law 11794, previously known as the Arouca Law, resulting in an increased focus, and rapid learning experience, on questions related to all aspects of animal experimentation. The law reinforces the idea that animal experiments must be based on ethical considerations and integrity-based assumptions, and provides a regulatory framework to achieve this. This review describes the health research involving animals and the current Brazilian framework for regulating laboratory animal science, and hopes to help to improve the awareness of the scientific community of these ethical and legal rules.

Ab initio thermodynamic model for magnesium carbonates and hydrates.

PubMed

Chaka, Anne M; Felmy, Andrew R

2014-09-04

An ab initio thermodynamic framework for predicting properties of hydrated magnesium carbonate minerals has been developed using density-functional theory linked to macroscopic thermodynamics through the experimental chemical potentials for MgO, water, and CO2. Including semiempirical dispersion via the Grimme method and small corrections to the generalized gradient approximation of Perdew, Burke, and Ernzerhof for the heat of formation yields a model with quantitative agreement for the benchmark minerals brucite, magnesite, nesquehonite, and hydromagnesite. The model shows how small differences in experimental conditions determine whether nesquehonite, hydromagnesite, or magnesite is the result of laboratory synthesis from carbonation of brucite, and what transformations are expected to occur on geological time scales. Because of the reliance on parameter-free first-principles methods, the model is reliably extensible to experimental conditions not readily accessible to experiment and to any mineral composition for which the structure is known or can be hypothesized, including structures containing defects, substitutions, or transitional structures during solid state transformations induced by temperature changes or processes such as water, CO2, or O2 diffusion. Demonstrated applications of the ab initio thermodynamic framework include an independent means to evaluate differences in thermodynamic data for lansfordite, predicting the properties of Mg analogues of Ca-based hydrated carbonates monohydrocalcite and ikaite, which have not been observed in nature, and an estimation of the thermodynamics of barringtonite from the stoichiometry and a single experimental observation.

Central safety factor and β N control on NSTX-U via beam power and plasma boundary shape modification, using TRANSP for closed loop simulations

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

Boyer, M. D.; Andre, R.; Gates, D. A.

The high-performance operational goals of NSTX-U will require development of advanced feedback control algorithms, including control of ßN and the safety factor profile. In this work, a novel approach to simultaneously controlling ßN and the value of the safety factor on the magnetic axis, q0, through manipulation of the plasma boundary shape and total beam power, is proposed. Simulations of the proposed scheme show promising results and motivate future experimental implementation and eventual integration into a more complex current profile control scheme planned to include actuation of individual beam powers, density, and loop voltage. As part of this work, amore » flexible framework for closed loop simulations within the high-fidelity code TRANSP was developed. The framework, used here to identify control-design-oriented models and to tune and test the proposed controller, exploits many of the predictive capabilities of TRANSP and provides a means for performing control calculations based on user-supplied data (controller matrices, target waveforms, etc.). The flexible framework should enable high-fidelity testing of a variety of control algorithms, thereby reducing the amount of expensive experimental time needed to implement new control algorithms on NSTX-U and other devices.« less

Small-scale multi-axial hybrid simulation of a shear-critical reinforced concrete frame

NASA Astrophysics Data System (ADS)

Sadeghian, Vahid; Kwon, Oh-Sung; Vecchio, Frank

2017-10-01

This study presents a numerical multi-scale simulation framework which is extended to accommodate hybrid simulation (numerical-experimental integration). The framework is enhanced with a standardized data exchange format and connected to a generalized controller interface program which facilitates communication with various types of laboratory equipment and testing configurations. A small-scale experimental program was conducted using a six degree-of-freedom hydraulic testing equipment to verify the proposed framework and provide additional data for small-scale testing of shearcritical reinforced concrete structures. The specimens were tested in a multi-axial hybrid simulation manner under a reversed cyclic loading condition simulating earthquake forces. The physical models were 1/3.23-scale representations of a beam and two columns. A mixed-type modelling technique was employed to analyze the remainder of the structures. The hybrid simulation results were compared against those obtained from a large-scale test and finite element analyses. The study found that if precautions are taken in preparing model materials and if the shear-related mechanisms are accurately considered in the numerical model, small-scale hybrid simulations can adequately simulate the behaviour of shear-critical structures. Although the findings of the study are promising, to draw general conclusions additional test data are required.

Central safety factor and βN control on NSTX-U via beam power and plasma boundary shape modification, using TRANSP for closed loop simulations

NASA Astrophysics Data System (ADS)

Boyer, M. D.; Andre, R.; Gates, D. A.; Gerhardt, S.; Goumiri, I. R.; Menard, J.

2015-05-01

The high-performance operational goals of NSTX-U will require development of advanced feedback control algorithms, including control of βN and the safety factor profile. In this work, a novel approach to simultaneously controlling βN and the value of the safety factor on the magnetic axis, q0, through manipulation of the plasma boundary shape and total beam power, is proposed. Simulations of the proposed scheme show promising results and motivate future experimental implementation and eventual integration into a more complex current profile control scheme planned to include actuation of individual beam powers, density, and loop voltage. As part of this work, a flexible framework for closed loop simulations within the high-fidelity code TRANSP was developed. The framework, used here to identify control-design-oriented models and to tune and test the proposed controller, exploits many of the predictive capabilities of TRANSP and provides a means for performing control calculations based on user-supplied data (controller matrices, target waveforms, etc). The flexible framework should enable high-fidelity testing of a variety of control algorithms, thereby reducing the amount of expensive experimental time needed to implement new control algorithms on NSTX-U and other devices.

Analysis and Modeling of DIII-D Experiments With OMFIT and Neural Networks

NASA Astrophysics Data System (ADS)

Meneghini, O.; Luna, C.; Smith, S. P.; Lao, L. L.; GA Theory Team

2013-10-01

The OMFIT integrated modeling framework is designed to facilitate experimental data analysis and enable integrated simulations. This talk introduces this framework and presents a selection of its applications to the DIII-D experiment. Examples include kinetic equilibrium reconstruction analysis; evaluation of MHD stability in the core and in the edge; and self-consistent predictive steady-state transport modeling. The OMFIT framework also provides the platform for an innovative approach based on neural networks to predict electron and ion energy fluxes. In our study a multi-layer feed-forward back-propagation neural network is built and trained over a database of DIII-D data. It is found that given the same parameters that the highest fidelity models use, the neural network model is able to predict to a large degree the heat transport profiles observed in the DIII-D experiments. Once the network is built, the numerical cost of evaluating the transport coefficients is virtually nonexistent, thus making the neural network model particularly well suited for plasma control and quick exploration of operational scenarios. The implementation of the neural network model and benchmark with experimental results and gyro-kinetic models will be discussed. Work supported in part by the US DOE under DE-FG02-95ER54309.

Experimental and Numerical Modeling of Fluid Flow Processes in Continuous Casting: Results from the LIMMCAST-Project

NASA Astrophysics Data System (ADS)

Timmel, K.; Kratzsch, C.; Asad, A.; Schurmann, D.; Schwarze, R.; Eckert, S.

2017-07-01

The present paper reports about numerical simulations and model experiments concerned with the fluid flow in the continuous casting process of steel. This work was carried out in the LIMMCAST project in the framework of the Helmholtz alliance LIMTECH. A brief description of the LIMMCAST facilities used for the experimental modeling at HZDR is given here. Ultrasonic and inductive techniques and the X-ray radioscopy were employed for flow measurements or visualizations of two-phase flow regimes occurring in the submerged entry nozzle and the mold. Corresponding numerical simulations were performed at TUBAF taking into account the dimensions and properties of the model experiments. Numerical models were successfully validated using the experimental data base. The reasonable and in many cases excellent agreement of numerical with experimental data allows to extrapolate the models to real casting configurations. Exemplary results will be presented here showing the effect of electromagnetic brakes or electromagnetic stirrers on the flow in the mold or illustrating the properties of two-phase flows resulting from an Ar injection through the stopper rod.

Experimental Demonstration of the Einstein-Podolsky-Rosen Steering Game Based on the All-Versus-Nothing Proof

NASA Astrophysics Data System (ADS)

Sun, Kai; Xu, Jin-Shi; Ye, Xiang-Jun; Wu, Yu-Chun; Chen, Jing-Ling; Li, Chuan-Feng; Guo, Guang-Can

2014-10-01

Einstein-Podolsky-Rosen (EPR) steering, a generalization of the original concept of "steering" proposed by Schrödinger, describes the ability of one system to nonlocally affect another system's states through local measurements. Some experimental efforts to test EPR steering in terms of inequalities have been made, which usually require many measurement settings. Analogy to the "all-versus-nothing" (AVN) proof of Bell's theorem without inequalities, testing steerability without inequalities would be more strong and require less resources. Moreover, the practical meaning of steering implies that it should also be possible to store the state information on the side to be steered, a result that has not yet been experimentally demonstrated. Using a recent AVN criterion for two-qubit entangled states, we experimentally implement a practical steering game using quantum memory. Furthermore, we develop a theoretical method to deal with the noise and finite measurement statistics within the AVN framework and apply it to analyze the experimental data. Our results clearly show the facilitation of the AVN criterion for testing steerability and provide a particularly strong perspective for understanding EPR steering.

A mechanics framework for a progressive failure methodology for laminated composites

NASA Technical Reports Server (NTRS)

Harris, Charles E.; Allen, David H.; Lo, David C.

1989-01-01

A laminate strength and life prediction methodology has been postulated for laminated composites which accounts for the progressive development of microstructural damage to structural failure. A damage dependent constitutive model predicts the stress redistribution in an average sense that accompanies damage development in laminates. Each mode of microstructural damage is represented by a second-order tensor valued internal state variable which is a strain like quantity. The mechanics framework together with the global-local strategy for predicting laminate strength and life is presented in the paper. The kinematic effects of damage are represented by effective engineering moduli in the global analysis and the results of the global analysis provide the boundary conditions for the local ply level stress analysis. Damage evolution laws are based on experimental results.

Skin Lesion Analysis towards Melanoma Detection Using Deep Learning Network.

PubMed

Li, Yuexiang; Shen, Linlin

2018-02-11

Skin lesions are a severe disease globally. Early detection of melanoma in dermoscopy images significantly increases the survival rate. However, the accurate recognition of melanoma is extremely challenging due to the following reasons: low contrast between lesions and skin, visual similarity between melanoma and non-melanoma lesions, etc. Hence, reliable automatic detection of skin tumors is very useful to increase the accuracy and efficiency of pathologists. In this paper, we proposed two deep learning methods to address three main tasks emerging in the area of skin lesion image processing, i.e., lesion segmentation (task 1), lesion dermoscopic feature extraction (task 2) and lesion classification (task 3). A deep learning framework consisting of two fully convolutional residual networks (FCRN) is proposed to simultaneously produce the segmentation result and the coarse classification result. A lesion index calculation unit (LICU) is developed to refine the coarse classification results by calculating the distance heat-map. A straight-forward CNN is proposed for the dermoscopic feature extraction task. The proposed deep learning frameworks were evaluated on the ISIC 2017 dataset. Experimental results show the promising accuracies of our frameworks, i.e., 0.753 for task 1, 0.848 for task 2 and 0.912 for task 3 were achieved.

Guiding the Design of Lessons by Using the MAPLET Framework: Matching Aims, Processes, Learner Expertise and Technologies

ERIC Educational Resources Information Center

Ifenthaler, Dirk; Gosper, Maree

2014-01-01

This paper introduces the MAPLET framework that was developed to map and link teaching aims, learning processes, learner expertise and technologies. An experimental study with 65 participants is reported to test the effectiveness of the framework as a guide to the design of lessons embedded within larger units of study. The findings indicate the…

Alternative theories of gravity and Lorentz violation

NASA Astrophysics Data System (ADS)

Xu, Rui; Foster, Joshua; Kostelecky, V. Alan

2017-01-01

General relativity has achieved many successes, including the prediction of experimental results. However, its incompatibility with quantum theory remains an obstacle. By extending the foundational properties of general relativity, alternative theories of gravity can be constructed. In this talk, we focus on fermion couplings in the weak-gravity limit of certain alternative theories of gravity. Under suitable experimental circumstances, some of these couplings match terms appearing in the gravitational SME, which is a general framework describing violations of local Lorentz invariance. Existing limits on Lorentz violation can therefore be used to constrain certain Lorentz-invariant alternative theories of gravity.

Self-injection-locking linewidth narrowing in a semiconductor laser coupled to an external fiber-optic ring resonator

NASA Astrophysics Data System (ADS)

Korobko, Dmitry A.; Zolotovskii, Igor O.; Panajotov, Krassimir; Spirin, Vasily V.; Fotiadi, Andrei A.

2017-12-01

We develop a theoretical framework for modeling of semiconductor laser coupled to an external fiber-optic ring resonator. The developed approach has shown good qualitative agreement between theoretical predictions and experimental results for particular configuration of a self-injection locked DFB laser delivering narrow-band radiation. The model is capable of describing the main features of the experimentally measured laser outputs such as laser line narrowing, spectral shape of generated radiation, mode-hoping instabilities and makes possible exploring the key physical mechanisms responsible for the laser operation stability.

BagMOOV: A novel ensemble for heart disease prediction bootstrap aggregation with multi-objective optimized voting.

PubMed

Bashir, Saba; Qamar, Usman; Khan, Farhan Hassan

2015-06-01

Conventional clinical decision support systems are based on individual classifiers or simple combination of these classifiers which tend to show moderate performance. This research paper presents a novel classifier ensemble framework based on enhanced bagging approach with multi-objective weighted voting scheme for prediction and analysis of heart disease. The proposed model overcomes the limitations of conventional performance by utilizing an ensemble of five heterogeneous classifiers: Naïve Bayes, linear regression, quadratic discriminant analysis, instance based learner and support vector machines. Five different datasets are used for experimentation, evaluation and validation. The datasets are obtained from publicly available data repositories. Effectiveness of the proposed ensemble is investigated by comparison of results with several classifiers. Prediction results of the proposed ensemble model are assessed by ten fold cross validation and ANOVA statistics. The experimental evaluation shows that the proposed framework deals with all type of attributes and achieved high diagnosis accuracy of 84.16 %, 93.29 % sensitivity, 96.70 % specificity, and 82.15 % f-measure. The f-ratio higher than f-critical and p value less than 0.05 for 95 % confidence interval indicate that the results are extremely statistically significant for most of the datasets.

A Combined Experimental and Computational Study on the Stability of Nanofluids Containing Metal Organic Frameworks

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

Annapureddy, Harsha Vardhan Reddy; Nune, Satish K.; Motkuri, Radha K.

2015-01-08

Computational studies on nanofluids composed of metal organic frameworks (MOFs) were performed using molecular modeling techniques. Grand Canonical Monte Carlo (GCMC) simulations were used to study adsorption behavior of 1,1,1,3,3-pentafluoropropane (R-245fa) in a MIL-101 MOF at various temperatures. To understand the stability of the nanofluid composed of MIL-101 particles, we performed molecular dynamics simulations to compute potentials of mean force between hypothetical MIL-101 fragments terminated with two different kinds of modulators in R-245fa and water. Our computed potentials of mean force results indicate that the MOF particles tend to disperse better in water than in R-245fa. The reasons for thismore » observation were analyzed and discussed. Our results agree with experimental results indicating that the employed potential models and modeling approaches provide good description of molecular interactions and the reliabilities. Work performed by LXD was supported by the U.S. Department of Energy (DOE), Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences. Work performed by HVRA, SKN, RKM, and PBM was supported by the Office of Energy Efficiency and Renewable Energy, Geothermal Technologies Program. Pacific Northwest National Laboratory is a multiprogram national laboratory operated for DOE by Battelle.« less

An Integrated Finite Element-based Simulation Framework: From Hole Piercing to Hole Expansion

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

Hu, Xiaohua; Sun, Xin; Golovashchenko, Segey F.

An integrated finite element-based modeling framework is developed to predict the hole expansion ratio (HER) of AA6111-T4 sheet by considering the piercing-induced damages around the hole edge. Using damage models and parameters calibrated from previously reported tensile stretchability studies, the predicted HER correlates well with experimentally measured HER values for different hole piercing clearances. The hole piercing model shows burrs are not generated on the sheared surface for clearances less than 20%, which corresponds well with the experimental data on pierced holes cross-sections. Finite-element-calculated HER also is not especially sensitive to piercing clearances less than this value. However, as clearancesmore » increase to 30% and further to 40%, the HER values are predicted to be considerably smaller, also consistent with experimental measurements. Upon validation, the integrated modeling framework is used to examine the effects of different hole piercing and hole expansion conditions on the critical HERs for AA6111-T4.« less

Crystal plasticity modeling of irradiation growth in Zircaloy-2

NASA Astrophysics Data System (ADS)

Patra, Anirban; Tomé, Carlos N.; Golubov, Stanislav I.

2017-08-01

A physically based reaction-diffusion model is implemented in the visco-plastic self-consistent (VPSC) crystal plasticity framework to simulate irradiation growth in hcp Zr and its alloys. The reaction-diffusion model accounts for the defects produced by the cascade of displaced atoms, their diffusion to lattice sinks and the contribution to crystallographic strain at the level of single crystals. The VPSC framework accounts for intergranular interactions and irradiation creep, and calculates the strain in the polycrystalline ensemble. A novel scheme is proposed to model the simultaneous evolution of both, number density and radius, of irradiation-induced dislocation loops directly from experimental data of dislocation density evolution during irradiation. This framework is used to predict the irradiation growth behaviour of cold-worked Zircaloy-2 and trends compared to available experimental data. The role of internal stresses in inducing irradiation creep is discussed. Effects of grain size, texture and external stress on the coupled irradiation growth and creep behaviour are also studied and compared with available experimental data.

Microscopic Study of the 6Li(p, α)3He Reaction at Low Energies

NASA Astrophysics Data System (ADS)

Solovyev, Alexander; Igashov, Sergey

2018-01-01

The 6Li(p, α)3He reaction important for nuclear astrophysics is studied in the framework of a microscopic approach based on a multichannel algebraic version of the resonating group model. Astrophysical S-factor for the reaction is calculated at low energies. The obtained result is compared with experimental data and other theoretical calculations.

Meaning and Function of Dummy Auxiliaries in Adult Acquisition of Dutch as an Additional Language

ERIC Educational Resources Information Center

Julien, Manuela; van Hout, Roeland; van de Craats, Ineke

2016-01-01

This article presents the results of experimental data on language production and comprehension. These show that adult learners of Dutch as an additional language, with different language backgrounds, and a L2 proficiency below level A2 (Waystage) of the Common European Framework of Reference for Languages (CEFR; Council of Europe, 2001), use…

Optimizing Estimated Loss Reduction for Active Sampling in Rank Learning

DTIC Science & Technology

2008-01-01

active learning framework for SVM-based and boosting-based rank learning. Our approach suggests sampling based on maximizing the estimated loss differential over unlabeled data. Experimental results on two benchmark corpora show that the proposed model substantially reduces the labeling effort, and achieves superior performance rapidly with as much as 30% relative improvement over the margin-based sampling

Developing a Novel Hydrogen Sponge with Ideal Binding Energy and High Surface Area for Practical Hydrogen Storage

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

Chung, T. C. Mike

This Phase I (5 quarters) research project was to examine the validity of a new class of boron-containing polymer (B-polymer) frameworks, serving as the adsorbents for the practical onboard H2 storage applications. Three B-polymer frameworks were synthesized and investigated, which include B-poly(butyenylstyrene) (B-PBS) framework (A), B-poly(phenyldiacetyene) (B-PPDA) framework (B), and B-poly(phenyltriacetylene) (B-PPTA) framework (C). They are 2-D polymer structures with the repeating cyclic units that spontaneously form open morphology and the B-doped (p-type) π-electrons delocalized surfaces. The ideal B-polymer framework shall exhibit open micropores (pore size in the range of 1-1.5nm) with high surface area (>3000 m 2/g), and themore » B-dopants in the conjugated framework shall provide high surface energy for interacting with H 2 molecules (an ideal H 2 binding energy in the range of 15-25 kJ/mol). The pore size distribution and H2 binding energy were investigated at both Penn State and NREL laboratories. So far, the experimental results show the successful synthesis of B-polymer frameworks with the relatively well-defined planar (2-D) structures. The intrinsically formed porous morphology exhibits a broad pore size distribution (in the range of 0.5-10 nm) with specific surface area (~1000 m 2/g). The miss-alignment between 2-D layers may block some micropore channels and limit gas diffusion throughout the entire matrix. In addition, the 2-D planar conjugated structure may also allow free π-electrons delocalization throughout the framework, which significantly reduces the acidity of B-moieties (electron-deficiency).The resulting 2-D B-polymer frameworks only exhibit a small increase of H 2 binding energy in the range of 8-9 KJ/mole (quite constant over the whole sorption range).« less

Manifestation of α clustering in 10Be via α -knockout reaction

NASA Astrophysics Data System (ADS)

Lyu, Mengjiao; Yoshida, Kazuki; Kanada-En'yo, Yoshiko; Ogata, Kazuyuki

2018-04-01

Background: Proton-induced α -knockout reactions may allow direct experimental observation of α clustering in nuclei. This is obtained by relating the theoretical descriptions of clustering states to the experimental reaction observables. It is desired to introduce microscopic structure models into the theoretical frameworks for α -knockout reactions. Purpose: Our goal is to probe the α clustering in the 10Be nucleus by proton-induced α -knockout reaction observables. Method: We adopt an extended version of the Tohsaki-Horiuchi-Schuck-Röpke wave function of 10Be and integrate it with the distorted-wave impulse approximation framework for the calculation of (p ,p α ) -knockout reactions. Results: We make the first calculation for the 10Be(p ,p α )6He reaction at 250 MeV by implementing a microscopic α -cluster wave function, and we predict the triple-differential cross section (TDX). Furthermore, by constructing artificial states of the target nucleus 10Be with compact or dilute spatial distributions, the TDX is found to be highly sensitive to the extent of clustering in the target nuclei. Conclusions: These results provide reliable manifestation of α clustering in 10Be.

Computational Analysis of Advanced Shape-Memory Alloy Devices Through a Robust Modeling Framework

NASA Astrophysics Data System (ADS)

Scalet, Giulia; Conti, Michele; Auricchio, Ferdinando

2017-06-01

Shape-memory alloys (SMA) provide significant advantages in various industrial fields, but their manufacturing and commercialization are currently hindered. This is attributed mainly to the poor knowledge of material behavior and the lack of standards in its mechanical characterization. SMA products are usually developed by trial-and-error testing to address specific design requirements, thus increasing costs and time. The development of simulation tools offers a possible solution to assist engineers and designers and allows to better understand SMA transformation phenomena. Accordingly, the purpose of the present paper is to numerically analyze and predict the response of spring-like actuators and septal occluders, which are industrial components exploiting the shape-memory and pseudoelastic properties of SMAs, respectively. The methodology includes two main stages: the implementation of the three-dimensional phenomenological model known as Souza- Auricchio model and the finite element modeling of the device. A discussion about the steps of each stage, as parameter identification and model generalizations, is provided. Validation results are presented through a comparison with the results of a performed experimental campaign. The framework proves good prediction capabilities and allows to reduce the number of experimental tests in the future.

Taylor bubbles at high viscosity ratios: experiments and numerical simulations

NASA Astrophysics Data System (ADS)

Hewakandamby, Buddhika; Hasan, Abbas; Azzopardi, Barry; Xie, Zhihua; Pain, Chris; Matar, Omar

2015-11-01

The Taylor bubble is a single long bubble which nearly fills the entire cross section of a liquid-filled circular tube, often occurring in gas-liquid slug flows in many industrial applications, particularly oil and gas production. The objective of this study is to investigate the fluid dynamics of three-dimensional Taylor bubble rising in highly viscous silicone oil in a vertical pipe. An adaptive unstructured mesh modelling framework is adopted here which can modify and adapt anisotropic unstructured meshes to better represent the underlying physics of bubble rising and reduce computational effort without sacrificing accuracy. The numerical framework consists of a mixed control volume and finite element formulation, a `volume of fluid'-type method for the interface-capturing based on a compressive control volume advection method, and a force-balanced algorithm for the surface tension implementation. Experimental results for the Taylor bubble shape and rise velocity are presented, together with numerical results for the dynamics of the bubbles. A comparison of the simulation predictions with experimental data available in the literature is also presented to demonstrate the capabilities of our numerical method. EPSRC Programme Grant, MEMPHIS, EP/K0039761/1.

Elucidating the breathing of the metal-organic framework MIL-53(Sc) with ab initio molecular dynamics simulations and in situ X-ray powder diffraction experiments.

PubMed

Chen, Linjiang; Mowat, John P S; Fairen-Jimenez, David; Morrison, Carole A; Thompson, Stephen P; Wright, Paul A; Düren, Tina

2013-10-23

Ab initio molecular dynamics (AIMD) simulations have been used to predict structural transitions of the breathing metal-organic framework (MOF) MIL-53(Sc) in response to changes in temperature over the range 100-623 K and adsorption of CO2 at 0-0.9 bar at 196 K. The method has for the first time been shown to predict successfully both temperature-dependent structural changes and the structural response to variable sorbate uptake of a flexible MOF. AIMD employing dispersion-corrected density functional theory accurately simulated the experimentally observed closure of MIL-53(Sc) upon solvent removal and the transition of the empty MOF from the closed-pore phase to the very-narrow-pore phase (symmetry change from P2(1)/c to C2/c) with increasing temperature, indicating that it can directly take into account entropic as well as enthalpic effects. We also used AIMD simulations to mimic the CO2 adsorption of MIL-53(Sc) in silico by allowing the MIL-53(Sc) framework to evolve freely in response to CO2 loadings corresponding to the two steps in the experimental adsorption isotherm. The resulting structures enabled the structure determination of the two CO2-containing intermediate and large-pore phases observed by experimental synchrotron X-ray diffraction studies with increasing CO2 pressure; this would not have been possible for the intermediate structure via conventional methods because of diffraction peak broadening. Furthermore, the strong and anisotropic peak broadening observed for the intermediate structure could be explained in terms of fluctuations of the framework predicted by the AIMD simulations. Fundamental insights from the molecular-level interactions further revealed the origin of the breathing of MIL-53(Sc) upon temperature variation and CO2 adsorption. These simulations illustrate the power of the AIMD method for the prediction and understanding of the behavior of flexible microporous solids.

Experimental Learning Enhancing Improvisation Skills

ERIC Educational Resources Information Center

Pereira Christopoulos, Tania; Wilner, Adriana; Trindade Bestetti, Maria Luisa

2016-01-01

Purpose: This study aims to present improvisation training and experimentation as an alternative method to deal with unexpected events in which structured processes do not seem to work. Design/Methodology/Approach: Based on the literature of sensemaking and improvisation, the study designs a framework and process model of experimental learning…

Integrated corridor management analysis, modeling, and simulation experimental plan for the test corridor.

DOT National Transportation Integrated Search

2008-03-01

This document, the AMS Experimental Plan, lays out the scope of analysis that will be conducted through the application of the AMS methodology to the Test Corridor. The specific objectives of the Experimental Plan are: create an AMS framework that id...

Dynamic behaviour of a rolling tyre: Experimental and numerical analyses

NASA Astrophysics Data System (ADS)

Gonzalez Diaz, Cristobal; Kindt, Peter; Middelberg, Jason; Vercammen, Stijn; Thiry, Christophe; Close, Roland; Leyssens, Jan

2016-03-01

Based on the results of experimental and numerical analyses, the effect of rotation on the tyre dynamic behaviour is investigated. Better understanding of these effects will further improve the ability to control and optimize the noise and vibrations that result from the interaction between the road surface and the rolling tyre. Therefore, more understanding in the complex tyre dynamic properties will contribute to develop tyre design strategies to lower the tyre/road noise while less affecting other tyre performances. The presented work is performed in the framework of the European industry-academia project TIRE-DYN, with partners Goodyear, Katholieke Universiteit Leuven and LMS International. The effect of rotation on the tyre dynamic behaviour is quantified for different operating conditions of the tyre, such as load, air pressure and rotation speed. By means of experimental and numerical analyses, the effects of rotation on the tyre dynamic behaviour are studied.

A two-dimensional statistical framework connecting thermodynamic profiles with filaments in the scrape off layer and application to experiments

NASA Astrophysics Data System (ADS)

Militello, F.; Farley, T.; Mukhi, K.; Walkden, N.; Omotani, J. T.

2018-05-01

A statistical framework was introduced in Militello and Omotani [Nucl. Fusion 56, 104004 (2016)] to correlate the dynamics and statistics of L-mode and inter-ELM plasma filaments with the radial profiles of thermodynamic quantities they generate in the Scrape Off Layer. This paper extends the framework to cases in which the filaments are emitted from the separatrix at different toroidal positions and with a finite toroidal velocity. It is found that the toroidal velocity does not affect the profiles, while the toroidal distribution of filament emission renormalises the waiting time between two events. Experimental data collected by visual camera imaging are used to evaluate the statistics of the fluctuations, to inform the choice of the probability distribution functions used in the application of the framework. It is found that the toroidal separation of the filaments is exponentially distributed, thus suggesting the lack of a toroidal modal structure. Finally, using these measurements, the framework is applied to an experimental case and good agreement is found.

Robust adaptive control modeling of human arm movements subject to altered gravity and mechanical loads

NASA Astrophysics Data System (ADS)

Tryfonidis, Michail

It has been observed that during orbital spaceflight the absence of gravitation related sensory inputs causes incongruence between the expected and the actual sensory feedback resulting from voluntary movements. This incongruence results in a reinterpretation or neglect of gravity-induced sensory input signals. Over time, new internal models develop, gradually compensating for the loss of spatial reference. The study of adaptation of goal-directed movements is the main focus of this thesis. The hypothesis is that during the adaptive learning process the neural connections behave in ways that can be described by an adaptive control method. The investigation presented in this thesis includes two different sets of experiments. A series of dart throwing experiments took place onboard the space station Mir. Experiments also took place at the Biomechanics lab at MIT, where the subjects performed a series of continuous trajectory tracking movements while a planar robotic manipulandum exerted external torques on the subjects' moving arms. The experimental hypothesis for both experiments is that during the first few trials the subjects will perform poorly trying to follow a prescribed trajectory, or trying to hit a target. A theoretical framework is developed that is a modification of the sliding control method used in robotics. The new control framework is an attempt to explain the adaptive behavior of the subjects. Numerical simulations of the proposed framework are compared with experimental results and predictions from competitive models. The proposed control methodology extends the results of the sliding mode theory to human motor control. The resulting adaptive control model of the motor system is robust to external dynamics, even those of negative gain, uses only position and velocity feedback, and achieves bounded steady-state error without explicit knowledge of the system's nonlinearities. In addition, the experimental and modeling results demonstrate that visuomotor learning is important not only for error correction through internal model adaptation on ground or in microgravity, but also for the minimization of the total mean-square error in the presence of random variability. Thus human intelligent decision displays certain attributes that seem to conform to Bayesian statistical games. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)

Steganalysis based on reducing the differences of image statistical characteristics

NASA Astrophysics Data System (ADS)

Wang, Ran; Niu, Shaozhang; Ping, Xijian; Zhang, Tao

2018-04-01

Compared with the process of embedding, the image contents make a more significant impact on the differences of image statistical characteristics. This makes the image steganalysis to be a classification problem with bigger withinclass scatter distances and smaller between-class scatter distances. As a result, the steganalysis features will be inseparate caused by the differences of image statistical characteristics. In this paper, a new steganalysis framework which can reduce the differences of image statistical characteristics caused by various content and processing methods is proposed. The given images are segmented to several sub-images according to the texture complexity. Steganalysis features are separately extracted from each subset with the same or close texture complexity to build a classifier. The final steganalysis result is figured out through a weighted fusing process. The theoretical analysis and experimental results can demonstrate the validity of the framework.

A continuum dislocation dynamics framework for plasticity of polycrystalline materials

NASA Astrophysics Data System (ADS)

Askari, Hesam Aldin

The objective of this research is to investigate the mechanical response of polycrystals in different settings to identify the mechanisms that give rise to specific response observed in the deformation process. Particularly the large deformation of magnesium alloys and yield properties of copper in small scales are investigated. We develop a continuum dislocation dynamics framework based on dislocation mechanisms and interaction laws and implement this formulation in a viscoplastic self-consistent scheme to obtain the mechanical response in a polycrystalline system. The versatility of this method allows various applications in the study of problems involving large deformation, study of microstructure and its evolution, superplasticity, study of size effect in polycrystals and stochastic plasticity. The findings from the numerical solution are compared to the experimental results to validate the simulation results. We apply this framework to study the deformation mechanisms in magnesium alloys at moderate to fast strain rates and room temperature to 450 °C. Experiments for the same range of strain rates and temperatures were carried out to obtain the mechanical and material properties, and to compare with the numerical results. The numerical approach for magnesium is divided into four main steps; 1) room temperature unidirectional loading 2) high temperature deformation without grain boundary sliding 3) high temperature with grain boundary sliding mechanism 4) room temperature cyclic loading. We demonstrate the capability of our modeling approach in prediction of mechanical properties and texture evolution and discuss the improvement obtained by using the continuum dislocation dynamics method. The framework was also applied to nano-sized copper polycrystals to study the yield properties at small scales and address the observed yield scatter. By combining our developed method with a Monte Carlo simulation approach, the stochastic plasticity at small length scales was studied and the sources of the uncertainty in the polycrystalline structure are discussed. Our results suggest that the stochastic response is mainly because of a) stochastic plasticity due to dislocation substructure inside crystals and b) the microstructure of the polycrystalline material. The extent of the uncertainty is correlated to the "effective cell length" in the sampling procedure whether using simulations and experimental approach.

The effect of pressure on open-framework silicates: elastic behaviour and crystal-fluid interaction

NASA Astrophysics Data System (ADS)

Gatta, G. D.; Lotti, P.; Tabacchi, G.

2018-02-01

The elastic behaviour and the structural evolution of microporous materials compressed hydrostatically in a pressure-transmitting fluid are drastically affected by the potential crystal-fluid interaction, with a penetration of new molecules through the zeolitic cavities in response to applied pressure. In this manuscript, the principal mechanisms that govern the P-behaviour of zeolites with and without crystal-fluid interaction are described, on the basis of previous experimental findings and computational modelling studies. When no crystal-fluid interaction occurs, the effects of pressure are mainly accommodated by tilting of (quasi-rigid) tetrahedra around O atoms that behave as hinges. Tilting of tetrahedra is the dominant mechanism at low-mid P-regime, whereas distortion and compression of tetrahedra represent the mechanisms which usually dominate the mid-high P regime. One of the most common deformation mechanisms in zeolitic framework is the increase of channels ellipticity. The deformation mechanisms are dictated by the topological configuration of the tetrahedral framework; however, the compressibility of the cavities is controlled by the nature and bonding configuration of the ionic and molecular content, resulting in different unit-cell volume compressibility in isotypic structures. The experimental results pertaining to compression in "penetrating" fluids, and thus with crystal-fluid interaction, showed that not all the zeolites experience a P-induced intrusion of new monoatomic species or molecules from the P-transmitting fluids. For example, zeolites with well-stuffed channels at room conditions (e.g. natural zeolites) tend to hinder the penetration of new species through the zeolitic cavities. Several variables govern the sorption phenomena at high pressure, among those: the "free diameters" of the framework cavities, the chemical nature and the configuration of the extra-framework population, the partial pressure of the penetrating molecule in the fluid (if mixed with other non-penetrating molecules), the rate of P-increase, the surface/volume ratio of the crystallites under investigations and the temperature at which the experiment is conducted. An overview of the intrusion phenomena of monoatomic species (e.g. He, Ar, Kr), small (e.g. H2O, CO2) and complex molecules, along with the P-induced polymerization phenomena (e.g. C2H2, C2H4, C2H6O, C2H6O2, BNH6, electrolytic MgCl2·21H2O solution) is provided, with a discussion of potential technological and geological implications of these experimental findings.

Extended Theories of Gravitation. Observation Protocols and Experimental Tests

NASA Astrophysics Data System (ADS)

Fatibene, Lorenzo; Ferraris, Marco; Francaviglia, Mauro; Magnano, Guido

2013-09-01

Within the framework of extended theories of gravitation we shall discuss physical equivalences among different formalisms and classical tests. As suggested by the Ehlers-Pirani-Schild framework, the conformal invariance will be preserved and its effect on observational protocols discussed. Accordingly, we shall review standard tests showing how Palatini f(R)-theories naturally passes solar system tests. Observation protocols will be discussed in this wider framework.

Mathematical Problem Solving Ability of Junior High School Students through Ang’s Framework for Mathematical Modelling Instruction

NASA Astrophysics Data System (ADS)

Fasni, N.; Turmudi, T.; Kusnandi, K.

2017-09-01

This research background of this research is the importance of student problem solving abilities. The purpose of this study is to find out whether there are differences in the ability to solve mathematical problems between students who have learned mathematics using Ang’s Framework for Mathematical Modelling Instruction (AFFMMI) and students who have learned using scientific approach (SA). The method used in this research is a quasi-experimental method with pretest-postest control group design. Data analysis of mathematical problem solving ability using Indepent Sample Test. The results showed that there was a difference in the ability to solve mathematical problems between students who received learning with Ang’s Framework for Mathematical Modelling Instruction and students who received learning with a scientific approach. AFFMMI focuses on mathematical modeling. This modeling allows students to solve problems. The use of AFFMMI is able to improve the solving ability.

Estimating parameters with pre-specified accuracies in distributed parameter systems using optimal experiment design

NASA Astrophysics Data System (ADS)

Potters, M. G.; Bombois, X.; Mansoori, M.; Hof, Paul M. J. Van den

2016-08-01

Estimation of physical parameters in dynamical systems driven by linear partial differential equations is an important problem. In this paper, we introduce the least costly experiment design framework for these systems. It enables parameter estimation with an accuracy that is specified by the experimenter prior to the identification experiment, while at the same time minimising the cost of the experiment. We show how to adapt the classical framework for these systems and take into account scaling and stability issues. We also introduce a progressive subdivision algorithm that further generalises the experiment design framework in the sense that it returns the lowest cost by finding the optimal input signal, and optimal sensor and actuator locations. Our methodology is then applied to a relevant problem in heat transfer studies: estimation of conductivity and diffusivity parameters in front-face experiments. We find good correspondence between numerical and theoretical results.

Semantic Framework of Internet of Things for Smart Cities: Case Studies.

PubMed

Zhang, Ningyu; Chen, Huajun; Chen, Xi; Chen, Jiaoyan

2016-09-14

In recent years, the advancement of sensor technology has led to the generation of heterogeneous Internet-of-Things (IoT) data by smart cities. Thus, the development and deployment of various aspects of IoT-based applications are necessary to mine the potential value of data to the benefit of people and their lives. However, the variety, volume, heterogeneity, and real-time nature of data obtained from smart cities pose considerable challenges. In this paper, we propose a semantic framework that integrates the IoT with machine learning for smart cities. The proposed framework retrieves and models urban data for certain kinds of IoT applications based on semantic and machine-learning technologies. Moreover, we propose two case studies: pollution detection from vehicles and traffic pattern detection. The experimental results show that our system is scalable and capable of accommodating a large number of urban regions with different types of IoT applications.

Semantic Framework of Internet of Things for Smart Cities: Case Studies

PubMed Central

Zhang, Ningyu; Chen, Huajun; Chen, Xi; Chen, Jiaoyan

2016-01-01

In recent years, the advancement of sensor technology has led to the generation of heterogeneous Internet-of-Things (IoT) data by smart cities. Thus, the development and deployment of various aspects of IoT-based applications are necessary to mine the potential value of data to the benefit of people and their lives. However, the variety, volume, heterogeneity, and real-time nature of data obtained from smart cities pose considerable challenges. In this paper, we propose a semantic framework that integrates the IoT with machine learning for smart cities. The proposed framework retrieves and models urban data for certain kinds of IoT applications based on semantic and machine-learning technologies. Moreover, we propose two case studies: pollution detection from vehicles and traffic pattern detection. The experimental results show that our system is scalable and capable of accommodating a large number of urban regions with different types of IoT applications. PMID:27649185

In Vivo Investigation of the Effectiveness of a Hyper-viscoelastic Model in Simulating Brain Retraction

NASA Astrophysics Data System (ADS)

Li, Ping; Wang, Weiwei; Zhang, Chenxi; An, Yong; Song, Zhijian

2016-07-01

Intraoperative brain retraction leads to a misalignment between the intraoperative positions of the brain structures and their previous positions, as determined from preoperative images. In vitro swine brain sample uniaxial tests showed that the mechanical response of brain tissue to compression and extension could be described by the hyper-viscoelasticity theory. The brain retraction caused by the mechanical process is a combination of brain tissue compression and extension. In this paper, we first constructed a hyper-viscoelastic framework based on the extended finite element method (XFEM) to simulate intraoperative brain retraction. To explore its effectiveness, we then applied this framework to an in vivo brain retraction simulation. The simulation strictly followed the clinical scenario, in which seven swine were subjected to brain retraction. Our experimental results showed that the hyper-viscoelastic XFEM framework is capable of simulating intraoperative brain retraction and improving the navigation accuracy of an image-guided neurosurgery system (IGNS).

PRESAGE: PRivacy-preserving gEnetic testing via SoftwAre Guard Extension.

PubMed

Chen, Feng; Wang, Chenghong; Dai, Wenrui; Jiang, Xiaoqian; Mohammed, Noman; Al Aziz, Md Momin; Sadat, Md Nazmus; Sahinalp, Cenk; Lauter, Kristin; Wang, Shuang

2017-07-26

Advances in DNA sequencing technologies have prompted a wide range of genomic applications to improve healthcare and facilitate biomedical research. However, privacy and security concerns have emerged as a challenge for utilizing cloud computing to handle sensitive genomic data. We present one of the first implementations of Software Guard Extension (SGX) based securely outsourced genetic testing framework, which leverages multiple cryptographic protocols and minimal perfect hash scheme to enable efficient and secure data storage and computation outsourcing. We compared the performance of the proposed PRESAGE framework with the state-of-the-art homomorphic encryption scheme, as well as the plaintext implementation. The experimental results demonstrated significant performance over the homomorphic encryption methods and a small computational overhead in comparison to plaintext implementation. The proposed PRESAGE provides an alternative solution for secure and efficient genomic data outsourcing in an untrusted cloud by using a hybrid framework that combines secure hardware and multiple crypto protocols.

Design and performance frameworks for constructing problem-solving simulations.

PubMed

Stevens, Ron; Palacio-Cayetano, Joycelin

2003-01-01

Rapid advancements in hardware, software, and connectivity are helping to shorten the times needed to develop computer simulations for science education. These advancements, however, have not been accompanied by corresponding theories of how best to design and use these technologies for teaching, learning, and testing. Such design frameworks ideally would be guided less by the strengths/limitations of the presentation media and more by cognitive analyses detailing the goals of the tasks, the needs and abilities of students, and the resulting decision outcomes needed by different audiences. This article describes a problem-solving environment and associated theoretical framework for investigating how students select and use strategies as they solve complex science problems. A framework is first described for designing on-line problem spaces that highlights issues of content, scale, cognitive complexity, and constraints. While this framework was originally designed for medical education, it has proven robust and has been successfully applied to learning environments from elementary school through medical school. Next, a similar framework is detailed for collecting student performance and progress data that can provide evidence of students' strategic thinking and that could potentially be used to accelerate student progress. Finally, experimental validation data are presented that link strategy selection and use with other metrics of scientific reasoning and student achievement.

Design and Performance Frameworks for Constructing Problem-Solving Simulations

PubMed Central

Stevens, Ron; Palacio-Cayetano, Joycelin

2003-01-01

Rapid advancements in hardware, software, and connectivity are helping to shorten the times needed to develop computer simulations for science education. These advancements, however, have not been accompanied by corresponding theories of how best to design and use these technologies for teaching, learning, and testing. Such design frameworks ideally would be guided less by the strengths/limitations of the presentation media and more by cognitive analyses detailing the goals of the tasks, the needs and abilities of students, and the resulting decision outcomes needed by different audiences. This article describes a problem-solving environment and associated theoretical framework for investigating how students select and use strategies as they solve complex science problems. A framework is first described for designing on-line problem spaces that highlights issues of content, scale, cognitive complexity, and constraints. While this framework was originally designed for medical education, it has proven robust and has been successfully applied to learning environments from elementary school through medical school. Next, a similar framework is detailed for collecting student performance and progress data that can provide evidence of students' strategic thinking and that could potentially be used to accelerate student progress. Finally, experimental validation data are presented that link strategy selection and use with other metrics of scientific reasoning and student achievement. PMID:14506505

An active monitoring method for flood events

NASA Astrophysics Data System (ADS)

Chen, Zeqiang; Chen, Nengcheng; Du, Wenying; Gong, Jianya

2018-07-01

Timely and active detecting and monitoring of a flood event are critical for a quick response, effective decision-making and disaster reduction. To achieve the purpose, this paper proposes an active service framework for flood monitoring based on Sensor Web services and an active model for the concrete implementation of the active service framework. The framework consists of two core components-active warning and active planning. The active warning component is based on a publish-subscribe mechanism implemented by the Sensor Event Service. The active planning component employs the Sensor Planning Service to control the execution of the schemes and models and plans the model input data. The active model, called SMDSA, defines the quantitative calculation method for five elements, scheme, model, data, sensor, and auxiliary information, as well as their associations. Experimental monitoring of the Liangzi Lake flood in the summer of 2010 is conducted to test the proposed framework and model. The results show that 1) the proposed active service framework is efficient for timely and automated flood monitoring. 2) The active model, SMDSA, is a quantitative calculation method used to monitor floods from manual intervention to automatic computation. 3) As much preliminary work as possible should be done to take full advantage of the active service framework and the active model.

78 FR 58123 - Migratory Bird Hunting; Final Frameworks for Late-Season Migratory Bird Hunting Regulations

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-20

... recommended changing Indiana's experimental late Canada goose season status to operational. Service Response: We concur with the Mississippi Flyway Council's recommendation to make Indiana's experimental late Canada goose season in the Terre Haute region operational. In 2007, Indiana initiated an experimental...

Thermodynamically consistent relations involving plasticity, internal energy and thermal effects.

PubMed

Schreyer, H L; Maudlin, P J

2005-11-15

Experimental data associated with plastic deformations indicate that the temperature is less than that predicted from dissipation based on plastic work. To obtain reasonable correlation between theoretical and experimental results, the plastic work is often multiplied by a constant beta. This paper provides an alternative thermodynamic framework in which it is proposed that there is an additional internal energy associated with dislocation pile-up or increase in dislocation density. The form of this internal energy follows from experimental data that relates flow stress to dislocation density and to equivalent plastic strain. The result is that beta is not a constant but a derived function. Representative results for beta and temperature as functions of effective plastic strain are provided for both an uncoupled and a coupled thermoplastic theory. In addition to providing features that are believed to be representative of many metals, the formulation can be used as a basis for more advanced theories such as those needed for large deformations and general forms of internal energy.

Numerical validation of selected computer programs in nonlinear analysis of steel frame exposed to fire

NASA Astrophysics Data System (ADS)

Maślak, Mariusz; Pazdanowski, Michał; Woźniczka, Piotr

2018-01-01

Validation of fire resistance for the same steel frame bearing structure is performed here using three different numerical models, i.e. a bar one prepared in the SAFIR environment, and two 3D models developed within the framework of Autodesk Simulation Mechanical (ASM) and an alternative one developed in the environment of the Abaqus code. The results of the computer simulations performed are compared with the experimental results obtained previously, in a laboratory fire test, on a structure having the same characteristics and subjected to the same heating regimen. Comparison of the experimental and numerically determined displacement evolution paths for selected nodes of the considered frame during the simulated fire exposure constitutes the basic criterion applied to evaluate the validity of the numerical results obtained. The experimental and numerically determined estimates of critical temperature specific to the considered frame and related to the limit state of bearing capacity in fire have been verified as well.

A Learning Framework for Development.

ERIC Educational Resources Information Center

Chi, Michelene T. H.; Rees, Ernest T.

1983-01-01

Responding to recent advances in developmental and cognitive science research on knowledge acquisition, this report presents a theoretical framework for analyzing cognitive development as a process of learning. The first section summarizes three developmental characteristics recognized in both the Piagetian and the quantita experimental tradition:…

Dynamical dark matter: A new framework for dark-matter physics

NASA Astrophysics Data System (ADS)

Dienes, Keith R.; Thomas, Brooks

2013-05-01

Although much remains unknown about the dark matter of the universe, one property is normally considered sacrosanct: dark matter must be stable well beyond cosmological time scales. However, a new framework for dark-matter physics has recently been proposed which challenges this assumption. In the "dynamical dark matter" (DDM) framework, the dark sector consists of a vast ensemble of individual dark-matter components with differing masses, lifetimes, and cosmological abundances. Moreover, the usual requirement of stability is replaced by a delicate balancing between lifetimes and cosmological abundances across the ensemble as a whole. As a result, it is possible for the DDM ensemble to remain consistent with all experimental and observational bounds on dark matter while nevertheless giving rise to collective behaviors which transcend those normally associated with traditional dark-matter candidates. These include a new, non-trivial darkmatter equation of state as well as potentially distinctive signatures in collider and direct-detection experiments. In this review article, we provide a self-contained introduction to the DDM framework and summarize some of the work which has recently been done in this area. We also present an explicit model within the DDM framework, and outline a number of ideas for future investigation.

Inductive reasoning in the context of discovery: Analogy as an experimental stratagem in the history and philosophy of science.

PubMed

Fisher, Amy A

2018-06-01

Building on Norton's "material theory of induction," this paper shows through careful historical analysis that analogy can act as a methodological principle or stratagem, providing experimentalists with a useful framework to assess data and devise novel experiments. Although this particular case study focuses on late eighteenth and early nineteenth-century experiments on the properties and composition of acids, the results of this investigation may be extended and applied to other research programs. A stage in-between what Steinle calls "exploratory experimentation" and robust theory, I argue that analogy encouraged research to substantiate why the likenesses should outweigh the differences (or vice versa) when evaluating results and designing experiments. Copyright © 2018 Elsevier Ltd. All rights reserved.

Modeling of 1.5 μm range gated imaging for small surface vessel identification

NASA Astrophysics Data System (ADS)

Espinola, Richard L.; Steinvall, Ove; Elmquist, Magnus; Karlsson, Kjell

2010-10-01

Within the framework of the NATO group (NATO SET-132/RTG-72) on imaging ladars, a test was performed to collect simultaneous multi-mode LADAR signatures of maritime objects entering and leaving San Diego Harbor. Beside ladars, passive sensors were also employed during the test which occurred during April 2009 from Point Loma and the harbor in San Diego. This paper will report on 1.5 μm gated imaging on a number of small civilian surface vessels with the aim to present human perception experimental results and comparisons with sensor performance models developed by US Army RDECOM CERDEC NVESD. We use controlled human perception tests to measure target identification performance and compare the experimental results with model predictions.

Computational and experimental investigation of free vibration and flutter of bridge decks

NASA Astrophysics Data System (ADS)

Helgedagsrud, Tore A.; Bazilevs, Yuri; Mathisen, Kjell M.; Øiseth, Ole A.

2018-06-01

A modified rigid-object formulation is developed, and employed as part of the fluid-object interaction modeling framework from Akkerman et al. (J Appl Mech 79(1):010905, 2012. https://doi.org/10.1115/1.4005072) to simulate free vibration and flutter of long-span bridges subjected to strong winds. To validate the numerical methodology, companion wind tunnel experiments have been conducted. The results show that the computational framework captures very precisely the aeroelastic behavior in terms of aerodynamic stiffness, damping and flutter characteristics. Considering its relative simplicity and accuracy, we conclude from our study that the proposed free-vibration simulation technique is a valuable tool in engineering design of long-span bridges.

Supervised Semantic Classification for Nuclear Proliferation Monitoring

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

Vatsavai, Raju; Cheriyadat, Anil M; Gleason, Shaun Scott

2010-01-01

Existing feature extraction and classification approaches are not suitable for monitoring proliferation activity using high-resolution multi-temporal remote sensing imagery. In this paper we present a supervised semantic labeling framework based on the Latent Dirichlet Allocation method. This framework is used to analyze over 120 images collected under different spatial and temporal settings over the globe representing three major semantic categories: airports, nuclear, and coal power plants. Initial experimental results show a reasonable discrimination of these three categories even though coal and nuclear images share highly common and overlapping objects. This research also identified several research challenges associated with nuclear proliferationmore » monitoring using high resolution remote sensing images.« less

Heterogeneous data fusion for brain tumor classification.

PubMed

Metsis, Vangelis; Huang, Heng; Andronesi, Ovidiu C; Makedon, Fillia; Tzika, Aria

2012-10-01

Current research in biomedical informatics involves analysis of multiple heterogeneous data sets. This includes patient demographics, clinical and pathology data, treatment history, patient outcomes as well as gene expression, DNA sequences and other information sources such as gene ontology. Analysis of these data sets could lead to better disease diagnosis, prognosis, treatment and drug discovery. In this report, we present a novel machine learning framework for brain tumor classification based on heterogeneous data fusion of metabolic and molecular datasets, including state-of-the-art high-resolution magic angle spinning (HRMAS) proton (1H) magnetic resonance spectroscopy and gene transcriptome profiling, obtained from intact brain tumor biopsies. Our experimental results show that our novel framework outperforms any analysis using individual dataset.

Combinatorial Fusion Analysis for Meta Search Information Retrieval

NASA Astrophysics Data System (ADS)

Hsu, D. Frank; Taksa, Isak

Leading commercial search engines are built as single event systems. In response to a particular search query, the search engine returns a single list of ranked search results. To find more relevant results the user must frequently try several other search engines. A meta search engine was developed to enhance the process of multi-engine querying. The meta search engine queries several engines at the same time and fuses individual engine results into a single search results list. The fusion of multiple search results has been shown (mostly experimentally) to be highly effective. However, the question of why and how the fusion should be done still remains largely unanswered. In this chapter, we utilize the combinatorial fusion analysis proposed by Hsu et al. to analyze combination and fusion of multiple sources of information. A rank/score function is used in the design and analysis of our framework. The framework provides a better understanding of the fusion phenomenon in information retrieval. For example, to improve the performance of the combined multiple scoring systems, it is necessary that each of the individual scoring systems has relatively high performance and the individual scoring systems are diverse. Additionally, we illustrate various applications of the framework using two examples from the information retrieval domain.

JCell--a Java-based framework for inferring regulatory networks from time series data.

PubMed

Spieth, C; Supper, J; Streichert, F; Speer, N; Zell, A

2006-08-15

JCell is a Java-based application for reconstructing gene regulatory networks from experimental data. The framework provides several algorithms to identify genetic and metabolic dependencies based on experimental data conjoint with mathematical models to describe and simulate regulatory systems. Owing to the modular structure, researchers can easily implement new methods. JCell is a pure Java application with additional scripting capabilities and thus widely usable, e.g. on parallel or cluster computers. The software is freely available for download at http://www-ra.informatik.uni-tuebingen.de/software/JCell.

A logic-based method to build signaling networks and propose experimental plans.

PubMed

Rougny, Adrien; Gloaguen, Pauline; Langonné, Nathalie; Reiter, Eric; Crépieux, Pascale; Poupon, Anne; Froidevaux, Christine

2018-05-18

With the dramatic increase of the diversity and the sheer quantity of biological data generated, the construction of comprehensive signaling networks that include precise mechanisms cannot be carried out manually anymore. In this context, we propose a logic-based method that allows building large signaling networks automatically. Our method is based on a set of expert rules that make explicit the reasoning made by biologists when interpreting experimental results coming from a wide variety of experiment types. These rules allow formulating all the conclusions that can be inferred from a set of experimental results, and thus building all the possible networks that explain these results. Moreover, given an hypothesis, our system proposes experimental plans to carry out in order to validate or invalidate it. To evaluate the performance of our method, we applied our framework to the reconstruction of the FSHR-induced and the EGFR-induced signaling networks. The FSHR is known to induce the transactivation of the EGFR, but very little is known on the resulting FSH- and EGF-dependent network. We built a single network using data underlying both networks. This leads to a new hypothesis on the activation of MEK by p38MAPK, which we validate experimentally. These preliminary results represent a first step in the demonstration of a cross-talk between these two major MAP kinases pathways.

A framework for grouping nanoparticles based on their measurable characteristics.

PubMed

Sayes, Christie M; Smith, P Alex; Ivanov, Ivan V

2013-01-01

There is a need to take a broader look at nanotoxicological studies. Eventually, the field will demand that some generalizations be made. To begin to address this issue, we posed a question: are metal colloids on the nanometer-size scale a homogeneous group? In general, most people can agree that the physicochemical properties of nanomaterials can be linked and related to their induced toxicological responses. The focus of this study was to determine how a set of selected physicochemical properties of five specific metal-based colloidal materials on the nanometer-size scale - silver, copper, nickel, iron, and zinc - could be used as nanodescriptors that facilitate the grouping of these metal-based colloids. The example of the framework pipeline processing provided in this paper shows the utility of specific statistical and pattern recognition techniques in grouping nanoparticles based on experimental data about their physicochemical properties. Interestingly, the results of the analyses suggest that a seemingly homogeneous group of nanoparticles could be separated into sub-groups depending on interdependencies observed in their nanodescriptors. These particles represent an important category of nanomaterials that are currently mass produced. Each has been reputed to induce toxicological and/or cytotoxicological effects. Here, we propose an experimental methodology coupled with mathematical and statistical modeling that can serve as a prototype for a rigorous framework that aids in the ability to group nanomaterials together and to facilitate the subsequent analysis of trends in data based on quantitative modeling of nanoparticle-specific structure-activity relationships. The computational part of the proposed framework is rather general and can be applied to other groups of nanomaterials as well.

An efficient depth map preprocessing method based on structure-aided domain transform smoothing for 3D view generation

PubMed Central

Ma, Liyan; Qiu, Bo; Cui, Mingyue; Ding, Jianwei

2017-01-01

Depth image-based rendering (DIBR), which is used to render virtual views with a color image and the corresponding depth map, is one of the key techniques in the 2D to 3D conversion process. Due to the absence of knowledge about the 3D structure of a scene and its corresponding texture, DIBR in the 2D to 3D conversion process, inevitably leads to holes in the resulting 3D image as a result of newly-exposed areas. In this paper, we proposed a structure-aided depth map preprocessing framework in the transformed domain, which is inspired by recently proposed domain transform for its low complexity and high efficiency. Firstly, our framework integrates hybrid constraints including scene structure, edge consistency and visual saliency information in the transformed domain to improve the performance of depth map preprocess in an implicit way. Then, adaptive smooth localization is cooperated and realized in the proposed framework to further reduce over-smoothness and enhance optimization in the non-hole regions. Different from the other similar methods, the proposed method can simultaneously achieve the effects of hole filling, edge correction and local smoothing for typical depth maps in a united framework. Thanks to these advantages, it can yield visually satisfactory results with less computational complexity for high quality 2D to 3D conversion. Numerical experimental results demonstrate the excellent performances of the proposed method. PMID:28407027

Hierarchy-associated semantic-rule inference framework for classifying indoor scenes

NASA Astrophysics Data System (ADS)

Yu, Dan; Liu, Peng; Ye, Zhipeng; Tang, Xianglong; Zhao, Wei

2016-03-01

Typically, the initial task of classifying indoor scenes is challenging, because the spatial layout and decoration of a scene can vary considerably. Recent efforts at classifying object relationships commonly depend on the results of scene annotation and predefined rules, making classification inflexible. Furthermore, annotation results are easily affected by external factors. Inspired by human cognition, a scene-classification framework was proposed using the empirically based annotation (EBA) and a match-over rule-based (MRB) inference system. The semantic hierarchy of images is exploited by EBA to construct rules empirically for MRB classification. The problem of scene classification is divided into low-level annotation and high-level inference from a macro perspective. Low-level annotation involves detecting the semantic hierarchy and annotating the scene with a deformable-parts model and a bag-of-visual-words model. In high-level inference, hierarchical rules are extracted to train the decision tree for classification. The categories of testing samples are generated from the parts to the whole. Compared with traditional classification strategies, the proposed semantic hierarchy and corresponding rules reduce the effect of a variable background and improve the classification performance. The proposed framework was evaluated on a popular indoor scene dataset, and the experimental results demonstrate its effectiveness.

Robust Dehaze Algorithm for Degraded Image of CMOS Image Sensors.

PubMed

Qu, Chen; Bi, Du-Yan; Sui, Ping; Chao, Ai-Nong; Wang, Yun-Fei

2017-09-22

The CMOS (Complementary Metal-Oxide-Semiconductor) is a new type of solid image sensor device widely used in object tracking, object recognition, intelligent navigation fields, and so on. However, images captured by outdoor CMOS sensor devices are usually affected by suspended atmospheric particles (such as haze), causing a reduction in image contrast, color distortion problems, and so on. In view of this, we propose a novel dehazing approach based on a local consistent Markov random field (MRF) framework. The neighboring clique in traditional MRF is extended to the non-neighboring clique, which is defined on local consistent blocks based on two clues, where both the atmospheric light and transmission map satisfy the character of local consistency. In this framework, our model can strengthen the restriction of the whole image while incorporating more sophisticated statistical priors, resulting in more expressive power of modeling, thus, solving inadequate detail recovery effectively and alleviating color distortion. Moreover, the local consistent MRF framework can obtain details while maintaining better results for dehazing, which effectively improves the image quality captured by the CMOS image sensor. Experimental results verified that the method proposed has the combined advantages of detail recovery and color preservation.

From mechanisms to function: an integrated framework of animal innovation

PubMed Central

Tebbich, Sabine; Griffin, Andrea S.; Peschl, Markus F.; Sterelny, Kim

2016-01-01

Animal innovations range from the discovery of novel food types to the invention of completely novel behaviours. Innovations can give access to new opportunities, and thus enable innovating agents to invade and create novel niches. This in turn can pave the way for morphological adaptation and adaptive radiation. The mechanisms that make innovations possible are probably as diverse as the innovations themselves. So too are their evolutionary consequences. Perhaps because of this diversity, we lack a unifying framework that links mechanism to function. We propose a framework for animal innovation that describes the interactions between mechanism, fitness benefit and evolutionary significance, and which suggests an expanded range of experimental approaches. In doing so, we split innovation into factors (components and phases) that can be manipulated systematically, and which can be investigated both experimentally and with correlational studies. We apply this framework to a selection of cases, showing how it helps us ask more precise questions and design more revealing experiments. PMID:26926285

Fast image interpolation via random forests.

PubMed

Huang, Jun-Jie; Siu, Wan-Chi; Liu, Tian-Rui

2015-10-01

This paper proposes a two-stage framework for fast image interpolation via random forests (FIRF). The proposed FIRF method gives high accuracy, as well as requires low computation. The underlying idea of this proposed work is to apply random forests to classify the natural image patch space into numerous subspaces and learn a linear regression model for each subspace to map the low-resolution image patch to high-resolution image patch. The FIRF framework consists of two stages. Stage 1 of the framework removes most of the ringing and aliasing artifacts in the initial bicubic interpolated image, while Stage 2 further refines the Stage 1 interpolated image. By varying the number of decision trees in the random forests and the number of stages applied, the proposed FIRF method can realize computationally scalable image interpolation. Extensive experimental results show that the proposed FIRF(3, 2) method achieves more than 0.3 dB improvement in peak signal-to-noise ratio over the state-of-the-art nonlocal autoregressive modeling (NARM) method. Moreover, the proposed FIRF(1, 1) obtains similar or better results as NARM while only takes its 0.3% computational time.

Unsteady Analyses of Valve Systems in Rocket Engine Testing Environments

NASA Technical Reports Server (NTRS)

Shipman, Jeremy; Hosangadi, Ashvin; Ahuja, Vineet

2004-01-01

This paper discusses simulation technology used to support the testing of rocket propulsion systems by performing high fidelity analyses of feed system components. A generalized multi-element framework has been used to perform simulations of control valve systems. This framework provides the flexibility to resolve the structural and functional complexities typically associated with valve-based high pressure feed systems that are difficult to deal with using traditional Computational Fluid Dynamics (CFD) methods. In order to validate this framework for control valve systems, results are presented for simulations of a cryogenic control valve at various plug settings and compared to both experimental data and simulation results obtained at NASA Stennis Space Center. A detailed unsteady analysis has also been performed for a pressure regulator type control valve used to support rocket engine and component testing at Stennis Space Center. The transient simulation captures the onset of a modal instability that has been observed in the operation of the valve. A discussion of the flow physics responsible for the instability and a prediction of the dominant modes associated with the fluctuations is presented.

Airplane detection based on fusion framework by combining saliency model with Deep Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Dou, Hao; Sun, Xiao; Li, Bin; Deng, Qianqian; Yang, Xubo; Liu, Di; Tian, Jinwen

2018-03-01

Aircraft detection from very high resolution remote sensing images, has gained more increasing interest in recent years due to the successful civil and military applications. However, several problems still exist: 1) how to extract the high-level features of aircraft; 2) locating objects within such a large image is difficult and time consuming; 3) A common problem of multiple resolutions of satellite images still exists. In this paper, inspirited by biological visual mechanism, the fusion detection framework is proposed, which fusing the top-down visual mechanism (deep CNN model) and bottom-up visual mechanism (GBVS) to detect aircraft. Besides, we use multi-scale training method for deep CNN model to solve the problem of multiple resolutions. Experimental results demonstrate that our method can achieve a better detection result than the other methods.

Functional Validation and Comparison Framework for EIT Lung Imaging

PubMed Central

Meybohm, Patrick; Weiler, Norbert; Frerichs, Inéz; Adler, Andy

2014-01-01

Introduction Electrical impedance tomography (EIT) is an emerging clinical tool for monitoring ventilation distribution in mechanically ventilated patients, for which many image reconstruction algorithms have been suggested. We propose an experimental framework to assess such algorithms with respect to their ability to correctly represent well-defined physiological changes. We defined a set of clinically relevant ventilation conditions and induced them experimentally in 8 pigs by controlling three ventilator settings (tidal volume, positive end-expiratory pressure and the fraction of inspired oxygen). In this way, large and discrete shifts in global and regional lung air content were elicited. Methods We use the framework to compare twelve 2D EIT reconstruction algorithms, including backprojection (the original and still most frequently used algorithm), GREIT (a more recent consensus algorithm for lung imaging), truncated singular value decomposition (TSVD), several variants of the one-step Gauss-Newton approach and two iterative algorithms. We consider the effects of using a 3D finite element model, assuming non-uniform background conductivity, noise modeling, reconstructing for electrode movement, total variation (TV) reconstruction, robust error norms, smoothing priors, and using difference vs. normalized difference data. Results and Conclusions Our results indicate that, while variation in appearance of images reconstructed from the same data is not negligible, clinically relevant parameters do not vary considerably among the advanced algorithms. Among the analysed algorithms, several advanced algorithms perform well, while some others are significantly worse. Given its vintage and ad-hoc formulation backprojection works surprisingly well, supporting the validity of previous studies in lung EIT. PMID:25110887

PCA based feature reduction to improve the accuracy of decision tree c4.5 classification

NASA Astrophysics Data System (ADS)

Nasution, M. Z. F.; Sitompul, O. S.; Ramli, M.

2018-03-01

Splitting attribute is a major process in Decision Tree C4.5 classification. However, this process does not give a significant impact on the establishment of the decision tree in terms of removing irrelevant features. It is a major problem in decision tree classification process called over-fitting resulting from noisy data and irrelevant features. In turns, over-fitting creates misclassification and data imbalance. Many algorithms have been proposed to overcome misclassification and overfitting on classifications Decision Tree C4.5. Feature reduction is one of important issues in classification model which is intended to remove irrelevant data in order to improve accuracy. The feature reduction framework is used to simplify high dimensional data to low dimensional data with non-correlated attributes. In this research, we proposed a framework for selecting relevant and non-correlated feature subsets. We consider principal component analysis (PCA) for feature reduction to perform non-correlated feature selection and Decision Tree C4.5 algorithm for the classification. From the experiments conducted using available data sets from UCI Cervical cancer data set repository with 858 instances and 36 attributes, we evaluated the performance of our framework based on accuracy, specificity and precision. Experimental results show that our proposed framework is robust to enhance classification accuracy with 90.70% accuracy rates.

A framework of multitemplate ensemble for fingerprint verification

NASA Astrophysics Data System (ADS)

Yin, Yilong; Ning, Yanbin; Ren, Chunxiao; Liu, Li

2012-12-01

How to improve performance of an automatic fingerprint verification system (AFVS) is always a big challenge in biometric verification field. Recently, it becomes popular to improve the performance of AFVS using ensemble learning approach to fuse related information of fingerprints. In this article, we propose a novel framework of fingerprint verification which is based on the multitemplate ensemble method. This framework is consisted of three stages. In the first stage, enrollment stage, we adopt an effective template selection method to select those fingerprints which best represent a finger, and then, a polyhedron is created by the matching results of multiple template fingerprints and a virtual centroid of the polyhedron is given. In the second stage, verification stage, we measure the distance between the centroid of the polyhedron and a query image. In the final stage, a fusion rule is used to choose a proper distance from a distance set. The experimental results on the FVC2004 database prove the improvement on the effectiveness of the new framework in fingerprint verification. With a minutiae-based matching method, the average EER of four databases in FVC2004 drops from 10.85 to 0.88, and with a ridge-based matching method, the average EER of these four databases also decreases from 14.58 to 2.51.

Experimental study of adaptive pointing and tracking for large flexible space structures

NASA Technical Reports Server (NTRS)

Boussalis, D.; Bayard, D. S.; Ih, C.; Wang, S. J.; Ahmed, A.

1991-01-01

This paper describes an experimental study of adaptive pointing and tracking control for flexible spacecraft conducted on a complex ground experiment facility. The algorithm used in this study is based on a multivariable direct model reference adaptive control law. Several experimental validation studies were performed earlier using this algorithm for vibration damping and robust regulation, with excellent results. The current work extends previous studies by addressing the pointing and tracking problem. As is consistent with an adaptive control framework, the plant is assumed to be poorly known to the extent that only system level knowledge of its dynamics is available. Explicit bounds on the steady-state pointing error are derived as functions of the adaptive controller design parameters. It is shown that good tracking performance can be achieved in an experimental setting by adjusting adaptive controller design weightings according to the guidelines indicated by the analytical expressions for the error.

Framework for hyperspectral image processing and quantification for cancer detection during animal tumor surgery.

PubMed

Lu, Guolan; Wang, Dongsheng; Qin, Xulei; Halig, Luma; Muller, Susan; Zhang, Hongzheng; Chen, Amy; Pogue, Brian W; Chen, Zhuo Georgia; Fei, Baowei

2015-01-01

Hyperspectral imaging (HSI) is an imaging modality that holds strong potential for rapid cancer detection during image-guided surgery. But the data from HSI often needs to be processed appropriately in order to extract the maximum useful information that differentiates cancer from normal tissue. We proposed a framework for hyperspectral image processing and quantification, which includes a set of steps including image preprocessing, glare removal, feature extraction, and ultimately image classification. The framework has been tested on images from mice with head and neck cancer, using spectra from 450- to 900-nm wavelength. The image analysis computed Fourier coefficients, normalized reflectance, mean, and spectral derivatives for improved accuracy. The experimental results demonstrated the feasibility of the hyperspectral image processing and quantification framework for cancer detection during animal tumor surgery, in a challenging setting where sensitivity can be low due to a modest number of features present, but potential for fast image classification can be high. This HSI approach may have potential application in tumor margin assessment during image-guided surgery, where speed of assessment may be the dominant factor.

Quantifying Extrinsic Noise in Gene Expression Using the Maximum Entropy Framework

PubMed Central

Dixit, Purushottam D.

2013-01-01

We present a maximum entropy framework to separate intrinsic and extrinsic contributions to noisy gene expression solely from the profile of expression. We express the experimentally accessible probability distribution of the copy number of the gene product (mRNA or protein) by accounting for possible variations in extrinsic factors. The distribution of extrinsic factors is estimated using the maximum entropy principle. Our results show that extrinsic factors qualitatively and quantitatively affect the probability distribution of the gene product. We work out, in detail, the transcription of mRNA from a constitutively expressed promoter in Escherichia coli. We suggest that the variation in extrinsic factors may account for the observed wider-than-Poisson distribution of mRNA copy numbers. We successfully test our framework on a numerical simulation of a simple gene expression scheme that accounts for the variation in extrinsic factors. We also make falsifiable predictions, some of which are tested on previous experiments in E. coli whereas others need verification. Application of the presented framework to more complex situations is also discussed. PMID:23790383

Localizing text in scene images by boundary clustering, stroke segmentation, and string fragment classification.

PubMed

Yi, Chucai; Tian, Yingli

2012-09-01

In this paper, we propose a novel framework to extract text regions from scene images with complex backgrounds and multiple text appearances. This framework consists of three main steps: boundary clustering (BC), stroke segmentation, and string fragment classification. In BC, we propose a new bigram-color-uniformity-based method to model both text and attachment surface, and cluster edge pixels based on color pairs and spatial positions into boundary layers. Then, stroke segmentation is performed at each boundary layer by color assignment to extract character candidates. We propose two algorithms to combine the structural analysis of text stroke with color assignment and filter out background interferences. Further, we design a robust string fragment classification based on Gabor-based text features. The features are obtained from feature maps of gradient, stroke distribution, and stroke width. The proposed framework of text localization is evaluated on scene images, born-digital images, broadcast video images, and images of handheld objects captured by blind persons. Experimental results on respective datasets demonstrate that the framework outperforms state-of-the-art localization algorithms.

Framework for hyperspectral image processing and quantification for cancer detection during animal tumor surgery

NASA Astrophysics Data System (ADS)

Lu, Guolan; Wang, Dongsheng; Qin, Xulei; Halig, Luma; Muller, Susan; Zhang, Hongzheng; Chen, Amy; Pogue, Brian W.; Chen, Zhuo Georgia; Fei, Baowei

2015-12-01

Hyperspectral imaging (HSI) is an imaging modality that holds strong potential for rapid cancer detection during image-guided surgery. But the data from HSI often needs to be processed appropriately in order to extract the maximum useful information that differentiates cancer from normal tissue. We proposed a framework for hyperspectral image processing and quantification, which includes a set of steps including image preprocessing, glare removal, feature extraction, and ultimately image classification. The framework has been tested on images from mice with head and neck cancer, using spectra from 450- to 900-nm wavelength. The image analysis computed Fourier coefficients, normalized reflectance, mean, and spectral derivatives for improved accuracy. The experimental results demonstrated the feasibility of the hyperspectral image processing and quantification framework for cancer detection during animal tumor surgery, in a challenging setting where sensitivity can be low due to a modest number of features present, but potential for fast image classification can be high. This HSI approach may have potential application in tumor margin assessment during image-guided surgery, where speed of assessment may be the dominant factor.

Quantifying extrinsic noise in gene expression using the maximum entropy framework.

PubMed

Dixit, Purushottam D

2013-06-18

We present a maximum entropy framework to separate intrinsic and extrinsic contributions to noisy gene expression solely from the profile of expression. We express the experimentally accessible probability distribution of the copy number of the gene product (mRNA or protein) by accounting for possible variations in extrinsic factors. The distribution of extrinsic factors is estimated using the maximum entropy principle. Our results show that extrinsic factors qualitatively and quantitatively affect the probability distribution of the gene product. We work out, in detail, the transcription of mRNA from a constitutively expressed promoter in Escherichia coli. We suggest that the variation in extrinsic factors may account for the observed wider-than-Poisson distribution of mRNA copy numbers. We successfully test our framework on a numerical simulation of a simple gene expression scheme that accounts for the variation in extrinsic factors. We also make falsifiable predictions, some of which are tested on previous experiments in E. coli whereas others need verification. Application of the presented framework to more complex situations is also discussed. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Silver-induced reconstruction of an adeninate-based metal–organic framework for encapsulation of luminescent adenine-stabilized silver clusters† †Electronic supplementary information (ESI) available: Experimental details and additional structural, physicochemical and optical characterisation. See DOI: 10.1039/c6tc00260a Click here for additional data file.

PubMed Central

Jonckheere, Dries; Coutino-Gonzalez, Eduardo; Baekelant, Wouter; Bueken, Bart; Reinsch, Helge; Stassen, Ivo; Fenwick, Oliver; Richard, Fanny; Samorì, Paolo; Ameloot, Rob; Hofkens, Johan

2016-01-01

Bright luminescent silver-adenine species were successfully stabilized in the pores of the MOF-69A (zinc biphenyldicarboxylate) metal–organic framework, starting from the intrinsically blue luminescent bio-MOF-1 (zinc adeninate 4,4′-biphenyldicarboxylate). Bio-MOF-1 is transformed to the MOF-69A framework by selectively leaching structural adenine linkers from the original framework using silver nitrate solutions in aqueous ethanol. Simultaneously, bright blue-green luminescent silver-adenine clusters are formed inside the pores of the recrystallized MOF-69A matrix in high local concentrations. The structural transition and concurrent changes in optical properties were characterized using a range of structural, physicochemical and spectroscopic techniques (steady-state and time-resolved luminescence, quantum yield determination, fluorescence microscopy). The presented results open new avenues for exploring the use of MOFs containing luminescent silver clusters for solid-state lighting and sensor applications. PMID:28496980

Selective O 2 Sorption at Ambient Temperatures via Node Distortions in Sc-MIL-100

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

Sava Gallis, Dorina F.; Chapman, Karena W.; Rodriguez, Mark A.

2016-05-24

An open pored metal–organic framework (MOF) with oxygen selectivity at exceptionally high temperatures is confirmed by synthesis, sorption, and synchrotron structural analyses. The large-pore MIL-100 framework with access to the metal center (e.g., Sc and Fe) resulted in preferential O2 over N2 gas uptake at temperatures ranging from 77 K to ambient temperatures (258, 298, and 313 K). Most notably, Sc-MIL-100 shows exceptional O2 sorption; pair distribution function analyses indicate that this is due to distortions in the framework owing to the size of Sc atoms, in particular in the trimer metal cluster. Experimental studies also correlate very well withmore » GCMC simulations, confirming more favorable O2-framework interactions at pressures up to 1 bar, due to the close proximity of O2 to the high density of metal centers in the small tetrahedral cages. Both materials maintain their crystallinity upon gas adsorption cycling, are regenerable, and show exceptional promise for use in energy efficient oxygen purification processes, such as Pressure Swing Adsorption.« less

Numerical simulation of h-adaptive immersed boundary method for freely falling disks

NASA Astrophysics Data System (ADS)

Zhang, Pan; Xia, Zhenhua; Cai, Qingdong

2018-05-01

In this work, a freely falling disk with aspect ratio 1/10 is directly simulated by using an adaptive numerical model implemented on a parallel computation framework JASMIN. The adaptive numerical model is a combination of the h-adaptive mesh refinement technique and the implicit immersed boundary method (IBM). Our numerical results agree well with the experimental results in all of the six degrees of freedom of the disk. Furthermore, very similar vortex structures observed in the experiment were also obtained.

Ratios of Vector and Pseudoscalar B Meson Decay Constants in the Light-Cone Quark Model

NASA Astrophysics Data System (ADS)

Dhiman, Nisha; Dahiya, Harleen

2018-05-01

We study the decay constants of pseudoscalar and vector B meson in the framework of light-cone quark model. We apply the variational method to the relativistic Hamiltonian with the Gaussian-type trial wave function to obtain the values of β (scale parameter). Then with the help of known values of constituent quark masses, we obtain the numerical results for the decay constants f_P and f_V, respectively. We compare our numerical results with the existing experimental data.

Multigrid-based reconstruction algorithm for quantitative photoacoustic tomography

PubMed Central

Li, Shengfu; Montcel, Bruno; Yuan, Zhen; Liu, Wanyu; Vray, Didier

2015-01-01

This paper proposes a multigrid inversion framework for quantitative photoacoustic tomography reconstruction. The forward model of optical fluence distribution and the inverse problem are solved at multiple resolutions. A fixed-point iteration scheme is formulated for each resolution and used as a cost function. The simulated and experimental results for quantitative photoacoustic tomography reconstruction show that the proposed multigrid inversion can dramatically reduce the required number of iterations for the optimization process without loss of reliability in the results. PMID:26203371

An experimentally validated model for geometrically nonlinear plucking-based frequency up-conversion in energy harvesting

NASA Astrophysics Data System (ADS)

Kathpalia, B.; Tan, D.; Stern, I.; Erturk, A.

2018-01-01

It is well known that plucking-based frequency up-conversion can enhance the power output in piezoelectric energy harvesting by enabling cyclic free vibration at the fundamental bending mode of the harvester even for very low excitation frequencies. In this work, we present a geometrically nonlinear plucking-based framework for frequency up-conversion in piezoelectric energy harvesting under quasistatic excitations associated with low-frequency stimuli such as walking and similar rigid body motions. Axial shortening of the plectrum is essential to enable plucking excitation, which requires a nonlinear framework relating the plectrum parameters (e.g. overlap length between the plectrum and harvester) to the overall electrical power output. Von Kármán-type geometrically nonlinear deformation of the flexible plectrum cantilever is employed to relate the overlap length between the flexible (nonlinear) plectrum and the stiff (linear) harvester to the transverse quasistatic tip displacement of the plectrum, and thereby the tip load on the linear harvester in each plucking cycle. By combining the nonlinear plectrum mechanics and linear harvester dynamics with two-way electromechanical coupling, the electrical power output is obtained directly in terms of the overlap length. Experimental case studies and validations are presented for various overlap lengths and a set of electrical load resistance values. Further analysis results are reported regarding the combined effects of plectrum thickness and overlap length on the plucking force and harvested power output. The experimentally validated nonlinear plectrum-linear harvester framework proposed herein can be employed to design and optimize frequency up-conversion by properly choosing the plectrum parameters (geometry, material, overlap length, etc) as well as the harvester parameters.

Quantized thermal transport in single-atom junctions

NASA Astrophysics Data System (ADS)

Cui, Longji; Jeong, Wonho; Hur, Sunghoon; Matt, Manuel; Klöckner, Jan C.; Pauly, Fabian; Nielaba, Peter; Cuevas, Juan Carlos; Meyhofer, Edgar; Reddy, Pramod

2017-03-01

Thermal transport in individual atomic junctions and chains is of great fundamental interest because of the distinctive quantum effects expected to arise in them. By using novel, custom-fabricated, picowatt-resolution calorimetric scanning probes, we measured the thermal conductance of gold and platinum metallic wires down to single-atom junctions. Our work reveals that the thermal conductance of gold single-atom junctions is quantized at room temperature and shows that the Wiedemann-Franz law relating thermal and electrical conductance is satisfied even in single-atom contacts. Furthermore, we quantitatively explain our experimental results within the Landauer framework for quantum thermal transport. The experimental techniques reported here will enable thermal transport studies in atomic and molecular chains, which will be key to investigating numerous fundamental issues that thus far have remained experimentally inaccessible.

Physiology-based face recognition in the thermal infrared spectrum.

PubMed

Buddharaju, Pradeep; Pavlidis, Ioannis T; Tsiamyrtzis, Panagiotis; Bazakos, Mike

2007-04-01

The current dominant approaches to face recognition rely on facial characteristics that are on or over the skin. Some of these characteristics have low permanency can be altered, and their phenomenology varies significantly with environmental factors (e.g., lighting). Many methodologies have been developed to address these problems to various degrees. However, the current framework of face recognition research has a potential weakness due to its very nature. We present a novel framework for face recognition based on physiological information. The motivation behind this effort is to capitalize on the permanency of innate characteristics that are under the skin. To establish feasibility, we propose a specific methodology to capture facial physiological patterns using the bioheat information contained in thermal imagery. First, the algorithm delineates the human face from the background using the Bayesian framework. Then, it localizes the superficial blood vessel network using image morphology. The extracted vascular network produces contour shapes that are characteristic to each individual. The branching points of the skeletonized vascular network are referred to as Thermal Minutia Points (TMPs) and constitute the feature database. To render the method robust to facial pose variations, we collect for each subject to be stored in the database five different pose images (center, midleft profile, left profile, midright profile, and right profile). During the classification stage, the algorithm first estimates the pose of the test image. Then, it matches the local and global TMP structures extracted from the test image with those of the corresponding pose images in the database. We have conducted experiments on a multipose database of thermal facial images collected in our laboratory, as well as on the time-gap database of the University of Notre Dame. The good experimental results show that the proposed methodology has merit, especially with respect to the problem of low permanence over time. More importantly, the results demonstrate the feasibility of the physiological framework in face recognition and open the way for further methodological and experimental research in the area.

An Experimental Study on the Edgewise Compressive Failure of Paper Honeycomb Sandwich Panels with Respect to Various Aspect Ratios

NASA Astrophysics Data System (ADS)

Samad, W. A.; Warsame, A. A.; Khan, A.

2018-04-01

The present work investigates the edgewise compression failure for honeycomb paperboards. Various panels are tested under a fixed loading rate with varying aspect ratios. The influence of the varying properties aspect ratio on yield strength is recorded. The experimental results indicate that the honeycomb paperboards are subject a decrease in yield strength with an increase in aspect ratio towards more slender bodies. Buckling was not observed in any of the tested specimens. All experiments are conducted under the general framework of ASTM C364/C364M -16 with a few noted changes.

A new statistical method for transfer coefficient calculations in the framework of the general multiple-compartment model of transport for radionuclides in biological systems.

PubMed

Garcia, F; Arruda-Neto, J D; Manso, M V; Helene, O M; Vanin, V R; Rodriguez, O; Mesa, J; Likhachev, V P; Filho, J W; Deppman, A; Perez, G; Guzman, F; de Camargo, S P

1999-10-01

A new and simple statistical procedure (STATFLUX) for the calculation of transfer coefficients of radionuclide transport to animals and plants is proposed. The method is based on the general multiple-compartment model, which uses a system of linear equations involving geometrical volume considerations. By using experimentally available curves of radionuclide concentrations versus time, for each animal compartment (organs), flow parameters were estimated by employing a least-squares procedure, whose consistency is tested. Some numerical results are presented in order to compare the STATFLUX transfer coefficients with those from other works and experimental data.

Studies on Experimental Ontology and Knowledge Service Development in Bio-Environmental Engineering

NASA Astrophysics Data System (ADS)

Zhang, Yunliang

2018-01-01

The existing domain-related ontology and information service patterns are analyzed, and the main problems faced by the experimental scheme knowledge service were clarified. The ontology framework model for knowledge service of Bio-environmental Engineering was proposed from the aspects of experimental materials, experimental conditions and experimental instruments, and this ontology will be combined with existing knowledge organization systems to organize scientific and technological literatures, data and experimental schemes. With the similarity and priority calculation, it can improve the related domain research.

Energy-based culture medium design for biomanufacturing optimization: A case study in monoclonal antibody production by GS-NS0 cells.

PubMed

Quiroga-Campano, Ana L; Panoskaltsis, Nicki; Mantalaris, Athanasios

2018-03-02

Demand for high-value biologics, a rapidly growing pipeline, and pressure from competition, time-to-market and regulators, necessitate novel biomanufacturing approaches, including Quality by Design (QbD) principles and Process Analytical Technologies (PAT), to facilitate accelerated, efficient and effective process development platforms that ensure consistent product quality and reduced lot-to-lot variability. Herein, QbD and PAT principles were incorporated within an innovative in vitro-in silico integrated framework for upstream process development (UPD). The central component of the UPD framework is a mathematical model that predicts dynamic nutrient uptake and average intracellular ATP content, based on biochemical reaction networks, to quantify and characterize energy metabolism and its adaptive response, metabolic shifts, to maintain ATP homeostasis. The accuracy and flexibility of the model depends on critical cell type/product/clone-specific parameters, which are experimentally estimated. The integrated in vitro-in silico platform and the model's predictive capacity reduced burden, time and expense of experimentation resulting in optimal medium design compared to commercially available culture media (80% amino acid reduction) and a fed-batch feeding strategy that increased productivity by 129%. The framework represents a flexible and efficient tool that transforms, improves and accelerates conventional process development in biomanufacturing with wide applications, including stem cell-based therapies. Copyright © 2018. Published by Elsevier Inc.

Focusing effect of bent GaAs crystals for γ-ray Laue lenses: Monte Carlo and experimental results

NASA Astrophysics Data System (ADS)

Virgilli, E.; Frontera, F.; Rosati, P.; Bonnini, E.; Buffagni, E.; Ferrari, C.; Stephen, J. B.; Caroli, E.; Auricchio, N.; Basili, A.; Silvestri, S.

2016-02-01

We report on results of observation of the focusing effect from the planes (220) of Gallium Arsenide (GaAs) crystals. We have compared the experimental results with the Monte Carlo simulations of the focusing capability of GaAs tiles performed with a dedicated ray-tracer. The GaAs tiles were bent using a lapping process developed at the cnr/imem - Parma (Italy) in the framework of the laue project, funded by ASI, dedicated to build a broad band Laue lens prototype for astrophysical applications in the hard X-/soft γ-ray energy range (80-600 keV). We present and discuss the results obtained from their characterization, mainly in terms of focusing capability. Bent crystals will significantly increase the signal to noise ratio of a telescope based on a Laue lens, consequently leading to an unprecedented enhancement of sensitivity with respect to the present non focusing instrumentation.

Skin Lesion Analysis towards Melanoma Detection Using Deep Learning Network

PubMed Central

2018-01-01

Skin lesions are a severe disease globally. Early detection of melanoma in dermoscopy images significantly increases the survival rate. However, the accurate recognition of melanoma is extremely challenging due to the following reasons: low contrast between lesions and skin, visual similarity between melanoma and non-melanoma lesions, etc. Hence, reliable automatic detection of skin tumors is very useful to increase the accuracy and efficiency of pathologists. In this paper, we proposed two deep learning methods to address three main tasks emerging in the area of skin lesion image processing, i.e., lesion segmentation (task 1), lesion dermoscopic feature extraction (task 2) and lesion classification (task 3). A deep learning framework consisting of two fully convolutional residual networks (FCRN) is proposed to simultaneously produce the segmentation result and the coarse classification result. A lesion index calculation unit (LICU) is developed to refine the coarse classification results by calculating the distance heat-map. A straight-forward CNN is proposed for the dermoscopic feature extraction task. The proposed deep learning frameworks were evaluated on the ISIC 2017 dataset. Experimental results show the promising accuracies of our frameworks, i.e., 0.753 for task 1, 0.848 for task 2 and 0.912 for task 3 were achieved. PMID:29439500

Model-Based Reasoning in Upper-division Lab Courses

NASA Astrophysics Data System (ADS)

Lewandowski, Heather

2015-05-01

Modeling, which includes developing, testing, and refining models, is a central activity in physics. Well-known examples from AMO physics include everything from the Bohr model of the hydrogen atom to the Bose-Hubbard model of interacting bosons in a lattice. Modeling, while typically considered a theoretical activity, is most fully represented in the laboratory where measurements of real phenomena intersect with theoretical models, leading to refinement of models and experimental apparatus. However, experimental physicists use models in complex ways and the process is often not made explicit in physics laboratory courses. We have developed a framework to describe the modeling process in physics laboratory activities. The framework attempts to abstract and simplify the complex modeling process undertaken by expert experimentalists. The framework can be applied to understand typical processes such the modeling of the measurement tools, modeling ``black boxes,'' and signal processing. We demonstrate that the framework captures several important features of model-based reasoning in a way that can reveal common student difficulties in the lab and guide the development of curricula that emphasize modeling in the laboratory. We also use the framework to examine troubleshooting in the lab and guide students to effective methods and strategies.

Acoustic response characteristics of unsaturated porous media

NASA Astrophysics Data System (ADS)

Zhao, Haibo; Wang, Xiuming; Chen, Shumin; Li, Lailin

2010-08-01

By employing the plane wave analysis method, the dispersion equations associated with compressional and shear waves using Santos’s three-phase poroelastic theory were driven. Considering the reservoir pressure, the high frequency corrections and the coupling drag of two fluids in pores, the influences of frequency and gas saturation on the phase velocities and the inverse quality factors of four body waves predicted by Santos’s theory were discussed in detail. The theoretical velocities of the fast compressional and shear waves were compared with the results of the low and high frequency experiments from open publications, respectively. The results showed that they are in good agreement in the low frequency case rather than in the high frequency case. In the latter case, several popular poroelastic models were considered and compared with the experimental data. In the models, the results of White’s theory fit the experimental data, but the parameter b in White’s model has a significant impact on the results. Under the framework of the linear viscoelasticity theory, the attenuation mechanism of Santos’s model was extended, and the comparisons between the experimental and theoretical results were also made with respect to attenuation. For the case of water saturation less than 90%, the extended model makes good predictions of the inverse quality factor of shear wave. There is a significant difference between the experimental and theoretical results for the compressional wave, but the difference can be explained by the experimental data available.

Conceptual Modeling of a Quantum Key Distribution Simulation Framework Using the Discrete Event System Specification

DTIC Science & Technology

2014-09-18

and full/scale experimental verifications towards ground/ satellite quantum key distribution0 Oat Qhotonics 4235>9+7,=5;9!អ \\58^ Zin K. Dao Z. Miu T...Conceptual Modeling of a Quantum Key Distribution Simulation Framework Using the Discrete Event System Specification DISSERTATION Jeffrey D. Morris... QUANTUM KEY DISTRIBUTION SIMULATION FRAMEWORK USING THE DISCRETE EVENT SYSTEM SPECIFICATION DISSERTATION Presented to the Faculty Department of Systems

The edge-preservation multi-classifier relearning framework for the classification of high-resolution remotely sensed imagery

NASA Astrophysics Data System (ADS)

Han, Xiaopeng; Huang, Xin; Li, Jiayi; Li, Yansheng; Yang, Michael Ying; Gong, Jianya

2018-04-01

In recent years, the availability of high-resolution imagery has enabled more detailed observation of the Earth. However, it is imperative to simultaneously achieve accurate interpretation and preserve the spatial details for the classification of such high-resolution data. To this aim, we propose the edge-preservation multi-classifier relearning framework (EMRF). This multi-classifier framework is made up of support vector machine (SVM), random forest (RF), and sparse multinomial logistic regression via variable splitting and augmented Lagrangian (LORSAL) classifiers, considering their complementary characteristics. To better characterize complex scenes of remote sensing images, relearning based on landscape metrics is proposed, which iteratively quantizes both the landscape composition and spatial configuration by the use of the initial classification results. In addition, a novel tri-training strategy is proposed to solve the over-smoothing effect of relearning by means of automatic selection of training samples with low classification certainties, which always distribute in or near the edge areas. Finally, EMRF flexibly combines the strengths of relearning and tri-training via the classification certainties calculated by the probabilistic output of the respective classifiers. It should be noted that, in order to achieve an unbiased evaluation, we assessed the classification accuracy of the proposed framework using both edge and non-edge test samples. The experimental results obtained with four multispectral high-resolution images confirm the efficacy of the proposed framework, in terms of both edge and non-edge accuracy.

Parameterization models for pesticide exposure via crop consumption.

PubMed

Fantke, Peter; Wieland, Peter; Juraske, Ronnie; Shaddick, Gavin; Itoiz, Eva Sevigné; Friedrich, Rainer; Jolliet, Olivier

2012-12-04

An approach for estimating human exposure to pesticides via consumption of six important food crops is presented that can be used to extend multimedia models applied in health risk and life cycle impact assessment. We first assessed the variation of model output (pesticide residues per kg applied) as a function of model input variables (substance, crop, and environmental properties) including their possible correlations using matrix algebra. We identified five key parameters responsible for between 80% and 93% of the variation in pesticide residues, namely time between substance application and crop harvest, degradation half-lives in crops and on crop surfaces, overall residence times in soil, and substance molecular weight. Partition coefficients also play an important role for fruit trees and tomato (Kow), potato (Koc), and lettuce (Kaw, Kow). Focusing on these parameters, we develop crop-specific models by parametrizing a complex fate and exposure assessment framework. The parametric models thereby reflect the framework's physical and chemical mechanisms and predict pesticide residues in harvest using linear combinations of crop, crop surface, and soil compartments. Parametric model results correspond well with results from the complex framework for 1540 substance-crop combinations with total deviations between a factor 4 (potato) and a factor 66 (lettuce). Predicted residues also correspond well with experimental data previously used to evaluate the complex framework. Pesticide mass in harvest can finally be combined with reduction factors accounting for food processing to estimate human exposure from crop consumption. All parametric models can be easily implemented into existing assessment frameworks.

An information theoretic approach to use high-fidelity codes to calibrate low-fidelity codes

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

Lewis, Allison, E-mail: lewis.allison10@gmail.com; Smith, Ralph; Williams, Brian

For many simulation models, it can be prohibitively expensive or physically infeasible to obtain a complete set of experimental data to calibrate model parameters. In such cases, one can alternatively employ validated higher-fidelity codes to generate simulated data, which can be used to calibrate the lower-fidelity code. In this paper, we employ an information-theoretic framework to determine the reduction in parameter uncertainty that is obtained by evaluating the high-fidelity code at a specific set of design conditions. These conditions are chosen sequentially, based on the amount of information that they contribute to the low-fidelity model parameters. The goal is tomore » employ Bayesian experimental design techniques to minimize the number of high-fidelity code evaluations required to accurately calibrate the low-fidelity model. We illustrate the performance of this framework using heat and diffusion examples, a 1-D kinetic neutron diffusion equation, and a particle transport model, and include initial results from the integration of the high-fidelity thermal-hydraulics code Hydra-TH with a low-fidelity exponential model for the friction correlation factor.« less

Experimental analysis of in plane shear behaviour of woven composite reinforcements. Influence of tensions

NASA Astrophysics Data System (ADS)

Launay, Jean; Hivet, Gilles; Vu Duong, Ahn; Boisse, Philippe

2007-04-01

Two tests are mainly used to identify the shear behavior of fabrics. The "picture frame" which uses a lozenge framework made of four rigid and articulated bars and the "bias test" which is a tensile test on a sample with initially a 45° angle between the yarns and the edges. The picture frame test is the more commonly used because the whole specimen is theoretically in a pure shear state. Nevertheless the absence of tension in the woven reinforcement supposes a perfect alignment of fibres and positioning of the clamping point with regards to the framework articulations. In addition, it is often necessary in practice to impose an initial tension which is not quantified and whose consequences are ignored in the classical picture frame test. An experimental device making it possible to measure the tensions during the test is carried out. Different types of teste on different fabrics have been performed. Results presented here concern a twintex fabric that has been selected for a shear benchmark Thanks to this device, it is shown that tensions play an important role in plane shear behaviour.

In situ microcalorimetric investigation on the formation of cadmium-organic framework based on 5-mercaptoisophthalic acid

NASA Astrophysics Data System (ADS)

Cen, Huoshi; Liu, Wenlong; Nan, Zhaodong

In situ microcalorimetry was first used to study the crystal formation processes of porous metal-organic frameworks (MOF), [((CH3)2NH2)Cd(MIPA)]4ṡ×G, where H3MIPA is 5-Mercaptoisophthalic acid, G represents guest of DMA and H2O. An endothermic process occurred firstly, which is corresponding to the chemical reaction among the reactants. Exothermic processes followed the endothermal process are corresponding to crystal nucleation and growth. The experimental results demonstrate that a solid sample was first obtained at 150∘C for 24h. X-ray powder diffraction (XRD) peaks of the samples enhanced with the experimental time increasing from 24 to 60h (as 24, 35, 48 and 60h). The adsorption properties of the crystal obtained at 150∘C for 60h are more excellent than those reported and the same MOF synthesized at 150∘C for 72h. This study may give a method for investigation on MOFs formation mechanism and help to synthesize this kind of functional materials.

The role of privacy protection in healthcare information systems adoption.

PubMed

Hsu, Chien-Lung; Lee, Ming-Ren; Su, Chien-Hui

2013-10-01

Privacy protection is an important issue and challenge in healthcare information systems (HISs). Recently, some privacy-enhanced HISs are proposed. Users' privacy perception, intention, and attitude might affect the adoption of such systems. This paper aims to propose a privacy-enhanced HIS framework and investigate the role of privacy protection in HISs adoption. In the proposed framework, privacy protection, access control, and secure transmission modules are designed to enhance the privacy protection of a HIS. An experimental privacy-enhanced HIS is also implemented. Furthermore, we proposed a research model extending the unified theory of acceptance and use of technology by considering perceived security and information security literacy and then investigate user adoption of a privacy-enhanced HIS. The experimental results and analyses showed that user adoption of a privacy-enhanced HIS is directly affected by social influence, performance expectancy, facilitating conditions, and perceived security. Perceived security has a mediating effect between information security literacy and user adoption. This study proposes several implications for research and practice to improve designing, development, and promotion of a good healthcare information system with privacy protection.

SPH simulations of WBC adhesion to the endothelium: the role of haemodynamics and endothelial binding kinetics.

PubMed

Gholami, Babak; Comerford, Andrew; Ellero, Marco

2015-11-01

A multiscale Lagrangian particle solver introduced in our previous work is extended to model physiologically realistic near-wall cell dynamics. Three-dimensional simulation of particle trajectories is combined with realistic receptor-ligand adhesion behaviour to cover full cell interactions in the vicinity of the endothelium. The selected stochastic adhesion model, which is based on a Monte Carlo acceptance-rejection method, fits in our Lagrangian framework and does not compromise performance. Additionally, appropriate inflow/outflow boundary conditions are implemented for our SPH solver to enable realistic pulsatile flow simulation. The model is tested against in-vitro data from a 3D geometry with a stenosis and sudden expansion. In both steady and pulsatile flow conditions, results show close agreement with the experimental ones. Furthermore we demonstrate, in agreement with experimental observations, that haemodynamics alone does not account for adhesion of white blood cells, in this case U937 monocytic human cells. Our findings suggest that the current framework is fully capable of modelling cell dynamics in large arteries in a realistic and efficient manner.

Computational Biorheology of Human Blood Flow in Health and Disease

PubMed Central

Fedosov, Dmitry A.; Dao, Ming; Karniadakis, George Em; Suresh, Subra

2014-01-01

Hematologic disorders arising from infectious diseases, hereditary factors and environmental influences can lead to, and can be influenced by, significant changes in the shape, mechanical and physical properties of red blood cells (RBCs), and the biorheology of blood flow. Hence, modeling of hematologic disorders should take into account the multiphase nature of blood flow, especially in arterioles and capillaries. We present here an overview of a general computational framework based on dissipative particle dynamics (DPD) which has broad applicability in cell biophysics with implications for diagnostics, therapeutics and drug efficacy assessments for a wide variety of human diseases. This computational approach, validated by independent experimental results, is capable of modeling the biorheology of whole blood and its individual components during blood flow so as to investigate cell mechanistic processes in health and disease. DPD is a Lagrangian method that can be derived from systematic coarse-graining of molecular dynamics but can scale efficiently up to arterioles and can also be used to model RBCs down to the spectrin level. We start from experimental measurements of a single RBC to extract the relevant biophysical parameters, using single-cell measurements involving such methods as optical tweezers, atomic force microscopy and micropipette aspiration, and cell-population experiments involving microfluidic devices. We then use these validated RBC models to predict the biorheological behavior of whole blood in healthy or pathological states, and compare the simulations with experimental results involving apparent viscosity and other relevant parameters. While the approach discussed here is sufficiently general to address a broad spectrum of hematologic disorders including certain types of cancer, this paper specifically deals with results obtained using this computational framework for blood flow in malaria and sickle cell anemia. PMID:24419829

A Data Protection Framework for Learning Analytics

ERIC Educational Resources Information Center

Cormack, Andrew

2016-01-01

Most studies on the use of digital student data adopt an ethical framework derived from human-subject research, based on the informed consent of the experimental subject. However, consent gives universities little guidance on using learning analytics as a routine part of educational provision: which purposes are legitimate and which analyses…

Computational Design of Functionalized Metal–Organic Framework Nodes for Catalysis

PubMed Central

2017-01-01

Recent progress in the synthesis and characterization of metal–organic frameworks (MOFs) has opened the door to an increasing number of possible catalytic applications. The great versatility of MOFs creates a large chemical space, whose thorough experimental examination becomes practically impossible. Therefore, computational modeling is a key tool to support, rationalize, and guide experimental efforts. In this outlook we survey the main methodologies employed to model MOFs for catalysis, and we review selected recent studies on the functionalization of their nodes. We pay special attention to catalytic applications involving natural gas conversion. PMID:29392172

Inferential Framework for Autonomous Cryogenic Loading Operations

NASA Technical Reports Server (NTRS)

Luchinsky, Dmitry G.; Khasin, Michael; Timucin, Dogan; Sass, Jared; Perotti, Jose; Brown, Barbara

2017-01-01

We address problem of autonomous cryogenic management of loading operations on the ground and in space. As a step towards solution of this problem we develop a probabilistic framework for inferring correlations parameters of two-fluid cryogenic flow. The simulation of two-phase cryogenic flow is performed using nearly-implicit scheme. A concise set of cryogenic correlations is introduced. The proposed approach is applied to an analysis of the cryogenic flow in experimental Propellant Loading System built at NASA KSC. An efficient simultaneous optimization of a large number of model parameters is demonstrated and a good agreement with the experimental data is obtained.

Offline signature verification using convolution Siamese network

NASA Astrophysics Data System (ADS)

Xing, Zi-Jian; Yin, Fei; Wu, Yi-Chao; Liu, Cheng-Lin

2018-04-01

This paper presents an offline signature verification approach using convolutional Siamese neural network. Unlike the existing methods which consider feature extraction and metric learning as two independent stages, we adopt a deepleaning based framework which combines the two stages together and can be trained end-to-end. The experimental results on two offline public databases (GPDSsynthetic and CEDAR) demonstrate the superiority of our method on the offline signature verification problem.

Lifetime measurement of high spin states in (75) Kr

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

Sheikh, Javid; Trivedi, T.; Maurya, K.

2010-01-01

The lifetimes of high spin states of {sup 75}Kr have been determined via {sup 50}Cr ({sup 28}Si, 2pn) {sup 75}Kr reaction in positive parity band using the Doppler-shift attenuation method. The transition quadrupole moments Q deduced from lifetime measurements have been compared with {sup 75}Br. Experimental results obtained from lifetime measurement are interpreted in the framework of projected shell model.

dV/dt - Accelerating the Rate of Progress towards Extreme Scale Collaborative Science

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

Livny, Miron

This report introduces publications that report the results of a project that aimed to design a computational framework that enables computational experimentation at scale while supporting the model of “submit locally, compute globally”. The project focuses on estimating application resource needs, finding the appropriate computing resources, acquiring those resources,deploying the applications and data on the resources, managing applications and resources during run.

Radiative capture of proton by ^{12}C at low energy

NASA Astrophysics Data System (ADS)

Irgaziev, Bakhadir Fayzullaevich; Nabi, Jameel-Un; Kabir, Abdul

2018-07-01

Within the framework of potential cluster model, astrophysical S-factor of radiative capture reaction ^{12}C (p,γ)^{13}N has been calculated in the two body cluster model for the energy range 0-1 MeV. The nuclear interaction in the initial and final states is described by the Woods-Saxon potential. The calculated astrophysical S-factor and rates are compared with known experimental results.

Visual shape perception as Bayesian inference of 3D object-centered shape representations.

PubMed

Erdogan, Goker; Jacobs, Robert A

2017-11-01

Despite decades of research, little is known about how people visually perceive object shape. We hypothesize that a promising approach to shape perception is provided by a "visual perception as Bayesian inference" framework which augments an emphasis on visual representation with an emphasis on the idea that shape perception is a form of statistical inference. Our hypothesis claims that shape perception of unfamiliar objects can be characterized as statistical inference of 3D shape in an object-centered coordinate system. We describe a computational model based on our theoretical framework, and provide evidence for the model along two lines. First, we show that, counterintuitively, the model accounts for viewpoint-dependency of object recognition, traditionally regarded as evidence against people's use of 3D object-centered shape representations. Second, we report the results of an experiment using a shape similarity task, and present an extensive evaluation of existing models' abilities to account for the experimental data. We find that our shape inference model captures subjects' behaviors better than competing models. Taken as a whole, our experimental and computational results illustrate the promise of our approach and suggest that people's shape representations of unfamiliar objects are probabilistic, 3D, and object-centered. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Semantically enabled and statistically supported biological hypothesis testing with tissue microarray databases

PubMed Central

2011-01-01

Background Although many biological databases are applying semantic web technologies, meaningful biological hypothesis testing cannot be easily achieved. Database-driven high throughput genomic hypothesis testing requires both of the capabilities of obtaining semantically relevant experimental data and of performing relevant statistical testing for the retrieved data. Tissue Microarray (TMA) data are semantically rich and contains many biologically important hypotheses waiting for high throughput conclusions. Methods An application-specific ontology was developed for managing TMA and DNA microarray databases by semantic web technologies. Data were represented as Resource Description Framework (RDF) according to the framework of the ontology. Applications for hypothesis testing (Xperanto-RDF) for TMA data were designed and implemented by (1) formulating the syntactic and semantic structures of the hypotheses derived from TMA experiments, (2) formulating SPARQLs to reflect the semantic structures of the hypotheses, and (3) performing statistical test with the result sets returned by the SPARQLs. Results When a user designs a hypothesis in Xperanto-RDF and submits it, the hypothesis can be tested against TMA experimental data stored in Xperanto-RDF. When we evaluated four previously validated hypotheses as an illustration, all the hypotheses were supported by Xperanto-RDF. Conclusions We demonstrated the utility of high throughput biological hypothesis testing. We believe that preliminary investigation before performing highly controlled experiment can be benefited. PMID:21342584

Protocols for efficient simulations of long-time protein dynamics using coarse-grained CABS model.

PubMed

Jamroz, Michal; Kolinski, Andrzej; Kmiecik, Sebastian

2014-01-01

Coarse-grained (CG) modeling is a well-acknowledged simulation approach for getting insight into long-time scale protein folding events at reasonable computational cost. Depending on the design of a CG model, the simulation protocols vary from highly case-specific-requiring user-defined assumptions about the folding scenario-to more sophisticated blind prediction methods for which only a protein sequence is required. Here we describe the framework protocol for the simulations of long-term dynamics of globular proteins, with the use of the CABS CG protein model and sequence data. The simulations can start from a random or a selected (e.g., native) structure. The described protocol has been validated using experimental data for protein folding model systems-the prediction results agreed well with the experimental results.

General Theory of Absorption in Porous Materials: Restricted Multilayer Theory.

PubMed

Aduenko, Alexander A; Murray, Andy; Mendoza-Cortes, Jose L

2018-04-18

In this article, we present an approach for the generalization of adsorption of light gases in porous materials. This new theory goes beyond Langmuir and Brunauer-Emmett-Teller theories, which are the standard approaches that have a limited application to crystalline porous materials by their unphysical assumptions on the amount of possible adsorption layers. The derivation of a more general equation for any crystalline porous framework is presented, restricted multilayer theory. Our approach allows the determination of gas uptake considering only geometrical constraints of the porous framework and the interaction energy of the guest molecule with the framework. On the basis of this theory, we calculated optimal values for the adsorption enthalpy at different temperatures and pressures. We also present the use of this theory to determine the optimal linker length for a topologically equivalent framework series. We validate this theoretical approach by applying it to metal-organic frameworks (MOFs) and show that it reproduces the experimental results for seven different reported materials. We obtained the universal equation for the optimal linker length, given the topology of a porous framework. This work applied the general equation to MOFs and H 2 to create energy-storage materials; however, this theory can be applied to other crystalline porous materials and light gases, which opens the possibility of designing the next generations of energy-storage materials by first considering only the geometrical constraints of the porous materials.

Multi-task learning with group information for human action recognition

NASA Astrophysics Data System (ADS)

Qian, Li; Wu, Song; Pu, Nan; Xu, Shulin; Xiao, Guoqiang

2018-04-01

Human action recognition is an important and challenging task in computer vision research, due to the variations in human motion performance, interpersonal differences and recording settings. In this paper, we propose a novel multi-task learning framework with group information (MTL-GI) for accurate and efficient human action recognition. Specifically, we firstly obtain group information through calculating the mutual information according to the latent relationship between Gaussian components and action categories, and clustering similar action categories into the same group by affinity propagation clustering. Additionally, in order to explore the relationships of related tasks, we incorporate group information into multi-task learning. Experimental results evaluated on two popular benchmarks (UCF50 and HMDB51 datasets) demonstrate the superiority of our proposed MTL-GI framework.

Weighted fusion of depth and inertial data to improve view invariance for real-time human action recognition

NASA Astrophysics Data System (ADS)

Chen, Chen; Hao, Huiyan; Jafari, Roozbeh; Kehtarnavaz, Nasser

2017-05-01

This paper presents an extension to our previously developed fusion framework [10] involving a depth camera and an inertial sensor in order to improve its view invariance aspect for real-time human action recognition applications. A computationally efficient view estimation based on skeleton joints is considered in order to select the most relevant depth training data when recognizing test samples. Two collaborative representation classifiers, one for depth features and one for inertial features, are appropriately weighted to generate a decision making probability. The experimental results applied to a multi-view human action dataset show that this weighted extension improves the recognition performance by about 5% over equally weighted fusion deployed in our previous fusion framework.

Finger Vein Recognition Based on a Personalized Best Bit Map

PubMed Central

Yang, Gongping; Xi, Xiaoming; Yin, Yilong

2012-01-01

Finger vein patterns have recently been recognized as an effective biometric identifier. In this paper, we propose a finger vein recognition method based on a personalized best bit map (PBBM). Our method is rooted in a local binary pattern based method and then inclined to use the best bits only for matching. We first present the concept of PBBM and the generating algorithm. Then we propose the finger vein recognition framework, which consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PBBM achieves not only better performance, but also high robustness and reliability. In addition, PBBM can be used as a general framework for binary pattern based recognition. PMID:22438735

Designing perfect linear polarization converters using perfect electric and magnetic conducting surfaces

PubMed Central

Zhou, Gaochao; Tao, Xudong; Shen, Ze; Zhu, Guanghao; Jin, Biaobing; Kang, Lin; Xu, Weiwei; Chen, Jian; Wu, Peiheng

2016-01-01

We propose a kind of general framework for the design of a perfect linear polarization converter that works in the transmission mode. Using an intuitive picture that is based on the method of bi-directional polarization mode decomposition, it is shown that when the device under consideration simultaneously possesses two complementary symmetry planes, with one being equivalent to a perfect electric conducting surface and the other being equivalent to a perfect magnetic conducting surface, linear polarization conversion can occur with an efficiency of 100% in the absence of absorptive losses. The proposed framework is validated by two design examples that operate near 10 GHz, where the numerical, experimental and analytic results are in good agreements. PMID:27958313

Finger vein recognition based on a personalized best bit map.

PubMed

Yang, Gongping; Xi, Xiaoming; Yin, Yilong

2012-01-01

Finger vein patterns have recently been recognized as an effective biometric identifier. In this paper, we propose a finger vein recognition method based on a personalized best bit map (PBBM). Our method is rooted in a local binary pattern based method and then inclined to use the best bits only for matching. We first present the concept of PBBM and the generating algorithm. Then we propose the finger vein recognition framework, which consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PBBM achieves not only better performance, but also high robustness and reliability. In addition, PBBM can be used as a general framework for binary pattern based recognition.

A knowledge-based system for prototypical reasoning

NASA Astrophysics Data System (ADS)

Lieto, Antonio; Minieri, Andrea; Piana, Alberto; Radicioni, Daniele P.

2015-04-01

In this work we present a knowledge-based system equipped with a hybrid, cognitively inspired architecture for the representation of conceptual information. The proposed system aims at extending the classical representational and reasoning capabilities of the ontology-based frameworks towards the realm of the prototype theory. It is based on a hybrid knowledge base, composed of a classical symbolic component (grounded on a formal ontology) with a typicality based one (grounded on the conceptual spaces framework). The resulting system attempts to reconcile the heterogeneous approach to the concepts in Cognitive Science with the dual process theories of reasoning and rationality. The system has been experimentally assessed in a conceptual categorisation task where common sense linguistic descriptions were given in input, and the corresponding target concepts had to be identified. The results show that the proposed solution substantially extends the representational and reasoning 'conceptual' capabilities of standard ontology-based systems.

Those speedos become them: the role of self-objectification in gay and heterosexual men's body image.

PubMed

Martins, Yolanda; Tiggemann, Marika; Kirkbride, Alana

2007-05-01

Objectification Theory proposes that membership in sexually objectifying Western societies gradually socializes women to adopt an observer's perspective on their physical self. This leads to negative consequences, including body shame and restricted eating behavior. The authors extend this framework to investigate a subgroup of men, namely gay men, who also exist in a subculture that emphasizes and values physical appearance. Study 1 investigated trait differences in self-objectification and body image among gay and heterosexual men. Analyses indicated that gay men scored higher on self-objectification, body shame, body dissatisfaction, and drive for thinness. In Study 2, the authors experimentally manipulated state self-objectification and found that for gay men, increasing state self-objectification resulted in greater body shame and dissatisfaction and more restrained eating. Together, these results offer strong support to Objectification Theory as a useful framework from within which to view the experience of gay men.

Robust nonlinear control of vectored thrust aircraft

NASA Technical Reports Server (NTRS)

Doyle, John C.; Murray, Richard; Morris, John

1993-01-01

An interdisciplinary program in robust control for nonlinear systems with applications to a variety of engineering problems is outlined. Major emphasis will be placed on flight control, with both experimental and analytical studies. This program builds on recent new results in control theory for stability, stabilization, robust stability, robust performance, synthesis, and model reduction in a unified framework using Linear Fractional Transformations (LFT's), Linear Matrix Inequalities (LMI's), and the structured singular value micron. Most of these new advances have been accomplished by the Caltech controls group independently or in collaboration with researchers in other institutions. These recent results offer a new and remarkably unified framework for all aspects of robust control, but what is particularly important for this program is that they also have important implications for system identification and control of nonlinear systems. This combines well with Caltech's expertise in nonlinear control theory, both in geometric methods and methods for systems with constraints and saturations.

Online gesture spotting from visual hull data.

PubMed

Peng, Bo; Qian, Gang

2011-06-01

This paper presents a robust framework for online full-body gesture spotting from visual hull data. Using view-invariant pose features as observations, hidden Markov models (HMMs) are trained for gesture spotting from continuous movement data streams. Two major contributions of this paper are 1) view-invariant pose feature extraction from visual hulls, and 2) a systematic approach to automatically detecting and modeling specific nongesture movement patterns and using their HMMs for outlier rejection in gesture spotting. The experimental results have shown the view-invariance property of the proposed pose features for both training poses and new poses unseen in training, as well as the efficacy of using specific nongesture models for outlier rejection. Using the IXMAS gesture data set, the proposed framework has been extensively tested and the gesture spotting results are superior to those reported on the same data set obtained using existing state-of-the-art gesture spotting methods.

Learning Category-Specific Dictionary and Shared Dictionary for Fine-Grained Image Categorization.

PubMed

Gao, Shenghua; Tsang, Ivor Wai-Hung; Ma, Yi

2014-02-01

This paper targets fine-grained image categorization by learning a category-specific dictionary for each category and a shared dictionary for all the categories. Such category-specific dictionaries encode subtle visual differences among different categories, while the shared dictionary encodes common visual patterns among all the categories. To this end, we impose incoherence constraints among the different dictionaries in the objective of feature coding. In addition, to make the learnt dictionary stable, we also impose the constraint that each dictionary should be self-incoherent. Our proposed dictionary learning formulation not only applies to fine-grained classification, but also improves conventional basic-level object categorization and other tasks such as event recognition. Experimental results on five data sets show that our method can outperform the state-of-the-art fine-grained image categorization frameworks as well as sparse coding based dictionary learning frameworks. All these results demonstrate the effectiveness of our method.

Multinational Experiment 7. Outcome 3 - Cyber Domain. Objective 3.3: Concept Framework Version 3.0

DTIC Science & Technology

2012-10-03

experimentation in order to give some parameters for Decision Makers’ actions. A.5 DIFFERENT LEGAL FRAMEWORKS The juridical framework to which we refer, in...material effects (e.g. psychological impact), economic et al, or, especially in the military field, it may affect Operational Security (OPSEC). 7...not expected at all to be run as a mechanistic tool that produces univocal outputs on the base of juridically qualified inputs, making unnecessary

A model framework to describe growth-linked biodegradation of trace-level pollutants in the presence of coincidental carbon substrates and microbes.

PubMed

Liu, Li; Helbling, Damian E; Kohler, Hans-Peter E; Smets, Barth F

2014-11-18

Pollutants such as pesticides and their degradation products occur ubiquitously in natural aquatic environments at trace concentrations (μg L(-1) and lower). Microbial biodegradation processes have long been known to contribute to the attenuation of pesticides in contaminated environments. However, challenges remain in developing engineered remediation strategies for pesticide-contaminated environments because the fundamental processes that regulate growth-linked biodegradation of pesticides in natural environments remain poorly understood. In this research, we developed a model framework to describe growth-linked biodegradation of pesticides at trace concentrations. We used experimental data reported in the literature or novel simulations to explore three fundamental kinetic processes in isolation. We then combine these kinetic processes into a unified model framework. The three kinetic processes described were: the growth-linked biodegradation of micropollutant at environmentally relevant concentrations; the effect of coincidental assimilable organic carbon substrates; and the effect of coincidental microbes that compete for assimilable organic carbon substrates. We used Monod kinetic models to describe substrate utilization and microbial growth rates for specific pesticide and degrader pairs. We then extended the model to include terms for utilization of assimilable organic carbon substrates by the specific degrader and coincidental microbes, growth on assimilable organic carbon substrates by the specific degrader and coincidental microbes, and endogenous metabolism. The proposed model framework enables interpretation and description of a range of experimental observations on micropollutant biodegradation. The model provides a useful tool to identify environmental conditions with respect to the occurrence of assimilable organic carbon and coincidental microbes that may result in enhanced or reduced micropollutant biodegradation.

Culturally Targeted Strategies for Diabetes Prevention in Minority Populations: A Systematic Review and Framework

PubMed Central

Lagisetty, Pooja A.; Priyadarshini, Shubadra; Terrell, Stephanie; Hamati, Mary; Landgraf, Jessica; Chopra, Vineet; Heisler, Michele

2017-01-01

Purpose The purpose of this study is to (a) assess the effectiveness of culturally tailored diabetes prevention interventions in minority populations and (b) develop a novel framework to characterize four key domains of culturally tailored interventions. Prevention strategies specifically tailored to the culture of ethnic minority patients may help reduce the incidence of diabetes. Methods We searched PubMed, EMBASE, and CINAHL for English-language, randomized controlled trials (RCTs) or quasi-experimental (QE) trials testing culturally tailored interventions to prevent diabetes in minority populations. Two reviewers independently extracted data and assessed risk of bias. Inductive thematic analysis was used to develop a framework with four domains (FiLLM: Facilitating [i.e., delivering] Interventions through Language, Location and Message). The framework was used to assess the overall effectiveness of culturally tailored interventions. Results Thirty-four trials met eligibility criteria. Twelve studies were randomized controlled trials, and 22 were quasi-experimental trials. Twenty-five out of 34 studies (74%) that used cultural tailoring demonstrated significantly improved Hemoglobin A1C, fasting glucose, and/or weight loss. Of the 25 successful interventions, 21 (84%) incorporated at least three culturally targeted domains. Seven studies used all four domains and were all successful. The least utilized domain was delivery (4/34) of the intervention’s key educational message. Conclusions Culturally tailoring interventions across the four domains of facilitators, language, location, and messaging can be effective in improving risk factors for progression to diabetes among ethnic minority groups. Future studies should evaluate how specific tailoring approaches work compared to usual care as well as comparative effectiveness of each tailoring domain. Registration (PROSPERO registration: CRD42015016914) PMID:28118127

A COMPUTATIONAL AND EXPERIMENTAL STUDY OF METAL AND COVALENT ORGANIC FRAMEWORKS USED IN ADSORPTION COOLING

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

Jenks, Jeromy WJ; TeGrotenhuis, Ward E.; Motkuri, Radha K.

2015-07-09

Metal-organic frameworks (MOFs) have recently attracted enormous interest over the past few years due to their potential applications in energy storage and gas separation. However, there have been few reports on MOFs for adsorption cooling applications. Adsorption cooling technology is an established alternative to mechanical vapor compression refrigeration systems. Adsorption cooling is an excellent alternative in industrial environments where waste heat is available. Applications also include hybrid systems, refrigeration, power-plant dry cooling, cryogenics, vehicular systems and building HVAC. Adsorption based cooling and refrigeration systems have several advantages including few moving parts and negligible power consumption. Key disadvantages include large thermalmore » mass, bulkiness, complex controls, and low COP (0.2-0.5). We explored the use of metal organic frameworks that have very high mass loading and relatively low heats of adsorption, with certain combinations of refrigerants to demonstrate a new type of highly efficient adsorption chiller. An adsorption chiller based on MOFs suggests that a thermally-driven COP>1 may be possible with these materials, which would represent a fundamental breakthrough in performance of adsorption chiller technology. Computational fluid dynamics combined with a system level lumped-parameter model have been used to project size and performance for chillers with a cooling capacity ranging from a few kW to several thousand kW. In addition, a cost model has been developed to project manufactured cost of entire systems. These systems rely on stacked micro/mini-scale architectures to enhance heat and mass transfer. Presented herein are computational and experimental results for hydrophyilic MOFs, fluorophilic MOFs and also flourophilic Covalent-organic frameworks (COFs).« less

Spatio-temporal Granger causality: a new framework

PubMed Central

Luo, Qiang; Lu, Wenlian; Cheng, Wei; Valdes-Sosa, Pedro A.; Wen, Xiaotong; Ding, Mingzhou; Feng, Jianfeng

2015-01-01

That physiological oscillations of various frequencies are present in fMRI signals is the rule, not the exception. Herein, we propose a novel theoretical framework, spatio-temporal Granger causality, which allows us to more reliably and precisely estimate the Granger causality from experimental datasets possessing time-varying properties caused by physiological oscillations. Within this framework, Granger causality is redefined as a global index measuring the directed information flow between two time series with time-varying properties. Both theoretical analyses and numerical examples demonstrate that Granger causality is a monotonically increasing function of the temporal resolution used in the estimation. This is consistent with the general principle of coarse graining, which causes information loss by smoothing out very fine-scale details in time and space. Our results confirm that the Granger causality at the finer spatio-temporal scales considerably outperforms the traditional approach in terms of an improved consistency between two resting-state scans of the same subject. To optimally estimate the Granger causality, the proposed theoretical framework is implemented through a combination of several approaches, such as dividing the optimal time window and estimating the parameters at the fine temporal and spatial scales. Taken together, our approach provides a novel and robust framework for estimating the Granger causality from fMRI, EEG, and other related data. PMID:23643924

DyKOSMap: A framework for mapping adaptation between biomedical knowledge organization systems.

PubMed

Dos Reis, Julio Cesar; Pruski, Cédric; Da Silveira, Marcos; Reynaud-Delaître, Chantal

2015-06-01

Knowledge Organization Systems (KOS) and their associated mappings play a central role in several decision support systems. However, by virtue of knowledge evolution, KOS entities are modified over time, impacting mappings and potentially turning them invalid. This requires semi-automatic methods to maintain such semantic correspondences up-to-date at KOS evolution time. We define a complete and original framework based on formal heuristics that drives the adaptation of KOS mappings. Our approach takes into account the definition of established mappings, the evolution of KOS and the possible changes that can be applied to mappings. This study experimentally evaluates the proposed heuristics and the entire framework on realistic case studies borrowed from the biomedical domain, using official mappings between several biomedical KOSs. We demonstrate the overall performance of the approach over biomedical datasets of different characteristics and sizes. Our findings reveal the effectiveness in terms of precision, recall and F-measure of the suggested heuristics and methods defining the framework to adapt mappings affected by KOS evolution. The obtained results contribute and improve the quality of mappings over time. The proposed framework can adapt mappings largely automatically, facilitating thus the maintenance task. The implemented algorithms and tools support and minimize the work of users in charge of KOS mapping maintenance. Copyright © 2015 Elsevier Inc. All rights reserved.

How do we interest students in science?

NASA Astrophysics Data System (ADS)

Murray, L.

2016-02-01

In today's world science literacy is now, more than ever, critical to society. However, today's technically savvy student tends to be bored by "cook-book" laboratory exercises and dated lecture style, which typifies the way that most science courses are taught. To enhance student interest in and understanding of the sciences, we developed two unique programs, in which teachers were provided with the tools and hands-on experience that enabled them to implement research- and inquiry-based projects with their students. The approach was based a framework that is student driven and enables active participation and innovation in the study of the environment. The framework involved selection of a theme and an activity that captured the interest of the participants, participant development of research or investigative questions based on the theme, experimentation to address the research questions, formulation of conclusions, and communication of these results. The projects consisted of two parts: a professional development institute for teachers and the classroom implementation of student research projects, both of which incorporated the framework process. The institutes focused on modeling the framework process, with teachers actively developing questions, researching the question, formulating results and conclusions. This method empowered teachers to be confident in the implementation of the process with their students. With support from project staff, teachers followed up by incorporating the method of teaching with their students. Evaluation results from the programs concluded that projects such as these can increase student interest in and understanding of the scientific process.

FORESEE: Fully Outsourced secuRe gEnome Study basEd on homomorphic Encryption

PubMed Central

2015-01-01

Background The increasing availability of genome data motivates massive research studies in personalized treatment and precision medicine. Public cloud services provide a flexible way to mitigate the storage and computation burden in conducting genome-wide association studies (GWAS). However, data privacy has been widely concerned when sharing the sensitive information in a cloud environment. Methods We presented a novel framework (FORESEE: Fully Outsourced secuRe gEnome Study basEd on homomorphic Encryption) to fully outsource GWAS (i.e., chi-square statistic computation) using homomorphic encryption. The proposed framework enables secure divisions over encrypted data. We introduced two division protocols (i.e., secure errorless division and secure approximation division) with a trade-off between complexity and accuracy in computing chi-square statistics. Results The proposed framework was evaluated for the task of chi-square statistic computation with two case-control datasets from the 2015 iDASH genome privacy protection challenge. Experimental results show that the performance of FORESEE can be significantly improved through algorithmic optimization and parallel computation. Remarkably, the secure approximation division provides significant performance gain, but without missing any significance SNPs in the chi-square association test using the aforementioned datasets. Conclusions Unlike many existing HME based studies, in which final results need to be computed by the data owner due to the lack of the secure division operation, the proposed FORESEE framework support complete outsourcing to the cloud and output the final encrypted chi-square statistics. PMID:26733391

Large eddy simulation of piloted pulverised coal combustion using extended flamelet/progress variable model

NASA Astrophysics Data System (ADS)

Wen, Xu; Luo, Kun; Jin, Hanhui; Fan, Jianren

2017-09-01

An extended flamelet/progress variable (EFPV) model for simulating pulverised coal combustion (PCC) in the context of large eddy simulation (LES) is proposed, in which devolatilisation, char surface reaction and radiation are all taken into account. The pulverised coal particles are tracked in the Lagrangian framework with various sub-models and the sub-grid scale (SGS) effects of turbulent velocity and scalar fluctuations on the coal particles are modelled by the velocity-scalar joint filtered density function (VSJFDF) model. The presented model is then evaluated by LES of an experimental piloted coal jet flame and comparing the numerical results with the experimental data and the results from the eddy break up (EBU) model. Detailed quantitative comparisons are carried out. It is found that the proposed model performs much better than the EBU model on radial velocity and species concentrations predictions. Comparing against the adiabatic counterpart, we find that the predicted temperature is evidently lowered and agrees well with the experimental data if the conditional sampling method is adopted.

Unraveling the Semiconducting/Metallic Discrepancy in Ni 3(HITP) 2

DOE PAGES

Foster, Michael E.; Sohlberg, Karl; Allendorf, Mark D.; ...

2018-01-10

Here, Ni 3(2,3,6,7,10,11-hexaiminotriphenylene) 2 is a π-stacked layered metal–organic framework material with extended π-conjugation that is analogous to graphene. Published experimental results indicate that the material is semiconducting, but all theoretical studies to date predict the bulk material to be metallic. Given that previous experimental work was carried out on specimens containing complex nanocrystalline microstructures and the tendency for internal interfaces to introduce transport barriers, we apply DFT to investigate the influence of internal interface defects on the electronic structure of Ni 3(HITP) 2. The results show that interface defects can introduce a transport barrier by breaking the π-conjugation and/ormore » decreasing the dispersion of the electronic bands near the Fermi level. We demonstrate that the presence of defects can open a small gap, in the range of 15–200 meV, which is consistent with the experimentally inferred hopping barrier.« less

Uncertainty Quantification and Statistical Convergence Guidelines for PIV Data

NASA Astrophysics Data System (ADS)

Stegmeir, Matthew; Kassen, Dan

2016-11-01

As Particle Image Velocimetry has continued to mature, it has developed into a robust and flexible technique for velocimetry used by expert and non-expert users. While historical estimates of PIV accuracy have typically relied heavily on "rules of thumb" and analysis of idealized synthetic images, recently increased emphasis has been placed on better quantifying real-world PIV measurement uncertainty. Multiple techniques have been developed to provide per-vector instantaneous uncertainty estimates for PIV measurements. Often real-world experimental conditions introduce complications in collecting "optimal" data, and the effect of these conditions is important to consider when planning an experimental campaign. The current work utilizes the results of PIV Uncertainty Quantification techniques to develop a framework for PIV users to utilize estimated PIV confidence intervals to compute reliable data convergence criteria for optimal sampling of flow statistics. Results are compared using experimental and synthetic data, and recommended guidelines and procedures leveraging estimated PIV confidence intervals for efficient sampling for converged statistics are provided.

Secure and Efficient Regression Analysis Using a Hybrid Cryptographic Framework: Development and Evaluation

PubMed Central

Jiang, Xiaoqian; Aziz, Md Momin Al; Wang, Shuang; Mohammed, Noman

2018-01-01

Background Machine learning is an effective data-driven tool that is being widely used to extract valuable patterns and insights from data. Specifically, predictive machine learning models are very important in health care for clinical data analysis. The machine learning algorithms that generate predictive models often require pooling data from different sources to discover statistical patterns or correlations among different attributes of the input data. The primary challenge is to fulfill one major objective: preserving the privacy of individuals while discovering knowledge from data. Objective Our objective was to develop a hybrid cryptographic framework for performing regression analysis over distributed data in a secure and efficient way. Methods Existing secure computation schemes are not suitable for processing the large-scale data that are used in cutting-edge machine learning applications. We designed, developed, and evaluated a hybrid cryptographic framework, which can securely perform regression analysis, a fundamental machine learning algorithm using somewhat homomorphic encryption and a newly introduced secure hardware component of Intel Software Guard Extensions (Intel SGX) to ensure both privacy and efficiency at the same time. Results Experimental results demonstrate that our proposed method provides a better trade-off in terms of security and efficiency than solely secure hardware-based methods. Besides, there is no approximation error. Computed model parameters are exactly similar to plaintext results. Conclusions To the best of our knowledge, this kind of secure computation model using a hybrid cryptographic framework, which leverages both somewhat homomorphic encryption and Intel SGX, is not proposed or evaluated to this date. Our proposed framework ensures data security and computational efficiency at the same time. PMID:29506966

Application of a conceptional framework to interpret variability in rangeland responses to atmospheric CO2 enrichment

USDA-ARS?s Scientific Manuscript database

Plant productivity and other ecosystem processes vary widely in their responses to experimental increases in atmospheric carbon dioxide (CO2) concentration. We adapt a conceptual framework first suggested by Chapin et al. (1996) to define conditions that sustain ecosystems to address the question o...

Teaching Experimental Methods: A Framework for Hands-On Modules

ERIC Educational Resources Information Center

Doherty, David

2011-01-01

Experiments provide a simple and engaging framework for familiarizing students with the process of quantitative social research. In this article, I illustrate how experiments can be used in the classroom environment by describing a module that was implemented in four high school classrooms. The module familiarized students with how the scientific…

Pedagogic Design Guidelines for Multimedia Materials: A Call for Collaboration between Practitioners and Researchers

ERIC Educational Resources Information Center

Koumi, Jack

2013-01-01

This paper argues that pedagogic efficacy of multimedia packages (interactive multimedia presentations) cannot be achieved by experimental research in the absence of a detailed pedagogical screenwriting framework. Following a summary of relevant literature, such a framework is offered, consisting of micro-level design guidelines. The guidelines…

Investigation of effective strategies for developing creative science thinking

NASA Astrophysics Data System (ADS)

Yang, Kuay-Keng; Lee, Ling; Hong, Zuway-R.; Lin, Huann-shyang

2016-09-01

The purpose of this study was to explore the effectiveness of the creative inquiry-based science teaching on students' creative science thinking and science inquiry performance. A quasi-experimental design consisting one experimental group (N = 20) and one comparison group (N = 24) with pretest and post-test was conducted. The framework of the intervention focused on potential strategies such as promoting divergent and convergent thinking and providing an open, inquiry-based learning environment that are recommended by the literature. Results revealed that the experimental group students outperformed their counterparts in the comparison group on the performances of science inquiry and convergent thinking. Additional qualitative data analyses from classroom observations and case teacher interviews identified supportive teaching strategies (e.g. facilitating associative thinking, sharing impressive ideas, encouraging evidence-based conclusions, and reviewing and commenting on group presentations) for developing students' creative science thinking.

Calculations on the half-lives of Cluster decay in two-potential approach

NASA Astrophysics Data System (ADS)

Soylu, A.

The half-lives of the cluster decay (CD) from the isotopes having the known experimental values, the half-lives of the α-decay (AD) of same nuclei and also the branching ratios are obtained, within the framework of two-potential approach with cosh potential including with and without the isospin effects. Using two-potential approach and taking into account the isospin effects in the calculations decrease the rms values and they improve the results. The obtained branching ratios are in good agreement with the experimental ones for some isotopes. It is obtained that the isospin-dependent potentials have an influence on the half-lives of the cluster decays of nuclei. Present calculations would be important for predicting the experimental half-lives and branching ratios for the cluster decays of different types of isotopes.

Evolution beyond neo-Darwinism: a new conceptual framework.

PubMed

Noble, Denis

2015-01-01

Experimental results in epigenetics and related fields of biological research show that the Modern Synthesis (neo-Darwinist) theory of evolution requires either extension or replacement. This article examines the conceptual framework of neo-Darwinism, including the concepts of 'gene', 'selfish', 'code', 'program', 'blueprint', 'book of life', 'replicator' and 'vehicle'. This form of representation is a barrier to extending or replacing existing theory as it confuses conceptual and empirical matters. These need to be clearly distinguished. In the case of the central concept of 'gene', the definition has moved all the way from describing a necessary cause (defined in terms of the inheritable phenotype itself) to an empirically testable hypothesis (in terms of causation by DNA sequences). Neo-Darwinism also privileges 'genes' in causation, whereas in multi-way networks of interactions there can be no privileged cause. An alternative conceptual framework is proposed that avoids these problems, and which is more favourable to an integrated systems view of evolution. © 2015. Published by The Company of Biologists Ltd.

Superpixel guided active contour segmentation of retinal layers in OCT volumes

NASA Astrophysics Data System (ADS)

Bai, Fangliang; Gibson, Stuart J.; Marques, Manuel J.; Podoleanu, Adrian

2018-03-01

Retinal OCT image segmentation is a precursor to subsequent medical diagnosis by a clinician or machine learning algorithm. In the last decade, many algorithms have been proposed to detect retinal layer boundaries and simplify the image representation. Inspired by the recent success of superpixel methods for pre-processing natural images, we present a novel framework for segmentation of retinal layers in OCT volume data. In our framework, the region of interest (e.g. the fovea) is located using an adaptive-curve method. The cell layer boundaries are then robustly detected firstly using 1D superpixels, applied to A-scans, and then fitting active contours in B-scan images. Thereafter the 3D cell layer surfaces are efficiently segmented from the volume data. The framework was tested on healthy eye data and we show that it is capable of segmenting up to 12 layers. The experimental results imply the effectiveness of proposed method and indicate its robustness to low image resolution and intrinsic speckle noise.

In Vivo Investigation of the Effectiveness of a Hyper-viscoelastic Model in Simulating Brain Retraction

PubMed Central

Li, Ping; Wang, Weiwei; Zhang, Chenxi; An, Yong; Song, Zhijian

2016-01-01

Intraoperative brain retraction leads to a misalignment between the intraoperative positions of the brain structures and their previous positions, as determined from preoperative images. In vitro swine brain sample uniaxial tests showed that the mechanical response of brain tissue to compression and extension could be described by the hyper-viscoelasticity theory. The brain retraction caused by the mechanical process is a combination of brain tissue compression and extension. In this paper, we first constructed a hyper-viscoelastic framework based on the extended finite element method (XFEM) to simulate intraoperative brain retraction. To explore its effectiveness, we then applied this framework to an in vivo brain retraction simulation. The simulation strictly followed the clinical scenario, in which seven swine were subjected to brain retraction. Our experimental results showed that the hyper-viscoelastic XFEM framework is capable of simulating intraoperative brain retraction and improving the navigation accuracy of an image-guided neurosurgery system (IGNS). PMID:27387301

A Multiprocessor SoC Architecture with Efficient Communication Infrastructure and Advanced Compiler Support for Easy Application Development

NASA Astrophysics Data System (ADS)

Urfianto, Mohammad Zalfany; Isshiki, Tsuyoshi; Khan, Arif Ullah; Li, Dongju; Kunieda, Hiroaki

This paper presentss a Multiprocessor System-on-Chips (MPSoC) architecture used as an execution platform for the new C-language based MPSoC design framework we are currently developing. The MPSoC architecture is based on an existing SoC platform with a commercial RISC core acting as the host CPU. We extend the existing SoC with a multiprocessor-array block that is used as the main engine to run parallel applications modeled in our design framework. Utilizing several optimizations provided by our compiler, an efficient inter-communication between processing elements with minimum overhead is implemented. A host-interface is designed to integrate the existing RISC core to the multiprocessor-array. The experimental results show that an efficacious integration is achieved, proving that the designed communication module can be used to efficiently incorporate off-the-shelf processors as a processing element for MPSoC architectures designed using our framework.

A Web Service-Based Framework Model for People-Centric Sensing Applications Applied to Social Networking

PubMed Central

Nunes, David; Tran, Thanh-Dien; Raposo, Duarte; Pinto, André; Gomes, André; Silva, Jorge Sá

2012-01-01

As the Internet evolved, social networks (such as Facebook) have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users’ activities and locations, sharing this information amongst the user’s friends within a social networking site. We also present some screenshot results of our experimental prototype. PMID:22438732

A framework for list representation, enabling list stabilization through incorporation of gene exchangeabilities.

PubMed

Soneson, Charlotte; Fontes, Magnus

2012-01-01

Analysis of multivariate data sets from, for example, microarray studies frequently results in lists of genes which are associated with some response of interest. The biological interpretation is often complicated by the statistical instability of the obtained gene lists, which may partly be due to the functional redundancy among genes, implying that multiple genes can play exchangeable roles in the cell. In this paper, we use the concept of exchangeability of random variables to model this functional redundancy and thereby account for the instability. We present a flexible framework to incorporate the exchangeability into the representation of lists. The proposed framework supports straightforward comparison between any 2 lists. It can also be used to generate new more stable gene rankings incorporating more information from the experimental data. Using 2 microarray data sets, we show that the proposed method provides more robust gene rankings than existing methods with respect to sampling variations, without compromising the biological significance of the rankings.

Filtering Based Adaptive Visual Odometry Sensor Framework Robust to Blurred Images

PubMed Central

Zhao, Haiying; Liu, Yong; Xie, Xiaojia; Liao, Yiyi; Liu, Xixi

2016-01-01

Visual odometry (VO) estimation from blurred image is a challenging problem in practical robot applications, and the blurred images will severely reduce the estimation accuracy of the VO. In this paper, we address the problem of visual odometry estimation from blurred images, and present an adaptive visual odometry estimation framework robust to blurred images. Our approach employs an objective measure of images, named small image gradient distribution (SIGD), to evaluate the blurring degree of the image, then an adaptive blurred image classification algorithm is proposed to recognize the blurred images, finally we propose an anti-blurred key-frame selection algorithm to enable the VO robust to blurred images. We also carried out varied comparable experiments to evaluate the performance of the VO algorithms with our anti-blur framework under varied blurred images, and the experimental results show that our approach can achieve superior performance comparing to the state-of-the-art methods under the condition with blurred images while not increasing too much computation cost to the original VO algorithms. PMID:27399704

A Web Service-based framework model for people-centric sensing applications applied to social networking.

PubMed

Nunes, David; Tran, Thanh-Dien; Raposo, Duarte; Pinto, André; Gomes, André; Silva, Jorge Sá

2012-01-01

As the Internet evolved, social networks (such as Facebook) have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users' activities and locations, sharing this information amongst the user's friends within a social networking site. We also present some screenshot results of our experimental prototype.

Detecting Molecular Rotational Dynamics Complementing the Low-Frequency Terahertz Vibrations in a Zirconium-Based Metal-Organic Framework

NASA Astrophysics Data System (ADS)

Ryder, Matthew R.; Van de Voorde, Ben; Civalleri, Bartolomeo; Bennett, Thomas D.; Mukhopadhyay, Sanghamitra; Cinque, Gianfelice; Fernandez-Alonso, Felix; De Vos, Dirk; Rudić, Svemir; Tan, Jin-Chong

2017-06-01

We show clear experimental evidence of cooperative terahertz (THz) dynamics observed below 3 THz (˜100 cm-1 ), for a low-symmetry Zr-based metal-organic framework structure, termed MIL-140A [ZrO (O2C-C 6H4-CO2) ]. Utilizing a combination of high-resolution inelastic neutron scattering and synchrotron radiation far-infrared spectroscopy, we measured low-energy vibrations originating from the hindered rotations of organic linkers, whose energy barriers and detailed dynamics have been elucidated via ab initio density functional theory calculations. The complex pore architecture caused by the THz rotations has been characterized. We discovered an array of soft modes with trampolinelike motions, which could potentially be the source of anomalous mechanical phenomena such as negative thermal expansion. Our results demonstrate coordinated shear dynamics (2.47 THz), a mechanism which we have shown to destabilize the framework structure, in the exact crystallographic direction of the minimum shear modulus (Gmin ).

A Converse Approach to NMR Chemical Shifts for Norm-Conserving Pseudopotentials

NASA Astrophysics Data System (ADS)

Lopez, Graham; Ceresoli, Davide; Marzari, Nicola; Thonhauser, Timo

2010-03-01

Building on the recently developed converse approach for the ab-initio calculation of NMR chemical shifts [1], we present a corresponding framework that is suitable in connection with norm-conserving pseudopotentials. Our approach uses the GIPAW transformation [2] to set up a formalism where the derivative of the orbital magnetization [3] is taken with respect to a microscopic, localized magnetic dipole in the presence of pseudopotentials. The advantages of our method are that it is conceptually simple, the need for a linear-response framework is avoided, and it is applicable to large systems. We present results for calculations of several well-studied systems, including the carbon, hydrogen, fluorine, and phosphorus shifts in various molecules and solids. Our results are in very good agreement with both linear-response calculations and experimental results.[4pt] [1] T. Thonhauser et al., J. Chem. Phys. 131, 101101 (2009).[2] C. J. Pickard and F. Mauri, Phys. Rev. B 63, 245101 (2001).[3] T. Thonhauser et al., Phys. Rev. Lett. 95, 137205 (2005).

Experimental Validation of L1 Adaptive Control: Rohrs' Counterexample in Flight

NASA Technical Reports Server (NTRS)

Xargay, Enric; Hovakimyan, Naira; Dobrokhodov, Vladimir; Kaminer, Issac; Kitsios, Ioannis; Cao, Chengyu; Gregory, Irene M.; Valavani, Lena

2010-01-01

The paper presents new results on the verification and in-flight validation of an L1 adaptive flight control system, and proposes a general methodology for verification and validation of adaptive flight control algorithms. The proposed framework is based on Rohrs counterexample, a benchmark problem presented in the early 80s to show the limitations of adaptive controllers developed at that time. In this paper, the framework is used to evaluate the performance and robustness characteristics of an L1 adaptive control augmentation loop implemented onboard a small unmanned aerial vehicle. Hardware-in-the-loop simulations and flight test results confirm the ability of the L1 adaptive controller to maintain stability and predictable performance of the closed loop adaptive system in the presence of general (artificially injected) unmodeled dynamics. The results demonstrate the advantages of L1 adaptive control as a verifiable robust adaptive control architecture with the potential of reducing flight control design costs and facilitating the transition of adaptive control into advanced flight control systems.

Connecting defects and amorphization in UiO-66 and MIL-140 metal–organic frameworks: a combined experimental and computational study.

PubMed

Bennett, Thomas D; Todorova, Tanya K; Baxter, Emma F; Reid, David G; Gervais, Christel; Bueken, Bart; Van de Voorde, B; De Vos, Dirk; Keen, David A; Mellot-Draznieks, Caroline

2016-01-21

The mechanism and products of the structural collapse of the metal–organic frameworks (MOFs) UiO-66, MIL-140B and MIL-140C upon ball-milling are investigated through solid state 13C NMR and pair distribution function (PDF) studies, finding amorphization to proceed by the breaking of a fraction of metal–ligand bonding in each case. The amorphous products contain inorganic–organic bonding motifs reminiscent of the crystalline phases. Whilst the inorganic Zr6O4(OH)4 clusters of UiO-66 remain intact upon structural collapse, the ZrO backbone of the MIL-140 frameworks undergoes substantial distortion. Density functional theory calculations have been performed to investigate defective models of MIL-140B and show, through comparison of calculated and experimental 13C NMR spectra, that amorphization and defects in the materials are linked.

The Sharing Experimental Animal Resources, Coordinating Holdings (SEARCH) Framework: Encouraging Reduction, Replacement, and Refinement in Animal Research.

PubMed

Morrissey, Bethny; Blyth, Karen; Carter, Phil; Chelala, Claude; Jones, Louise; Holen, Ingunn; Speirs, Valerie

2017-01-01

While significant medical breakthroughs have been achieved through using animal models, our experience shows that often there is surplus material remaining that is frequently never revisited but could be put to good use by other scientists. Recognising that most scientists are willing to share this material on a collaborative basis, it makes economic, ethical, and academic sense to explore the option to utilise this precious resource before generating new/additional animal models and associated samples. To bring together those requiring animal tissue and those holding this type of archival material, we have devised a framework called Sharing Experimental Animal Resources, Coordinating Holdings (SEARCH) with the aim of making remaining material derived from animal studies in biomedical research more visible and accessible to the scientific community. We encourage journals, funding bodies, and scientists to unite in promoting a new way of approaching animal research by adopting the SEARCH framework.

The Sharing Experimental Animal Resources, Coordinating Holdings (SEARCH) Framework: Encouraging Reduction, Replacement, and Refinement in Animal Research

PubMed Central

Morrissey, Bethny; Blyth, Karen; Carter, Phil; Chelala, Claude; Jones, Louise; Holen, Ingunn; Speirs, Valerie

2017-01-01

While significant medical breakthroughs have been achieved through using animal models, our experience shows that often there is surplus material remaining that is frequently never revisited but could be put to good use by other scientists. Recognising that most scientists are willing to share this material on a collaborative basis, it makes economic, ethical, and academic sense to explore the option to utilise this precious resource before generating new/additional animal models and associated samples. To bring together those requiring animal tissue and those holding this type of archival material, we have devised a framework called Sharing Experimental Animal Resources, Coordinating Holdings (SEARCH) with the aim of making remaining material derived from animal studies in biomedical research more visible and accessible to the scientific community. We encourage journals, funding bodies, and scientists to unite in promoting a new way of approaching animal research by adopting the SEARCH framework. PMID:28081116

Ensemble Semi-supervised Frame-work for Brain Magnetic Resonance Imaging Tissue Segmentation.

PubMed

Azmi, Reza; Pishgoo, Boshra; Norozi, Narges; Yeganeh, Samira

2013-04-01

Brain magnetic resonance images (MRIs) tissue segmentation is one of the most important parts of the clinical diagnostic tools. Pixel classification methods have been frequently used in the image segmentation with two supervised and unsupervised approaches up to now. Supervised segmentation methods lead to high accuracy, but they need a large amount of labeled data, which is hard, expensive, and slow to obtain. Moreover, they cannot use unlabeled data to train classifiers. On the other hand, unsupervised segmentation methods have no prior knowledge and lead to low level of performance. However, semi-supervised learning which uses a few labeled data together with a large amount of unlabeled data causes higher accuracy with less trouble. In this paper, we propose an ensemble semi-supervised frame-work for segmenting of brain magnetic resonance imaging (MRI) tissues that it has been used results of several semi-supervised classifiers simultaneously. Selecting appropriate classifiers has a significant role in the performance of this frame-work. Hence, in this paper, we present two semi-supervised algorithms expectation filtering maximization and MCo_Training that are improved versions of semi-supervised methods expectation maximization and Co_Training and increase segmentation accuracy. Afterward, we use these improved classifiers together with graph-based semi-supervised classifier as components of the ensemble frame-work. Experimental results show that performance of segmentation in this approach is higher than both supervised methods and the individual semi-supervised classifiers.

Fabrication of silver nanoparticles doped in the zeolite framework and antibacterial activity

PubMed Central

Shameli, Kamyar; Ahmad, Mansor Bin; Zargar, Mohsen; Yunus, Wan Md Zin Wan; Ibrahim, Nor Azowa

2011-01-01

Using the chemical reduction method, silver nanoparticles (Ag NPs) were effectively synthesized into the zeolite framework in the absence of any heat treatment. Zeolite, silver nitrate, and sodium borohydride were used as an inorganic solid support, a silver precursor, and a chemical reduction agent, respectively. Silver ions were introduced into the porous zeolite lattice by an ion-exchange path. After the reduction process, Ag NPs formed in the zeolite framework, with a mean diameter of about 2.12–3.11 nm. The most favorable experimental condition for the synthesis of Ag/zeolite nanocomposites (NCs) is described in terms of the initial concentration of AgNO3. The Ag/zeolite NCs were characterized by ultraviolet-visible spectroscopy, powder X-ray diffraction, transmission electron microscopy, scanning electron microscopy, energy dispersive X-ray fluorescence, and Fourier transform infrared. The results show that Ag NPs form a spherical shape with uniform homogeneity in the particle size. The antibacterial activity of Ag NPs in zeolites was investigated against Gram-negative bacteria (ie, Escherichia coli and Shigella dysentriae) and Gram-positive bacteria (ie, Staphylococcus aureus and methicillin-resistant Staphylococcus aureus) by disk diffusion method using Mueller–Hinton agar at different sizes of Ag NPs. All of the synthesized Ag/zeolite NCs were found to have antibacterial activity. These results show that Ag NPs in the zeolite framework can be useful in different biological research and biomedical applications. PMID:21383858

Fabrication of silver nanoparticles doped in the zeolite framework and antibacterial activity.

PubMed

Shameli, Kamyar; Ahmad, Mansor Bin; Zargar, Mohsen; Yunus, Wan Md Zin Wan; Ibrahim, Nor Azowa

2011-01-01

Using the chemical reduction method, silver nanoparticles (Ag NPs) were effectively synthesized into the zeolite framework in the absence of any heat treatment. Zeolite, silver nitrate, and sodium borohydride were used as an inorganic solid support, a silver precursor, and a chemical reduction agent, respectively. Silver ions were introduced into the porous zeolite lattice by an ion-exchange path. After the reduction process, Ag NPs formed in the zeolite framework, with a mean diameter of about 2.12-3.11 nm. The most favorable experimental condition for the synthesis of Ag/zeolite nanocomposites (NCs) is described in terms of the initial concentration of AgNO(3). The Ag/zeolite NCs were characterized by ultraviolet-visible spectroscopy, powder X-ray diffraction, transmission electron microscopy, scanning electron microscopy, energy dispersive X-ray fluorescence, and Fourier transform infrared. The results show that Ag NPs form a spherical shape with uniform homogeneity in the particle size. The antibacterial activity of Ag NPs in zeolites was investigated against Gram-negative bacteria (ie, Escherichia coli and Shigella dysentriae) and Gram-positive bacteria (ie, Staphylococcus aureus and methicillin-resistant Staphylococcus aureus) by disk diffusion method using Mueller-Hinton agar at different sizes of Ag NPs. All of the synthesized Ag/zeolite NCs were found to have antibacterial activity. These results show that Ag NPs in the zeolite framework can be useful in different biological research and biomedical applications.

A postprocessing method in the HMC framework for predicting gene function based on biological instrumental data

NASA Astrophysics Data System (ADS)

Feng, Shou; Fu, Ping; Zheng, Wenbin

2018-03-01

Predicting gene function based on biological instrumental data is a complicated and challenging hierarchical multi-label classification (HMC) problem. When using local approach methods to solve this problem, a preliminary results processing method is usually needed. This paper proposed a novel preliminary results processing method called the nodes interaction method. The nodes interaction method revises the preliminary results and guarantees that the predictions are consistent with the hierarchy constraint. This method exploits the label dependency and considers the hierarchical interaction between nodes when making decisions based on the Bayesian network in its first phase. In the second phase, this method further adjusts the results according to the hierarchy constraint. Implementing the nodes interaction method in the HMC framework also enhances the HMC performance for solving the gene function prediction problem based on the Gene Ontology (GO), the hierarchy of which is a directed acyclic graph that is more difficult to tackle. The experimental results validate the promising performance of the proposed method compared to state-of-the-art methods on eight benchmark yeast data sets annotated by the GO.

Impact of metal and anion substitutions on the hydrogen storage properties of M-BTT metal-organic frameworks.

PubMed

Sumida, Kenji; Stück, David; Mino, Lorenzo; Chai, Jeng-Da; Bloch, Eric D; Zavorotynska, Olena; Murray, Leslie J; Dincă, Mircea; Chavan, Sachin; Bordiga, Silvia; Head-Gordon, Martin; Long, Jeffrey R

2013-01-23

Microporous metal-organic frameworks are a class of materials being vigorously investigated for mobile hydrogen storage applications. For high-pressure storage at ambient temperatures, the M(3)[(M(4)Cl)(3)(BTT)(8)](2) (M-BTT; BTT(3-) = 1,3,5-benzenetristetrazolate) series of frameworks are of particular interest due to the high density of exposed metal cation sites on the pore surface. These sites give enhanced zero-coverage isosteric heats of adsorption (Q(st)) approaching the optimal value for ambient storage applications. However, the Q(st) parameter provides only a limited insight into the thermodynamics of the individual adsorption sites, the tuning of which is paramount for optimizing the storage performance. Here, we begin by performing variable-temperature infrared spectroscopy studies of Mn-, Fe-, and Cu-BTT, allowing the thermodynamics of H(2) adsorption to be probed experimentally. This is complemented by a detailed DFT study, in which molecular fragments representing the metal clusters within the extended solid are simulated to obtain a more thorough description of the structural and thermodynamic aspects of H(2) adsorption at the strongest binding sites. Then, the effect of substitutions at the metal cluster (metal ion and anion within the tetranuclear cluster) is discussed, showing that the configuration of this unit indeed plays an important role in determining the affinity of the framework toward H(2). Interestingly, the theoretical study has identified that the Zn-based analogs would be expected to facilitate enhanced adsorption profiles over the compounds synthesized experimentally, highlighting the importance of a combined experimental and theoretical approach to the design and synthesis of new frameworks for H(2) storage applications.

Low-lying electromagnetic transition strengths in 180Pt

NASA Astrophysics Data System (ADS)

Müller-Gatermann, C.; Dewald, A.; Fransen, C.; Braunroth, T.; Jolie, J.; Litzinger, J.; Régis, J. M.; von Spee, F.; Warr, N.; Zell, K. O.; Grahn, T.; Greenlees, P. T.; Hauschild, K.; Jakobsson, U.; Julin, R.; Juutinen, S.; Ketelhut, S.; Nieminen, P.; Nyman, M.; Peura, P.; Rahkila, P.; Ruotsalainen, P.; Sandzelius, M.; Sarén, J.; Scholey, C.; Sorri, J.; Stolze, S.; Uusitalo, J.; Petkov, P.

2018-02-01

Lifetime measurements have been performed using the 98Mo(86Kr,4 n )180Pt reaction at a beam energy of 380 MeV, and the recoil distance Doppler-shift method. In a second experiment the 168Yb(16O,4 n )180Pt reaction at a beam energy of 88 MeV using the Ge-gated γ -γ fast timing technique was used to determine lifetimes. Lifetimes of the four lowest yrast states of 180Pt have been determined. The experimental data are compared to calculations within the framework of the interacting boson model and the general collective model. Both models predict a deformed ground state and are consistent with all the remaining experimental results.

The quadrupole moments of some even–even nuclei around the mass of A ~ 80: {sup 68−80}Ge on the neighborhood of {sup 76−84}Kr and {sup 76−84}Se isotopes

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

Yoruk, Abdulkadir, E-mail: yorukabdulkadir@hotmail.com; Turkan, Nureddin, E-mail: nureddin.turkan@medeniyet.edu.tr

2016-09-15

We have carried out the calculation of the quadrupole moments Q(2{sub 1}{sup +}) and electromagnetic transition rates B(E2) of some levels within the framework of the interacting boson model for even-mass Ge nuclei. The presented predictions of the quadrupole moments and B(E2) ratios for Ge nuclei are compared with the results of some previous experimental and theoretical ones along with those of the neighboring Kr and Se isotopes and then it was seen that they agree well with the previous experimental and theoretical ones.

Neutron and photon shielding benchmark calculations by MCNP on the LR-0 experimental facility.

PubMed

Hordósy, G

2005-01-01

In the framework of the REDOS project, the space-energy distribution of the neutron and photon flux has been calculated over the pressure vessel simulator thickness of the LR-0 experimental reactor, Rez, Czech Republic. The results calculated by the Monte Carlo code MCNP4C are compared with the measurements performed in the Nuclear Research Institute, Rez. The spectra have been measured at the barrel, in front of, inside and behind the pressure vessel in different configurations. The neutron measurements were performed in the energy range 0.1-10 MeV. This work has been done in the frame of the 5th Frame Work Programme of the European Community 1998-2002.

Random anisotropy model approach on ion beam sputtered Co 20Cu 80 granular alloy

NASA Astrophysics Data System (ADS)

Errahmani, H.; Hassanaı̈n, N.; Berrada, A.; Abid, M.; Lassri, H.; Schmerber, G.; Dinia, A.

2002-03-01

The Co 20Cu 80 granular film has been elaborated using ion beam sputtering technique. The magnetic properties of the sample were studied in the temperature range 5-300 K at H⩽50 kOe. From the thermomagnetisation curve, which is found to obey to the Bloch law, we have extracted the spin wave stiffness constant D and the exchange constant A. The magnetic experimental results have been interpreted in the framework of random anisotropy model. We have determined the local anisotropy constant KL and the local correlation length of anisotropy axis Ra, which is compared to the experimental grains size obtained by transmission electronic microscopy.

In-silico experiments of zebrafish behaviour: modeling swimming in three dimensions

NASA Astrophysics Data System (ADS)

Mwaffo, Violet; Butail, Sachit; Porfiri, Maurizio

2017-01-01

Zebrafish is fast becoming a species of choice in biomedical research for the investigation of functional and dysfunctional processes coupled with their genetic and pharmacological modulation. As with mammals, experimentation with zebrafish constitutes a complicated ethical issue that calls for the exploration of alternative testing methods to reduce the number of subjects, refine experimental designs, and replace live animals. Inspired by the demonstrated advantages of computational studies in other life science domains, we establish an authentic data-driven modelling framework to simulate zebrafish swimming in three dimensions. The model encapsulates burst-and-coast swimming style, speed modulation, and wall interaction, laying the foundations for in-silico experiments of zebrafish behaviour. Through computational studies, we demonstrate the ability of the model to replicate common ethological observables such as speed and spatial preference, and anticipate experimental observations on the correlation between tank dimensions on zebrafish behaviour. Reaching to other experimental paradigms, our framework is expected to contribute to a reduction in animal use and suffering.

In-silico experiments of zebrafish behaviour: modeling swimming in three dimensions

PubMed Central

Mwaffo, Violet; Butail, Sachit; Porfiri, Maurizio

2017-01-01

Zebrafish is fast becoming a species of choice in biomedical research for the investigation of functional and dysfunctional processes coupled with their genetic and pharmacological modulation. As with mammals, experimentation with zebrafish constitutes a complicated ethical issue that calls for the exploration of alternative testing methods to reduce the number of subjects, refine experimental designs, and replace live animals. Inspired by the demonstrated advantages of computational studies in other life science domains, we establish an authentic data-driven modelling framework to simulate zebrafish swimming in three dimensions. The model encapsulates burst-and-coast swimming style, speed modulation, and wall interaction, laying the foundations for in-silico experiments of zebrafish behaviour. Through computational studies, we demonstrate the ability of the model to replicate common ethological observables such as speed and spatial preference, and anticipate experimental observations on the correlation between tank dimensions on zebrafish behaviour. Reaching to other experimental paradigms, our framework is expected to contribute to a reduction in animal use and suffering. PMID:28071731

Electromagnetic axial anomaly in a generalized linear sigma model

NASA Astrophysics Data System (ADS)

Fariborz, Amir H.; Jora, Renata

2017-06-01

We construct the electromagnetic anomaly effective term for a generalized linear sigma model with two chiral nonets, one with a quark-antiquark structure, the other one with a four-quark content. We compute in the leading order of this framework the decays into two photons of six pseudoscalars: π0(137 ), π0(1300 ), η (547 ), η (958 ), η (1295 ) and η (1760 ). Our results agree well with the available experimental data.

Auxetic Metamaterials under Direct Impact Loads in a Structural Health Monitoring Framework

DTIC Science & Technology

2013-01-01

of two types of sandwich composites composed of E-Glass Vinyl-Ester (EVE) face sheets and Corecell™ A-series foam with a polyurea interlayer (5...Using a shock tube apparatus to subject samples to high-intensity impulse loading, results show that the addition of polyurea interlayer improves the...051307-7. 5. Gardner, N.; Wang, E.; Kumar, P.; Shulka, A. Blast Mitigation in a Sandwich Composite Using Graded Core and Polyurea . Experimental

Probing Actinide Electronic Structure through Pu Cluster Calculations

DOE PAGES

Ryzhkov, Mickhail V.; Mirmelstein, Alexei; Yu, Sung-Woo; ...

2013-02-26

The calculations for the electronic structure of clusters of plutonium have been performed, within the framework of the relativistic discrete-variational method. Moreover, these theoretical results and those calculated earlier for related systems have been compared to spectroscopic data produced in the experimental investigations of bulk systems, including photoelectron spectroscopy. Observation of the changes in the Pu electronic structure as a function of size provides powerful insight for aspects of bulk Pu electronic structure.

Rapid development of Proteomic applications with the AIBench framework.

PubMed

López-Fernández, Hugo; Reboiro-Jato, Miguel; Glez-Peña, Daniel; Méndez Reboredo, José R; Santos, Hugo M; Carreira, Ricardo J; Capelo-Martínez, José L; Fdez-Riverola, Florentino

2011-09-15

In this paper we present two case studies of Proteomics applications development using the AIBench framework, a Java desktop application framework mainly focused in scientific software development. The applications presented in this work are Decision Peptide-Driven, for rapid and accurate protein quantification, and Bacterial Identification, for Tuberculosis biomarker search and diagnosis. Both tools work with mass spectrometry data, specifically with MALDI-TOF spectra, minimizing the time required to process and analyze the experimental data. Copyright 2011 The Author(s). Published by Journal of Integrative Bioinformatics.

A FRAMEWORK TO DESIGN AND OPTIMIZE CHEMICAL FLOODING PROCESSES

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

Mojdeh Delshad; Gary A. Pope; Kamy Sepehrnoori

2005-07-01

The goal of this proposed research is to provide an efficient and user friendly simulation framework for screening and optimizing chemical/microbial enhanced oil recovery processes. The framework will include (1) a user friendly interface to identify the variables that have the most impact on oil recovery using the concept of experimental design and response surface maps, (2) UTCHEM reservoir simulator to perform the numerical simulations, and (3) an economic model that automatically imports the simulation production data to evaluate the profitability of a particular design. Such a reservoir simulation framework is not currently available to the oil industry. The objectivesmore » of Task 1 are to develop three primary modules representing reservoir, chemical, and well data. The modules will be interfaced with an already available experimental design model. The objective of the Task 2 is to incorporate UTCHEM reservoir simulator and the modules with the strategic variables and developing the response surface maps to identify the significant variables from each module. The objective of the Task 3 is to develop the economic model designed specifically for the chemical processes targeted in this proposal and interface the economic model with UTCHEM production output. Task 4 is on the validation of the framework and performing simulations of oil reservoirs to screen, design and optimize the chemical processes.« less

A Framework to Design and Optimize Chemical Flooding Processes

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

Mojdeh Delshad; Gary A. Pope; Kamy Sepehrnoori

2006-08-31

The goal of this proposed research is to provide an efficient and user friendly simulation framework for screening and optimizing chemical/microbial enhanced oil recovery processes. The framework will include (1) a user friendly interface to identify the variables that have the most impact on oil recovery using the concept of experimental design and response surface maps, (2) UTCHEM reservoir simulator to perform the numerical simulations, and (3) an economic model that automatically imports the simulation production data to evaluate the profitability of a particular design. Such a reservoir simulation framework is not currently available to the oil industry. The objectivesmore » of Task 1 are to develop three primary modules representing reservoir, chemical, and well data. The modules will be interfaced with an already available experimental design model. The objective of the Task 2 is to incorporate UTCHEM reservoir simulator and the modules with the strategic variables and developing the response surface maps to identify the significant variables from each module. The objective of the Task 3 is to develop the economic model designed specifically for the chemical processes targeted in this proposal and interface the economic model with UTCHEM production output. Task 4 is on the validation of the framework and performing simulations of oil reservoirs to screen, design and optimize the chemical processes.« less

A FRAMEWORK TO DESIGN AND OPTIMIZE CHEMICAL FLOODING PROCESSES

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

Mojdeh Delshad; Gary A. Pope; Kamy Sepehrnoori

2004-11-01

The goal of this proposed research is to provide an efficient and user friendly simulation framework for screening and optimizing chemical/microbial enhanced oil recovery processes. The framework will include (1) a user friendly interface to identify the variables that have the most impact on oil recovery using the concept of experimental design and response surface maps, (2) UTCHEM reservoir simulator to perform the numerical simulations, and (3) an economic model that automatically imports the simulation production data to evaluate the profitability of a particular design. Such a reservoir simulation framework is not currently available to the oil industry. The objectivesmore » of Task 1 are to develop three primary modules representing reservoir, chemical, and well data. The modules will be interfaced with an already available experimental design model. The objective of the Task 2 is to incorporate UTCHEM reservoir simulator and the modules with the strategic variables and developing the response surface maps to identify the significant variables from each module. The objective of the Task 3 is to develop the economic model designed specifically for the chemical processes targeted in this proposal and interface the economic model with UTCHEM production output. Task 4 is on the validation of the framework and performing simulations of oil reservoirs to screen, design and optimize the chemical processes.« less

Experimental Analysis of the Role of Fluid Transport Properties in Fluid-Induced Fracture Initiation and Propagation

NASA Astrophysics Data System (ADS)

Boutt, D.; McPherson, B. J.; Cook, B. K.; Goodwin, L. B.; Williams, J. R.; Lee, M. Y.; Patteson, R.

2003-12-01

It is well known that pore fluid pressure fundamentally influences a rock's mechanical response to stress. However, most measures of the mechanical behavior of rock (e.g. shear strength, Young's modulus) do not incorporate, either explicitly or implicitly, pore fluid pressure or transport properties of rock. Current empirical and theoretical criteria that define the amount of stress a given body of rock can support before fracturing also lack a direct connection between fluid transport and mechanical properties. Our research goal is to use laboratory experimental results to elucidate correlations between rock transport properties and fracture behavior under idealized loading conditions. In strongly coupled fluid-solid systems the evolution of the solid framework is influenced by the fluid and vice versa. These couplings often result in changes of the bulk material properties (i.e. permeability and failure strength) with respect to the fluid's ability to move through the solid and the solids ability to transmit momentum. Feedbacks between fluid and solid framework ultimately play key roles in understanding the spatial and temporal evolution of the coupled fluid-solid system. Discretely coupled models of fluid and solid mechanics were developed a priori to design an experimental approach for testing the role of fluid transport parameters in rock fracture. The experimental approach consists of first loading a fluid saturated cylindrical rock specimen under hydrostatic conditions and then applying a differential stress such that the maximum stress is perpendicular to the cylinder long axis. At the beginning of the test the minimum stress and the fluid pressure are dropped at the same time such that the resulting difference in the initial fluid pressure and the final fluid pressure is greater than the final minimum stress. These loading conditions should produce a fluid driven tensile fracture that is perpendicular to the cylinder long axis. Initial analyses using numerical simulations with similar boundary conditions suggest that resulting fracture propagation rates and fracture spacing are controlled by the rocks hydraulic diffusivity. Modeled rocks with higher permeability had fractures with larger apertures, more localized deformation, and greater fracture spacing. Intuitively, these results are consistent with permeability controlling the time required for pressure to come to equilibrium with the new boundary conditions. Finally, more general goals of this research include using these core-scale experimental data and discrete simulation results to calibrate larger-scale, more traditional continuum models of geologic deformation.

Brain tumor classification and segmentation using sparse coding and dictionary learning.

PubMed

Salman Al-Shaikhli, Saif Dawood; Yang, Michael Ying; Rosenhahn, Bodo

2016-08-01

This paper presents a novel fully automatic framework for multi-class brain tumor classification and segmentation using a sparse coding and dictionary learning method. The proposed framework consists of two steps: classification and segmentation. The classification of the brain tumors is based on brain topology and texture. The segmentation is based on voxel values of the image data. Using K-SVD, two types of dictionaries are learned from the training data and their associated ground truth segmentation: feature dictionary and voxel-wise coupled dictionaries. The feature dictionary consists of global image features (topological and texture features). The coupled dictionaries consist of coupled information: gray scale voxel values of the training image data and their associated label voxel values of the ground truth segmentation of the training data. For quantitative evaluation, the proposed framework is evaluated using different metrics. The segmentation results of the brain tumor segmentation (MICCAI-BraTS-2013) database are evaluated using five different metric scores, which are computed using the online evaluation tool provided by the BraTS-2013 challenge organizers. Experimental results demonstrate that the proposed approach achieves an accurate brain tumor classification and segmentation and outperforms the state-of-the-art methods.

Study of inclusive single-jet production in the framework of kt-factorization unintegrated parton distributions

NASA Astrophysics Data System (ADS)

Aminzadeh Nik, R.; Modarres, M.; Masouminia, M. R.

2018-05-01

The present work is intended to study the double-differential cross section of the inclusive single-jet production as the functions of the transverse momentum and the rapidity of the jet in the high-energy hadron-hadron collisions. The angular-ordering-constraint kt-factorization framework is used to calculate the above cross section that is available experimentally. The conditions are taken in accordance with the LHC experiments. The results are compared and analyzed using the existing CMS LHC data. The scheme-dependent unintegrated parton distribution functions (UPDF) of Kimber-Martin-Ryskin (KMR) and Martin-Ryskin-Watt (MRW) in the leading-order and the next-to-leading order (NLO) are used to predict the input partonic UPDF. The utilized phenomenological frameworks prove to be relatively successful in generating satisfactory results compared to the different experiment data, such as CMS (8 and 13 TeV). Extensive discussions and comparisons are made regarding the behavior of the contributing partonic subprocesses. Finally, it is shown that the application of the KMR UPDF to the single-jet differential cross sections have better agreement with the CMS data; on the other hand, they are very similar to those of NLO-MRW.

LIPID11: A Modular Framework for Lipid Simulations using Amber

PubMed Central

Skjevik, Åge A.; Madej, Benjamin D.; Walker, Ross C.; eigen, Knut T

2013-01-01

Accurate simulation of complex lipid bilayers has long been a goal in condensed phase molecular dynamics (MD). Structure and function of membrane-bound proteins are highly dependent on the lipid bilayer environment and are challenging to study through experimental methods. Within Amber, there has been limited focus on lipid simulations, although some success has been seen with the use of the General Amber Force Field (GAFF). However, to date there are no dedicated Amber lipid force fields. In this paper we describe a new charge derivation strategy for lipids consistent with the Amber RESP approach, and a new atom and residue naming and type convention. In the first instance, we have combined this approach with GAFF parameters. The result is LIPID11, a flexible, modular framework for the simulation of lipids that is fully compatible with the existing Amber force fields. The charge derivation procedure, capping strategy and nomenclature for LIPID11, along with preliminary simulation results and a discussion of the planned long-term parameter development are presented here. Our findings suggest that Lipid11 is a modular framework feasible for phospholipids and a flexible starting point for the development of a comprehensive, Amber-compatible lipid force field. PMID:22916730

Examining the Value of a Scaffolded Critique Framework to Promote Argumentative and Explanatory Writings Within an Argument-Based Inquiry Approach

NASA Astrophysics Data System (ADS)

Jang, Jeong-yoon; Hand, Brian

2017-12-01

This study investigated the value of using a scaffolded critique framework to promote two different types of writing—argumentative writing and explanatory writing—with different purposes within an argument-based inquiry approach known as the Science Writing Heuristic (SWH) approach. A quasi-experimental design with sixth and seventh grade students taught by two teachers was used. A total of 170 students participated in the study, with 87 in the control group (four classes) and 83 in the treatment group (four classes). All students used the SWH templates as an argumentative writing to guide their written work and completed these templates during the SWH investigations of each unit. After completing the SWH investigations, both groups of students were asked to complete the summary writing task as an explanatory writing at the end of each unit. All students' writing samples were scored using analytical frameworks developed for the study. The results indicated that the treatment group performed significantly better on the explanatory writing task than the control group. In addition, the results of the partial correlation suggested that there is a very strong significantly positive relationship between the argumentative writing and the explanatory writing.

An Unsupervised Online Spike-Sorting Framework.

PubMed

Knieling, Simeon; Sridharan, Kousik S; Belardinelli, Paolo; Naros, Georgios; Weiss, Daniel; Mormann, Florian; Gharabaghi, Alireza

2016-08-01

Extracellular neuronal microelectrode recordings can include action potentials from multiple neurons. To separate spikes from different neurons, they can be sorted according to their shape, a procedure referred to as spike-sorting. Several algorithms have been reported to solve this task. However, when clustering outcomes are unsatisfactory, most of them are difficult to adjust to achieve the desired results. We present an online spike-sorting framework that uses feature normalization and weighting to maximize the distinctiveness between different spike shapes. Furthermore, multiple criteria are applied to either facilitate or prevent cluster fusion, thereby enabling experimenters to fine-tune the sorting process. We compare our method to established unsupervised offline (Wave_Clus (WC)) and online (OSort (OS)) algorithms by examining their performance in sorting various test datasets using two different scoring systems (AMI and the Adamos metric). Furthermore, we evaluate sorting capabilities on intra-operative recordings using established quality metrics. Compared to WC and OS, our algorithm achieved comparable or higher scores on average and produced more convincing sorting results for intra-operative datasets. Thus, the presented framework is suitable for both online and offline analysis and could substantially improve the quality of microelectrode-based data evaluation for research and clinical application.

How measurement science can improve confidence in research results.

PubMed

Plant, Anne L; Becker, Chandler A; Hanisch, Robert J; Boisvert, Ronald F; Possolo, Antonio M; Elliott, John T

2018-04-01

The current push for rigor and reproducibility is driven by a desire for confidence in research results. Here, we suggest a framework for a systematic process, based on consensus principles of measurement science, to guide researchers and reviewers in assessing, documenting, and mitigating the sources of uncertainty in a study. All study results have associated ambiguities that are not always clarified by simply establishing reproducibility. By explicitly considering sources of uncertainty, noting aspects of the experimental system that are difficult to characterize quantitatively, and proposing alternative interpretations, the researcher provides information that enhances comparability and reproducibility.

The Effect of Visual Information on the Manual Approach and Landing

NASA Technical Reports Server (NTRS)

Wewerinke, P. H.

1982-01-01

The effect of visual information in combination with basic display information on the approach performance. A pre-experimental model analysis was performed in terms of the optimal control model. The resulting aircraft approach performance predictions were compared with the results of a moving base simulator program. The results illustrate that the model provides a meaningful description of the visual (scene) perception process involved in the complex (multi-variable, time varying) manual approach task with a useful predictive capability. The theoretical framework was shown to allow a straight-forward investigation of the complex interaction of a variety of task variables.

Niche construction game cancer cells play

NASA Astrophysics Data System (ADS)

Bergman, Aviv; Gligorijevic, Bojana

2015-10-01

Niche construction concept was originally defined in evolutionary biology as the continuous interplay between natural selection via environmental conditions and the modification of these conditions by the organism itself. Processes unraveling during cancer metastasis include construction of niches, which cancer cells use towards more efficient survival, transport into new environments and preparation of the remote sites for their arrival. Many elegant experiments were done lately illustrating, for example, the premetastatic niche construction, but there is practically no mathematical modeling done which would apply the niche construction framework. To create models useful for understanding niche construction role in cancer progression, we argue that a) genetic, b) phenotypic and c) ecological levels are to be included. While the model proposed here is phenomenological in its current form, it can be converted into a predictive outcome model via experimental measurement of the model parameters. Here we give an overview of an experimentally formulated problem in cancer metastasis and propose how niche construction framework can be utilized and broadened to model it. Other life science disciplines, such as host-parasite coevolution, may also benefit from niche construction framework adaptation, to satisfy growing need for theoretical considerations of data collected by experimental biology.

Niche construction game cancer cells play.

PubMed

Bergman, Aviv; Gligorijevic, Bojana

2015-10-01

Niche construction concept was originally defined in evolutionary biology as the continuous interplay between natural selection via environmental conditions and the modification of these conditions by the organism itself. Processes unraveling during cancer metastasis include construction of niches, which cancer cells use towards more efficient survival, transport into new environments and preparation of the remote sites for their arrival. Many elegant experiments were done lately illustrating, for example, the premetastatic niche construction, but there is practically no mathematical modeling done which would apply the niche construction framework. To create models useful for understanding niche construction role in cancer progression, we argue that a) genetic, b) phenotypic and c) ecological levels are to be included. While the model proposed here is phenomenological in its current form, it can be converted into a predictive outcome model via experimental measurement of the model parameters. Here we give an overview of an experimentally formulated problem in cancer metastasis and propose how niche construction framework can be utilized and broadened to model it. Other life science disciplines, such as host-parasite coevolution, may also benefit from niche construction framework adaptation, to satisfy growing need for theoretical considerations of data collected by experimental biology.

Decay {B to K^ast(to Kπ)ℓ+ ℓ-} in Covariant Quark Model

NASA Astrophysics Data System (ADS)

Dubnička, S.; Dubničková, A. Z.; Habyl, N.; Ivanov, M. A.; Liptaj, A.; Nurbakova, G. S.

2016-03-01

Our article is devoted to the study of the rare {B to K^ast ℓ^+ℓ^-} decay where {ℓ=e,μ,τ}. We compute the relevant form factors in the framework of the covariant quark model with infrared confinement in the full kinematical momentum transfer region. The calculated form factors are used to evaluate branching fractions and polarization observables in the cascade decay {B to K^ast(to Kπ)ℓ^+ℓ^-}. We compare the obtained results with available experimental data and the results from other theoretical approaches.

An Approach to a Comprehensive Test Framework for Analysis and Evaluation of Text Line Segmentation Algorithms

PubMed Central

Brodic, Darko; Milivojevic, Dragan R.; Milivojevic, Zoran N.

2011-01-01

The paper introduces a testing framework for the evaluation and validation of text line segmentation algorithms. Text line segmentation represents the key action for correct optical character recognition. Many of the tests for the evaluation of text line segmentation algorithms deal with text databases as reference templates. Because of the mismatch, the reliable testing framework is required. Hence, a new approach to a comprehensive experimental framework for the evaluation of text line segmentation algorithms is proposed. It consists of synthetic multi-like text samples and real handwritten text as well. Although the tests are mutually independent, the results are cross-linked. The proposed method can be used for different types of scripts and languages. Furthermore, two different procedures for the evaluation of algorithm efficiency based on the obtained error type classification are proposed. The first is based on the segmentation line error description, while the second one incorporates well-known signal detection theory. Each of them has different capabilities and convenience, but they can be used as supplements to make the evaluation process efficient. Overall the proposed procedure based on the segmentation line error description has some advantages, characterized by five measures that describe measurement procedures. PMID:22164106

Large-scale DNA Barcode Library Generation for Biomolecule Identification in High-throughput Screens.

PubMed

Lyons, Eli; Sheridan, Paul; Tremmel, Georg; Miyano, Satoru; Sugano, Sumio

2017-10-24

High-throughput screens allow for the identification of specific biomolecules with characteristics of interest. In barcoded screens, DNA barcodes are linked to target biomolecules in a manner allowing for the target molecules making up a library to be identified by sequencing the DNA barcodes using Next Generation Sequencing. To be useful in experimental settings, the DNA barcodes in a library must satisfy certain constraints related to GC content, homopolymer length, Hamming distance, and blacklisted subsequences. Here we report a novel framework to quickly generate large-scale libraries of DNA barcodes for use in high-throughput screens. We show that our framework dramatically reduces the computation time required to generate large-scale DNA barcode libraries, compared with a naїve approach to DNA barcode library generation. As a proof of concept, we demonstrate that our framework is able to generate a library consisting of one million DNA barcodes for use in a fragment antibody phage display screening experiment. We also report generating a general purpose one billion DNA barcode library, the largest such library yet reported in literature. Our results demonstrate the value of our novel large-scale DNA barcode library generation framework for use in high-throughput screening applications.

An effective framework for finding similar cases of dengue from audio and text data using domain thesaurus and case base reasoning

NASA Astrophysics Data System (ADS)

Sandhu, Rajinder; Kaur, Jaspreet; Thapar, Vivek

2018-02-01

Dengue, also known as break-bone fever, is a tropical disease transmitted by mosquitoes. If the similarity between dengue infected users can be identified, it can help government's health agencies to manage the outbreak more effectively. To find similarity between cases affected by Dengue, user's personal and health information are the two fundamental requirements. Identification of similar symptoms, causes, effects, predictions and treatment procedures, is important. In this paper, an effective framework is proposed which finds similar patients suffering from dengue using keyword aware domain thesaurus and case base reasoning method. This paper focuses on the use of ontology dependent domain thesaurus technique to extract relevant keywords and then build cases with the help of case base reasoning method. Similar cases can be shared with users, nearby hospitals and health organizations to manage the problem more adequately. Two million case bases were generated to test the proposed similarity method. Experimental evaluations of proposed framework resulted in high accuracy and low error rate for finding similar cases of dengue as compared to UPCC and IPCC algorithms. The framework developed in this paper is for dengue but can easily be extended to other domains also.

Preparation of alumina-hercynite nano-spinel via one-step thermal conversion of Fe-doped metal-organic framework MIL-53(Al)

NASA Astrophysics Data System (ADS)

Chen, Shuyi; Lu, Huigong; Wu, Yi-nan; Gu, Yifan; Li, Fengting; Morlay, Catherine

2016-09-01

Alumina-hercynite nano-spinel powders were prepared via one-step pyrolysis of iron-acetylacetone-doped Al-based metal-organic framework (MOF), i.e., MIL-53(Al). Organic ferric source, iron acetylacetone, was incorporated in situ into the framework of MIL-53(Al) during the solvothermal synthesis process. Under high-temperature pyrolysis, alumina derived from the MIL-53(Al) matrix and ferric oxides originated from the decomposition of organic ferric precursor in the framework were thermally converted into hercynite (FeAl2O4). The prepared samples were characterized using transmission electron microscopy, X-ray diffraction, N2 sorption, thermogravimetry, Raman spectroscopy and X-ray photoelectron spectroscopy. The final products were identified to be composed of alumina, hercynite and trace amounts of carbon depending on pyrolysis temperature. The experimental results showed that hercynite phase can be obtained and stabilized at low temperatures between 900 and 1100 °C under inert atmosphere. The final products were composed of nano-sized particles with an average size below 100 nm of individual crystal and specific surface areas of 18-49 m2 g-1.

The influence of precipitation kinetics on trace element partitioning between solid and liquid solutions: A coupled fluid dynamics/thermodynamics framework to predict distribution coefficients

NASA Astrophysics Data System (ADS)

Kavner, A.

2017-12-01

In a multicomponent multiphase geochemical system undergoing a chemical reaction such as precipitation and/or dissolution, the partitioning of species between phases is determined by a combination of thermodynamic properties and transport processes. The interpretation of the observed distribution of trace elements requires models integrating coupled chemistry and mechanical transport. Here, a framework is presented that predicts the kinetic effects on the distribution of species between two reacting phases. Based on a perturbation theory combining Navier-Stokes fluid flow and chemical reactivity, the framework predicts rate-dependent partition coefficients in a variety of different systems. We present the theoretical framework, with applications to two systems: 1. species- and isotope-dependent Soret diffusion of species in a multicomponent silicate melt subjected to a temperature gradient, and 2. Elemental partitioning and isotope fractionation during precipitation of a multicomponent solid from a multicomponent liquid phase. Predictions will be compared with results from experimental studies. The approach has applications for understanding chemical exchange in at boundary layers such as the Earth's surface magmatic systems and at the core/mantle boundary.

Finger vein recognition based on the hyperinformation feature

NASA Astrophysics Data System (ADS)

Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Yang, Lu

2014-01-01

The finger vein is a promising biometric pattern for personal identification due to its advantages over other existing biometrics. In finger vein recognition, feature extraction is a critical step, and many feature extraction methods have been proposed to extract the gray, texture, or shape of the finger vein. We treat them as low-level features and present a high-level feature extraction framework. Under this framework, base attribute is first defined to represent the characteristics of a certain subcategory of a subject. Then, for an image, the correlation coefficient is used for constructing the high-level feature, which reflects the correlation between this image and all base attributes. Since the high-level feature can reveal characteristics of more subcategories and contain more discriminative information, we call it hyperinformation feature (HIF). Compared with low-level features, which only represent the characteristics of one subcategory, HIF is more powerful and robust. In order to demonstrate the potential of the proposed framework, we provide a case study to extract HIF. We conduct comprehensive experiments to show the generality of the proposed framework and the efficiency of HIF on our databases, respectively. Experimental results show that HIF significantly outperforms the low-level features.

An approach to a comprehensive test framework for analysis and evaluation of text line segmentation algorithms.

PubMed

Brodic, Darko; Milivojevic, Dragan R; Milivojevic, Zoran N

2011-01-01

The paper introduces a testing framework for the evaluation and validation of text line segmentation algorithms. Text line segmentation represents the key action for correct optical character recognition. Many of the tests for the evaluation of text line segmentation algorithms deal with text databases as reference templates. Because of the mismatch, the reliable testing framework is required. Hence, a new approach to a comprehensive experimental framework for the evaluation of text line segmentation algorithms is proposed. It consists of synthetic multi-like text samples and real handwritten text as well. Although the tests are mutually independent, the results are cross-linked. The proposed method can be used for different types of scripts and languages. Furthermore, two different procedures for the evaluation of algorithm efficiency based on the obtained error type classification are proposed. The first is based on the segmentation line error description, while the second one incorporates well-known signal detection theory. Each of them has different capabilities and convenience, but they can be used as supplements to make the evaluation process efficient. Overall the proposed procedure based on the segmentation line error description has some advantages, characterized by five measures that describe measurement procedures.

Compressed sensing for energy-efficient wireless telemonitoring of noninvasive fetal ECG via block sparse Bayesian learning.

PubMed

Zhang, Zhilin; Jung, Tzyy-Ping; Makeig, Scott; Rao, Bhaskar D

2013-02-01

Fetal ECG (FECG) telemonitoring is an important branch in telemedicine. The design of a telemonitoring system via a wireless body area network with low energy consumption for ambulatory use is highly desirable. As an emerging technique, compressed sensing (CS) shows great promise in compressing/reconstructing data with low energy consumption. However, due to some specific characteristics of raw FECG recordings such as nonsparsity and strong noise contamination, current CS algorithms generally fail in this application. This paper proposes to use the block sparse Bayesian learning framework to compress/reconstruct nonsparse raw FECG recordings. Experimental results show that the framework can reconstruct the raw recordings with high quality. Especially, the reconstruction does not destroy the interdependence relation among the multichannel recordings. This ensures that the independent component analysis decomposition of the reconstructed recordings has high fidelity. Furthermore, the framework allows the use of a sparse binary sensing matrix with much fewer nonzero entries to compress recordings. Particularly, each column of the matrix can contain only two nonzero entries. This shows that the framework, compared to other algorithms such as current CS algorithms and wavelet algorithms, can greatly reduce code execution in CPU in the data compression stage.

Modeling of ultrasonic processes utilizing a generic software framework

NASA Astrophysics Data System (ADS)

Bruns, P.; Twiefel, J.; Wallaschek, J.

2017-06-01

Modeling of ultrasonic processes is typically characterized by a high degree of complexity. Different domains and size scales must be regarded, so that it is rather difficult to build up a single detailed overall model. Developing partial models is a common approach to overcome this difficulty. In this paper a generic but simple software framework is presented which allows to coupe arbitrary partial models by slave modules with well-defined interfaces and a master module for coordination. Two examples are given to present the developed framework. The first one is the parameterization of a load model for ultrasonically-induced cavitation. The piezoelectric oscillator, its mounting, and the process load are described individually by partial models. These partial models then are coupled using the framework. The load model is composed of spring-damper-elements which are parameterized by experimental results. In the second example, the ideal mounting position for an oscillator utilized in ultrasonic assisted machining of stone is determined. Partial models for the ultrasonic oscillator, its mounting, the simplified contact process, and the workpiece’s material characteristics are presented. For both applications input and output variables are defined to meet the requirements of the framework’s interface.

A unified framework for image retrieval using keyword and visual features.

PubMed

Jing, Feng; Li, Mingling; Zhang, Hong-Jiang; Zhang, Bo

2005-07-01

In this paper, a unified image retrieval framework based on both keyword annotations and visual features is proposed. In this framework, a set of statistical models are built based on visual features of a small set of manually labeled images to represent semantic concepts and used to propagate keywords to other unlabeled images. These models are updated periodically when more images implicitly labeled by users become available through relevance feedback. In this sense, the keyword models serve the function of accumulation and memorization of knowledge learned from user-provided relevance feedback. Furthermore, two sets of effective and efficient similarity measures and relevance feedback schemes are proposed for query by keyword scenario and query by image example scenario, respectively. Keyword models are combined with visual features in these schemes. In particular, a new, entropy-based active learning strategy is introduced to improve the efficiency of relevance feedback for query by keyword. Furthermore, a new algorithm is proposed to estimate the keyword features of the search concept for query by image example. It is shown to be more appropriate than two existing relevance feedback algorithms. Experimental results demonstrate the effectiveness of the proposed framework.

A compressive sensing based secure watermark detection and privacy preserving storage framework.

PubMed

Qia Wang; Wenjun Zeng; Jun Tian

2014-03-01

Privacy is a critical issue when the data owners outsource data storage or processing to a third party computing service, such as the cloud. In this paper, we identify a cloud computing application scenario that requires simultaneously performing secure watermark detection and privacy preserving multimedia data storage. We then propose a compressive sensing (CS)-based framework using secure multiparty computation (MPC) protocols to address such a requirement. In our framework, the multimedia data and secret watermark pattern are presented to the cloud for secure watermark detection in a CS domain to protect the privacy. During CS transformation, the privacy of the CS matrix and the watermark pattern is protected by the MPC protocols under the semi-honest security model. We derive the expected watermark detection performance in the CS domain, given the target image, watermark pattern, and the size of the CS matrix (but without the CS matrix itself). The correctness of the derived performance has been validated by our experiments. Our theoretical analysis and experimental results show that secure watermark detection in the CS domain is feasible. Our framework can also be extended to other collaborative secure signal processing and data-mining applications in the cloud.

Intraoperative Image-based Multiview 2D/3D Registration for Image-Guided Orthopaedic Surgery: Incorporation of Fiducial-Based C-Arm Tracking and GPU-Acceleration

PubMed Central

Armand, Mehran; Armiger, Robert S.; Kutzer, Michael D.; Basafa, Ehsan; Kazanzides, Peter; Taylor, Russell H.

2012-01-01

Intraoperative patient registration may significantly affect the outcome of image-guided surgery (IGS). Image-based registration approaches have several advantages over the currently dominant point-based direct contact methods and are used in some industry solutions in image-guided radiation therapy with fixed X-ray gantries. However, technical challenges including geometric calibration and computational cost have precluded their use with mobile C-arms for IGS. We propose a 2D/3D registration framework for intraoperative patient registration using a conventional mobile X-ray imager combining fiducial-based C-arm tracking and graphics processing unit (GPU)-acceleration. The two-stage framework 1) acquires X-ray images and estimates relative pose between the images using a custom-made in-image fiducial, and 2) estimates the patient pose using intensity-based 2D/3D registration. Experimental validations using a publicly available gold standard dataset, a plastic bone phantom and cadaveric specimens have been conducted. The mean target registration error (mTRE) was 0.34 ± 0.04 mm (success rate: 100%, registration time: 14.2 s) for the phantom with two images 90° apart, and 0.99 ± 0.41 mm (81%, 16.3 s) for the cadaveric specimen with images 58.5° apart. The experimental results showed the feasibility of the proposed registration framework as a practical alternative for IGS routines. PMID:22113773

Functional validation and comparison framework for EIT lung imaging.

PubMed

Grychtol, Bartłomiej; Elke, Gunnar; Meybohm, Patrick; Weiler, Norbert; Frerichs, Inéz; Adler, Andy

2014-01-01

Electrical impedance tomography (EIT) is an emerging clinical tool for monitoring ventilation distribution in mechanically ventilated patients, for which many image reconstruction algorithms have been suggested. We propose an experimental framework to assess such algorithms with respect to their ability to correctly represent well-defined physiological changes. We defined a set of clinically relevant ventilation conditions and induced them experimentally in 8 pigs by controlling three ventilator settings (tidal volume, positive end-expiratory pressure and the fraction of inspired oxygen). In this way, large and discrete shifts in global and regional lung air content were elicited. We use the framework to compare twelve 2D EIT reconstruction algorithms, including backprojection (the original and still most frequently used algorithm), GREIT (a more recent consensus algorithm for lung imaging), truncated singular value decomposition (TSVD), several variants of the one-step Gauss-Newton approach and two iterative algorithms. We consider the effects of using a 3D finite element model, assuming non-uniform background conductivity, noise modeling, reconstructing for electrode movement, total variation (TV) reconstruction, robust error norms, smoothing priors, and using difference vs. normalized difference data. Our results indicate that, while variation in appearance of images reconstructed from the same data is not negligible, clinically relevant parameters do not vary considerably among the advanced algorithms. Among the analysed algorithms, several advanced algorithms perform well, while some others are significantly worse. Given its vintage and ad-hoc formulation backprojection works surprisingly well, supporting the validity of previous studies in lung EIT.

Annotating images by mining image search results.

PubMed

Wang, Xin-Jing; Zhang, Lei; Li, Xirong; Ma, Wei-Ying

2008-11-01

Although it has been studied for years by the computer vision and machine learning communities, image annotation is still far from practical. In this paper, we propose a novel attempt at model-free image annotation, which is a data-driven approach that annotates images by mining their search results. Some 2.4 million images with their surrounding text are collected from a few photo forums to support this approach. The entire process is formulated in a divide-and-conquer framework where a query keyword is provided along with the uncaptioned image to improve both the effectiveness and efficiency. This is helpful when the collected data set is not dense everywhere. In this sense, our approach contains three steps: 1) the search process to discover visually and semantically similar search results, 2) the mining process to identify salient terms from textual descriptions of the search results, and 3) the annotation rejection process to filter out noisy terms yielded by Step 2. To ensure real-time annotation, two key techniques are leveraged-one is to map the high-dimensional image visual features into hash codes, the other is to implement it as a distributed system, of which the search and mining processes are provided as Web services. As a typical result, the entire process finishes in less than 1 second. Since no training data set is required, our approach enables annotating with unlimited vocabulary and is highly scalable and robust to outliers. Experimental results on both real Web images and a benchmark image data set show the effectiveness and efficiency of the proposed algorithm. It is also worth noting that, although the entire approach is illustrated within the divide-and conquer framework, a query keyword is not crucial to our current implementation. We provide experimental results to prove this.

Pre-service Teacher Extraneous Cognitive Load in the Pedagogical Content and Knowledge of Solar System Course

NASA Astrophysics Data System (ADS)

Permana, I.; Redjeki, S.; Hamidah, I.; Safitri, N.

2017-09-01

This study reported the student’s Extraneous Cognitive Load (ECL) in the Pedagogical Content and Knowledge of solar system Course. Participants in the study were 31 pre-service elementary school teachers from the university in Bogor Indonesia. The data collected from ECL were obtained using a Likert 4-scale questionnaire and interview. After taking lectures, we asked for some mental effort from pre-service elementary school teachers to attend courses in order to assess the ECL. The courses include 3 topics and they were non-experimental worksheet, developing experimental worksheet using Vee Diagram framework, and analysis for curriculum by grade IV, V and VI. Results of the data analysis showed that the course strategy resulted by ECL was relatively low. The ECL increased in the course of curriculum analysis due to material complexity.

Competition between monomeric and dimeric crystals in schematic models for globular proteins.

PubMed

Fusco, Diana; Charbonneau, Patrick

2014-07-17

Advances in experimental techniques and in theoretical models have improved our understanding of protein crystallization. However, they have also left open questions regarding the protein phase behavior and self-assembly kinetics, such as why (nearly) identical crystallization conditions can sometimes result in the formation of different crystal forms. Here, we develop a patchy particle model with competing sets of patches that provides a microscopic explanation of this phenomenon. We identify different regimes in which one or two crystal forms can coexist with a low-density fluid. Using analytical approximations, we extend our findings to different crystal phases, providing a general framework for treating protein crystallization when multiple crystal forms compete. Our results also suggest different experimental routes for targeting a specific crystal form, and for reducing the dynamical competition between the two forms, thus facilitating protein crystal assembly.

Principal Stratification as a Framework for Investigating Mediational Processes in Experimental Settings

ERIC Educational Resources Information Center

Page, Lindsay C.

2012-01-01

Experimental evaluations are increasingly common in the U.S. educational policy-research context. Often, in investigations of multifaceted interventions, researchers and policymakers alike are interested in not only "whether" a given intervention impacted an outcome but also "why". What "features" of the intervention…

Alternative Approaches to Introductory Economics.

ERIC Educational Resources Information Center

Bonello, Frank J.; And Others

This document examines the educational output of three alternative approaches to introductory macroeconomics at the University of Notre Dame. The framework for evaluation consists of the cognitive and affective tradeoffs entailed by using a new experimental course as opposed to two more traditional courses. The experimental course is a freshman…

Study of the Inorganic Substitution in a Functionalized UiO-66 Metal-Organic Framework

NASA Astrophysics Data System (ADS)

Yasin, Alhassan Salman

Metal-Organic Frameworks (MOFs) have received considerable attention and fast development in the past few years. These materials have demonstrated a wide range of applications due to their porosity, tailorability of optical properties, and chemical selectivity. This report catalogs common MOF designs based on application and diversity in various fields, as well as conduct an in-depth study of inorganic substitution in a functionalized MOF. This study investigates the band gap modulation in response to inorganic ion substitution within a thermally stable UiO-66 Metal-Organic Framework (MOF). A combination of density functional theory (DFT) predictions in conjunction with experimental predictions were used to map out the complete composition space for three inorganic ions (Zr, Hf, Ti) and three functional groups. The three functional groups include an amino group (NH2), a nitro group (NO2), and a hydrogenated case (H). The smallest determined band gap was for a partially substituted UiO-66(Ti5Zr1)-NH2 resulting in 2.60eV. Theoretical findings sup-port that Ti can be fully substituted within the lattice resulting in a predicted band gap as low as 1.62(2.77)eV. Band gap modulation was reasoned to be a result of a mid gap state introduced through the amino functionalization and HOMO shifting as a result of increased binding of the Ti-O-C bonds.

Using the Bifocal Modeling Framework to Resolve "Discrepant Events" between Physical Experiments and Virtual Models in Biology

ERIC Educational Resources Information Center

Blikstein, Paulo; Fuhrmann, Tamar; Salehi, Shima

2016-01-01

In this paper, we investigate an approach to supporting students' learning in science through a combination of physical experimentation and virtual modeling. We present a study that utilizes a scientific inquiry framework, which we call "bifocal modeling," to link student-designed experiments and computer models in real time. In this…

Electron collisions with small esters: A joint experimental-theoretical investigation

NASA Astrophysics Data System (ADS)

de Souza, G. L. C.; da Silva, L. A.; de Sousa, W. J. C.; Sugohara, R. T.; Iga, I.; dos Santos, A. S.; Machado, L. E.; Homem, M. G. P.; Brescansin, L. M.; Lucchese, R. R.; Lee, M.-T.

2016-03-01

A theoretical and experimental investigation on elastic electron scattering by two small esters, namely, methyl formate and ethyl acetate, is reported. Experimental differential, integral, and momentum-transfer cross sections are given in the 30-1000 eV and 10∘-120∘ ranges. The relative-flow technique was used to determine such quantities. Particularly for methyl formate, a theoretical study was also carried out in the 1-500 eV range. A complex optical potential derived from a Hartree-Fock molecular wave function was used to represent the collision dynamics, whereas the Padé approximation was used to solve the scattering equations. In addition, calculations based on the framework of the independent-atom model (IAM) were also performed for both targets. In general, there is good agreement between our experimental data and the present theoretical results calculated using the Padé approximation. The theoretical results using the IAM also agree well with the experimental data at 200 eV and above. Moreover, for methyl formate, our calculations reveal a 2A'' (π*) resonance at about 3.0 eV and a σ*-type resonance centered at about 8.0 eV in the 2A' scattering channel. The π* resonance is also seen in other targets containing a carbonyl group.

Performance metrics for Inertial Confinement Fusion implosions: aspects of the technical framework for measuring progress in the National Ignition Campaign

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

Spears, B K; Glenzer, S; Edwards, M J

The National Ignition Campaign (NIC) uses non-igniting 'THD' capsules to study and optimize the hydrodynamic assembly of the fuel without burn. These capsules are designed to simultaneously reduce DT neutron yield and to maintain hydrodynamic similarity with the DT ignition capsule. We will discuss nominal THD performance and the associated experimental observables. We will show the results of large ensembles of numerical simulations of THD and DT implosions and their simulated diagnostic outputs. These simulations cover a broad range of both nominal and off nominal implosions. We will focus on the development of an experimental implosion performance metric called themore » experimental ignition threshold factor (ITFX). We will discuss the relationship between ITFX and other integrated performance metrics, including the ignition threshold factor (ITF), the generalized Lawson criterion (GLC), and the hot spot pressure (HSP). We will then consider the experimental results of the recent NIC THD campaign. We will show that we can observe the key quantities for producing a measured ITFX and for inferring the other performance metrics. We will discuss trends in the experimental data, improvement in ITFX, and briefly the upcoming tuning campaign aimed at taking the next steps in performance improvement on the path to ignition on NIF.« less

Performance metrics for inertial confinement fusion implosions: Aspects of the technical framework for measuring progress in the National Ignition Campaign

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

Spears, Brian K.; Glenzer, S.; Edwards, M. J.

The National Ignition Campaign (NIC) uses non-igniting 'tritium hydrogen deuterium (THD)' capsules to study and optimize the hydrodynamic assembly of the fuel without burn. These capsules are designed to simultaneously reduce DT neutron yield and to maintain hydrodynamic similarity with the DT ignition capsule. We will discuss nominal THD performance and the associated experimental observables. We will show the results of large ensembles of numerical simulations of THD and DT implosions and their simulated diagnostic outputs. These simulations cover a broad range of both nominal and off-nominal implosions. We will focus on the development of an experimental implosion performance metricmore » called the experimental ignition threshold factor (ITFX). We will discuss the relationship between ITFX and other integrated performance metrics, including the ignition threshold factor (ITF), the generalized Lawson criterion (GLC), and the hot spot pressure (HSP). We will then consider the experimental results of the recent NIC THD campaign. We will show that we can observe the key quantities for producing a measured ITFX and for inferring the other performance metrics. We will discuss trends in the experimental data, improvement in ITFX, and briefly the upcoming tuning campaign aimed at taking the next steps in performance improvement on the path to ignition on NIF.« less

Experimental evolution and the dynamics of genomic mutation rate modifiers.

PubMed

Raynes, Y; Sniegowski, P D

2014-11-01

Because genes that affect mutation rates are themselves subject to mutation, mutation rates can be influenced by natural selection and other evolutionary forces. The population genetics of mutation rate modifier alleles has been a subject of theoretical interest for many decades. Here, we review experimental contributions to our understanding of mutation rate modifier dynamics. Numerous evolution experiments have shown that mutator alleles (modifiers that elevate the genomic mutation rate) can readily rise to high frequencies via genetic hitchhiking in non-recombining microbial populations. Whereas these results certainly provide an explanatory framework for observations of sporadically high mutation rates in pathogenic microbes and in cancer lineages, it is nonetheless true that most natural populations have very low mutation rates. This raises the interesting question of how mutator hitchhiking is suppressed or its phenotypic effect reversed in natural populations. Very little experimental work has addressed this question; with this in mind, we identify some promising areas for future experimental investigation.

Recognition without identification, erroneous familiarity, and déjà vu.

PubMed

O'Connor, Akira R; Moulin, Chris J A

2010-06-01

Déjà vu is characterized by the recognition of a situation concurrent with the awareness that this recognition is inappropriate. Although forms of déjà vu resolve in favor of the inappropriate recognition and therefore have behavioral consequences, typical déjà vu experiences resolve in favor of the awareness that the sensation of recognition is inappropriate. The resultant lack of behavioral modification associated with typical déjà vu means that clinicians and experimenters rely heavily on self-report when observing the experience. In this review, we focus on recent déjà vu research. We consider issues facing neuropsychological, neuroscientific, and cognitive experimental frameworks attempting to explore and experimentally generate the experience. In doing this, we suggest the need for more experimentation and a more cautious interpretation of research findings, particularly as many techniques being used to explore déjà vu are in the early stages of development.

Carbon nanotube thin film strain sensors: comparison between experimental tests and numerical simulations

NASA Astrophysics Data System (ADS)

Lee, Bo Mi; Loh, Kenneth J.

2017-04-01

Carbon nanotubes can be randomly deposited in polymer thin film matrices to form nanocomposite strain sensors. However, a computational framework that enables the direct design of these nanocomposite thin films is still lacking. The objective of this study is to derive an experimentally validated and two-dimensional numerical model of carbon nanotube-based thin film strain sensors. This study consisted of two parts. First, multi-walled carbon nanotube (MWCNT)-Pluronic strain sensors were fabricated using vacuum filtration, and their physical, electrical, and electromechanical properties were evaluated. Second, scanning electron microscope images of the films were used for identifying topological features of the percolated MWCNT network, where the information obtained was then utilized for developing the numerical model. Validation of the numerical model was achieved by ensuring that the area ratios (of MWCNTs relative to the polymer matrix) were equivalent for both the experimental and modeled cases. Strain sensing behavior of the percolation-based model was simulated and then compared to experimental test results.

PREMIX: PRivacy-preserving EstiMation of Individual admiXture.

PubMed

Chen, Feng; Dow, Michelle; Ding, Sijie; Lu, Yao; Jiang, Xiaoqian; Tang, Hua; Wang, Shuang

2016-01-01

In this paper we proposed a framework: PRivacy-preserving EstiMation of Individual admiXture (PREMIX) using Intel software guard extensions (SGX). SGX is a suite of software and hardware architectures to enable efficient and secure computation over confidential data. PREMIX enables multiple sites to securely collaborate on estimating individual admixture within a secure enclave inside Intel SGX. We implemented a feature selection module to identify most discriminative Single Nucleotide Polymorphism (SNP) based on informativeness and an Expectation Maximization (EM)-based Maximum Likelihood estimator to identify the individual admixture. Experimental results based on both simulation and 1000 genome data demonstrated the efficiency and accuracy of the proposed framework. PREMIX ensures a high level of security as all operations on sensitive genomic data are conducted within a secure enclave using SGX.

Plasmonic nanopatch array with integrated metal–organic framework for enhanced infrared absorption gas sensing

DOE PAGES

Chong, Xinyuan; Kim, Ki-joong; Zhang, Yujing; ...

2017-06-06

In this letter, we present a nanophotonic device consisting of plasmonic nanopatch array (NPA) with integrated metal–organic framework (MOF) for enhanced infrared absorption gas sensing. By designing a gold NPA on a sapphire substrate, we are able to achieve enhanced optical field that spatially overlaps with the MOF layer, which can adsorb carbon dioxide (CO 2) with high capacity. Additionally, experimental results show that this hybrid plasmonic–MOF device can effectively increase the infrared absorption path of on-chip gas sensors by more than 1100-fold. Lastly, the demonstration of infrared absorption spectroscopy of CO 2 using the hybrid plasmonic–MOF device proves amore » promising strategy for future on-chip gas sensing with ultra-compact size.« less

Hybrid Intrusion Forecasting Framework for Early Warning System

NASA Astrophysics Data System (ADS)

Kim, Sehun; Shin, Seong-Jun; Kim, Hyunwoo; Kwon, Ki Hoon; Han, Younggoo

Recently, cyber attacks have become a serious hindrance to the stability of Internet. These attacks exploit interconnectivity of networks, propagate in an instant, and have become more sophisticated and evolutionary. Traditional Internet security systems such as firewalls, IDS and IPS are limited in terms of detecting recent cyber attacks in advance as these systems respond to Internet attacks only after the attacks inflict serious damage. In this paper, we propose a hybrid intrusion forecasting system framework for an early warning system. The proposed system utilizes three types of forecasting methods: time-series analysis, probabilistic modeling, and data mining method. By combining these methods, it is possible to take advantage of the forecasting technique of each while overcoming their drawbacks. Experimental results show that the hybrid intrusion forecasting method outperforms each of three forecasting methods.

Plant Species Identification by Bi-channel Deep Convolutional Networks

NASA Astrophysics Data System (ADS)

He, Guiqing; Xia, Zhaoqiang; Zhang, Qiqi; Zhang, Haixi; Fan, Jianping

2018-04-01

Plant species identification achieves much attention recently as it has potential application in the environmental protection and human life. Although deep learning techniques can be directly applied for plant species identification, it still needs to be designed for this specific task to obtain the state-of-art performance. In this paper, a bi-channel deep learning framework is developed for identifying plant species. In the framework, two different sub-networks are fine-tuned over their pretrained models respectively. And then a stacking layer is used to fuse the output of two different sub-networks. We construct a plant dataset of Orchidaceae family for algorithm evaluation. Our experimental results have demonstrated that our bi-channel deep network can achieve very competitive performance on accuracy rates compared to the existing deep learning algorithm.

Criticality and Connectivity in Macromolecular Charge Complexation

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

Qin, Jian; de Pablo, Juan J.

We examine the role of molecular connectivity and architecture on the complexation of ionic macromolecules (polyelectrolytes) of finite size. A unified framework is developed and applied to evaluate the electrostatic correlation free energy for point-like, rod-like, and coil-like molecules. That framework is generalized to molecules of variable fractal dimensions, including dendrimers. Analytical expressions for the free energy, correlation length, and osmotic pressure are derived, thereby enabling consideration of the effects of charge connectivity, fractal dimension, and backbone stiffness on the complexation behavior of a wide range of polyelectrolytes. Results are presented for regions in the immediate vicinity of the criticalmore » region and far from it. A transparent and explicit expression for the coexistence curve is derived in order to facilitate analysis of experimentally observed phase diagrams.« less

Plasmonic nanopatch array with integrated metal–organic framework for enhanced infrared absorption gas sensing

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

Chong, Xinyuan; Kim, Ki-joong; Zhang, Yujing

In this letter, we present a nanophotonic device consisting of plasmonic nanopatch array (NPA) with integrated metal–organic framework (MOF) for enhanced infrared absorption gas sensing. By designing a gold NPA on a sapphire substrate, we are able to achieve enhanced optical field that spatially overlaps with the MOF layer, which can adsorb carbon dioxide (CO 2) with high capacity. Additionally, experimental results show that this hybrid plasmonic–MOF device can effectively increase the infrared absorption path of on-chip gas sensors by more than 1100-fold. Lastly, the demonstration of infrared absorption spectroscopy of CO 2 using the hybrid plasmonic–MOF device proves amore » promising strategy for future on-chip gas sensing with ultra-compact size.« less

Does the Superior Colliculus Control Perceptual Sensitivity or Choice Bias during Attention? Evidence from a Multialternative Decision Framework

PubMed Central

Steinmetz, Nicholas A.; Moore, Tirin; Knudsen, Eric I.

2017-01-01

Distinct networks in the forebrain and the midbrain coordinate to control spatial attention. The critical involvement of the superior colliculus (SC)—the central structure in the midbrain network—in visuospatial attention has been shown by four seminal, published studies in monkeys (Macaca mulatta) performing multialternative tasks. However, due to the lack of a mechanistic framework for interpreting behavioral data in such tasks, the nature of the SC's contribution to attention remains unclear. Here we present and validate a novel decision framework for analyzing behavioral data in multialternative attention tasks. We apply this framework to re-examine the behavioral evidence from these published studies. Our model is a multidimensional extension to signal detection theory that distinguishes between two major classes of attentional mechanisms: those that alter the quality of sensory information or “sensitivity,” and those that alter the selective gating of sensory information or “choice bias.” Model-based simulations and model-based analyses of data from these published studies revealed a converging pattern of results that indicated that choice-bias changes, rather than sensitivity changes, were the primary outcome of SC manipulation. Our results suggest that the SC contributes to attentional performance predominantly by generating a spatial choice bias for stimuli at a selected location, and that this bias operates downstream of forebrain mechanisms that enhance sensitivity. The findings lead to a testable mechanistic framework of how the midbrain and forebrain networks interact to control spatial attention. SIGNIFICANCE STATEMENT Attention involves the selection of the most relevant information for differential sensory processing and decision making. While the mechanisms by which attention alters sensory encoding (sensitivity control) are well studied, the mechanisms by which attention alters decisional weighting of sensory evidence (choice-bias control) are poorly understood. Here, we introduce a model of multialternative decision making that distinguishes bias from sensitivity effects in attention tasks. With our model, we simulate experimental data from four seminal studies that microstimulated or inactivated a key attention-related midbrain structure, the superior colliculus (SC). We demonstrate that the experimental effects of SC manipulation are entirely consistent with the SC controlling attention by changing choice bias, thereby shedding new light on how the brain mediates attention. PMID:28100734

Does the Superior Colliculus Control Perceptual Sensitivity or Choice Bias during Attention? Evidence from a Multialternative Decision Framework.

PubMed

Sridharan, Devarajan; Steinmetz, Nicholas A; Moore, Tirin; Knudsen, Eric I

2017-01-18

Distinct networks in the forebrain and the midbrain coordinate to control spatial attention. The critical involvement of the superior colliculus (SC)-the central structure in the midbrain network-in visuospatial attention has been shown by four seminal, published studies in monkeys (Macaca mulatta) performing multialternative tasks. However, due to the lack of a mechanistic framework for interpreting behavioral data in such tasks, the nature of the SC's contribution to attention remains unclear. Here we present and validate a novel decision framework for analyzing behavioral data in multialternative attention tasks. We apply this framework to re-examine the behavioral evidence from these published studies. Our model is a multidimensional extension to signal detection theory that distinguishes between two major classes of attentional mechanisms: those that alter the quality of sensory information or "sensitivity," and those that alter the selective gating of sensory information or "choice bias." Model-based simulations and model-based analyses of data from these published studies revealed a converging pattern of results that indicated that choice-bias changes, rather than sensitivity changes, were the primary outcome of SC manipulation. Our results suggest that the SC contributes to attentional performance predominantly by generating a spatial choice bias for stimuli at a selected location, and that this bias operates downstream of forebrain mechanisms that enhance sensitivity. The findings lead to a testable mechanistic framework of how the midbrain and forebrain networks interact to control spatial attention. Attention involves the selection of the most relevant information for differential sensory processing and decision making. While the mechanisms by which attention alters sensory encoding (sensitivity control) are well studied, the mechanisms by which attention alters decisional weighting of sensory evidence (choice-bias control) are poorly understood. Here, we introduce a model of multialternative decision making that distinguishes bias from sensitivity effects in attention tasks. With our model, we simulate experimental data from four seminal studies that microstimulated or inactivated a key attention-related midbrain structure, the superior colliculus (SC). We demonstrate that the experimental effects of SC manipulation are entirely consistent with the SC controlling attention by changing choice bias, thereby shedding new light on how the brain mediates attention. Copyright © 2017 the authors 0270-6474/17/370480-32$15.00/0.

The operant-respondent distinction: Future directions

PubMed Central

Pear, Joseph J.; Eldridge, Gloria D.

1984-01-01

The operant-respondent distinction has provided a major organizing framework for the data generated through the experimental analysis of behavior. Problems have been encountered, however, in using it as an explanatory concept for such phenomena as avoidance and conditioned suppression. Data now exist that do not fit neatly into the framework. Moreover, the discovery of autoshaping has highlighted difficulties in isolating the two types of behavior and conditioning. Despite these problems, the operant-respondent framework remains the most successful paradigm currently available for organizing behavioral data. Research and theoretical efforts should therefore probably be directed to modifying the framework to account for disparate data. PMID:16812402

Understanding climate impacts on vegetation using a spatiotemporal non-linear Granger causality framework

NASA Astrophysics Data System (ADS)

Papagiannopoulou, Christina; Decubber, Stijn; Miralles, Diego; Demuzere, Matthias; Dorigo, Wouter; Verhoest, Niko; Waegeman, Willem

2017-04-01

Satellite data provide an abundance of information about crucial climatic and environmental variables. These data - consisting of global records, spanning up to 35 years and having the form of multivariate time series with different spatial and temporal resolutions - enable the study of key climate-vegetation interactions. Although methods which are based on correlations and linear models are typically used for this purpose, their assumptions for linearity about the climate-vegetation relationships are too simplistic. Therefore, we adopt a recently proposed non-linear Granger causality analysis [1], in which we incorporate spatial information, concatenating data from neighboring pixels and training a joint model on the combined data. Experimental results based on global data sets show that considering non-linear relationships leads to a higher explained variance of past vegetation dynamics, compared to simple linear models. Our approach consists of several steps. First, we compile an extensive database [1], which includes multiple data sets for land surface temperature, near-surface air temperature, surface radiation, precipitation, snow water equivalents and surface soil moisture. Based on this database, high-level features are constructed and considered as predictors in our machine-learning framework. These high-level features include (de-trended) seasonal anomalies, lagged variables, past cumulative variables, and extreme indices, all calculated based on the raw climatic data. Second, we apply a spatiotemporal non-linear Granger causality framework - in which the linear predictive model is substituted for a non-linear machine learning algorithm - in order to assess which of these predictor variables Granger-cause vegetation dynamics at each 1° pixel. We use the de-trended anomalies of Normalized Difference Vegetation Index (NDVI) to characterize vegetation, being the target variable of our framework. Experimental results indicate that climate strongly (Granger-)causes vegetation dynamics in most regions globally. More specifically, water availability is the most dominant vegetation driver, being the dominant vegetation driver in 54% of the vegetated surface. Furthermore, our results show that precipitation and soil moisture have prolonged impacts on vegetation in semiarid regions, with up to 10% of additional explained variance on the vegetation dynamics occurring three months later. Finally, hydro-climatic extremes seem to have a remarkable impact on vegetation, since they also explain up to 10% of additional variance of vegetation in certain regions despite their infrequent occurrence. References [1] Papagiannopoulou, C., Miralles, D. G., Verhoest, N. E. C., Dorigo, W. A., and Waegeman, W.: A non-linear Granger causality framework to investigate climate-vegetation dynamics, Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-266, in review, 2016.

Model-based reasoning in the physics laboratory: Framework and initial results

NASA Astrophysics Data System (ADS)

Zwickl, Benjamin M.; Hu, Dehui; Finkelstein, Noah; Lewandowski, H. J.

2015-12-01

[This paper is part of the Focused Collection on Upper Division Physics Courses.] We review and extend existing frameworks on modeling to develop a new framework that describes model-based reasoning in introductory and upper-division physics laboratories. Constructing and using models are core scientific practices that have gained significant attention within K-12 and higher education. Although modeling is a broadly applicable process, within physics education, it has been preferentially applied to the iterative development of broadly applicable principles (e.g., Newton's laws of motion in introductory mechanics). A significant feature of the new framework is that measurement tools (in addition to the physical system being studied) are subjected to the process of modeling. Think-aloud interviews were used to refine the framework and demonstrate its utility by documenting examples of model-based reasoning in the laboratory. When applied to the think-aloud interviews, the framework captures and differentiates students' model-based reasoning and helps identify areas of future research. The interviews showed how students productively applied similar facets of modeling to the physical system and measurement tools: construction, prediction, interpretation of data, identification of model limitations, and revision. Finally, we document students' challenges in explicitly articulating assumptions when constructing models of experimental systems and further challenges in model construction due to students' insufficient prior conceptual understanding. A modeling perspective reframes many of the seemingly arbitrary technical details of measurement tools and apparatus as an opportunity for authentic and engaging scientific sense making.

Towards a quantitative description of tunneling conductance of superconductors: Application to LiFeAs

DOE PAGES

Kreisel, A.; Nelson, R.; Berlijn, T.; ...

2016-12-27

Since the discovery of iron-based superconductors, a number of theories have been put forward to explain the qualitative origin of pairing, but there have been few attempts to make quantitative, material-specific comparisons to experimental results. The spin-fluctuation theory of electronic pairing, based on first-principles electronic structure calculations, makes predictions for the superconducting gap. Within the same framework, the surface wave functions may also be calculated, allowing, e.g., for detailed comparisons between theoretical results and measured scanning tunneling topographs and spectra. We present such a comparison between theory and experiment on the Fe-based superconductor LiFeAs. Our results for the homogeneous surfacemore » as well as impurity states are presented as a benchmark test of the theory. For the homogeneous system, we argue that the maxima of topographic image intensity may be located at positions above either the As or Li atoms, depending on tip height and the setpoint current of the measurement. We further report the experimental observation of transitions between As- and Li-registered lattices as functions of both tip height and setpoint bias, in agreement with this prediction. Next, we give a detailed comparison between the simulated scanning tunneling microscopy images of transition-metal defects with experiment. Finally, we discuss possible extensions of the current framework to obtain a theory with true predictive power for scanning tunneling microscopy in Fe-based systems.« less

Towards a quantitative description of tunneling conductance of superconductors: Application to LiFeAs

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

Kreisel, A.; Nelson, R.; Berlijn, T.

Since the discovery of iron-based superconductors, a number of theories have been put forward to explain the qualitative origin of pairing, but there have been few attempts to make quantitative, material-specific comparisons to experimental results. The spin-fluctuation theory of electronic pairing, based on first-principles electronic structure calculations, makes predictions for the superconducting gap. Within the same framework, the surface wave functions may also be calculated, allowing, e.g., for detailed comparisons between theoretical results and measured scanning tunneling topographs and spectra. We present such a comparison between theory and experiment on the Fe-based superconductor LiFeAs. Our results for the homogeneous surfacemore » as well as impurity states are presented as a benchmark test of the theory. For the homogeneous system, we argue that the maxima of topographic image intensity may be located at positions above either the As or Li atoms, depending on tip height and the setpoint current of the measurement. We further report the experimental observation of transitions between As- and Li-registered lattices as functions of both tip height and setpoint bias, in agreement with this prediction. Next, we give a detailed comparison between the simulated scanning tunneling microscopy images of transition-metal defects with experiment. Finally, we discuss possible extensions of the current framework to obtain a theory with true predictive power for scanning tunneling microscopy in Fe-based systems.« less

Understanding Collective Activities of People from Videos.

PubMed

Wongun Choi; Savarese, Silvio

2014-06-01

This paper presents a principled framework for analyzing collective activities at different levels of semantic granularity from videos. Our framework is capable of jointly tracking multiple individuals, recognizing activities performed by individuals in isolation (i.e., atomic activities such as walking or standing), recognizing the interactions between pairs of individuals (i.e., interaction activities) as well as understanding the activities of group of individuals (i.e., collective activities). A key property of our work is that it can coherently combine bottom-up information stemming from detections or fragments of tracks (or tracklets) with top-down evidence. Top-down evidence is provided by a newly proposed descriptor that captures the coherent behavior of groups of individuals in a spatial-temporal neighborhood of the sequence. Top-down evidence provides contextual information for establishing accurate associations between detections or tracklets across frames and, thus, for obtaining more robust tracking results. Bottom-up evidence percolates upwards so as to automatically infer collective activity labels. Experimental results on two challenging data sets demonstrate our theoretical claims and indicate that our model achieves enhances tracking results and the best collective classification results to date.

Evaluating E-Training for Public Library Staff: A Quasi-Experimental Investigation

ERIC Educational Resources Information Center

Dalston, Teresa

2009-01-01

A comparative evaluation framework of instructional interventions for implementation of online training for public library staff would enable a better understanding of how to improve the effectiveness, efficiency and efficacy of training in certain training environments. This dissertation describes a quasi-experimental study of a two-week,…

Sensing, Measuring and Modelling the Mechanical Properties of Sandstone

NASA Astrophysics Data System (ADS)

Antony, S. J.; Olugbenga, A.; Ozerkan, N. G.

2018-02-01

We present a hybrid framework for simulating the strength and dilation characteristics of sandstone. Where possible, the grain-scale properties of sandstone are evaluated experimentally in detail. Also, using photo-stress analysis, we sense the deviator stress (/strain) distribution at the micro-scale and its components along the orthogonal directions on the surface of a V-notch sandstone sample under mechanical loading. Based on this measurement and applying a grain-scale model, the optical anisotropy index K 0 is inferred at the grain scale. This correlated well with the grain contact stiffness ratio K evaluated using ultrasound sensors independently. Thereafter, in addition to other experimentally characterised structural and grain-scale properties of sandstone, K is fed as an input into the discrete element modelling of fracture strength and dilation of the sandstone samples. Physical bulk-scale experiments are also conducted to evaluate the load-displacement relation, dilation and bulk fracture strength characteristics of sandstone samples under compression and shear. A good level of agreement is obtained between the results of the simulations and experiments. The current generic framework could be applied to understand the internal and bulk mechanical properties of such complex opaque and heterogeneous materials more realistically in future.

Context variations and pluri-methodological issues concerning the expression of a social representation: the example of the Gypsy community.

PubMed

Piermattéo, Anthony; Lo Monaco, Grégory; Moreau, Laure; Girandola, Fabien; Tavani, Jean-Louis

2014-11-20

Within the social representations' field of research, the "mute zone" hypothesis considers that some objects are characterized by counternormative content that people usually do not express in standard conditions of production. Within the framework of this approach, this study aims to explore the variations in the expression about the Gypsy community following the manipulation of different contexts and the issues associated with a pluri-methodological approach of data analysis. Indeed, two methodologies have been combined. The participants were asked to express themselves in public or in private. In addition, the identity of the experimenter was also manipulated as she presented herself as a Gypsy or not. Then, through a set of analyses based on a methodological triangulation approach, we were able to observe a recurrent modulation of the participants' answers. These analyses highlighted a greater incidence of the expression of counternormative elements when the context of expression was private and especially when the experimenter did not present herself as a Gypsy (p < .01, η p ² = .06). These results will be discussed in terms of the contribution of the methodologies employed and their comparison within the framework of the study of counternormative content.

Robust Optical Recognition of Cursive Pashto Script Using Scale, Rotation and Location Invariant Approach

PubMed Central

Ahmad, Riaz; Naz, Saeeda; Afzal, Muhammad Zeshan; Amin, Sayed Hassan; Breuel, Thomas

2015-01-01

The presence of a large number of unique shapes called ligatures in cursive languages, along with variations due to scaling, orientation and location provides one of the most challenging pattern recognition problems. Recognition of the large number of ligatures is often a complicated task in oriental languages such as Pashto, Urdu, Persian and Arabic. Research on cursive script recognition often ignores the fact that scaling, orientation, location and font variations are common in printed cursive text. Therefore, these variations are not included in image databases and in experimental evaluations. This research uncovers challenges faced by Arabic cursive script recognition in a holistic framework by considering Pashto as a test case, because Pashto language has larger alphabet set than Arabic, Persian and Urdu. A database containing 8000 images of 1000 unique ligatures having scaling, orientation and location variations is introduced. In this article, a feature space based on scale invariant feature transform (SIFT) along with a segmentation framework has been proposed for overcoming the above mentioned challenges. The experimental results show a significantly improved performance of proposed scheme over traditional feature extraction techniques such as principal component analysis (PCA). PMID:26368566

Fuzzy logic based sensor performance evaluation of vehicle mounted metal detector systems

NASA Astrophysics Data System (ADS)

Abeynayake, Canicious; Tran, Minh D.

2015-05-01

Vehicle Mounted Metal Detector (VMMD) systems are widely used for detection of threat objects in humanitarian demining and military route clearance scenarios. Due to the diverse nature of such operational conditions, operational use of VMMD without a proper understanding of its capability boundaries may lead to heavy causalities. Multi-criteria fitness evaluations are crucial for determining capability boundaries of any sensor-based demining equipment. Evaluation of sensor based military equipment is a multi-disciplinary topic combining the efforts of researchers, operators, managers and commanders having different professional backgrounds and knowledge profiles. Information acquired through field tests usually involves uncertainty, vagueness and imprecision due to variations in test and evaluation conditions during a single test or series of tests. This report presents a fuzzy logic based methodology for experimental data analysis and performance evaluation of VMMD. This data evaluation methodology has been developed to evaluate sensor performance by consolidating expert knowledge with experimental data. A case study is presented by implementing the proposed data analysis framework in a VMMD evaluation scenario. The results of this analysis confirm accuracy, practicability and reliability of the fuzzy logic based sensor performance evaluation framework.

Simulation and Experimental Study of Metal Organic Frameworks Used in Adsorption Cooling

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

Jenks, Jeromy J.; Motkuri, Radha K.; TeGrotenhuis, Ward

2016-10-11

Metal-organic frameworks (MOFs) have recently attracted enormous interest over the past few years in energy storage and gas separation, yet there have been few reports for adsorption cooling applications. Adsorption cooling technology is an established alternative to mechanical vapor compression refrigeration systems and is an excellent alternative in industrial environments where waste heat is available. We explored the use of MOFs that have very high mass loading and relatively low heats of adsorption, with certain combinations of refrigerants to demonstrate a new type of highly efficient adsorption chiller. Computational fluid dynamics combined with a system level lumped-parameter model have beenmore » used to project size and performance for chillers with a cooling capacity ranging from a few kW to several thousand kW. These systems rely on stacked micro/mini-scale architectures to enhance heat and mass transfer. Recent computational studies of an adsorption chiller based on MOFs suggests that a thermally-driven coefficient of performance greater than one may be possible, which would represent a fundamental breakthrough in performance of adsorption chiller technology. Presented herein are computational and experimental results for hydrophyilic and fluorophilic MOFs.« less

Semantic annotation of Web data applied to risk in food.

PubMed

Hignette, Gaëlle; Buche, Patrice; Couvert, Olivier; Dibie-Barthélemy, Juliette; Doussot, David; Haemmerlé, Ollivier; Mettler, Eric; Soler, Lydie

2008-11-30

A preliminary step to risk in food assessment is the gathering of experimental data. In the framework of the Sym'Previus project (http://www.symprevius.org), a complete data integration system has been designed, grouping data provided by industrial partners and data extracted from papers published in the main scientific journals of the domain. Those data have been classified by means of a predefined vocabulary, called ontology. Our aim is to complement the database with data extracted from the Web. In the framework of the WebContent project (www.webcontent.fr), we have designed a semi-automatic acquisition tool, called @WEB, which retrieves scientific documents from the Web. During the @WEB process, data tables are extracted from the documents and then annotated with the ontology. We focus on the data tables as they contain, in general, a synthesis of data published in the documents. In this paper, we explain how the columns of the data tables are automatically annotated with data types of the ontology and how the relations represented by the table are recognised. We also give the results of our experimentation to assess the quality of such an annotation.

Preliminary Analysis of the BASALA-H Experimental Programme

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

Blaise, Patrick; Fougeras, Philippe; Philibert, Herve

2002-07-01

This paper is focused on the preliminary analysis of results obtained on the first cores of the first phase of the BASALA (Boiling water reactor Advanced core physics Study Aimed at mox fuel Lattice) programme, aimed at studying the neutronic parameters in ABWR core in hot conditions, currently under investigation in the French EOLE critical facility, within the framework of a cooperation between NUPEC, CEA and Cogema. The first 'on-line' analysis of the results has been made, using a new preliminary design and safety scheme based on the French APOLLO-2 code in its 2.4 qualified version and associated CEA-93 V4more » (JEF-2.2) Library, that will enable the Experimental Physics Division (SPEx) to perform future core designs. It describes the scheme adopted and the results obtained in various cases, going to the critical size determination to the reactivity worth of the perturbed configurations (voided, over-moderated, and poisoned with Gd{sub 2}O{sub 3}-UO{sub 2} pins). A preliminary study on the experimental results on the MISTRAL-4 is resumed, and the comparison of APOLLO-2 versus MCNP-4C calculations on these cores is made. The results obtained show very good agreements between the two codes, and versus the experiment. This work opens the way to the future full analysis of the experimental results of the qualifying teams with completely validated schemes, based on the new 2.5 version of the APOLLO-2 code. (authors)« less

Measurement of Workload: Physics, Psychophysics, and Metaphysics

NASA Technical Reports Server (NTRS)

Gopher, D.

1984-01-01

The present paper reviews the results of two experiments in which workload analysis was conducted based upon performance measures, brain evoked potentials and magnitude estimations of subjective load. The three types of measures were jointly applied to the description of the behavior of subjects in a wide battery of experimental tasks. Data analysis shows both instances of association and dissociation between types of measures. A general conceptual framework and methodological guidelines are proposed to account for these findings.

Dark solitons in mode-locked lasers.

PubMed

Ablowitz, Mark J; Horikis, Theodoros P; Nixon, Sean D; Frantzeskakis, Dimitri J

2011-03-15

Dark soliton formation in mode-locked lasers is investigated by means of a power-energy saturation model that incorporates gain and filtering saturated with energy, and loss saturated with power. It is found that general initial conditions evolve (mode-lock) into dark solitons under appropriate requirements also met in experimental observations. The resulting pulses are essentially dark solitons of the unperturbed nonlinear Schrödinger equation. Notably, the same framework also describes bright pulses in anomalous and normally dispersive lasers.

Chaos without nonlinear dynamics.

PubMed

Corron, Ned J; Hayes, Scott T; Pethel, Shawn D; Blakely, Jonathan N

2006-07-14

A linear, second-order filter driven by randomly polarized pulses is shown to generate a waveform that is chaotic under time reversal. That is, the filter output exhibits determinism and a positive Lyapunov exponent when viewed backward in time. The filter is demonstrated experimentally using a passive electronic circuit, and the resulting waveform exhibits a Lorenz-like butterfly structure. This phenomenon suggests that chaos may be connected to physical theories whose underlying framework is not that of a traditional deterministic nonlinear dynamical system.

An experimental study on CHVE's performance evaluation.

PubMed

Paiva, Paulo V F; Machado, Liliane S; Oliveira, Jauvane C

2012-01-01

Virtual reality-based training simulators, with collaborative capabilities, are known to improve the way users interact with one another while learning or improving skills on a given medical procedure. Performance evaluation of Collaborative Haptic Virtual Environments (CHVE) allows us to understand how such systems can work in the Internet, as well as the requirements for multisensorial and real-time data. This work discloses new performance evaluation results for the collaborative module of the CyberMed VR framework.

Attempt to probe nuclear charge radii by cluster and proton emissions

NASA Astrophysics Data System (ADS)

Qian, Yibin; Ren, Zhongzhou; Ni, Dongdong

2013-05-01

We deduce the rms nuclear charge radii for ground states of light and medium-mass nuclei from experimental data of cluster radioactivity and proton emission in a unified framework. On the basis of the density-dependent cluster model, the calculated decay half-lives are obtained within the modified two-potential approach. The charge distribution of emitted clusters in the cluster decay and that of daughter nuclei in the proton emission are determined to correspondingly reproduce the experimental half-lives within the folding model. The obtained charge distribution is then employed to give the rms charge radius of the studied nuclei. Satisfactory agreement between theory and experiment is achieved for available experimental data, and the present results are found to be consistent with theoretical estimations. This study is expected to be helpful in the future detection of nuclear sizes, especially for these exotic nuclei near the proton dripline.

Particle Shape Effect on Macroscopic Behaviour of Underground Structures: Numerical and Experimental Study

NASA Astrophysics Data System (ADS)

Szarf, Krzysztof; Combe, Gael; Villard, Pascal

2015-02-01

The mechanical performance of underground flexible structures such as buried pipes or culverts made of plastics depend not only on the properties of the structure, but also on the material surrounding it. Flexible drains can deflect by 30% with the joints staying tight, or even invert. Large deformations of the structure are difficult to model in the framework of Finite Element Method, but straightforward in Discrete Element Methods. Moreover, Discrete Element approach is able to provide information about the grain-grain and grain-structure interactions at the microscale. This paper presents numerical and experimental investigations of flexible buried pipe behaviour with focus placed on load transfer above the buried structure. Numerical modeling was able to reproduce the experimental results. Load repartition was observed, being affected by a number of factors such as particle shape, pipe friction and pipe stiffness.

Experimental realization of dynamo action: present status and prospects

NASA Astrophysics Data System (ADS)

Giesecke, André; Stefani, Frank; Gundrum, Thomas; Gerbeth, Gunter; Nore, Caroline; Léorat, Jacques

2013-07-01

In the last decades, the experimental study of dynamo action has made great progress. However, after the dynamo experiments in Karlsruhe and Riga, the von-Kármán-Sodium (VKS) dynamo is only the third facility that has been able to demonstrate fluid flow driven self-generation of magnetic fields in a laboratory experiment. Further progress in the experimental examination of dynamo action is expected from the planned precession driven dynamo experiment that will be designed in the framework of the liquid sodium facility DRESDYN (DREsden Sodium facility for DYNamo and thermohydraulic studies). In this paper, we briefly present numerical models of the VKS dynamo that demonstrate the close relation between the axisymmetric field observed in that experiment and the soft iron material used for the flow driving impellers. We further show recent results of preparatory water experiments and design studies related to the precession dynamo and delineate the scientific prospects for the final set-up.

Experimental and Numerical Analysis of Microstructures and Stress States of Shot-Peened GH4169 Superalloys

NASA Astrophysics Data System (ADS)

Hu, Dianyin; Gao, Ye; Meng, Fanchao; Song, Jun; Wang, Rongqiao

2018-04-01

Combining experiments and finite element analysis (FEA), a systematic study was performed to analyze the microstructural evolution and stress states of shot-peened GH4169 superalloy over a variety of peening intensities and coverages. A dislocation density evolution model was integrated into the representative volume FEA model to quantitatively predict microstructural evolution in the surface layers and compared with experimental results. It was found that surface roughness and through-depth residual stress profile are more sensitive to shot-peening intensity compared to coverage due to the high kinetic energy involved. Moreover, a surface nanocrystallization layer was discovered in the top surface region of GH4169 for all shot-peening conditions. However, the grain refinement was more intensified under high shot-peening coverage, under which enough time was permitted for grain refinement. The grain size gradient predicted by the numerical framework showed good agreement with experimental observations.

A Framework for Quantifying Measurement Uncertainties and Uncertainty Propagation in HCCI/LTGC Engine Experiments

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

Petitpas, Guillaume; McNenly, Matthew J.; Whitesides, Russell A.

In this study, a framework for estimating experimental measurement uncertainties for a Homogenous Charge Compression Ignition (HCCI)/Low-Temperature Gasoline Combustion (LTGC) engine testing facility is presented. Detailed uncertainty quantification is first carried out for the measurement of the in-cylinder pressure, whose variations during the cycle provide most of the information for performance evaluation. Standard uncertainties of other measured quantities, such as the engine geometry and speed, the air and fuel flow rate and the intake/exhaust dry molar fractions are also estimated. Propagating those uncertainties using a Monte Carlo simulation and Bayesian inference methods then allows for estimation of uncertainties of themore » mass-average temperature and composition at IVC and throughout the cycle; and also of the engine performances such as gross Integrated Mean Effective Pressure, Heat Release and Ringing Intensity. Throughout the analysis, nominal values for uncertainty inputs were taken from a well-characterized engine test facility. However, the analysis did not take into account the calibration practice of experiments run in that facility and the resulting uncertainty values are therefore not indicative of the expected accuracy of those experimental results. A future study will employ the methodology developed here to explore the effects of different calibration methods on the different uncertainty values in order to evaluate best practices for accurate engine measurements.« less

A Framework for Quantifying Measurement Uncertainties and Uncertainty Propagation in HCCI/LTGC Engine Experiments

DOE PAGES

Petitpas, Guillaume; McNenly, Matthew J.; Whitesides, Russell A.

2017-03-28

In this study, a framework for estimating experimental measurement uncertainties for a Homogenous Charge Compression Ignition (HCCI)/Low-Temperature Gasoline Combustion (LTGC) engine testing facility is presented. Detailed uncertainty quantification is first carried out for the measurement of the in-cylinder pressure, whose variations during the cycle provide most of the information for performance evaluation. Standard uncertainties of other measured quantities, such as the engine geometry and speed, the air and fuel flow rate and the intake/exhaust dry molar fractions are also estimated. Propagating those uncertainties using a Monte Carlo simulation and Bayesian inference methods then allows for estimation of uncertainties of themore » mass-average temperature and composition at IVC and throughout the cycle; and also of the engine performances such as gross Integrated Mean Effective Pressure, Heat Release and Ringing Intensity. Throughout the analysis, nominal values for uncertainty inputs were taken from a well-characterized engine test facility. However, the analysis did not take into account the calibration practice of experiments run in that facility and the resulting uncertainty values are therefore not indicative of the expected accuracy of those experimental results. A future study will employ the methodology developed here to explore the effects of different calibration methods on the different uncertainty values in order to evaluate best practices for accurate engine measurements.« less

PsyGlass: Capitalizing on Google Glass for naturalistic data collection.

PubMed

Paxton, Alexandra; Rodriguez, Kevin; Dale, Rick

2015-09-01

As commercial technology moves further into wearable technologies, cognitive and psychological scientists can capitalize on these devices to facilitate naturalistic research designs while still maintaining strong experimental control. One such wearable technology is Google Glass (Google, Inc.: www.google.com/glass), which can present wearers with audio and visual stimuli while tracking a host of multimodal data. In this article, we introduce PsyGlass, a framework for incorporating Google Glass into experimental work that is freely available for download and community improvement over time (www.github.com/a-paxton/PsyGlass). As a proof of concept, we use this framework to investigate dual-task pressures on naturalistic interaction. The preliminary study demonstrates how designs from classic experimental psychology may be integrated in naturalistic interactive designs with emerging technologies. We close with a series of recommendations for using PsyGlass and a discussion of how wearable technology more broadly may contribute to new or adapted naturalistic research designs.

Swept shock/boundary-layer interactions: Scaling laws, flowfield structure, and experimental methods

NASA Technical Reports Server (NTRS)

Settles, Gary S.

1993-01-01

A general review is given of several decades of research on the scaling laws and flowfield structures of swept shock wave/turbulent boundary layer interactions. Attention is further restricted to the experimental study and physical understanding of the steady-state aspects of these flows. The interaction produced by a sharp, upright fin mounted on a flat plate is taken as an archetype. An overall framework of quasiconical symmetry describing such interactions is first developed. Boundary-layer separation, the interaction footprint, Mach number scaling, and Reynolds number scaling are then considered, followed by a discussion of the quasiconical similarity of interactions produced by geometrically-dissimilar shock generators. The detailed structure of these interaction flowfields is next reviewed, and is illustrated by both qualitative visualizations and quantitative flow images in the quasiconical framework. Finally, the experimental techniques used to investigate such flows are reviewed, with emphasis on modern non-intrusive optical flow diagnostics.

Experimental validation of a new heterogeneous mechanical test design

NASA Astrophysics Data System (ADS)

Aquino, J.; Campos, A. Andrade; Souto, N.; Thuillier, S.

2018-05-01

Standard material parameters identification strategies generally use an extensive number of classical tests for collecting the required experimental data. However, a great effort has been made recently by the scientific and industrial communities to support this experimental database on heterogeneous tests. These tests can provide richer information on the material behavior allowing the identification of a more complete set of material parameters. This is a result of the recent development of full-field measurements techniques, like digital image correlation (DIC), that can capture the heterogeneous deformation fields on the specimen surface during the test. Recently, new specimen geometries were designed to enhance the richness of the strain field and capture supplementary strain states. The butterfly specimen is an example of these new geometries, designed through a numerical optimization procedure where an indicator capable of evaluating the heterogeneity and the richness of strain information. However, no experimental validation was yet performed. The aim of this work is to experimentally validate the heterogeneous butterfly mechanical test in the parameter identification framework. For this aim, DIC technique and a Finite Element Model Up-date inverse strategy are used together for the parameter identification of a DC04 steel, as well as the calculation of the indicator. The experimental tests are carried out in a universal testing machine with the ARAMIS measuring system to provide the strain states on the specimen surface. The identification strategy is accomplished with the data obtained from the experimental tests and the results are compared to a reference numerical solution.

A Framework for Land Cover Classification Using Discrete Return LiDAR Data: Adopting Pseudo-Waveform and Hierarchical Segmentation

NASA Technical Reports Server (NTRS)

Jung, Jinha; Pasolli, Edoardo; Prasad, Saurabh; Tilton, James C.; Crawford, Melba M.

2014-01-01

Acquiring current, accurate land-use information is critical for monitoring and understanding the impact of anthropogenic activities on natural environments.Remote sensing technologies are of increasing importance because of their capability to acquire information for large areas in a timely manner, enabling decision makers to be more effective in complex environments. Although optical imagery has demonstrated to be successful for land cover classification, active sensors, such as light detection and ranging (LiDAR), have distinct capabilities that can be exploited to improve classification results. However, utilization of LiDAR data for land cover classification has not been fully exploited. Moreover, spatial-spectral classification has recently gained significant attention since classification accuracy can be improved by extracting additional information from the neighboring pixels. Although spatial information has been widely used for spectral data, less attention has been given to LiDARdata. In this work, a new framework for land cover classification using discrete return LiDAR data is proposed. Pseudo-waveforms are generated from the LiDAR data and processed by hierarchical segmentation. Spatial featuresare extracted in a region-based way using a new unsupervised strategy for multiple pruning of the segmentation hierarchy. The proposed framework is validated experimentally on a real dataset acquired in an urban area. Better classification results are exhibited by the proposed framework compared to the cases in which basic LiDAR products such as digital surface model and intensity image are used. Moreover, the proposed region-based feature extraction strategy results in improved classification accuracies in comparison with a more traditional window-based approach.

Labyrinthine flows across multilayer graphene-based membranes

NASA Astrophysics Data System (ADS)

Yoshida, Hiroaki

Graphene-based materials have recently found extremely wide applications for fluidic purposes thanks to remarkable developments in micro-/nano-fabrication techniques. In particular, high permeability and specific selectivity have been reported for these graphene-based membranes, such as the graphene-oxide membranes, with however controversial experimental results. There is therefore an urgent need to propose a theoretical framework of fluid transport in these architectures in order to rationalize the experimental results.In this presentation, we report a theoretical study of mass transport across multilayer graphene based membranes, which we benchmark by atomic-scale molecular dynamics. Specifically, we consider the water flow across multiple graphene layers with an inter-layer distance ranging from sub-nanometer to a few nanometers. The graphene layers have nanoslits aligned in a staggered fashion, and thus the water flows involve multiple twists and turns. We compare the continuum model predictions for the permeability with the lattice Boltzmann calculations and molecular dynamics simulations. The highlight is that, in spite of extreme confinement, the permeability across the graphene-based membrane is quantitatively predicted on the basis of a properly designed continuum model. The framework of this study constitutes a benchmark to which we compare favourably published experimental data.In addition, flow properties of a water-ethanol mixture are presented, demonstrating the possibility of a novel separation technique. While the membrane is permeable to both pure liquids, it exhibits a counter-intuitive ``self-semi-permeability'' to water in the presence of the mixture. This suggests a robust and versatile membrane-based separation method built on a pressure-driven reverse-osmosis process, which is considerably less energy consuming than distillation processes. The author acknowledges the ERC project Micromegas and the ANR projects BlueEnergy and Equip@Meso.

A Fast, Open EEG Classification Framework Based on Feature Compression and Channel Ranking

PubMed Central

Han, Jiuqi; Zhao, Yuwei; Sun, Hongji; Chen, Jiayun; Ke, Ang; Xu, Gesen; Zhang, Hualiang; Zhou, Jin; Wang, Changyong

2018-01-01

Superior feature extraction, channel selection and classification methods are essential for designing electroencephalography (EEG) classification frameworks. However, the performance of most frameworks is limited by their improper channel selection methods and too specifical design, leading to high computational complexity, non-convergent procedure and narrow expansibility. In this paper, to remedy these drawbacks, we propose a fast, open EEG classification framework centralized by EEG feature compression, low-dimensional representation, and convergent iterative channel ranking. First, to reduce the complexity, we use data clustering to compress the EEG features channel-wise, packing the high-dimensional EEG signal, and endowing them with numerical signatures. Second, to provide easy access to alternative superior methods, we structurally represent each EEG trial in a feature vector with its corresponding numerical signature. Thus, the recorded signals of many trials shrink to a low-dimensional structural matrix compatible with most pattern recognition methods. Third, a series of effective iterative feature selection approaches with theoretical convergence is introduced to rank the EEG channels and remove redundant ones, further accelerating the EEG classification process and ensuring its stability. Finally, a classical linear discriminant analysis (LDA) model is employed to classify a single EEG trial with selected channels. Experimental results on two real world brain-computer interface (BCI) competition datasets demonstrate the promising performance of the proposed framework over state-of-the-art methods. PMID:29713262

Multi-level multi-task learning for modeling cross-scale interactions in nested geospatial data

USGS Publications Warehouse

Yuan, Shuai; Zhou, Jiayu; Tan, Pang-Ning; Fergus, Emi; Wagner, Tyler; Sorrano, Patricia

2017-01-01

Predictive modeling of nested geospatial data is a challenging problem as the models must take into account potential interactions among variables defined at different spatial scales. These cross-scale interactions, as they are commonly known, are particularly important to understand relationships among ecological properties at macroscales. In this paper, we present a novel, multi-level multi-task learning framework for modeling nested geospatial data in the lake ecology domain. Specifically, we consider region-specific models to predict lake water quality from multi-scaled factors. Our framework enables distinct models to be developed for each region using both its local and regional information. The framework also allows information to be shared among the region-specific models through their common set of latent factors. Such information sharing helps to create more robust models especially for regions with limited or no training data. In addition, the framework can automatically determine cross-scale interactions between the regional variables and the local variables that are nested within them. Our experimental results show that the proposed framework outperforms all the baseline methods in at least 64% of the regions for 3 out of 4 lake water quality datasets evaluated in this study. Furthermore, the latent factors can be clustered to obtain a new set of regions that is more aligned with the response variables than the original regions that were defined a priori from the ecology domain.

A Columnar Storage Strategy with Spatiotemporal Index for Big Climate Data

NASA Astrophysics Data System (ADS)

Hu, F.; Bowen, M. K.; Li, Z.; Schnase, J. L.; Duffy, D.; Lee, T. J.; Yang, C. P.

2015-12-01

Large collections of observational, reanalysis, and climate model output data may grow to as large as a 100 PB in the coming years, so climate dataset is in the Big Data domain, and various distributed computing frameworks have been utilized to address the challenges by big climate data analysis. However, due to the binary data format (NetCDF, HDF) with high spatial and temporal dimensions, the computing frameworks in Apache Hadoop ecosystem are not originally suited for big climate data. In order to make the computing frameworks in Hadoop ecosystem directly support big climate data, we propose a columnar storage format with spatiotemporal index to store climate data, which will support any project in the Apache Hadoop ecosystem (e.g. MapReduce, Spark, Hive, Impala). With this approach, the climate data will be transferred into binary Parquet data format, a columnar storage format, and spatial and temporal index will be built and attached into the end of Parquet files to enable real-time data query. Then such climate data in Parquet data format could be available to any computing frameworks in Hadoop ecosystem. The proposed approach is evaluated using the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) climate reanalysis dataset. Experimental results show that this approach could efficiently overcome the gap between the big climate data and the distributed computing frameworks, and the spatiotemporal index could significantly accelerate data querying and processing.

Surface Protonation at the Rutile (110) Interface: Explicit Incorporation of Solvation Structure within the Refined MUSIC Model Framework

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

Machesky, Michael L.; Predota, M.; Wesolowski, David J

The detailed solvation structure at the (110) surface of rutile ({alpha}-TiO{sub 2}) in contact with bulk liquid water has been obtained primarily from experimentally verified classical molecular dynamics (CMD) simulations of the ab initio-optimized surface in contact with SPC/E water. The results are used to explicitly quantify H-bonding interactions, which are then used within the refined MUSIC model framework to predict surface oxygen protonation constants. Quantum mechanical molecular dynamics (QMD) simulations in the presence of freely dissociable water molecules produced H-bond distributions around deprotonated surface oxygens very similar to those obtained by CMD with nondissociable SPC/E water, thereby confirming thatmore » the less computationally intensive CMD simulations provide accurate H-bond information. Utilizing this H-bond information within the refined MUSIC model, along with manually adjusted Ti-O surface bond lengths that are nonetheless within 0.05 {angstrom} of those obtained from static density functional theory (DFT) calculations and measured in X-ray reflectivity experiments (as well as bulk crystal values), give surface protonation constants that result in a calculated zero net proton charge pH value (pHznpc) at 25 C that agrees quantitatively with the experimentally determined value (5.4 {+-} 0.2) for a specific rutile powder dominated by the (110) crystal face. Moreover, the predicted pH{sub znpc} values agree to within 0.1 pH unit with those measured at all temperatures between 10 and 250 C. A slightly smaller manual adjustment of the DFT-derived Ti-O surface bond lengths was sufficient to bring the predicted pH{sub znpc} value of the rutile (110) surface at 25 C into quantitative agreement with the experimental value (4.8 {+-} 0.3) obtained from a polished and annealed rutile (110) single crystal surface in contact with dilute sodium nitrate solutions using second harmonic generation (SHG) intensity measurements as a function of ionic strength. Additionally, the H-bond interactions between protolyzable surface oxygen groups and water were found to be stronger than those between bulk water molecules at all temperatures investigated in our CMD simulations (25, 150 and 250 C). Comparison with the protonation scheme previously determined for the (110) surface of isostructural cassiterite ({alpha}-SnO{sub 2}) reveals that the greater extent of H-bonding on the latter surface, and in particular between water and the terminal hydroxyl group (Sn-OH) results in the predicted protonation constant for that group being lower than for the bridged oxygen (Sn-O-Sn), while the reverse is true for the rutile (110) surface. These results demonstrate the importance of H-bond structure in dictating surface protonation behavior, and that explicit use of this solvation structure within the refined MUSIC model framework results in predicted surface protonation constants that are also consistent with a variety of other experimental and computational data.« less

Surface protonation at the rutile (110) interface: explicit incorporation of solvation structure within the refined MUSIC model framework.

PubMed

Machesky, Michael L; Predota, Milan; Wesolowski, David J; Vlcek, Lukas; Cummings, Peter T; Rosenqvist, Jörgen; Ridley, Moira K; Kubicki, James D; Bandura, Andrei V; Kumar, Nitin; Sofo, Jorge O

2008-11-04

The detailed solvation structure at the (110) surface of rutile (alpha-TiO2) in contact with bulk liquid water has been obtained primarily from experimentally verified classical molecular dynamics (CMD) simulations of the ab initio-optimized surface in contact with SPC/E water. The results are used to explicitly quantify H-bonding interactions, which are then used within the refined MUSIC model framework to predict surface oxygen protonation constants. Quantum mechanical molecular dynamics (QMD) simulations in the presence of freely dissociable water molecules produced H-bond distributions around deprotonated surface oxygens very similar to those obtained by CMD with nondissociable SPC/E water, thereby confirming that the less computationally intensive CMD simulations provide accurate H-bond information. Utilizing this H-bond information within the refined MUSIC model, along with manually adjusted Ti-O surface bond lengths that are nonetheless within 0.05 A of those obtained from static density functional theory (DFT) calculations and measured in X-ray reflectivity experiments (as well as bulk crystal values), give surface protonation constants that result in a calculated zero net proton charge pH value (pHznpc) at 25 degrees C that agrees quantitatively with the experimentally determined value (5.4+/-0.2) for a specific rutile powder dominated by the (110) crystal face. Moreover, the predicted pHznpc values agree to within 0.1 pH unit with those measured at all temperatures between 10 and 250 degrees C. A slightly smaller manual adjustment of the DFT-derived Ti-O surface bond lengths was sufficient to bring the predicted pHznpcvalue of the rutile (110) surface at 25 degrees C into quantitative agreement with the experimental value (4.8+/-0.3) obtained from a polished and annealed rutile (110) single crystal surface in contact with dilute sodium nitrate solutions using second harmonic generation (SHG) intensity measurements as a function of ionic strength. Additionally, the H-bond interactions between protolyzable surface oxygen groups and water were found to be stronger than those between bulk water molecules at all temperatures investigated in our CMD simulations (25, 150 and 250 degrees C). Comparison with the protonation scheme previously determined for the (110) surface of isostructural cassiterite (alpha-SnO2) reveals that the greater extent of H-bonding on the latter surface, and in particular between water and the terminal hydroxyl group (Sn-OH) results in the predicted protonation constant for that group being lower than for the bridged oxygen (Sn-O-Sn), while the reverse is true for the rutile (110) surface. These results demonstrate the importance of H-bond structure in dictating surface protonation behavior, and that explicit use of this solvation structure within the refined MUSIC model framework results in predicted surface protonation constants that are also consistent with a variety of other experimental and computational data.

Examining the Value of a Scaffolded Critique Framework to Promote Argumentative and Explanatory Writings within an Argument-Based Inquiry Approach

ERIC Educational Resources Information Center

Jang, Jeong-yoon; Hand, Brian

2017-01-01

This study investigated the value of using a scaffolded critique framework to promote two different types of writing--argumentative writing and explanatory writing--with different purposes within an argument-based inquiry approach known as the Science Writing Heuristic (SWH) approach. A quasi-experimental design with sixth and seventh grade…

A New Framework for Systematic Reviews: Application to Social Skills Interventions for Preschoolers with Autism

ERIC Educational Resources Information Center

Goldstein, Howard; Lackey, Kimberly C.; Schneider, Naomi J. B.

2014-01-01

This review presents a novel framework for evaluating evidence based on a set of parallel criteria that can be applied to both group and single-subject experimental design (SSED) studies. The authors illustrate use of this evaluation system in a systematic review of 67 articles investigating social skills interventions for preschoolers with autism…

An Experimental Design of a Foundational Framework for the Application of Affective Computing to Soaring Flight Simulation and Training

ERIC Educational Resources Information Center

Moon, Shannon

2017-01-01

In the absence of tools for intelligent tutoring systems for soaring flight simulation training, this study evaluated a framework foundation to measure pilot performance, affect, and physiological response to training in real-time. Volunteers were asked to perform a series of flight tasks selected from Federal Aviation Administration Practical…

Modeling Criminal Activity in Urban Landscapes

NASA Astrophysics Data System (ADS)

Brantingham, Patricia; Glässer, Uwe; Jackson, Piper; Vajihollahi, Mona

Computational and mathematical methods arguably have an enormous potential for serving practical needs in crime analysis and prevention by offering novel tools for crime investigations and experimental platforms for evidence-based policy making. We present a comprehensive formal framework and tool support for mathematical and computational modeling of criminal behavior to facilitate systematic experimental studies of a wide range of criminal activities in urban environments. The focus is on spatial and temporal aspects of different forms of crime, including opportunistic and serial violent crimes. However, the proposed framework provides a basis to push beyond conventional empirical research and engage the use of computational thinking and social simulations in the analysis of terrorism and counter-terrorism.

Predictive framework for estimating exposure of birds to pharmaceuticals

USGS Publications Warehouse

Bean, Thomas G.; Arnold, Kathryn E.; Lane, Julie M.; Bergström, Ed; Thomas-Oates, Jane; Rattner, Barnett A.; Boxall, Allistair B.A.

2017-01-01

We present and evaluate a framework for estimating concentrations of pharmaceuticals over time in wildlife feeding at wastewater treatment plants (WWTPs). The framework is composed of a series of predictive steps involving the estimation of pharmaceutical concentration in wastewater, accumulation into wildlife food items, and uptake by wildlife with subsequent distribution into, and elimination from, tissues. Because many pharmacokinetic parameters for wildlife are unavailable for the majority of drugs in use, a read-across approach was employed using either rodent or human data on absorption, distribution, metabolism, and excretion. Comparison of the different steps in the framework against experimental data for the scenario where birds are feeding on a WWTP contaminated with fluoxetine showed that estimated concentrations in wastewater treatment works were lower than measured concentrations; concentrations in food could be reasonably estimated if experimental bioaccumulation data are available; and read-across from rodent data worked better than human to bird read-across. The framework provides adequate predictions of plasma concentrations and of elimination behavior in birds but yields poor predictions of distribution in tissues. The approach holds promise, but it is important that we improve our understanding of the physiological similarities and differences between wild birds and domesticated laboratory mammals used in pharmaceutical efficacy/safety trials, so that the wealth of data available can be applied more effectively in ecological risk assessments.

Predictive framework for estimating exposure of birds to pharmaceuticals.

PubMed

Bean, Thomas G; Arnold, Kathryn E; Lane, Julie M; Bergström, Ed; Thomas-Oates, Jane; Rattner, Barnett A; Boxall, Alistair B A

2017-09-01

We present and evaluate a framework for estimating concentrations of pharmaceuticals over time in wildlife feeding at wastewater treatment plants (WWTPs). The framework is composed of a series of predictive steps involving the estimation of pharmaceutical concentration in wastewater, accumulation into wildlife food items, and uptake by wildlife with subsequent distribution into, and elimination from, tissues. Because many pharmacokinetic parameters for wildlife are unavailable for the majority of drugs in use, a read-across approach was employed using either rodent or human data on absorption, distribution, metabolism, and excretion. Comparison of the different steps in the framework against experimental data for the scenario where birds are feeding on a WWTP contaminated with fluoxetine showed that estimated concentrations in wastewater treatment works were lower than measured concentrations; concentrations in food could be reasonably estimated if experimental bioaccumulation data are available; and read-across from rodent data worked better than human to bird read-across. The framework provides adequate predictions of plasma concentrations and of elimination behavior in birds but yields poor predictions of distribution in tissues. The approach holds promise, but it is important that we improve our understanding of the physiological similarities and differences between wild birds and domesticated laboratory mammals used in pharmaceutical efficacy/safety trials, so that the wealth of data available can be applied more effectively in ecological risk assessments. Environ Toxicol Chem 2017;36:2335-2344. © 2017 SETAC. © 2017 SETAC.

Multiple electron processes of He and Ne by proton impact

NASA Astrophysics Data System (ADS)

Terekhin, Pavel Nikolaevich; Montenegro, Pablo; Quinto, Michele; Monti, Juan; Fojon, Omar; Rivarola, Roberto

2016-05-01

A detailed investigation of multiple electron processes (single and multiple ionization, single capture, transfer-ionization) of He and Ne is presented for proton impact at intermediate and high collision energies. Exclusive absolute cross sections for these processes have been obtained by calculation of transition probabilities in the independent electron and independent event models as a function of impact parameter in the framework of the continuum distorted wave-eikonal initial state theory. A binomial analysis is employed to calculate exclusive probabilities. The comparison with available theoretical and experimental results shows that exclusive probabilities are needed for a reliable description of the experimental data. The developed approach can be used for obtaining the input database for modeling multiple electron processes of charged particles passing through the matter.

Ergonomic office design and aging: a quasi-experimental field study of employee reactions to an ergonomics intervention program.

PubMed

May, Douglas R; Reed, Kendra; Schwoerer, Catherine E; Potter, Paul

2004-04-01

A naturally occurring quasi-experimental longitudinal field study of 87 municipal employees using pretest and posttest measures investigated the effects of an office workstation ergonomics intervention program on employees' perceptions of their workstation characteristics, levels of persistent pain, eyestrain, and workstation satisfaction. The study examined whether reactions differed between younger and older employees. Results revealed that workstation improvements were associated with enhanced perceptions of the workstation's ergonomic qualities, less upper back pain, and greater workstation satisfaction. Among those experiencing an improvement, the perceptions of workstation ergonomic qualities increased more for younger than older employees, supporting the "impressionable years" framework in the psychological literature on aging. Implications for human resources managers are discussed.

Differential cross sections for ionizations of H and H2 by 75 keV proton impact

NASA Astrophysics Data System (ADS)

Igarashi, A.; Gulyás, L.

2018-02-01

We have calculated total, partial and fully differential cross sections (FDCSs) for ionizations of H and H2 by 75 keV proton impact within the framework of the continuum-distorted-wave-eikonal-initial-state (CDW-EIS) approximation. Applying the single active electron model, the interaction between the projectile and the target ion is taken into account in the impact parameter picture. Extension of the CDW-EIS model to the molecular target is performed using the two-effective center approximation. The obtained results are compared with those of experimental and other theoretical data when available. The agreements between the theories and the experimental data are generally reasonable except for some cases of the FDCSs.

The tert-butyl cation on zeolite Y: A theoretical and experimental study

NASA Astrophysics Data System (ADS)

Rosenbach, Nilton, Jr.; dos Santos, Alex P. A.; Franco, Marcelo; Mota, Claudio J. A.

2010-01-01

The structure and energy of the tert-butyl cation on zeolite Y were calculated at ONIOM(MP2(FULL)/6-31G( d, p):MNDO) level. The results indicated that the tert-butyl cation is a minimum and lies between 40 and 51 kJ mol -1 above in energy to the tert-butoxide, depending on the level of calculation. Both species are stabilized through hydrogen bonding interactions with the framework oxygen atoms. Experimental data of nucleophilic substitution of tert-butylchloride and bromide over NaY impregnated with NaCl or NaBr give additional support for the formation of the tert-butyl cation as a discrete intermediate on zeolite Y, in agreement with the calculations.

Solving and Learning Soft Temporal Constraints: Experimental Scenario and Examples

NASA Technical Reports Server (NTRS)

Rossi, F.; Venable, K. B.; Sperduti, A.; Khatib, L.; Morris, P.; Morris, R.; Koga, Dennis (Technical Monitor)

2001-01-01

Soft temporal constraint problems allow to describe in a natural way scenarios where events happen over time and preferences are associated to event distances and durations. However, sometimes such local preferences are difficult to set, and it may be easier instead to associate preferences to some complete solutions of the problem. To model everything in a uniform way via local preferences only, and also to take advantage of the existing constraint solvers which exploit only local preference use machine learning techniques which learn the local preferences from the global ones. In this paper we describe the existing framework for both solving and learning preferences in temporal constraint problems, the implemented modules, the experimental scenario, and preliminary results on some examples.

Numerical-experimental investigation of PE/EVA foam injection molded parts

NASA Astrophysics Data System (ADS)

Spina, Roberto

The main objective of the presented work is to propose a robust framework to test foaming injection molded parts, with the aim of establishing a standard testing cycle for the evaluation of a new foam material based on numerical and experimental results. The research purpose is to assess parameters influencing several aspects, such as foam morphology and compression behavior, using useful suggestions from finite element analysis. The investigated polymeric blend consisted of a mixture of low density polyethylenes (LDPEs), a high-density polyethylene (HDPE), an ethylene-vinyl acetate (EVA) and an azodicarbonamide (ADC). The thermal, rheological and compression properties of the blend are fully described, as well as the numerical models and the parameters of the injection molding process.

A novel framework for virtual prototyping of rehabilitation exoskeletons.

PubMed

Agarwal, Priyanshu; Kuo, Pei-Hsin; Neptune, Richard R; Deshpande, Ashish D

2013-06-01

Human-worn rehabilitation exoskeletons have the potential to make therapeutic exercises increasingly accessible to disabled individuals while reducing the cost and labor involved in rehabilitation therapy. In this work, we propose a novel human-model-in-the-loop framework for virtual prototyping (design, control and experimentation) of rehabilitation exoskeletons by merging computational musculoskeletal analysis with simulation-based design techniques. The framework allows to iteratively optimize design and control algorithm of an exoskeleton using simulation. We introduce biomechanical, morphological, and controller measures to quantify the performance of the device for optimization study. Furthermore, the framework allows one to carry out virtual experiments for testing specific "what-if" scenarios to quantify device performance and recovery progress. To illustrate the application of the framework, we present a case study wherein the design and analysis of an index-finger exoskeleton is carried out using the proposed framework.

Hierarchical control and performance evaluation of multi-vehicle autonomous systems

NASA Astrophysics Data System (ADS)

Balakirsky, Stephen; Scrapper, Chris; Messina, Elena

2005-05-01

This paper will describe how the Mobility Open Architecture Tools and Simulation (MOAST) framework can facilitate performance evaluations of RCS compliant multi-vehicle autonomous systems. This framework provides an environment that allows for simulated and real architectural components to function seamlessly together. By providing repeatable environmental conditions, this framework allows for the development of individual components as well as component performance metrics. MOAST is composed of high-fidelity and low-fidelity simulation systems, a detailed model of real-world terrain, actual hardware components, a central knowledge repository, and architectural glue to tie all of the components together. This paper will describe the framework"s components in detail and provide an example that illustrates how the framework can be utilized to develop and evaluate a single architectural component through the use of repeatable trials and experimentation that includes both virtual and real components functioning together

A software framework for developing measurement applications under variable requirements.

PubMed

Arpaia, Pasquale; Buzio, Marco; Fiscarelli, Lucio; Inglese, Vitaliano

2012-11-01

A framework for easily developing software for measurement and test applications under highly and fast-varying requirements is proposed. The framework allows the software quality, in terms of flexibility, usability, and maintainability, to be maximized. Furthermore, the development effort is reduced and finalized, by relieving the test engineer of development details. The framework can be configured for satisfying a large set of measurement applications in a generic field for an industrial test division, a test laboratory, or a research center. As an experimental case study, the design, the implementation, and the assessment inside the application to a measurement scenario of magnet testing at the European Organization for Nuclear Research is reported.

Parent Praise to 1-3 Year-Olds Predicts Children’s Motivational Frameworks 5 Years Later

PubMed Central

Gunderson, Elizabeth A.; Gripshover, Sarah J.; Romero, Carissa; Dweck, Carol S.; Goldin-Meadow, Susan; Levine, Susan C.

2013-01-01

In laboratory studies, praising children’s effort encourages them to adopt incremental motivational frameworks—they believe ability is malleable, attribute success to hard work, enjoy challenges, and generate strategies for improvement. In contrast, praising children’s inherent abilities encourages them to adopt fixed-ability frameworks. Does the praise parents spontaneously give children at home show the same effects? Although parents’ early praise of inherent characteristics was not associated with children’s later fixed-ability frameworks, parents’ praise of children’s effort at 14-38 months (N=53) did predict incremental frameworks at 7-8 years, suggesting that causal mechanisms identified in experimental work may be operating in home environments. PMID:23397904

Ensemble Semi-supervised Frame-work for Brain Magnetic Resonance Imaging Tissue Segmentation

PubMed Central

Azmi, Reza; Pishgoo, Boshra; Norozi, Narges; Yeganeh, Samira

2013-01-01

Brain magnetic resonance images (MRIs) tissue segmentation is one of the most important parts of the clinical diagnostic tools. Pixel classification methods have been frequently used in the image segmentation with two supervised and unsupervised approaches up to now. Supervised segmentation methods lead to high accuracy, but they need a large amount of labeled data, which is hard, expensive, and slow to obtain. Moreover, they cannot use unlabeled data to train classifiers. On the other hand, unsupervised segmentation methods have no prior knowledge and lead to low level of performance. However, semi-supervised learning which uses a few labeled data together with a large amount of unlabeled data causes higher accuracy with less trouble. In this paper, we propose an ensemble semi-supervised frame-work for segmenting of brain magnetic resonance imaging (MRI) tissues that it has been used results of several semi-supervised classifiers simultaneously. Selecting appropriate classifiers has a significant role in the performance of this frame-work. Hence, in this paper, we present two semi-supervised algorithms expectation filtering maximization and MCo_Training that are improved versions of semi-supervised methods expectation maximization and Co_Training and increase segmentation accuracy. Afterward, we use these improved classifiers together with graph-based semi-supervised classifier as components of the ensemble frame-work. Experimental results show that performance of segmentation in this approach is higher than both supervised methods and the individual semi-supervised classifiers. PMID:24098863

Causality Analysis of fMRI Data Based on the Directed Information Theory Framework.

PubMed

Wang, Zhe; Alahmadi, Ahmed; Zhu, David C; Li, Tongtong

2016-05-01

This paper aims to conduct fMRI-based causality analysis in brain connectivity by exploiting the directed information (DI) theory framework. Unlike the well-known Granger causality (GC) analysis, which relies on the linear prediction technique, the DI theory framework does not have any modeling constraints on the sequences to be evaluated and ensures estimation convergence. Moreover, it can be used to generate the GC graphs. In this paper, first, we introduce the core concepts in the DI framework. Second, we present how to conduct causality analysis using DI measures between two time series. We provide the detailed procedure on how to calculate the DI for two finite-time series. The two major steps involved here are optimal bin size selection for data digitization and probability estimation. Finally, we demonstrate the applicability of DI-based causality analysis using both the simulated data and experimental fMRI data, and compare the results with that of the GC analysis. Our analysis indicates that GC analysis is effective in detecting linear or nearly linear causal relationship, but may have difficulty in capturing nonlinear causal relationships. On the other hand, DI-based causality analysis is more effective in capturing both linear and nonlinear causal relationships. Moreover, it is observed that brain connectivity among different regions generally involves dynamic two-way information transmissions between them. Our results show that when bidirectional information flow is present, DI is more effective than GC to quantify the overall causal relationship.

FORESEE: Fully Outsourced secuRe gEnome Study basEd on homomorphic Encryption.

PubMed

Zhang, Yuchen; Dai, Wenrui; Jiang, Xiaoqian; Xiong, Hongkai; Wang, Shuang

2015-01-01

The increasing availability of genome data motivates massive research studies in personalized treatment and precision medicine. Public cloud services provide a flexible way to mitigate the storage and computation burden in conducting genome-wide association studies (GWAS). However, data privacy has been widely concerned when sharing the sensitive information in a cloud environment. We presented a novel framework (FORESEE: Fully Outsourced secuRe gEnome Study basEd on homomorphic Encryption) to fully outsource GWAS (i.e., chi-square statistic computation) using homomorphic encryption. The proposed framework enables secure divisions over encrypted data. We introduced two division protocols (i.e., secure errorless division and secure approximation division) with a trade-off between complexity and accuracy in computing chi-square statistics. The proposed framework was evaluated for the task of chi-square statistic computation with two case-control datasets from the 2015 iDASH genome privacy protection challenge. Experimental results show that the performance of FORESEE can be significantly improved through algorithmic optimization and parallel computation. Remarkably, the secure approximation division provides significant performance gain, but without missing any significance SNPs in the chi-square association test using the aforementioned datasets. Unlike many existing HME based studies, in which final results need to be computed by the data owner due to the lack of the secure division operation, the proposed FORESEE framework support complete outsourcing to the cloud and output the final encrypted chi-square statistics.

Towards a Quantitative Endogenous Network Theory of Cancer Genesis and Progression: beyond ``cancer as diseases of genome''

NASA Astrophysics Data System (ADS)

Ao, Ping

2011-03-01

There has been a tremendous progress in cancer research. However, it appears the current dominant cancer research framework of regarding cancer as diseases of genome leads impasse. Naturally questions have been asked that whether it is possible to develop alternative frameworks such that they can connect both to mutations and other genetic/genomic effects and to environmental factors. Furthermore, such framework can be made quantitative and with predictions experimentally testable. In this talk, I will present a positive answer to this calling. I will explain on our construction of endogenous network theory based on molecular-cellular agencies as dynamical variable. Such cancer theory explicitly demonstrates a profound connection to many fundamental concepts in physics, as such stochastic non-equilibrium processes, ``energy'' landscape, metastability, etc. It suggests that neneath cancer's daunting complexity may lie a simplicity that gives grounds for hope. The rationales behind such theory, its predictions, and its initial experimental verifications will be presented. Supported by USA NIH and China NSF.

linkedISA: semantic representation of ISA-Tab experimental metadata.

PubMed

González-Beltrán, Alejandra; Maguire, Eamonn; Sansone, Susanna-Assunta; Rocca-Serra, Philippe

2014-01-01

Reporting and sharing experimental metadata- such as the experimental design, characteristics of the samples, and procedures applied, along with the analysis results, in a standardised manner ensures that datasets are comprehensible and, in principle, reproducible, comparable and reusable. Furthermore, sharing datasets in formats designed for consumption by humans and machines will also maximize their use. The Investigation/Study/Assay (ISA) open source metadata tracking framework facilitates standards-compliant collection, curation, visualization, storage and sharing of datasets, leveraging on other platforms to enable analysis and publication. The ISA software suite includes several components used in increasingly diverse set of life science and biomedical domains; it is underpinned by a general-purpose format, ISA-Tab, and conversions exist into formats required by public repositories. While ISA-Tab works well mainly as a human readable format, we have also implemented a linked data approach to semantically define the ISA-Tab syntax. We present a semantic web representation of the ISA-Tab syntax that complements ISA-Tab's syntactic interoperability with semantic interoperability. We introduce the linkedISA conversion tool from ISA-Tab to the Resource Description Framework (RDF), supporting mappings from the ISA syntax to multiple community-defined, open ontologies and capitalising on user-provided ontology annotations in the experimental metadata. We describe insights of the implementation and how annotations can be expanded driven by the metadata. We applied the conversion tool as part of Bio-GraphIIn, a web-based application supporting integration of the semantically-rich experimental descriptions. Designed in a user-friendly manner, the Bio-GraphIIn interface hides most of the complexities to the users, exposing a familiar tabular view of the experimental description to allow seamless interaction with the RDF representation, and visualising descriptors to drive the query over the semantic representation of the experimental design. In addition, we defined queries over the linkedISA RDF representation and demonstrated its use over the linkedISA conversion of datasets from Nature' Scientific Data online publication. Our linked data approach has allowed us to: 1) make the ISA-Tab semantics explicit and machine-processable, 2) exploit the existing ontology-based annotations in the ISA-Tab experimental descriptions, 3) augment the ISA-Tab syntax with new descriptive elements, 4) visualise and query elements related to the experimental design. Reasoning over ISA-Tab metadata and associated data will facilitate data integration and knowledge discovery.

Probabilistic cross-link analysis and experiment planning for high-throughput elucidation of protein structure.

PubMed

Ye, Xiaoduan; O'Neil, Patrick K; Foster, Adrienne N; Gajda, Michal J; Kosinski, Jan; Kurowski, Michal A; Bujnicki, Janusz M; Friedman, Alan M; Bailey-Kellogg, Chris

2004-12-01

Emerging high-throughput techniques for the characterization of protein and protein-complex structures yield noisy data with sparse information content, placing a significant burden on computation to properly interpret the experimental data. One such technique uses cross-linking (chemical or by cysteine oxidation) to confirm or select among proposed structural models (e.g., from fold recognition, ab initio prediction, or docking) by testing the consistency between cross-linking data and model geometry. This paper develops a probabilistic framework for analyzing the information content in cross-linking experiments, accounting for anticipated experimental error. This framework supports a mechanism for planning experiments to optimize the information gained. We evaluate potential experiment plans using explicit trade-offs among key properties of practical importance: discriminability, coverage, balance, ambiguity, and cost. We devise a greedy algorithm that considers those properties and, from a large number of combinatorial possibilities, rapidly selects sets of experiments expected to discriminate pairs of models efficiently. In an application to residue-specific chemical cross-linking, we demonstrate the ability of our approach to plan experiments effectively involving combinations of cross-linkers and introduced mutations. We also describe an experiment plan for the bacteriophage lambda Tfa chaperone protein in which we plan dicysteine mutants for discriminating threading models by disulfide formation. Preliminary results from a subset of the planned experiments are consistent and demonstrate the practicality of planning. Our methods provide the experimenter with a valuable tool (available from the authors) for understanding and optimizing cross-linking experiments.

Towards a whole-cell modeling approach for synthetic biology

NASA Astrophysics Data System (ADS)

Purcell, Oliver; Jain, Bonny; Karr, Jonathan R.; Covert, Markus W.; Lu, Timothy K.

2013-06-01

Despite rapid advances over the last decade, synthetic biology lacks the predictive tools needed to enable rational design. Unlike established engineering disciplines, the engineering of synthetic gene circuits still relies heavily on experimental trial-and-error, a time-consuming and inefficient process that slows down the biological design cycle. This reliance on experimental tuning is because current modeling approaches are unable to make reliable predictions about the in vivo behavior of synthetic circuits. A major reason for this lack of predictability is that current models view circuits in isolation, ignoring the vast number of complex cellular processes that impinge on the dynamics of the synthetic circuit and vice versa. To address this problem, we present a modeling approach for the design of synthetic circuits in the context of cellular networks. Using the recently published whole-cell model of Mycoplasma genitalium, we examined the effect of adding genes into the host genome. We also investigated how codon usage correlates with gene expression and find agreement with existing experimental results. Finally, we successfully implemented a synthetic Goodwin oscillator in the whole-cell model. We provide an updated software framework for the whole-cell model that lays the foundation for the integration of whole-cell models with synthetic gene circuit models. This software framework is made freely available to the community to enable future extensions. We envision that this approach will be critical to transforming the field of synthetic biology into a rational and predictive engineering discipline.

Investigation of Effective Strategies for Developing Creative Science Thinking

ERIC Educational Resources Information Center

Yang, Kuay-Keng; Lee, Ling; Hong, Zuway-R; Lin, Huann-shyang

2016-01-01

The purpose of this study was to explore the effectiveness of the creative inquiry-based science teaching on students' creative science thinking and science inquiry performance. A quasi-experimental design consisting one experimental group (N = 20) and one comparison group (N = 24) with pretest and post-test was conducted. The framework of the…

The Use of Techniques of Sensory Evaluation as a Framework for Teaching Experimental Methods.

ERIC Educational Resources Information Center

Bennett, R.; Hamilton, M.

1981-01-01

Describes sensory assessment techniques and conditions for their satisfactory performance, including how they can provide open-ended exercises and advantages as relatively inexpensive and simple methods of teaching experimentation. Experiments described focus on diffusion of salt into potatoes after being cooked in boiled salted water. (Author/JN)

Unpacking the Hidden Efficacies of Learning in Productive Failure

ERIC Educational Resources Information Center

Hung, David; Chen, Victor; Lim, Seo Hong

2009-01-01

This paper describes a framework for learning where learners undergo experimentations with the phenomena at hand according to progressive and staged goals. Bowling is used as a case study in this paper. The premise for experimentations is that learners can experience hidden efficacies, including the formation of "bad habits." A distinction is made…

Extending the boundaries of the Declaration of Helsinki: a case study of an unethical experiment in a non-medical setting

PubMed Central

Richter, E.; Barach, P.; Berman, T.; Ben-David, G; Weinberger, Z.

2001-01-01

To examine the ethical issues involved in governmental decisions with potential health risks, we review the history of the decision to raise the interurban speed limit in Israel in light of its impact on road death and injury. In 1993, the Israeli Ministry of Transportation initiated an "experiment" to raise the interurban speed limit from 90 to 100 kph. The "experiment" did not include a protocol and did not specify cut-off points for early termination in the case of adverse results. After the raise in the speed limit, the death toll on interurban roads rose as a result of a sudden increase in speeds and case fatality rates. The committee's decision is a case study in unfettered human experimentation and public health risks when the setting is non-medical and lacks a defined ethical framework. The case study states the case for extending Helsinki type safeguards to experimentation in non-medical settings. Key Words: Declaration of Helsinki • human experimentation • speed limit PMID:11314157

Experimental and theoretical study of magnetohydrodynamic ship models.

PubMed

Cébron, David; Viroulet, Sylvain; Vidal, Jérémie; Masson, Jean-Paul; Viroulet, Philippe

2017-01-01

Magnetohydrodynamic (MHD) ships represent a clear demonstration of the Lorentz force in fluids, which explains the number of students practicals or exercises described on the web. However, the related literature is rather specific and no complete comparison between theory and typical small scale experiments is currently available. This work provides, in a self-consistent framework, a detailed presentation of the relevant theoretical equations for small MHD ships and experimental measurements for future benchmarks. Theoretical results of the literature are adapted to these simple battery/magnets powered ships moving on salt water. Comparison between theory and experiments are performed to validate each theoretical step such as the Tafel and the Kohlrausch laws, or the predicted ship speed. A successful agreement is obtained without any adjustable parameter. Finally, based on these results, an optimal design is then deduced from the theory. Therefore this work provides a solid theoretical and experimental ground for small scale MHD ships, by presenting in detail several approximations and how they affect the boat efficiency. Moreover, the theory is general enough to be adapted to other contexts, such as large scale ships or industrial flow measurement techniques.

Transformation-Induced, Geometrically Necessary, Dislocation-Based Flow Curve Modeling of Dual-Phase Steels: Effect of Grain Size

NASA Astrophysics Data System (ADS)

Ramazani, Ali; Mukherjee, Krishnendu; Prahl, Ulrich; Bleck, Wolfgang

2012-10-01

The flow behavior of dual-phase (DP) steels is modeled on the finite-element method (FEM) framework on the microscale, considering the effect of the microstructure through the representative volume element (RVE) approach. Two-dimensional RVEs were created from microstructures of experimentally obtained DP steels with various ferrite grain sizes. The flow behavior of single phases was modeled through the dislocation-based work-hardening approach. The volume change during austenite-to-martensite transformation was modeled, and the resultant prestrained areas in the ferrite were considered to be the storage place of transformation-induced, geometrically necessary dislocations (GNDs). The flow curves of DP steels with varying ferrite grain sizes, but constant martensite fractions, were obtained from the literature. The flow curves of simulations that take into account the GND are in better agreement with those of experimental flow curves compared with those of predictions without consideration of the GND. The experimental results obeyed the Hall-Petch relationship between yield stress and flow stress and the simulations predicted this as well.

Experimental and theoretical study of magnetohydrodynamic ship models

PubMed Central

Viroulet, Sylvain; Vidal, Jérémie; Masson, Jean-Paul; Viroulet, Philippe

2017-01-01

Magnetohydrodynamic (MHD) ships represent a clear demonstration of the Lorentz force in fluids, which explains the number of students practicals or exercises described on the web. However, the related literature is rather specific and no complete comparison between theory and typical small scale experiments is currently available. This work provides, in a self-consistent framework, a detailed presentation of the relevant theoretical equations for small MHD ships and experimental measurements for future benchmarks. Theoretical results of the literature are adapted to these simple battery/magnets powered ships moving on salt water. Comparison between theory and experiments are performed to validate each theoretical step such as the Tafel and the Kohlrausch laws, or the predicted ship speed. A successful agreement is obtained without any adjustable parameter. Finally, based on these results, an optimal design is then deduced from the theory. Therefore this work provides a solid theoretical and experimental ground for small scale MHD ships, by presenting in detail several approximations and how they affect the boat efficiency. Moreover, the theory is general enough to be adapted to other contexts, such as large scale ships or industrial flow measurement techniques. PMID:28665941

Identifying the perceptive users for online social systems

PubMed Central

Liu, Xiao-Lu; Guo, Qiang; Han, Jing-Ti

2017-01-01

In this paper, the perceptive user, who could identify the high-quality objects in their initial lifespan, is presented. By tracking the ratings given to the rewarded objects, we present a method to identify the user perceptibility, which is defined as the capability that a user can identify these objects at their early lifespan. Moreover, we investigate the behavior patterns of the perceptive users from three dimensions: User activity, correlation characteristics of user rating series and user reputation. The experimental results for the empirical networks indicate that high perceptibility users show significantly different behavior patterns with the others: Having larger degree, stronger correlation of rating series and higher reputation. Furthermore, in view of the hysteresis in finding the rewarded objects, we present a general framework for identifying the high perceptibility users based on user behavior patterns. The experimental results show that this work is helpful for deeply understanding the collective behavior patterns for online users. PMID:28704382

Identifying the perceptive users for online social systems.

PubMed

Liu, Jian-Guo; Liu, Xiao-Lu; Guo, Qiang; Han, Jing-Ti

2017-01-01

In this paper, the perceptive user, who could identify the high-quality objects in their initial lifespan, is presented. By tracking the ratings given to the rewarded objects, we present a method to identify the user perceptibility, which is defined as the capability that a user can identify these objects at their early lifespan. Moreover, we investigate the behavior patterns of the perceptive users from three dimensions: User activity, correlation characteristics of user rating series and user reputation. The experimental results for the empirical networks indicate that high perceptibility users show significantly different behavior patterns with the others: Having larger degree, stronger correlation of rating series and higher reputation. Furthermore, in view of the hysteresis in finding the rewarded objects, we present a general framework for identifying the high perceptibility users based on user behavior patterns. The experimental results show that this work is helpful for deeply understanding the collective behavior patterns for online users.

Light-optimized growth of cyanobacterial cultures: Growth phases and productivity of biomass and secreted molecules in light-limited batch growth.

PubMed

Clark, Ryan L; McGinley, Laura L; Purdy, Hugh M; Korosh, Travis C; Reed, Jennifer L; Root, Thatcher W; Pfleger, Brian F

2018-03-27

Cyanobacteria are photosynthetic microorganisms whose metabolism can be modified through genetic engineering for production of a wide variety of molecules directly from CO 2 , light, and nutrients. Diverse molecules have been produced in small quantities by engineered cyanobacteria to demonstrate the feasibility of photosynthetic biorefineries. Consequently, there is interest in engineering these microorganisms to increase titer and productivity to meet industrial metrics. Unfortunately, differing experimental conditions and cultivation techniques confound comparisons of strains and metabolic engineering strategies. In this work, we discuss the factors governing photoautotrophic growth and demonstrate nutritionally replete conditions in which a model cyanobacterium can be grown to stationary phase with light as the sole limiting substrate. We introduce a mathematical framework for understanding the dynamics of growth and product secretion in light-limited cyanobacterial cultures. Using this framework, we demonstrate how cyanobacterial growth in differing experimental systems can be easily scaled by the volumetric photon delivery rate using the model organisms Synechococcus sp. strain PCC7002 and Synechococcus elongatus strain UTEX2973. We use this framework to predict scaled up growth and product secretion in 1L photobioreactors of two strains of Synechococcus PCC7002 engineered for production of l-lactate or L-lysine. The analytical framework developed in this work serves as a guide for future metabolic engineering studies of cyanobacteria to allow better comparison of experiments performed in different experimental systems and to further investigate the dynamics of growth and product secretion. Copyright © 2018 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Applications of system identification methods to the prediction of helicopter stability, control and handling characteristics

NASA Technical Reports Server (NTRS)

Padfield, G. D.; Duval, R. K.

1982-01-01

A set of results on rotorcraft system identification is described. Flight measurements collected on an experimental Puma helicopter are reviewed and some notable characteristics highlighted. Following a brief review of previous work in rotorcraft system identification, the results of state estimation and model structure estimation processes applied to the Puma data are presented. The results, which were obtained using NASA developed software, are compared with theoretical predictions of roll, yaw and pitching moment derivatives for a 6 degree of freedom model structure. Anomalies are reported. The theoretical methods used are described. A framework for reduced order modelling is outlined.

New approach for determination of the influence of long-range order and selected ring oscillations on IR spectra in zeolites

NASA Astrophysics Data System (ADS)

Mikuła, Andrzej; Król, Magdalena; Mozgawa, Włodzimierz; Koleżyński, Andrzej

2018-04-01

Vibrational spectroscopy can be considered as one of the most important methods used for structural characterization of various porous aluminosilicate materials, including zeolites. On the other hand, vibrational spectra of zeolites are still difficult to interpret, particularly in the pseudolattice region, where bands related to ring oscillations can be observed. Using combination of theoretical and computational approach, a detailed analysis of these regions of spectra is possible; such analysis should be, however, carried out employing models with different level of complexity and simultaneously the same theory level. In this work, an attempt was made to identify ring oscillations in vibrational spectra of selected zeolite structures. A series of ab initio calculations focused on S4R, S6R, and as a novelty, 5-1 isolated clusters, as well as periodic siliceous frameworks built from those building units (ferrierite (FER), mordenite (MOR) and heulandite (HEU) type) have been carried out. Due to the hierarchical structure of zeolite frameworks it can be expected that the total envelope of the zeolite spectra should be with good accuracy a sum of the spectra of structural elements that build each zeolite framework. Based on the results of HF calculations, normal vibrations have been visualized and detailed analysis of pseudolattice range of resulting theoretical spectra have been carried out. Obtained results have been applied for interpretation of experimental spectra of selected zeolites.

Secure and Efficient Regression Analysis Using a Hybrid Cryptographic Framework: Development and Evaluation.

PubMed

Sadat, Md Nazmus; Jiang, Xiaoqian; Aziz, Md Momin Al; Wang, Shuang; Mohammed, Noman

2018-03-05

Machine learning is an effective data-driven tool that is being widely used to extract valuable patterns and insights from data. Specifically, predictive machine learning models are very important in health care for clinical data analysis. The machine learning algorithms that generate predictive models often require pooling data from different sources to discover statistical patterns or correlations among different attributes of the input data. The primary challenge is to fulfill one major objective: preserving the privacy of individuals while discovering knowledge from data. Our objective was to develop a hybrid cryptographic framework for performing regression analysis over distributed data in a secure and efficient way. Existing secure computation schemes are not suitable for processing the large-scale data that are used in cutting-edge machine learning applications. We designed, developed, and evaluated a hybrid cryptographic framework, which can securely perform regression analysis, a fundamental machine learning algorithm using somewhat homomorphic encryption and a newly introduced secure hardware component of Intel Software Guard Extensions (Intel SGX) to ensure both privacy and efficiency at the same time. Experimental results demonstrate that our proposed method provides a better trade-off in terms of security and efficiency than solely secure hardware-based methods. Besides, there is no approximation error. Computed model parameters are exactly similar to plaintext results. To the best of our knowledge, this kind of secure computation model using a hybrid cryptographic framework, which leverages both somewhat homomorphic encryption and Intel SGX, is not proposed or evaluated to this date. Our proposed framework ensures data security and computational efficiency at the same time. ©Md Nazmus Sadat, Xiaoqian Jiang, Md Momin Al Aziz, Shuang Wang, Noman Mohammed. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 05.03.2018.

Metadata management and semantics in microarray repositories.

PubMed

Kocabaş, F; Can, T; Baykal, N

2011-12-01

The number of microarray and other high-throughput experiments on primary repositories keeps increasing as do the size and complexity of the results in response to biomedical investigations. Initiatives have been started on standardization of content, object model, exchange format and ontology. However, there are backlogs and inability to exchange data between microarray repositories, which indicate that there is a great need for a standard format and data management. We have introduced a metadata framework that includes a metadata card and semantic nets that make experimental results visible, understandable and usable. These are encoded in syntax encoding schemes and represented in RDF (Resource Description Frame-word), can be integrated with other metadata cards and semantic nets, and can be exchanged, shared and queried. We demonstrated the performance and potential benefits through a case study on a selected microarray repository. We concluded that the backlogs can be reduced and that exchange of information and asking of knowledge discovery questions can become possible with the use of this metadata framework.

Influencing Republicans' and Democrats' attitudes toward Obamacare: Effects of imagined vicarious cognitive dissonance on political attitudes.

PubMed

Cooper, Joel; Feldman, Lauren A; Blackman, Shane F

2018-04-16

The field of experimental social psychology is appropriately interested in using novel theoretical approaches to implement change in the social world. In the current study, we extended cognitive dissonance theory by creating a new framework of social influence: imagined vicarious dissonance. We used the framework to influence attitudes on an important and controversial political attitude: U.S. citizens' support for the Affordable Care Act (ACA). 36 Republicans and 84 Democrats were asked to imagine fellow Republicans and Democrats, respectively, making attitude discrepant statements under high and low choice conditions about support for the ACA. The data showed that vicarious dissonance, established by imagining a group member make a counterattitudinal speech under high-choice conditions (as compared to low-choice conditions), resulted in greater support for the Act by Republicans and marginally diminished support by Democrats. The results suggest a promising role for the application of vicarious dissonance theory to relevant societal issues and for further understanding the relationship of dissonance and people's identification with their social groups.

The Aeroacoustics of Turbulent Flows

NASA Technical Reports Server (NTRS)

Goldstein, M. E.

2008-01-01

Aerodynamic noise prediction has been an important and challenging research area since James Lighthill first introduced his Acoustic Analogy Approach over fifty years ago. This talk attempts to provide a unified framework for the subsequent theoretical developments in this field. It assumes that there is no single approach that is optimal in all situations and uses the framework as a basis for discussing the strengths weaknesses of the various approaches to this topic. But the emphasis here will be on the important problem of predicting the noise from high speed air jets. Specific results will presented for round jets in the 0.5 to 1.4 Mach number range and compared with experimental data taken on the Glenn SHAR rig. It is demonstrated that nonparallel mean flow effects play an important role in predicting the noise at the supersonic Mach numbers. The results explain the failure of previous attempts based on the parallel flow Lilley model (which has served as the foundation for most jet noise analyses during past two decades).

HERAFitter: Open source QCD fit project

DOE PAGES

Alekhin, S.; Behnke, O.; Belov, P.; ...

2015-07-01

HERAFitter is an open-source package that provides a framework for the determination of the parton distribution functions (PDFs) of the proton and for many different kinds of analyses in Quantum Chromodynamics (QCD). It encodes results from a wide range of experimental measurements in lepton-proton deep inelastic scattering and proton-proton (proton-antiproton) collisions at hadron colliders. These are complemented with a variety of theoretical options for calculating PDF-dependent cross section predictions corresponding to the measurements. The framework covers a large number of the existing methods and schemes used for PDF determination. The data and theoretical predictions are brought together through numerous methodologicalmore » options for carrying out PDF fits and plotting tools to help visualise the results. While primarily based on the approach of collinear factorisation, HERAFitter also provides facilities for fits of dipole models and transverse-momentum dependent PDFs. The package can be used to study the impact of new precise measurements from hadron colliders. This paper describes the general structure of HERAFitter and its wide choice of options.« less

Accurate van der Waals force field for gas adsorption in porous materials.

PubMed

Sun, Lei; Yang, Li; Zhang, Ya-Dong; Shi, Qi; Lu, Rui-Feng; Deng, Wei-Qiao

2017-09-05

An accurate van der Waals force field (VDW FF) was derived from highly precise quantum mechanical (QM) calculations. Small molecular clusters were used to explore van der Waals interactions between gas molecules and porous materials. The parameters of the accurate van der Waals force field were determined by QM calculations. To validate the force field, the prediction results from the VDW FF were compared with standard FFs, such as UFF, Dreiding, Pcff, and Compass. The results from the VDW FF were in excellent agreement with the experimental measurements. This force field can be applied to the prediction of the gas density (H 2 , CO 2 , C 2 H 4 , CH 4 , N 2 , O 2 ) and adsorption performance inside porous materials, such as covalent organic frameworks (COFs), zeolites and metal organic frameworks (MOFs), consisting of H, B, N, C, O, S, Si, Al, Zn, Mg, Ni, and Co. This work provides a solid basis for studying gas adsorption in porous materials. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Probing adsorption sites of carbon dioxide in metal organic framework of [Zn(bdc)(dpds)]n: A molecular simulation study

NASA Astrophysics Data System (ADS)

Lu, Shih-I.; Liao, Jian-Min; Huang, Xiao-Zhuang; Lin, Chia-Hsun; Ke, Szu-Yu; Wang, Chih-Chieh

2017-11-01

We used force-field based grand-canonical Monte Carlo simulation method and density functional theory to study adsorption characteristics of carbon dioxide (CO2) molecules in a metal-organic framework (MOF) compound, [Zn(bdc)(dpds)]n. The studied MOF include a metal ion (Zn(II)), an anion organic linker (dianion of benzene dicarboxylicacid, bdc2-) and a neutral organic linker (4,4‧-dipyridyldisulfide, dpds). Results from calculated adsorption isotherms and enthalpies of adsorption agree with the experimental data. The interactions between the adsorbed CO2 and the organic linkers were examined in simulations. Calculated results show available absorption sites are surrounded by two dpds ligands in which an S-S bond as an N-N‧ spacer connect two pyridines. In contrast, the bdc2- ligand does not give a significant contribution to the substantial adsorption amount even though it contains the carboxylate group that provides available bonding site to CO2.

Game theoretic approach for cooperative feature extraction in camera networks

NASA Astrophysics Data System (ADS)

Redondi, Alessandro E. C.; Baroffio, Luca; Cesana, Matteo; Tagliasacchi, Marco

2016-07-01

Visual sensor networks (VSNs) consist of several camera nodes with wireless communication capabilities that can perform visual analysis tasks such as object identification, recognition, and tracking. Often, VSN deployments result in many camera nodes with overlapping fields of view. In the past, such redundancy has been exploited in two different ways: (1) to improve the accuracy/quality of the visual analysis task by exploiting multiview information or (2) to reduce the energy consumed for performing the visual task, by applying temporal scheduling techniques among the cameras. We propose a game theoretic framework based on the Nash bargaining solution to bridge the gap between the two aforementioned approaches. The key tenet of the proposed framework is for cameras to reduce the consumed energy in the analysis process by exploiting the redundancy in the reciprocal fields of view. Experimental results in both simulated and real-life scenarios confirm that the proposed scheme is able to increase the network lifetime, with a negligible loss in terms of visual analysis accuracy.

A Content-Adaptive Analysis and Representation Framework for Audio Event Discovery from "Unscripted" Multimedia

NASA Astrophysics Data System (ADS)

Radhakrishnan, Regunathan; Divakaran, Ajay; Xiong, Ziyou; Otsuka, Isao

2006-12-01

We propose a content-adaptive analysis and representation framework to discover events using audio features from "unscripted" multimedia such as sports and surveillance for summarization. The proposed analysis framework performs an inlier/outlier-based temporal segmentation of the content. It is motivated by the observation that "interesting" events in unscripted multimedia occur sparsely in a background of usual or "uninteresting" events. We treat the sequence of low/mid-level features extracted from the audio as a time series and identify subsequences that are outliers. The outlier detection is based on eigenvector analysis of the affinity matrix constructed from statistical models estimated from the subsequences of the time series. We define the confidence measure on each of the detected outliers as the probability that it is an outlier. Then, we establish a relationship between the parameters of the proposed framework and the confidence measure. Furthermore, we use the confidence measure to rank the detected outliers in terms of their departures from the background process. Our experimental results with sequences of low- and mid-level audio features extracted from sports video show that "highlight" events can be extracted effectively as outliers from a background process using the proposed framework. We proceed to show the effectiveness of the proposed framework in bringing out suspicious events from surveillance videos without any a priori knowledge. We show that such temporal segmentation into background and outliers, along with the ranking based on the departure from the background, can be used to generate content summaries of any desired length. Finally, we also show that the proposed framework can be used to systematically select "key audio classes" that are indicative of events of interest in the chosen domain.

Initial Demonstration of the Real-Time Safety Monitoring Framework for the National Airspace System Using Flight Data

NASA Technical Reports Server (NTRS)

Roychoudhury, Indranil; Daigle, Matthew; Goebel, Kai; Spirkovska, Lilly; Sankararaman, Shankar; Ossenfort, John; Kulkarni, Chetan; McDermott, William; Poll, Scott

2016-01-01

As new operational paradigms and additional aircraft are being introduced into the National Airspace System (NAS), maintaining safety in such a rapidly growing environment becomes more challenging. It is therefore desirable to have an automated framework to provide an overview of the current safety of the airspace at different levels of granularity, as well an understanding of how the state of the safety will evolve into the future given the anticipated flight plans, weather forecast, predicted health of assets in the airspace, and so on. Towards this end, as part of our earlier work, we formulated the Real-Time Safety Monitoring (RTSM) framework for monitoring and predicting the state of safety and to predict unsafe events. In our previous work, the RTSM framework was demonstrated in simulation on three different constructed scenarios. In this paper, we further develop the framework and demonstrate it on real flight data from multiple data sources. Specifically, the flight data is obtained through the Shadow Mode Assessment using Realistic Technologies for the National Airspace System (SMART-NAS) Testbed that serves as a central point of collection, integration, and access of information from these different data sources. By testing and evaluating using real-world scenarios, we may accelerate the acceptance of the RTSM framework towards deployment. In this paper we demonstrate the framework's capability to not only estimate the state of safety in the NAS, but predict the time and location of unsafe events such as a loss of separation between two aircraft, or an aircraft encountering convective weather. The experimental results highlight the capability of the approach, and the kind of information that can be provided to operators to improve their situational awareness in the context of safety.

A nonproprietary, nonsecret program for calculating Stirling cryocoolers

NASA Technical Reports Server (NTRS)

Martini, W. R.

1985-01-01

A design program for an integrated Stirling cycle cryocooler was written on an IBM-PC computer. The program is easy to use and shows the trends and itemizes the losses. The calculated results were compared with some measured performance values. The program predicts somewhat optimistic performance and needs to be calibrated more with experimental measurements. Adding a multiplier to the friction factor can bring the calculated rsults in line with the limited test results so far available. The program is offered as a good framework on which to build a truly useful design program for all types of cryocoolers.

Developments and Validations of Fully Coupled CFD and Practical Vortex Transport Method for High-Fidelity Wake Modeling in Fixed and Rotary Wing Applications

NASA Technical Reports Server (NTRS)

Anusonti-Inthra, Phuriwat

2010-01-01

A novel Computational Fluid Dynamics (CFD) coupling framework using a conventional Reynolds-Averaged Navier-Stokes (BANS) solver to resolve the near-body flow field and a Particle-based Vorticity Transport Method (PVTM) to predict the evolution of the far field wake is developed, refined, and evaluated for fixed and rotary wing cases. For the rotary wing case, the RANS/PVTM modules are loosely coupled to a Computational Structural Dynamics (CSD) module that provides blade motion and vehicle trim information. The PVTM module is refined by the addition of vortex diffusion, stretching, and reorientation models as well as an efficient memory model. Results from the coupled framework are compared with several experimental data sets (a fixed-wing wind tunnel test and a rotary-wing hover test).

Structured sparse linear graph embedding.

PubMed

Wang, Haixian

2012-03-01

Subspace learning is a core issue in pattern recognition and machine learning. Linear graph embedding (LGE) is a general framework for subspace learning. In this paper, we propose a structured sparse extension to LGE (SSLGE) by introducing a structured sparsity-inducing norm into LGE. Specifically, SSLGE casts the projection bases learning into a regression-type optimization problem, and then the structured sparsity regularization is applied to the regression coefficients. The regularization selects a subset of features and meanwhile encodes high-order information reflecting a priori structure information of the data. The SSLGE technique provides a unified framework for discovering structured sparse subspace. Computationally, by using a variational equality and the Procrustes transformation, SSLGE is efficiently solved with closed-form updates. Experimental results on face image show the effectiveness of the proposed method. Copyright © 2011 Elsevier Ltd. All rights reserved.

Model of dissolution in the framework of tissue engineering and drug delivery.

PubMed

Sanz-Herrera, J A; Soria, L; Reina-Romo, E; Torres, Y; Boccaccini, A R

2018-05-22

Dissolution phenomena are ubiquitously present in biomaterials in many different fields. Despite the advantages of simulation-based design of biomaterials in medical applications, additional efforts are needed to derive reliable models which describe the process of dissolution. A phenomenologically based model, available for simulation of dissolution in biomaterials, is introduced in this paper. The model turns into a set of reaction-diffusion equations implemented in a finite element numerical framework. First, a parametric analysis is conducted in order to explore the role of model parameters on the overall dissolution process. Then, the model is calibrated and validated versus a straightforward but rigorous experimental setup. Results show that the mathematical model macroscopically reproduces the main physicochemical phenomena that take place in the tests, corroborating its usefulness for design of biomaterials in the tissue engineering and drug delivery research areas.

Implementation of data node in spatial information grid based on WS resource framework and WS notification

NASA Astrophysics Data System (ADS)

Zhang, Dengrong; Yu, Le

2006-10-01

Abstract-An approach of constructing a data node in spatial information grid (SIG) based on Web Service Resource Framework (WSRF) and Web Service Notification (WSN) is described in this paper. Attentions are paid to construct and implement SIG's resource layer, which is the most important part. A study on this layer find out, it is impossible to require persistent interaction with the clients of the services in common SIG architecture because of inheriting "stateless" and "not persistent" limitations of Web Service. A WSRF/WSN-based data node is designed to hurdle this short comes. Three different access modes are employed to test the availability of this node. Experimental results demonstrate this service node can successfully respond to standard OGC requests and returns specific spatial data in different network environment, also is stateful, dynamic and persistent.

Study on Building Extraction from High-Resolution Images Using Mbi

NASA Astrophysics Data System (ADS)

Ding, Z.; Wang, X. Q.; Li, Y. L.; Zhang, S. S.

2018-04-01

Building extraction from high resolution remote sensing images is a hot research topic in the field of photogrammetry and remote sensing. However, the diversity and complexity of buildings make building extraction methods still face challenges in terms of accuracy, efficiency, and so on. In this study, a new building extraction framework based on MBI and combined with image segmentation techniques, spectral constraint, shadow constraint, and shape constraint is proposed. In order to verify the proposed method, worldview-2, GF-2, GF-1 remote sensing images covered Xiamen Software Park were used for building extraction experiments. Experimental results indicate that the proposed method improve the original MBI significantly, and the correct rate is over 86 %. Furthermore, the proposed framework reduces the false alarms by 42 % on average compared to the performance of the original MBI.

A Decision Fusion Framework for Treatment Recommendation Systems.

PubMed

Mei, Jing; Liu, Haifeng; Li, Xiang; Xie, Guotong; Yu, Yiqin

2015-01-01

Treatment recommendation is a nontrivial task--it requires not only domain knowledge from evidence-based medicine, but also data insights from descriptive, predictive and prescriptive analysis. A single treatment recommendation system is usually trained or modeled with a limited (size or quality) source. This paper proposes a decision fusion framework, combining both knowledge-driven and data-driven decision engines for treatment recommendation. End users (e.g. using the clinician workstation or mobile apps) could have a comprehensive view of various engines' opinions, as well as the final decision after fusion. For implementation, we leverage several well-known fusion algorithms, such as decision templates and meta classifiers (of logistic and SVM, etc.). Using an outcome-driven evaluation metric, we compare the fusion engine with base engines, and our experimental results show that decision fusion is a promising way towards a more valuable treatment recommendation.

Transport Phenomena During Equiaxed Solidification of Alloys

NASA Technical Reports Server (NTRS)

Beckermann, C.; deGroh, H. C., III

1997-01-01

Recent progress in modeling of transport phenomena during dendritic alloy solidification is reviewed. Starting from the basic theorems of volume averaging, a general multiphase modeling framework is outlined. This framework allows for the incorporation of a variety of microscale phenomena in the macroscopic transport equations. For the case of diffusion dominated solidification, a simplified set of model equations is examined in detail and validated through comparisons with numerous experimental data for both columnar and equiaxed dendritic growth. This provides a critical assessment of the various model assumptions. Models that include melt flow and solid phase transport are also discussed, although their validation is still at an early stage. Several numerical results are presented that illustrate some of the profound effects of convective transport on the final compositional and structural characteristics of a solidified part. Important issues that deserve continuing attention are identified.

Electrical percolation in the presence of attractive interactions: An effective medium lattice approach applied to microemulsion systems

NASA Astrophysics Data System (ADS)

Hattori, Y.; Ushiki, H.; Engl, W.; Courbin, L.; Panizza, P.

2005-08-01

Within the framework of an effective medium approach and a mean-field approximation, we present a simple lattice model to treat electrical percolation in the presence of attractive interactions. We show that the percolation line depends on the magnitude of interactions. In 2 dimensions, the percolation line meets the binodal line at the critical point. A good qualitative agreement is observed with experimental results on a ternary AOT-based water-in-oil microemulsion system.

A Subband Coding Method for HDTV

NASA Technical Reports Server (NTRS)

Chung, Wilson; Kossentini, Faouzi; Smith, Mark J. T.

1995-01-01

This paper introduces a new HDTV coder based on motion compensation, subband coding, and high order conditional entropy coding. The proposed coder exploits the temporal and spatial statistical dependencies inherent in the HDTV signal by using intra- and inter-subband conditioning for coding both the motion coordinates and the residual signal. The new framework provides an easy way to control the system complexity and performance, and inherently supports multiresolution transmission. Experimental results show that the coder outperforms MPEG-2, while still maintaining relatively low complexity.

Comment on 'Entropy lowering in ion-atom collisions'

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

Ostrovsky, V. N.

2006-01-15

The recent experimental result by Nguyen et al. [Phys. Rev. A 71, 062714 (2005)] on the ratio of cross sections for charge exchange processes Rb{sup +}+Rb(5s){yields}Rb(5p)+Rb{sup +} and Rb{sup +}+Rb(5p){yields}Rb(5s)+Rb{sup +} is quantitatively derived from simple considerations within the general framework of the quasimolecular theory. Contrary to the expectations, applicability of the Demkov model for charge exchange with small energy defect is not shattered.

Epileptic seizure detection in EEG signal with GModPCA and support vector machine.

PubMed

Jaiswal, Abeg Kumar; Banka, Haider

2017-01-01

Epilepsy is one of the most common neurological disorders caused by recurrent seizures. Electroencephalograms (EEGs) record neural activity and can detect epilepsy. Visual inspection of an EEG signal for epileptic seizure detection is a time-consuming process and may lead to human error; therefore, recently, a number of automated seizure detection frameworks were proposed to replace these traditional methods. Feature extraction and classification are two important steps in these procedures. Feature extraction focuses on finding the informative features that could be used for classification and correct decision-making. Therefore, proposing effective feature extraction techniques for seizure detection is of great significance. Principal Component Analysis (PCA) is a dimensionality reduction technique used in different fields of pattern recognition including EEG signal classification. Global modular PCA (GModPCA) is a variation of PCA. In this paper, an effective framework with GModPCA and Support Vector Machine (SVM) is presented for epileptic seizure detection in EEG signals. The feature extraction is performed with GModPCA, whereas SVM trained with radial basis function kernel performed the classification between seizure and nonseizure EEG signals. Seven different experimental cases were conducted on the benchmark epilepsy EEG dataset. The system performance was evaluated using 10-fold cross-validation. In addition, we prove analytically that GModPCA has less time and space complexities as compared to PCA. The experimental results show that EEG signals have strong inter-sub-pattern correlations. GModPCA and SVM have been able to achieve 100% accuracy for the classification between normal and epileptic signals. Along with this, seven different experimental cases were tested. The classification results of the proposed approach were better than were compared the results of some of the existing methods proposed in literature. It is also found that the time and space complexities of GModPCA are less as compared to PCA. This study suggests that GModPCA and SVM could be used for automated epileptic seizure detection in EEG signal.

Ethnicity identification from face images

NASA Astrophysics Data System (ADS)

Lu, Xiaoguang; Jain, Anil K.

2004-08-01

Human facial images provide the demographic information, such as ethnicity and gender. Conversely, ethnicity and gender also play an important role in face-related applications. Image-based ethnicity identification problem is addressed in a machine learning framework. The Linear Discriminant Analysis (LDA) based scheme is presented for the two-class (Asian vs. non-Asian) ethnicity classification task. Multiscale analysis is applied to the input facial images. An ensemble framework, which integrates the LDA analysis for the input face images at different scales, is proposed to further improve the classification performance. The product rule is used as the combination strategy in the ensemble. Experimental results based on a face database containing 263 subjects (2,630 face images, with equal balance between the two classes) are promising, indicating that LDA and the proposed ensemble framework have sufficient discriminative power for the ethnicity classification problem. The normalized ethnicity classification scores can be helpful in the facial identity recognition. Useful as a "soft" biometric, face matching scores can be updated based on the output of ethnicity classification module. In other words, ethnicity classifier does not have to be perfect to be useful in practice.

A Component-Based FPGA Design Framework for Neuronal Ion Channel Dynamics Simulations

PubMed Central

Mak, Terrence S. T.; Rachmuth, Guy; Lam, Kai-Pui; Poon, Chi-Sang

2008-01-01

Neuron-machine interfaces such as dynamic clamp and brain-implantable neuroprosthetic devices require real-time simulations of neuronal ion channel dynamics. Field Programmable Gate Array (FPGA) has emerged as a high-speed digital platform ideal for such application-specific computations. We propose an efficient and flexible component-based FPGA design framework for neuronal ion channel dynamics simulations, which overcomes certain limitations of the recently proposed memory-based approach. A parallel processing strategy is used to minimize computational delay, and a hardware-efficient factoring approach for calculating exponential and division functions in neuronal ion channel models is used to conserve resource consumption. Performances of the various FPGA design approaches are compared theoretically and experimentally in corresponding implementations of the AMPA and NMDA synaptic ion channel models. Our results suggest that the component-based design framework provides a more memory economic solution as well as more efficient logic utilization for large word lengths, whereas the memory-based approach may be suitable for time-critical applications where a higher throughput rate is desired. PMID:17190033

Multiview human activity recognition system based on spatiotemporal template for video surveillance system

NASA Astrophysics Data System (ADS)

Kushwaha, Alok Kumar Singh; Srivastava, Rajeev

2015-09-01

An efficient view invariant framework for the recognition of human activities from an input video sequence is presented. The proposed framework is composed of three consecutive modules: (i) detect and locate people by background subtraction, (ii) view invariant spatiotemporal template creation for different activities, (iii) and finally, template matching is performed for view invariant activity recognition. The foreground objects present in a scene are extracted using change detection and background modeling. The view invariant templates are constructed using the motion history images and object shape information for different human activities in a video sequence. For matching the spatiotemporal templates for various activities, the moment invariants and Mahalanobis distance are used. The proposed approach is tested successfully on our own viewpoint dataset, KTH action recognition dataset, i3DPost multiview dataset, MSR viewpoint action dataset, VideoWeb multiview dataset, and WVU multiview human action recognition dataset. From the experimental results and analysis over the chosen datasets, it is observed that the proposed framework is robust, flexible, and efficient with respect to multiple views activity recognition, scale, and phase variations.

Non-lambertian reflectance modeling and shape recovery of faces using tensor splines.

PubMed

Kumar, Ritwik; Barmpoutis, Angelos; Banerjee, Arunava; Vemuri, Baba C

2011-03-01

Modeling illumination effects and pose variations of a face is of fundamental importance in the field of facial image analysis. Most of the conventional techniques that simultaneously address both of these problems work with the Lambertian assumption and thus fall short of accurately capturing the complex intensity variation that the facial images exhibit or recovering their 3D shape in the presence of specularities and cast shadows. In this paper, we present a novel Tensor-Spline-based framework for facial image analysis. We show that, using this framework, the facial apparent BRDF field can be accurately estimated while seamlessly accounting for cast shadows and specularities. Further, using local neighborhood information, the same framework can be exploited to recover the 3D shape of the face (to handle pose variation). We quantitatively validate the accuracy of the Tensor Spline model using a more general model based on the mixture of single-lobed spherical functions. We demonstrate the effectiveness of our technique by presenting extensive experimental results for face relighting, 3D shape recovery, and face recognition using the Extended Yale B and CMU PIE benchmark data sets.

Unified framework for automated iris segmentation using distantly acquired face images.

PubMed

Tan, Chun-Wei; Kumar, Ajay

2012-09-01

Remote human identification using iris biometrics has high civilian and surveillance applications and its success requires the development of robust segmentation algorithm to automatically extract the iris region. This paper presents a new iris segmentation framework which can robustly segment the iris images acquired using near infrared or visible illumination. The proposed approach exploits multiple higher order local pixel dependencies to robustly classify the eye region pixels into iris or noniris regions. Face and eye detection modules have been incorporated in the unified framework to automatically provide the localized eye region from facial image for iris segmentation. We develop robust postprocessing operations algorithm to effectively mitigate the noisy pixels caused by the misclassification. Experimental results presented in this paper suggest significant improvement in the average segmentation errors over the previously proposed approaches, i.e., 47.5%, 34.1%, and 32.6% on UBIRIS.v2, FRGC, and CASIA.v4 at-a-distance databases, respectively. The usefulness of the proposed approach is also ascertained from recognition experiments on three different publicly available databases.

GeoSegmenter: A statistically learned Chinese word segmenter for the geoscience domain

NASA Astrophysics Data System (ADS)

Huang, Lan; Du, Youfu; Chen, Gongyang

2015-03-01

Unlike English, the Chinese language has no space between words. Segmenting texts into words, known as the Chinese word segmentation (CWS) problem, thus becomes a fundamental issue for processing Chinese documents and the first step in many text mining applications, including information retrieval, machine translation and knowledge acquisition. However, for the geoscience subject domain, the CWS problem remains unsolved. Although a generic segmenter can be applied to process geoscience documents, they lack the domain specific knowledge and consequently their segmentation accuracy drops dramatically. This motivated us to develop a segmenter specifically for the geoscience subject domain: the GeoSegmenter. We first proposed a generic two-step framework for domain specific CWS. Following this framework, we built GeoSegmenter using conditional random fields, a principled statistical framework for sequence learning. Specifically, GeoSegmenter first identifies general terms by using a generic baseline segmenter. Then it recognises geoscience terms by learning and applying a model that can transform the initial segmentation into the goal segmentation. Empirical experimental results on geoscience documents and benchmark datasets showed that GeoSegmenter could effectively recognise both geoscience terms and general terms.

Reconstructing constructivism: causal models, Bayesian learning mechanisms, and the theory theory.

PubMed

Gopnik, Alison; Wellman, Henry M

2012-11-01

We propose a new version of the "theory theory" grounded in the computational framework of probabilistic causal models and Bayesian learning. Probabilistic models allow a constructivist but rigorous and detailed approach to cognitive development. They also explain the learning of both more specific causal hypotheses and more abstract framework theories. We outline the new theoretical ideas, explain the computational framework in an intuitive and nontechnical way, and review an extensive but relatively recent body of empirical results that supports these ideas. These include new studies of the mechanisms of learning. Children infer causal structure from statistical information, through their own actions on the world and through observations of the actions of others. Studies demonstrate these learning mechanisms in children from 16 months to 4 years old and include research on causal statistical learning, informal experimentation through play, and imitation and informal pedagogy. They also include studies of the variability and progressive character of intuitive theory change, particularly theory of mind. These studies investigate both the physical and the psychological and social domains. We conclude with suggestions for further collaborative projects between developmental and computational cognitive scientists.

A decomposition model and voxel selection framework for fMRI analysis to predict neural response of visual stimuli.

PubMed

Raut, Savita V; Yadav, Dinkar M

2018-03-28

This paper presents an fMRI signal analysis methodology using geometric mean curve decomposition (GMCD) and mutual information-based voxel selection framework. Previously, the fMRI signal analysis has been conducted using empirical mean curve decomposition (EMCD) model and voxel selection on raw fMRI signal. The erstwhile methodology loses frequency component, while the latter methodology suffers from signal redundancy. Both challenges are addressed by our methodology in which the frequency component is considered by decomposing the raw fMRI signal using geometric mean rather than arithmetic mean and the voxels are selected from EMCD signal using GMCD components, rather than raw fMRI signal. The proposed methodologies are adopted for predicting the neural response. Experimentations are conducted in the openly available fMRI data of six subjects, and comparisons are made with existing decomposition models and voxel selection frameworks. Subsequently, the effect of degree of selected voxels and the selection constraints are analyzed. The comparative results and the analysis demonstrate the superiority and the reliability of the proposed methodology.

Open-framework gallium borate with boric and metaboric acid molecules inside structural channels showing photocatalysis to water splitting.

PubMed

Gao, Wenliang; Jing, Yan; Yang, Jia; Zhou, Zhengyang; Yang, Dingfeng; Sun, Junliang; Lin, Jianhua; Cong, Rihong; Yang, Tao

2014-03-03

An open-framework gallium borate with intrinsic photocatalytic activities to water splitting has been discovered. Small inorganic molecules, H3BO3 and H3B3O6, are confined inside structural channels by multiple hydrogen bonds. It is the first example to experimentally show the structural template effect of boric acid in flux synthesis.

Joint radius-length distribution as a measure of anisotropic pore eccentricity: an experimental and analytical framework.

PubMed

Benjamini, Dan; Basser, Peter J

2014-12-07

In this work, we present an experimental design and analytical framework to measure the nonparametric joint radius-length (R-L) distribution of an ensemble of parallel, finite cylindrical pores, and more generally, the eccentricity distribution of anisotropic pores. Employing a novel 3D double pulsed-field gradient acquisition scheme, we first obtain both the marginal radius and length distributions of a population of cylindrical pores and then use these to constrain and stabilize the estimate of the joint radius-length distribution. Using the marginal distributions as constraints allows the joint R-L distribution to be reconstructed from an underdetermined system (i.e., more variables than equations), which requires a relatively small and feasible number of MR acquisitions. Three simulated representative joint R-L distribution phantoms corrupted by different noise levels were reconstructed to demonstrate the process, using this new framework. As expected, the broader the peaks in the joint distribution, the less stable and more sensitive to noise the estimation of the marginal distributions. Nevertheless, the reconstruction of the joint distribution is remarkably robust to increases in noise level; we attribute this characteristic to the use of the marginal distributions as constraints. Axons are known to exhibit local compartment eccentricity variations upon injury; the extent of the variations depends on the severity of the injury. Nonparametric estimation of the eccentricity distribution of injured axonal tissue is of particular interest since generally one cannot assume a parametric distribution a priori. Reconstructing the eccentricity distribution may provide vital information about changes resulting from injury or that occurred during development.

Visual Exploratory Search of Relationship Graphs on Smartphones

PubMed Central

Ouyang, Jianquan; Zheng, Hao; Kong, Fanbin; Liu, Tianming

2013-01-01

This paper presents a novel framework for Visual Exploratory Search of Relationship Graphs on Smartphones (VESRGS) that is composed of three major components: inference and representation of semantic relationship graphs on the Web via meta-search, visual exploratory search of relationship graphs through both querying and browsing strategies, and human-computer interactions via the multi-touch interface and mobile Internet on smartphones. In comparison with traditional lookup search methodologies, the proposed VESRGS system is characterized with the following perceived advantages. 1) It infers rich semantic relationships between the querying keywords and other related concepts from large-scale meta-search results from Google, Yahoo! and Bing search engines, and represents semantic relationships via graphs; 2) the exploratory search approach empowers users to naturally and effectively explore, adventure and discover knowledge in a rich information world of interlinked relationship graphs in a personalized fashion; 3) it effectively takes the advantages of smartphones’ user-friendly interfaces and ubiquitous Internet connection and portability. Our extensive experimental results have demonstrated that the VESRGS framework can significantly improve the users’ capability of seeking the most relevant relationship information to their own specific needs. We envision that the VESRGS framework can be a starting point for future exploration of novel, effective search strategies in the mobile Internet era. PMID:24223936

3D Reconstruction of Space Objects from Multi-Views by a Visible Sensor

PubMed Central

Zhang, Haopeng; Wei, Quanmao; Jiang, Zhiguo

2017-01-01

In this paper, a novel 3D reconstruction framework is proposed to recover the 3D structural model of a space object from its multi-view images captured by a visible sensor. Given an image sequence, this framework first estimates the relative camera poses and recovers the depths of the surface points by the structure from motion (SFM) method, then the patch-based multi-view stereo (PMVS) algorithm is utilized to generate a dense 3D point cloud. To resolve the wrong matches arising from the symmetric structure and repeated textures of space objects, a new strategy is introduced, in which images are added to SFM in imaging order. Meanwhile, a refining process exploiting the structural prior knowledge that most sub-components of artificial space objects are composed of basic geometric shapes is proposed and applied to the recovered point cloud. The proposed reconstruction framework is tested on both simulated image datasets and real image datasets. Experimental results illustrate that the recovered point cloud models of space objects are accurate and have a complete coverage of the surface. Moreover, outliers and points with severe noise are effectively filtered out by the refinement, resulting in an distinct improvement of the structure and visualization of the recovered points. PMID:28737675

Toward Understanding Drug Incorporation and Delivery from Biocompatible Metal-Organic Frameworks in View of Cutaneous Administration.

PubMed

Rojas, Sara; Colinet, Isabel; Cunha, Denise; Hidalgo, Tania; Salles, Fabrice; Serre, Christian; Guillou, Nathalie; Horcajada, Patricia

2018-03-31

Although metal-organic frameworks (MOFs) have widely demonstrated their convenient performances as drug-delivery systems, there is still work to do to fully understand the drug incorporation/delivery processes from these materials. In this work, a combined experimental and computational investigation of the main structural and physicochemical parameters driving drug adsorption/desorption kinetics was carried out. Two model drugs (aspirin and ibuprofen) and three water-stable, biocompatible MOFs (MIL-100(Fe), UiO-66(Zr), and MIL-127(Fe)) have been selected to obtain a variety of drug-matrix couples with different structural and physicochemical characteristics. This study evidenced that the drug-loading and drug-delivery processes are mainly governed by structural parameters (accessibility of the framework and drug volume) as well as the MOF/drug hydrophobic/hydrophilic balance. As a result, the delivery of the drug under simulated cutaneous conditions (aqueous media at 37 °C) demonstrated that these systems fulfill the requirements to be used as topical drug-delivery systems, such as released payload between 1 and 7 days. These results highlight the importance of the rational selection of MOFs, evidencing the effect of geometrical and chemical parameters of both the MOF and the drug on the drug adsorption and release.

Toward Understanding Drug Incorporation and Delivery from Biocompatible Metal–Organic Frameworks in View of Cutaneous Administration

PubMed Central

2018-01-01

Although metal–organic frameworks (MOFs) have widely demonstrated their convenient performances as drug-delivery systems, there is still work to do to fully understand the drug incorporation/delivery processes from these materials. In this work, a combined experimental and computational investigation of the main structural and physicochemical parameters driving drug adsorption/desorption kinetics was carried out. Two model drugs (aspirin and ibuprofen) and three water-stable, biocompatible MOFs (MIL-100(Fe), UiO-66(Zr), and MIL-127(Fe)) have been selected to obtain a variety of drug–matrix couples with different structural and physicochemical characteristics. This study evidenced that the drug-loading and drug-delivery processes are mainly governed by structural parameters (accessibility of the framework and drug volume) as well as the MOF/drug hydrophobic/hydrophilic balance. As a result, the delivery of the drug under simulated cutaneous conditions (aqueous media at 37 °C) demonstrated that these systems fulfill the requirements to be used as topical drug-delivery systems, such as released payload between 1 and 7 days. These results highlight the importance of the rational selection of MOFs, evidencing the effect of geometrical and chemical parameters of both the MOF and the drug on the drug adsorption and release. PMID:29623304

Word-level language modeling for P300 spellers based on discriminative graphical models

NASA Astrophysics Data System (ADS)

Delgado Saa, Jaime F.; de Pesters, Adriana; McFarland, Dennis; Çetin, Müjdat

2015-04-01

Objective. In this work we propose a probabilistic graphical model framework that uses language priors at the level of words as a mechanism to increase the performance of P300-based spellers. Approach. This paper is concerned with brain-computer interfaces based on P300 spellers. Motivated by P300 spelling scenarios involving communication based on a limited vocabulary, we propose a probabilistic graphical model framework and an associated classification algorithm that uses learned statistical models of language at the level of words. Exploiting such high-level contextual information helps reduce the error rate of the speller. Main results. Our experimental results demonstrate that the proposed approach offers several advantages over existing methods. Most importantly, it increases the classification accuracy while reducing the number of times the letters need to be flashed, increasing the communication rate of the system. Significance. The proposed approach models all the variables in the P300 speller in a unified framework and has the capability to correct errors in previous letters in a word, given the data for the current one. The structure of the model we propose allows the use of efficient inference algorithms, which in turn makes it possible to use this approach in real-time applications.

Adverse Outcome Pathways – Organizing Toxicological ...

EPA Pesticide Factsheets

The number of chemicals for which environmental regulatory decisions are required far exceeds the current capacity for toxicity testing. High throughput screening (HTS) commonly used for drug discovery has the potential to increase this capacity. The adverse outcome pathway (AOP) concept has emerged as a natural framework for connecting high throughput toxicity testing (HTT) results to potential impacts on humans and wildlife populations. An AOP consists of two main components that describe the biological mechanisms driving toxicity. Key events represent biological processes essential for causing the adverse outcome that are also measurable experimentally. Key event relationships capture the biological processes connecting the key events. Evidence documented for each KER based on measurements of the KEs can provide the confidence needed for extrapolating HTT from early key events to overt toxicity represented by later key events based on the AOP. The IPCS mode of action (MOA) framework incorporates information required for making a chemical-specific toxicity determination. Given the close relationship between the AOP and MOA frameworks, it is possible to assemble an MOA by incorporating HTT results, chemical properties including absorption, distribution, metabolism, and excretion (ADME), and an AOP describing the biological basis of toxicity thereby streamlining the process. While current applications focus on the assessment of risk for environmental chemicals,