Quantum Jarzynski equality of measurement-based work extraction

NASA Astrophysics Data System (ADS)

Morikuni, Yohei; Tajima, Hiroyasu; Hatano, Naomichi

2017-03-01

Many studies of quantum-size heat engines assume that the dynamics of an internal system is unitary and that the extracted work is equal to the energy loss of the internal system. Both assumptions, however, should be under scrutiny. In the present paper, we analyze quantum-scale heat engines, employing the measurement-based formulation of the work extraction recently introduced by Hayashi and Tajima [M. Hayashi and H. Tajima, arXiv:1504.06150]. We first demonstrate the inappropriateness of the unitary time evolution of the internal system (namely, the first assumption above) using a simple two-level system; we show that the variance of the energy transferred to an external system diverges when the dynamics of the internal system is approximated to a unitary time evolution. Second, we derive the quantum Jarzynski equality based on the formulation of Hayashi and Tajima as a relation for the work measured by an external macroscopic apparatus. The right-hand side of the equality reduces to unity for "natural" cyclic processes but fluctuates wildly for noncyclic ones, exceeding unity often. This fluctuation should be detectable in experiments and provide evidence for the present formulation.

Quantum Jarzynski equality of measurement-based work extraction.

PubMed

Morikuni, Yohei; Tajima, Hiroyasu; Hatano, Naomichi

2017-03-01

Many studies of quantum-size heat engines assume that the dynamics of an internal system is unitary and that the extracted work is equal to the energy loss of the internal system. Both assumptions, however, should be under scrutiny. In the present paper, we analyze quantum-scale heat engines, employing the measurement-based formulation of the work extraction recently introduced by Hayashi and Tajima [M. Hayashi and H. Tajima, arXiv:1504.06150]. We first demonstrate the inappropriateness of the unitary time evolution of the internal system (namely, the first assumption above) using a simple two-level system; we show that the variance of the energy transferred to an external system diverges when the dynamics of the internal system is approximated to a unitary time evolution. Second, we derive the quantum Jarzynski equality based on the formulation of Hayashi and Tajima as a relation for the work measured by an external macroscopic apparatus. The right-hand side of the equality reduces to unity for "natural" cyclic processes but fluctuates wildly for noncyclic ones, exceeding unity often. This fluctuation should be detectable in experiments and provide evidence for the present formulation.

Application of computational fluid dynamics for the simulation of cryogenic molecular sieve bed absorber of hydrogen isotopes recovery system for Indian LLCB-TBM

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

Gayathri Devi, V.; Sircar, A.; Sarkar, B.

One of the most challenging tasks in the design of the fuel cycle system lies in the effective design of Tritium Extraction System (TES) which involves proper extraction and purification of tritium in the fuel cycle of the fusion reactor. Indian Lead Lithium cooled Ceramic Breeder Test Blanket Module (LLCB-TBM) would extract hydrogen isotopes through Cryogenic Molecular Sieve Bed (CMSB) adsorber system. A prototype Hydrogen Isotopes Recovery System (HIRS) is being developed to validate the concepts for tritium extraction by adsorption mass transfer mechanism. In this study, a design model has been developed and analyzed to simulate the adsorption massmore » transfer kinetics in a fixed bed adsorption column. The simulation leads primarily to effective design of HIRS, which is a state-of-the-art technology. The paper describes the process simulation approach and the results of Computational Fluid Dynamics (CFD) analysis. The effects of different operating conditions are studied to investigate their influence on the hydrogen isotopes adsorption capacity. The results of the present simulation study would be used to understand the best optimized transport phenomenon before realizing the TES as a system for LLCB-TBM. (authors)« less

Performance enhancement for audio-visual speaker identification using dynamic facial muscle model.

PubMed

Asadpour, Vahid; Towhidkhah, Farzad; Homayounpour, Mohammad Mehdi

2006-10-01

Science of human identification using physiological characteristics or biometry has been of great concern in security systems. However, robust multimodal identification systems based on audio-visual information has not been thoroughly investigated yet. Therefore, the aim of this work to propose a model-based feature extraction method which employs physiological characteristics of facial muscles producing lip movements. This approach adopts the intrinsic properties of muscles such as viscosity, elasticity, and mass which are extracted from the dynamic lip model. These parameters are exclusively dependent on the neuro-muscular properties of speaker; consequently, imitation of valid speakers could be reduced to a large extent. These parameters are applied to a hidden Markov model (HMM) audio-visual identification system. In this work, a combination of audio and video features has been employed by adopting a multistream pseudo-synchronized HMM training method. Noise robust audio features such as Mel-frequency cepstral coefficients (MFCC), spectral subtraction (SS), and relative spectra perceptual linear prediction (J-RASTA-PLP) have been used to evaluate the performance of the multimodal system once efficient audio feature extraction methods have been utilized. The superior performance of the proposed system is demonstrated on a large multispeaker database of continuously spoken digits, along with a sentence that is phonetically rich. To evaluate the robustness of algorithms, some experiments were performed on genetically identical twins. Furthermore, changes in speaker voice were simulated with drug inhalation tests. In 3 dB signal to noise ratio (SNR), the dynamic muscle model improved the identification rate of the audio-visual system from 91 to 98%. Results on identical twins revealed that there was an apparent improvement on the performance for the dynamic muscle model-based system, in which the identification rate of the audio-visual system was enhanced from 87 to 96%.

Online flow cytometry reveals microbial dynamics influenced by concurrent natural and operational events in groundwater used for drinking water treatment.

PubMed

Besmer, Michael D; Epting, Jannis; Page, Rebecca M; Sigrist, Jürg A; Huggenberger, Peter; Hammes, Frederik

2016-12-07

Detailed measurements of physical, chemical and biological dynamics in groundwater are key to understanding the important processes in place and their influence on water quality - particularly when used for drinking water. Measuring temporal bacterial dynamics at high frequency is challenging due to the limitations in automation of sampling and detection of the conventional, cultivation-based microbial methods. In this study, fully automated online flow cytometry was applied in a groundwater system for the first time in order to monitor microbial dynamics in a groundwater extraction well. Measurements of bacterial concentrations every 15 minutes during 14 days revealed both aperiodic and periodic dynamics that could not be detected previously, resulting in total cell concentration (TCC) fluctuations between 120 and 280 cells μL -1 . The aperiodic dynamic was linked to river water contamination following precipitation events, while the (diurnal) periodic dynamic was attributed to changes in hydrological conditions as a consequence of intermittent groundwater extraction. Based on the high number of measurements, the two patterns could be disentangled and quantified separately. This study i) increases the understanding of system performance, ii) helps to optimize monitoring strategies, and iii) opens the possibility for more sophisticated (quantitative) microbial risk assessment of drinking water treatment systems.

Online flow cytometry reveals microbial dynamics influenced by concurrent natural and operational events in groundwater used for drinking water treatment

PubMed Central

Besmer, Michael D.; Epting, Jannis; Page, Rebecca M.; Sigrist, Jürg A.; Huggenberger, Peter; Hammes, Frederik

2016-01-01

Detailed measurements of physical, chemical and biological dynamics in groundwater are key to understanding the important processes in place and their influence on water quality – particularly when used for drinking water. Measuring temporal bacterial dynamics at high frequency is challenging due to the limitations in automation of sampling and detection of the conventional, cultivation-based microbial methods. In this study, fully automated online flow cytometry was applied in a groundwater system for the first time in order to monitor microbial dynamics in a groundwater extraction well. Measurements of bacterial concentrations every 15 minutes during 14 days revealed both aperiodic and periodic dynamics that could not be detected previously, resulting in total cell concentration (TCC) fluctuations between 120 and 280 cells μL−1. The aperiodic dynamic was linked to river water contamination following precipitation events, while the (diurnal) periodic dynamic was attributed to changes in hydrological conditions as a consequence of intermittent groundwater extraction. Based on the high number of measurements, the two patterns could be disentangled and quantified separately. This study i) increases the understanding of system performance, ii) helps to optimize monitoring strategies, and iii) opens the possibility for more sophisticated (quantitative) microbial risk assessment of drinking water treatment systems. PMID:27924920

System identification methods for aircraft flight control development and validation

NASA Technical Reports Server (NTRS)

Tischler, Mark B.

1995-01-01

System-identification methods compose a mathematical model, or series of models, from measurements of inputs and outputs of dynamic systems. The extracted models allow the characterization of the response of the overall aircraft or component subsystem behavior, such as actuators and on-board signal processing algorithms. This paper discusses the use of frequency-domain system-identification methods for the development and integration of aircraft flight-control systems. The extraction and analysis of models of varying complexity from nonparametric frequency-responses to transfer-functions and high-order state-space representations is illustrated using the Comprehensive Identification from FrEquency Responses (CIFER) system-identification facility. Results are presented for test data of numerous flight and simulation programs at the Ames Research Center including rotorcraft, fixed-wing aircraft, advanced short takeoff and vertical landing (ASTOVL), vertical/short takeoff and landing (V/STOL), tiltrotor aircraft, and rotor experiments in the wind tunnel. Excellent system characterization and dynamic response prediction is achieved for this wide class of systems. Examples illustrate the role of system-identification technology in providing an integrated flow of dynamic response data around the entire life-cycle of aircraft development from initial specifications, through simulation and bench testing, and into flight-test optimization.

A Tribute to J. C. Sprott

NASA Astrophysics Data System (ADS)

Nazarimehr, Fahimeh; Jafari, Sajad; Chen, Guanrong; Kapitaniak, Tomasz; Kuznetsov, Nikolay V.; Leonov, Gennady A.; Li, Chunbiao; Wei, Zhouchao

2017-12-01

In honor of his 75th birthday, we review the prominent works of Professor Julien Clinton Sprott in chaos and nonlinear dynamics. We categorize his works into three important groups. The first and most important group is identifying new dynamical systems with special properties. He has proposed different chaotic maps, flows, complex variable systems, nonautonomous systems, partial differential equations, fractional-order systems, delay differential systems, spatiotemporal systems, artificial neural networks, and chaotic electrical circuits. He has also studied dynamical properties of complex systems such as bifurcations and basins of attraction. He has done work on generating fractal art. He has examined models of real-world systems that exhibit chaos. The second group of his works comprise control and synchronization of chaos. Finally, the third group is extracting dynamical properties of systems using time-series analysis. This paper highlights the impact of Sprott’s work on the promotion of nonlinear dynamics.

In situ Orbit Extraction from Live, High Precision Collisionless Simulations of Systems Formed by Cold Collapse

NASA Astrophysics Data System (ADS)

Noriega-Mendoza, H.; Aguilar, L. A.

2018-04-01

We performed high precision, N-body simulations of the cold collapse of initially spherical, collisionless systems using the GYRFALCON code of Dehnen (2000). The collapses produce very prolate spheroidal configurations. After the collapse, the systems are simulated for 85 and 170 half-mass radius dynamical timescales, during which energy conservation is better than 0.005%. We use this period to extract individual particle orbits directly from the simulations. We then use the TAXON code of Carpintero and Aguilar (1998) to classify 1 to 1.5% of the extracted orbits from our final, relaxed configurations: less than 15% are chaotic orbits, 30% are box orbits and 60% are tube orbits (long and short axis). Our goal has been to prove that direct orbit extraction is feasible, and that there is no need to "freeze" the final N-body system configuration to extract a time-independent potential.

Querying databases of trajectories of differential equations: Data structures for trajectories

NASA Technical Reports Server (NTRS)

Grossman, Robert

1989-01-01

One approach to qualitative reasoning about dynamical systems is to extract qualitative information by searching or making queries on databases containing very large numbers of trajectories. The efficiency of such queries depends crucially upon finding an appropriate data structure for trajectories of dynamical systems. Suppose that a large number of parameterized trajectories gamma of a dynamical system evolving in R sup N are stored in a database. Let Eta is contained in set R sup N denote a parameterized path in Euclidean Space, and let the Euclidean Norm denote a norm on the space of paths. A data structure is defined to represent trajectories of dynamical systems, and an algorithm is sketched which answers queries.

An information extraction framework for cohort identification using electronic health records.

PubMed

Liu, Hongfang; Bielinski, Suzette J; Sohn, Sunghwan; Murphy, Sean; Wagholikar, Kavishwar B; Jonnalagadda, Siddhartha R; Ravikumar, K E; Wu, Stephen T; Kullo, Iftikhar J; Chute, Christopher G

2013-01-01

Information extraction (IE), a natural language processing (NLP) task that automatically extracts structured or semi-structured information from free text, has become popular in the clinical domain for supporting automated systems at point-of-care and enabling secondary use of electronic health records (EHRs) for clinical and translational research. However, a high performance IE system can be very challenging to construct due to the complexity and dynamic nature of human language. In this paper, we report an IE framework for cohort identification using EHRs that is a knowledge-driven framework developed under the Unstructured Information Management Architecture (UIMA). A system to extract specific information can be developed by subject matter experts through expert knowledge engineering of the externalized knowledge resources used in the framework.

The Extraction of Metals from Their Oxides and Sulphides.

ERIC Educational Resources Information Center

Price, Alun H.

1980-01-01

Briefly describes the application of thermodynamics (system at equilibrium) to the study of the extraction of metals from their oxides (dynamic situation). It is more relevant to study the temperature variation of the equilibrium constants of the reaction than to study the free energy approach. (Author/SK)

Dynamic pH junction high-speed counter-current chromatography coupled with microwave-assisted extraction for online separation and purification of alkaloids from Stephania cepharantha.

PubMed

Yuan, Zhiquan; Xiao, Xiaohua; Li, Gongke

2013-11-22

A simple and efficient dynamic pH junction high-speed counter-current chromatography method was developed and further applied to the online extraction, separation and purification of alkaloids from Stephania cepharantha by coupling with microwave-assisted extraction. Mineral acid and organic base were added into the mobile phase and the sample solution, respectively, leading to the formation of a dynamic pH junction in the column and causing focus of alkaloids. Selective focus of analytes can be achieved on the basis of velocity changes of the pH junction through appropriate selection of solvent systems and optimization of additive concentrations. The extract can be directly introduced into the HSCCC for the online extraction, separation and purification of alkaloids from S. cepharantha. Continuous separation can be easily achieved with the same solvent system. Under the optimum conditions, 6.0 g original sample was extracted with 60 mL of the upper phase of hexane-ethyl acetate-methanol-water (1:1:1:1, v/v/v/v) containing 10% triethylamine under 50 °C and 400 W irradiation power for 10 min, the extracts were directly separated and purified by high-speed counter-current chromatography. A total of 5.7 mg sinomenine, 8.3mg 6,7-di-O-acetylsinococuline, 17.9 mg berbamine, 12.7 mg isotetrandrine and 14.6 mg cepharanthine were obtained with purities of 96.7%, 93.7%, 98.7%, 97.3% and 99.3%, respectively. The online method provides good selectivity to ionizable compounds and improves the separation and purification efficiency of the high-speed counter-current chromatography technique. It has good potential for separation and purification of effective compounds from natural products. Copyright © 2013 Elsevier B.V. All rights reserved.

Renewable fluid dynamic energy derived from aquatic animal locomotion.

PubMed

Dabiri, John O

2007-09-01

Aquatic animals swimming in isolation and in groups are known to extract energy from the vortices in environmental flows, significantly reducing muscle activity required for locomotion. A model for the vortex dynamics associated with this phenomenon is developed, showing that the energy extraction mechanism can be described by simple criteria governing the kinematics of the vortices relative to the body in the flow. In this way, we need not make direct appeal to the fluid dynamics, which can be more difficult to evaluate than the kinematics. Examples of these principles as exhibited in swimming fish and existing energy conversion devices are described. A benefit of the developed framework is that the potentially infinite-dimensional parameter space of the fluid-structure interaction is reduced to a maximum of eight combinations of three parameters. The model may potentially aid in the design and evaluation of unsteady aero- and hydrodynamic energy conversion systems that surpass the Betz efficiency limit of steady fluid dynamic energy conversion systems.

A Risk Assessment System with Automatic Extraction of Event Types

NASA Astrophysics Data System (ADS)

Capet, Philippe; Delavallade, Thomas; Nakamura, Takuya; Sandor, Agnes; Tarsitano, Cedric; Voyatzi, Stavroula

In this article we describe the joint effort of experts in linguistics, information extraction and risk assessment to integrate EventSpotter, an automatic event extraction engine, into ADAC, an automated early warning system. By detecting as early as possible weak signals of emerging risks ADAC provides a dynamic synthetic picture of situations involving risk. The ADAC system calculates risk on the basis of fuzzy logic rules operated on a template graph whose leaves are event types. EventSpotter is based on a general purpose natural language dependency parser, XIP, enhanced with domain-specific lexical resources (Lexicon-Grammar). Its role is to automatically feed the leaves with input data.

Preliminary experiments on pharmacokinetic diffuse fluorescence tomography of CT-scanning mode

NASA Astrophysics Data System (ADS)

Zhang, Yanqi; Wang, Xin; Yin, Guoyan; Li, Jiao; Zhou, Zhongxing; Zhao, Huijuan; Gao, Feng; Zhang, Limin

2016-10-01

In vivo tomographic imaging of the fluorescence pharmacokinetic parameters in tissues can provide additional specific and quantitative physiological and pathological information to that of fluorescence concentration. This modality normally requires a highly-sensitive diffuse fluorescence tomography (DFT) working in dynamic way to finally extract the pharmacokinetic parameters from the measured pharmacokinetics-associated temporally-varying boundary intensity. This paper is devoted to preliminary experimental validation of our proposed direct reconstruction scheme of instantaneous sampling based pharmacokinetic-DFT: A highly-sensitive DFT system of CT-scanning mode working with parallel four photomultiplier-tube photon-counting channels is developed to generate an instantaneous sampling dataset; A direct reconstruction scheme then extracts images of the pharmacokinetic parameters using the adaptive-EKF strategy. We design a dynamic phantom that can simulate the agent metabolism in living tissue. The results of the dynamic phantom experiments verify the validity of the experiment system and reconstruction algorithms, and demonstrate that system provides good resolution, high sensitivity and quantitativeness at different pump speed.

Microalgae fractionation using steam explosion, dynamic and tangential cross-flow membrane filtration.

PubMed

Lorente, E; Hapońska, M; Clavero, E; Torras, C; Salvadó, J

2017-08-01

In this study, the microalga Nannochloropsis gaditana was subjected to acid catalysed steam explosion treatment and the resulting exploded material was subsequently fractionated to separate the different fractions (lipids, sugars and solids). Conventional and vibrational membrane setups were used with several polymeric commercial membranes. Two different routes were followed: 1) filtration+lipid solvent extraction and 2) lipid solvent extraction+filtration. Route 1 revealed to be much better since the used membrane for filtration was able to permeate the sugar aqueous phase and retained the fraction containing lipids; after this, an extraction required a much lower amount of solvent and a better recovering yield. Filtration allowed complete lipid rejection. Dynamic filtration improved permeability compared to the tangential cross-flow filtration. Best membrane performance was achieved using a 5000Da membrane with the dynamic system, obtaining a permeability of 6L/h/m 2 /bar. Copyright © 2017 Elsevier Ltd. All rights reserved.

Reconstruction of dynamic structures of experimental setups based on measurable experimental data only

NASA Astrophysics Data System (ADS)

Chen, Tian-Yu; Chen, Yang; Yang, Hu-Jiang; Xiao, Jing-Hua; Hu, Gang

2018-03-01

Nowadays, massive amounts of data have been accumulated in various and wide fields, it has become today one of the central issues in interdisciplinary fields to analyze existing data and extract as much useful information as possible from data. It is often that the output data of systems are measurable while dynamic structures producing these data are hidden, and thus studies to reveal system structures by analyzing available data, i.e., reconstructions of systems become one of the most important tasks of information extractions. In the past, most of the works in this respect were based on theoretical analyses and numerical verifications. Direct analyses of experimental data are very rare. In physical science, most of the analyses of experimental setups were based on the first principles of physics laws, i.e., so-called top-down analyses. In this paper, we conducted an experiment of “Boer resonant instrument for forced vibration” (BRIFV) and inferred the dynamic structure of the experimental set purely from the analysis of the measurable experimental data, i.e., by applying the bottom-up strategy. Dynamics of the experimental set is strongly nonlinear and chaotic, and itʼs subjects to inevitable noises. We proposed to use high-order correlation computations to treat nonlinear dynamics; use two-time correlations to treat noise effects. By applying these approaches, we have successfully reconstructed the structure of the experimental setup, and the dynamic system reconstructed with the measured data reproduces good experimental results in a wide range of parameters.

An Information Extraction Framework for Cohort Identification Using Electronic Health Records

PubMed Central

Liu, Hongfang; Bielinski, Suzette J.; Sohn, Sunghwan; Murphy, Sean; Wagholikar, Kavishwar B.; Jonnalagadda, Siddhartha R.; Ravikumar, K.E.; Wu, Stephen T.; Kullo, Iftikhar J.; Chute, Christopher G

Information extraction (IE), a natural language processing (NLP) task that automatically extracts structured or semi-structured information from free text, has become popular in the clinical domain for supporting automated systems at point-of-care and enabling secondary use of electronic health records (EHRs) for clinical and translational research. However, a high performance IE system can be very challenging to construct due to the complexity and dynamic nature of human language. In this paper, we report an IE framework for cohort identification using EHRs that is a knowledge-driven framework developed under the Unstructured Information Management Architecture (UIMA). A system to extract specific information can be developed by subject matter experts through expert knowledge engineering of the externalized knowledge resources used in the framework. PMID:24303255

Non-linear controls influence functions in an aircraft dynamics simulator

NASA Technical Reports Server (NTRS)

Guerreiro, Nelson M.; Hubbard, James E., Jr.; Motter, Mark A.

2006-01-01

In the development and testing of novel structural and controls concepts, such as morphing aircraft wings, appropriate models are needed for proper system characterization. In most instances, available system models do not provide the required additional degrees of freedom for morphing structures but may be modified to some extent to achieve a compatible system. The objective of this study is to apply wind tunnel data collected for an Unmanned Air Vehicle (UAV), that implements trailing edge morphing, to create a non-linear dynamics simulator, using well defined rigid body equations of motion, where the aircraft stability derivatives change with control deflection. An analysis of this wind tunnel data, using data extraction algorithms, was performed to determine the reference aerodynamic force and moment coefficients for the aircraft. Further, non-linear influence functions were obtained for each of the aircraft s control surfaces, including the sixteen trailing edge flap segments. These non-linear controls influence functions are applied to the aircraft dynamics to produce deflection-dependent aircraft stability derivatives in a non-linear dynamics simulator. Time domain analysis of the aircraft motion, trajectory, and state histories can be performed using these nonlinear dynamics and may be visualized using a 3-dimensional aircraft model. Linear system models can be extracted to facilitate frequency domain analysis of the system and for control law development. The results of this study are useful in similar projects where trailing edge morphing is employed and will be instrumental in the University of Maryland s continuing study of active wing load control.

Chaos in plasma simulation and experiment

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

Watts, C.; Newman, D.E.; Sprott, J.C.

1993-09-01

We investigate the possibility that chaos and simple determinism are governing the dynamics of reversed field pinch (RFP) plasmas using data from both numerical simulations and experiment. A large repertoire of nonlinear analysis techniques is used to identify low dimensional chaos. These tools include phase portraits and Poincard sections, correlation dimension, the spectrum of Lyapunov exponents and short term predictability. In addition, nonlinear noise reduction techniques are applied to the experimental data in an attempt to extract any underlying deterministic dynamics. Two model systems are used to simulate the plasma dynamics. These are -the DEBS code, which models global RFPmore » dynamics, and the dissipative trapped electron mode (DTEM) model, which models drift wave turbulence. Data from both simulations show strong indications of low,dimensional chaos and simple determinism. Experimental data were obtained from the Madison Symmetric Torus RFP and consist of a wide array of both global and local diagnostic signals. None of the signals shows any indication of low dimensional chaos or other simple determinism. Moreover, most of the analysis tools indicate the experimental system is very high dimensional with properties similar to noise. Nonlinear noise reduction is unsuccessful at extracting an underlying deterministic system.« less

Sparse learning of stochastic dynamical equations

NASA Astrophysics Data System (ADS)

Boninsegna, Lorenzo; Nüske, Feliks; Clementi, Cecilia

2018-06-01

With the rapid increase of available data for complex systems, there is great interest in the extraction of physically relevant information from massive datasets. Recently, a framework called Sparse Identification of Nonlinear Dynamics (SINDy) has been introduced to identify the governing equations of dynamical systems from simulation data. In this study, we extend SINDy to stochastic dynamical systems which are frequently used to model biophysical processes. We prove the asymptotic correctness of stochastic SINDy in the infinite data limit, both in the original and projected variables. We discuss algorithms to solve the sparse regression problem arising from the practical implementation of SINDy and show that cross validation is an essential tool to determine the right level of sparsity. We demonstrate the proposed methodology on two test systems, namely, the diffusion in a one-dimensional potential and the projected dynamics of a two-dimensional diffusion process.

Reduced-order modeling of fluids systems, with applications in unsteady aerodynamics

NASA Astrophysics Data System (ADS)

Dawson, Scott T. M.

This thesis focuses on two major themes: modeling and understanding the dynamics of rapidly pitching airfoils, and developing methods that can be used to extract models and pertinent features from datasets obtained in the study of these and other systems in fluid mechanics and aerodynamics. Much of the work utilizes in some capacity dynamic mode decomposition (DMD), a recently developed method to extract dynamical features and models from data. The investigation of pitching airfoils includes both wind tunnel experiments and direct numerical simulations. Experiments are performed on a NACA 0012 airfoil undergoing rapid pitching motion, with the focus on developing a switched linear modeling framework that can accurately predict unsteady aerodynamic forces and pressure distributions throughout arbitrary pitching motions. Numerical simulations are used to study the behavior of sinusoidally pitching airfoils. By systematically varying the amplitude, frequency, mean angle and axis of pitching, a comprehensive database of results is acquired, from which interesting regions in parameter space are identified and studied. Attention is given to pitching at "preferred" frequencies, where vortex shedding in the wake is excited or amplified, leading to larger lift forces. More generally, the ability to extract nonlinear models that describe the behavior of complex fluids systems can assist in not only understanding the dominant features of such systems, but also to achieve accurate prediction and control. One potential avenue to achieve this objective is through numerical approximation of the Koopman operator, an infinite-dimensional linear operator capable of describing finite-dimensional nonlinear systems, such as those that might describe the dominant dynamics of fluids systems. This idea is explored by showing that algorithms designed to approximate the Koopman operator can indeed be utilized to accurately model nonlinear fluids systems, even when the data available is limited or noisy. Data-driven algorithms can be adversely affected by noisy data. Focusing on DMD, it is shown analytically that the algorithm is biased to sensor noise, which explains a previously observed sensitivity to noisy data. Using this finding, a number of modifications to DMD are proposed, which all give better approximations of the true dynamics using noise-corrupted data.

Bayesian inversion analysis of nonlinear dynamics in surface heterogeneous reactions.

PubMed

Omori, Toshiaki; Kuwatani, Tatsu; Okamoto, Atsushi; Hukushima, Koji

2016-09-01

It is essential to extract nonlinear dynamics from time-series data as an inverse problem in natural sciences. We propose a Bayesian statistical framework for extracting nonlinear dynamics of surface heterogeneous reactions from sparse and noisy observable data. Surface heterogeneous reactions are chemical reactions with conjugation of multiple phases, and they have the intrinsic nonlinearity of their dynamics caused by the effect of surface-area between different phases. We adapt a belief propagation method and an expectation-maximization (EM) algorithm to partial observation problem, in order to simultaneously estimate the time course of hidden variables and the kinetic parameters underlying dynamics. The proposed belief propagation method is performed by using sequential Monte Carlo algorithm in order to estimate nonlinear dynamical system. Using our proposed method, we show that the rate constants of dissolution and precipitation reactions, which are typical examples of surface heterogeneous reactions, as well as the temporal changes of solid reactants and products, were successfully estimated only from the observable temporal changes in the concentration of the dissolved intermediate product.

Dynamic fractionation of trace metals in soil and sediment samples using rotating coiled column extraction and sequential injection microcolumn extraction: a comparative study.

PubMed

Rosende, Maria; Savonina, Elena Yu; Fedotov, Petr S; Miró, Manuel; Cerdà, Víctor; Wennrich, Rainer

2009-09-15

Dynamic fractionation has been recognized as an appealing alternative to conventional equilibrium-based sequential extraction procedures (SEPs) for partitioning of trace elements (TE) in environmental solid samples. This paper reports the first attempt for harmonization of flow-through dynamic fractionation using two novel methods, the so-called sequential injection microcolumn (SIMC) extraction and rotating coiled column (RCC) extraction. In SIMC extraction, a column packed with the solid sample is clustered in a sequential injection system, while in RCC, the particulate matter is retained under the action of centrifugal forces. In both methods, the leachants are continuously pumped through the solid substrates by the use of either peristaltic or syringe pumps. A five-step SEP was selected for partitioning of Cu, Pb and Zn in water soluble/exchangeable, acid-soluble, easily reducible, easily oxidizable and moderately reducible fractions from 0.2 to 0.5 g samples at an extractant flow rate of 1.0 mL min(-1) prior to leachate analysis by inductively coupled plasma-atomic emission spectrometry. Similarities and discrepancies between both dynamic approaches were ascertained by fractionation of TE in certified reference materials, namely, SRM 2711 Montana Soil and GBW 07311 sediment, and two real soil samples as well. Notwithstanding the different extraction conditions set by both methods, similar trends of metal distribution were in generally found. The most critical parameters for reliable assessment of mobilizable pools of TE in worse-case scenarios are the size-distribution of sample particles, the density of particles, the content of organic matter and the concentration of major elements. For reference materials and a soil rich in organic matter, the extraction in RCC results in slightly higher recoveries of environmentally relevant fractions of TE, whereas SIMC leaching is more effective for calcareous soils.

Simultaneous measurement of temperature and emissivity of lunar regolith simulant using dual-channel millimeter-wave radiometry.

PubMed

McCloy, J S; Sundaram, S K; Matyas, J; Woskov, P P

2011-05-01

Millimeter wave (MMW) radiometry can be used for simultaneous measurement of emissivity and temperature of materials under extreme environments (high temperature, pressure, and corrosive environments). The state-of-the-art dual channel MMW passive radiometer with active interferometric capabilities at 137 GHz described here allows for radiometric measurements of sample temperature and emissivity up to at least 1600 °C with simultaneous measurement of sample surface dynamics. These capabilities have been used to demonstrate dynamic measurement of melting of powders of simulated lunar regolith and static measurement of emissivity of solid samples. The paper presents the theoretical background and basis for the dual-receiver system, describes the hardware in detail, and demonstrates the data analysis. Post-experiment analysis of emissivity versus temperature allows further extraction from the radiometric data of millimeter wave viewing beam coupling factors, which provide corroboratory evidence to the interferometric data of the process dynamics observed. These results show the promise of the MMW system for extracting quantitative and qualitative process parameters for industrial processes and access to real-time dynamics of materials behavior in extreme environments.

Dynamic leaching and fractionation of trace elements from environmental solids exploiting a novel circulating-flow platform.

PubMed

Mori, Masanobu; Nakano, Koji; Sasaki, Masaya; Shinozaki, Haruka; Suzuki, Shiho; Okawara, Chitose; Miró, Manuel; Itabashi, Hideyuki

2016-02-01

A dynamic flow-through microcolumn extraction system based on extractant re-circulation is herein proposed as a novel analytical approach for simplification of bioaccessibility tests of trace elements in sediments. On-line metal leaching is undertaken in the format of all injection (AI) analysis, which is a sequel of flow injection analysis, but involving extraction under steady-state conditions. The minimum circulation times and flow rates required to determine the maximum bioaccessible pools of target metals (viz., Cu, Zn, Cd, and Pb) from lake and river sediment samples were estimated using Tessier's sequential extraction scheme and an acid single extraction test. The on-line AIA method was successfully validated by mass balance studies of CRM and real sediment samples. Tessier's test in on-line AI format demonstrated to be carried out by one third of extraction time (6h against more than 17 h by the conventional method), with better analytical precision (<9.2% against >15% by the conventional method) and significant decrease in blank readouts as compared with the manual batch counterpart. Copyright © 2015 Elsevier B.V. All rights reserved.

Multi-Component Profiling of Trace Volatiles in Blood by Gas Chromatography/Mass Spectrometry with Dynamic Headspace Extraction

PubMed Central

Kakuta, Shoji; Yamashita, Toshiyuki; Nishiumi, Shin; Yoshida, Masaru; Fukusaki, Eiichiro; Bamba, Takeshi

2015-01-01

A dynamic headspace extraction method (DHS) with high-pressure injection is described. This dynamic extraction method has superior sensitivity to solid phase micro extraction, SPME and is capable of extracting the entire gas phase by purging the headspace of a vial. Optimization of the DHS parameters resulted in a highly sensitive volatile profiling system with the ability to detect various volatile components including alcohols at nanogram levels. The average LOD for a standard volatile mixture was 0.50 ng mL−1, and the average LOD for alcohols was 0.66 ng mL−1. This method was used for the analysis of volatile components from biological samples and compared with acute and chronic inflammation models. The method permitted the identification of volatiles with the same profile pattern as in vitro oxidized lipid-derived volatiles. In addition, the concentration of alcohols and aldehydes from the acute inflammation model samples were significantly higher than that for the chronic inflammation model samples. The different profiles between these samples could also be identified by this method. Finally, it was possible to analyze alcohols and low-molecular-weight volatiles that are difficult to analyze by SPME in high sensitivity and to show volatile profiling based on multi-volatile simultaneous analysis. PMID:26819905

Multi-Component Profiling of Trace Volatiles in Blood by Gas Chromatography/Mass Spectrometry with Dynamic Headspace Extraction.

PubMed

Kakuta, Shoji; Yamashita, Toshiyuki; Nishiumi, Shin; Yoshida, Masaru; Fukusaki, Eiichiro; Bamba, Takeshi

2015-01-01

A dynamic headspace extraction method (DHS) with high-pressure injection is described. This dynamic extraction method has superior sensitivity to solid phase micro extraction, SPME and is capable of extracting the entire gas phase by purging the headspace of a vial. Optimization of the DHS parameters resulted in a highly sensitive volatile profiling system with the ability to detect various volatile components including alcohols at nanogram levels. The average LOD for a standard volatile mixture was 0.50 ng mL(-1), and the average LOD for alcohols was 0.66 ng mL(-1). This method was used for the analysis of volatile components from biological samples and compared with acute and chronic inflammation models. The method permitted the identification of volatiles with the same profile pattern as in vitro oxidized lipid-derived volatiles. In addition, the concentration of alcohols and aldehydes from the acute inflammation model samples were significantly higher than that for the chronic inflammation model samples. The different profiles between these samples could also be identified by this method. Finally, it was possible to analyze alcohols and low-molecular-weight volatiles that are difficult to analyze by SPME in high sensitivity and to show volatile profiling based on multi-volatile simultaneous analysis.

An open circuit voltage decay system for performing injection dependent lifetime spectroscopy

NASA Astrophysics Data System (ADS)

Lacouture, Shelby; Schrock, James; Hirsch, Emily; Bayne, Stephen; O'Brien, Heather; Ogunniyi, Aderinto A.

2017-09-01

Of all of the material parameters associated with a semiconductor, the carrier lifetime is by far the most complex and dynamic, being a function of the dominant recombination mechanism, the equilibrium number of carriers, the perturbations in carriers (e.g., carrier injection), and the temperature, to name the most prominent variables. The carrier lifetime is one of the most important parameters in bipolar devices, greatly affecting conductivity modulation, on-state voltage, and reverse recovery. Carrier lifetime is also a useful metric for device fabrication process control and material quality. As it is such a dynamic quantity, carrier lifetime cannot be quoted in a general range such as mobility; it must be measured. The following describes a stand-alone, wide-injection range open circuit voltage decay system with unique lifetime extraction algorithms. The system is initially used along with various lifetime spectroscopy techniques to extract fundamental recombination parameters from a commercial high-voltage PIN diode.

Parallel processing of real-time dynamic systems simulation on OSCAR (Optimally SCheduled Advanced multiprocessoR)

NASA Technical Reports Server (NTRS)

Kasahara, Hironori; Honda, Hiroki; Narita, Seinosuke

1989-01-01

Parallel processing of real-time dynamic systems simulation on a multiprocessor system named OSCAR is presented. In the simulation of dynamic systems, generally, the same calculation are repeated every time step. However, we cannot apply to Do-all or the Do-across techniques for parallel processing of the simulation since there exist data dependencies from the end of an iteration to the beginning of the next iteration and furthermore data-input and data-output are required every sampling time period. Therefore, parallelism inside the calculation required for a single time step, or a large basic block which consists of arithmetic assignment statements, must be used. In the proposed method, near fine grain tasks, each of which consists of one or more floating point operations, are generated to extract the parallelism from the calculation and assigned to processors by using optimal static scheduling at compile time in order to reduce large run time overhead caused by the use of near fine grain tasks. The practicality of the scheme is demonstrated on OSCAR (Optimally SCheduled Advanced multiprocessoR) which has been developed to extract advantageous features of static scheduling algorithms to the maximum extent.

Extraction of Dynamic Features from Hand Drawn Data for the Identification of Children with Handwriting Difficulty

ERIC Educational Resources Information Center

Khalid, Puspa Inayat; Yunus, Jasmy; Adnan, Robiah

2010-01-01

Studies have shown that differences between children with and without handwriting difficulties lie not only in the written product (static data) but also in dynamic data of handwriting process. Since writing system varies among countries and individuals, this study was conducted to determine the feasibility of using quantitative outcome measures…

Flow-through dynamic microextraction system for automatic in vitro assessment of chyme bioaccessibility in food commodities.

PubMed

Souza, Lais A; Rosende, María; Korn, Maria Graças A; Miró, Manuel

2018-10-05

An automatic flow-through dynamic extraction method is proposed for the first time for in vitro exploration, with high temporal resolution, of the transit of the chyme from the gastric to the duodenal compartment using the Versantvoort's fed-state physiologically relevant extraction test. The flow manifold was coupled on-line to an inductively coupled plasma optical emission spectrometer (ICP OES) for real-time elucidation of the bioaccessible elemental fraction of micronutrients (viz., Cu, Fe and Mn) in food commodities across the gastrointestinal tract. The simulated intestinal and bile biofluid (added to the gastric phase) was successively pumped at 1.0 mL min -1 through a large-bore column (maintained at 37.0 ± 2.0 °C) initially loaded with a weighed amount of linseed (250 mg) using a PVDF filter membrane (5.0 μm pore size) for retaining of the solid sample and in-line filtration of the extracts. The lack of bias (trueness) of the on-line gastrointestinal extraction method coupled to ICP OES was confirmed using mass balance validation following microwave assisted digestion of the residual (non-bioaccessible) elemental fraction. Mass balance validation yielded absolute recoveries spanning from 79 to 121% for the overall analytes and samples. On-line dynamic extraction was critically appraised against batch counterparts for both gastric and gastrointestinal compartments. Due to the lack of consensus in the literature regarding the agitation method for batch oral bioaccessibility testing, several extraction approaches (viz., magnetic stirring, end-over-end rotation and orbital shaking) were evaluated. Improved gastric extractability of Fe along with bioaccessible data comparable to the dynamic counterpart based on the continuous displacement of the extraction equilibrium was obtained with batchwise magnetic stirring, which is deemed most appropriate for ascertaining worst-case/maximum bioaccessibility scenarios. Copyright © 2018 Elsevier B.V. All rights reserved.

Chaos and simple determinism in reversed field pinch plasmas: Nonlinear analysis of numerical simulation and experimental data

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

Watts, Christopher A.

In this dissertation the possibility that chaos and simple determinism are governing the dynamics of reversed field pinch (RFP) plasmas is investigated. To properly assess this possibility, data from both numerical simulations and experiment are analyzed. A large repertoire of nonlinear analysis techniques is used to identify low dimensional chaos in the data. These tools include phase portraits and Poincare sections, correlation dimension, the spectrum of Lyapunov exponents and short term predictability. In addition, nonlinear noise reduction techniques are applied to the experimental data in an attempt to extract any underlying deterministic dynamics. Two model systems are used to simulatemore » the plasma dynamics. These are the DEBS code, which models global RFP dynamics, and the dissipative trapped electron mode (DTEM) model, which models drift wave turbulence. Data from both simulations show strong indications of low dimensional chaos and simple determinism. Experimental date were obtained from the Madison Symmetric Torus RFP and consist of a wide array of both global and local diagnostic signals. None of the signals shows any indication of low dimensional chaos or low simple determinism. Moreover, most of the analysis tools indicate the experimental system is very high dimensional with properties similar to noise. Nonlinear noise reduction is unsuccessful at extracting an underlying deterministic system.« less

[Study on the dynamic model with supercritical CO2 fluid extracting the lipophilic components in Panax notoginseng].

PubMed

Duan, Xian-Chun; Wang, Yong-Zhong; Zhang, Jun-Ru; Luo, Huan; Zhang, Heng; Xia, Lun-Zhu

2011-08-01

To establish a dynamics model for extracting the lipophilic components in Panax notoginseng with supercritical carbon dioxide (CO2). Based on the theory of counter-flow mass transfer and the molecular mass transfer between the material and the supercritical CO2 fluid under differential mass-conservation equation, a dynamics model was established and computed to compare forecasting result with the experiment process. A dynamics model has been established for supercritical CO2 to extract the lipophilic components in Panax notoginseng, the computed result of this model was consistent with the experiment process basically. The supercritical fluid extract dynamics model established in this research can expound the mechanism in the extract process of which lipophilic components of Panax notoginseng dissolve the mass transfer and is tallied with the actual extract process. This provides certain instruction for the supercritical CO2 fluid extract' s industrialization enlargement.

Optimal estimation of recurrence structures from time series

NASA Astrophysics Data System (ADS)

beim Graben, Peter; Sellers, Kristin K.; Fröhlich, Flavio; Hutt, Axel

2016-05-01

Recurrent temporal dynamics is a phenomenon observed frequently in high-dimensional complex systems and its detection is a challenging task. Recurrence quantification analysis utilizing recurrence plots may extract such dynamics, however it still encounters an unsolved pertinent problem: the optimal selection of distance thresholds for estimating the recurrence structure of dynamical systems. The present work proposes a stochastic Markov model for the recurrent dynamics that allows for the analytical derivation of a criterion for the optimal distance threshold. The goodness of fit is assessed by a utility function which assumes a local maximum for that threshold reflecting the optimal estimate of the system's recurrence structure. We validate our approach by means of the nonlinear Lorenz system and its linearized stochastic surrogates. The final application to neurophysiological time series obtained from anesthetized animals illustrates the method and reveals novel dynamic features of the underlying system. We propose the number of optimal recurrence domains as a statistic for classifying an animals' state of consciousness.

Static and dynamic superheated water extraction of essential oil components from Thymus vulgaris L.

PubMed

Dawidowicz, Andrzej L; Rado, Ewelina; Wianowska, Dorota

2009-09-01

Superheated water extraction (SWE) performed in both static and dynamic condition (S-SWE and D-SWE, respectively) was applied for the extraction of essential oil from Thymus vulgaris L. The influence of extraction pressure, temperature, time, and flow rate on the total yield of essential oil and the influence of extraction temperature on the extraction of some chosen components are discussed in the paper. The SWE extracts are related to PLE extracts with n-hexane and essential oil obtained by steam distillation. The superheated water extraction in dynamic condition seems to be a feasible option for the extraction of essential oil components from T. vulgaris L.

Automatic flow-through dynamic extraction: A fast tool to evaluate char-based remediation of multi-element contaminated mine soils.

PubMed

Rosende, María; Beesley, Luke; Moreno-Jimenez, Eduardo; Miró, Manuel

2016-02-01

An automatic in-vitro bioaccessibility test based upon dynamic microcolumn extraction in a programmable flow setup is herein proposed as a screening tool to evaluate bio-char based remediation of mine soils contaminated with trace elements as a compelling alternative to conventional phyto-availability tests. The feasibility of the proposed system was evaluated by extracting the readily bioaccessible pools of As, Pb and Zn in two contaminated mine soils before and after the addition of two biochars (9% (w:w)) of diverse source origin (pine and olive). Bioaccessible fractions under worst-case scenarios were measured using 0.001 mol L(-1) CaCl2 as extractant for mimicking plant uptake, and analysis of the extracts by inductively coupled optical emission spectrometry. The t-test of comparison of means revealed an efficient metal (mostly Pb and Zn) immobilization by the action of olive pruning-based biochar against the bare (control) soil at the 0.05 significance level. In-vitro flow-through bioaccessibility tests are compared for the first time with in-vivo phyto-toxicity assays in a microcosm soil study. By assessing seed germination and shoot elongation of Lolium perenne in contaminated soils with and without biochar amendments the dynamic flow-based bioaccessibility data proved to be in good agreement with the phyto-availability tests. Experimental results indicate that the dynamic extraction method is a viable and economical in-vitro tool in risk assessment explorations to evaluate the feasibility of a given biochar amendment for revegetation and remediation of metal contaminated soils in a mere 10 min against 4 days in case of phyto-toxicity assays. Copyright © 2015 Elsevier B.V. All rights reserved.

Effects of pyrite and sphalerite on population compositions, dynamics and copper extraction efficiency in chalcopyrite bioleaching process.

PubMed

Xiao, Yunhua; Liu, Xueduan; Dong, Weiling; Liang, Yili; Niu, Jiaojiao; Gu, Yabing; Ma, Liyuan; Hao, Xiaodong; Zhang, Xian; Xu, Zhen; Yin, Huaqun

2017-07-01

This study used an artificial microbial community with four known moderately thermophilic acidophiles (three bacteria including Acidithiobacillus caldus S1, Sulfobacillus thermosulfidooxidans ST and Leptospirillum ferriphilum YSK, and one archaea, Ferroplasma thermophilum L1) to explore the variation of microbial community structure, composition, dynamics and function (e.g., copper extraction efficiency) in chalcopyrite bioleaching (C) systems with additions of pyrite (CP) or sphalerite (CS). The community compositions and dynamics in the solution and on the ore surface were investigated by real-time quantitative PCR (qPCR). The results showed that the addition of pyrite or sphalerite changed the microbial community composition and dynamics dramatically during the chalcopyrite bioleaching process. For example, A. caldus (above 60%) was the dominant species at the initial stage in three groups, and at the middle stage, still dominated C group (above 70%), but it was replaced by L. ferriphilum (above 60%) in CP and CS groups; at the final stage, L. ferriphilum dominated C group, while F. thermophilum dominated CP group on the ore surface. Furthermore, the additions of pyrite or sphalerite both made the increase of redox potential (ORP) and the concentrations of Fe 3+ and H + , which would affect the microbial community compositions and copper extraction efficiency. Additionally, pyrite could enhance copper extraction efficiency (e.g., improving around 13.2% on day 6) during chalcopyrite bioleaching; on the contrary, sphalerite restrained it.

A hybrid system identification methodology for wireless structural health monitoring systems based on dynamic substructuring

NASA Astrophysics Data System (ADS)

Dragos, Kosmas; Smarsly, Kay

2016-04-01

System identification has been employed in numerous structural health monitoring (SHM) applications. Traditional system identification methods usually rely on centralized processing of structural response data to extract information on structural parameters. However, in wireless SHM systems the centralized processing of structural response data introduces a significant communication bottleneck. Exploiting the merits of decentralization and on-board processing power of wireless SHM systems, many system identification methods have been successfully implemented in wireless sensor networks. While several system identification approaches for wireless SHM systems have been proposed, little attention has been paid to obtaining information on the physical parameters (e.g. stiffness, damping) of the monitored structure. This paper presents a hybrid system identification methodology suitable for wireless sensor networks based on the principles of component mode synthesis (dynamic substructuring). A numerical model of the monitored structure is embedded into the wireless sensor nodes in a distributed manner, i.e. the entire model is segmented into sub-models, each embedded into one sensor node corresponding to the substructure the sensor node is assigned to. The parameters of each sub-model are estimated by extracting local mode shapes and by applying the equations of the Craig-Bampton method on dynamic substructuring. The proposed methodology is validated in a laboratory test conducted on a four-story frame structure to demonstrate the ability of the methodology to yield accurate estimates of stiffness parameters. Finally, the test results are discussed and an outlook on future research directions is provided.

Automated dynamic hollow fiber liquid-liquid-liquid microextraction combined with capillary electrophoresis for speciation of mercury in biological and environmental samples.

PubMed

Li, Pingjing; He, Man; Chen, Beibei; Hu, Bin

2015-10-09

A simple home-made automatic dynamic hollow fiber based liquid-liquid-liquid microextraction (AD-HF-LLLME) device was designed and constructed for the simultaneous extraction of organomercury and inorganic mercury species with the assistant of a programmable flow injection analyzer. With 18-crown-6 as the complexing reagent, mercury species including methyl-, ethyl-, phenyl- and inorganic mercury were extracted into the organic phase (chlorobenzene), and then back-extracted into the acceptor phase of 0.1% (m/v) 3-mercapto-1-propanesulfonic acid (MPS) aqueous solution. Compared with automatic static (AS)-HF-LLLME system, the extraction equilibrium of target mercury species was obtained in shorter time with higher extraction efficiency in AD-HF-LLLME system. Based on it, a new method of AD-HF-LLLME coupled with large volume sample stacking (LVSS)-capillary electrophoresis (CE)/UV detection was developed for the simultaneous analysis of methyl-, phenyl- and inorganic mercury species in biological samples and environmental water. Under the optimized conditions, AD-HF-LLLME provided high enrichment factors (EFs) of 149-253-fold within relatively short extraction equilibrium time (25min) and good precision with RSD between 3.8 and 8.1%. By combining AD-HF-LLLME with LVSS-CE/UV, EFs were magnified up to 2195-fold and the limits of detection (at S/N=3) for target mercury species were improved to be sub ppb level. Copyright © 2015 Elsevier B.V. All rights reserved.

Optimization of dynamic headspace extraction system for measurement of halogenated volatile organic compounds in liquid or viscous samples

NASA Astrophysics Data System (ADS)

Taniai, G.; Oda, H.; Kurihara, M.; Hashimoto, S.

2010-12-01

Halogenated volatile organic compounds (HVOCs) produced in the marine environment are thought to play a key role in atmospheric reactions, particularly those involved in the global radiation budget and the depression of tropospheric and stratospheric ozone. To evaluate HVOCs concentrations in the various natural samples, we developed an automated dynamic headspace extraction method for the determination of 15 HVOCs, such as chloromethane, bromomethane, bromoethane, iodomethane, iodoethane, bromochloromethane, 1-iodopropane, 2-iodopropane, dibromomethane, bromodichloromethane, chloroiodomethane, chlorodibromomethane, bromoiodomethane, tribromomethane, and diiodomethane. Dynamic headspace system (GERSTEL DHS) was used to purge the gas phase above samples and to trap HVOCs on the adsorbent column from the purge gas. We measured the HVOCs concentrations in the adsorbent column with gas chromatograph (Agilent 6890N)- mass spectrometer (Agilent 5975C). In dynamic headspace system, an glass tube containing Tenax TA or Tenax GR was used as adsorbent column for the collection of 15 HVOCs. The parameters for purge and trap extraction, such as purge flow rate (ml/min), purge volume (ml), incubation time (min), and agitator speed (rpm), were optimized. The detection limits of HVOCs in water samples were 1270 pM (chloromethane), 103 pM (bromomethane), 42.1 pM (iodomethane), and 1.4 to 10.2 pM (other HVOCs). The repeatability (relative standard deviation) for 15 HVOCs were < 9 % except chloromethane (16.2 %) and bromomethane (11.0 %). On the basis of the measurements for various samples, we concluded that this analytical method is useful for the determination of wide range of HVOCs with boiling points between - 24°C (chloromethane) and 181°C (diiodomethane) for the liquid or viscous samples.

Automated smoother for the numerical decoupling of dynamics models.

PubMed

Vilela, Marco; Borges, Carlos C H; Vinga, Susana; Vasconcelos, Ana Tereza R; Santos, Helena; Voit, Eberhard O; Almeida, Jonas S

2007-08-21

Structure identification of dynamic models for complex biological systems is the cornerstone of their reverse engineering. Biochemical Systems Theory (BST) offers a particularly convenient solution because its parameters are kinetic-order coefficients which directly identify the topology of the underlying network of processes. We have previously proposed a numerical decoupling procedure that allows the identification of multivariate dynamic models of complex biological processes. While described here within the context of BST, this procedure has a general applicability to signal extraction. Our original implementation relied on artificial neural networks (ANN), which caused slight, undesirable bias during the smoothing of the time courses. As an alternative, we propose here an adaptation of the Whittaker's smoother and demonstrate its role within a robust, fully automated structure identification procedure. In this report we propose a robust, fully automated solution for signal extraction from time series, which is the prerequisite for the efficient reverse engineering of biological systems models. The Whittaker's smoother is reformulated within the context of information theory and extended by the development of adaptive signal segmentation to account for heterogeneous noise structures. The resulting procedure can be used on arbitrary time series with a nonstationary noise process; it is illustrated here with metabolic profiles obtained from in-vivo NMR experiments. The smoothed solution that is free of parametric bias permits differentiation, which is crucial for the numerical decoupling of systems of differential equations. The method is applicable in signal extraction from time series with nonstationary noise structure and can be applied in the numerical decoupling of system of differential equations into algebraic equations, and thus constitutes a rather general tool for the reverse engineering of mechanistic model descriptions from multivariate experimental time series.

A method of ECG template extraction for biometrics applications.

PubMed

Zhou, Xiang; Lu, Yang; Chen, Meng; Bao, Shu-Di; Miao, Fen

2014-01-01

ECG has attracted widespread attention as one of the most important non-invasive physiological signals in healthcare-system related biometrics for its characteristics like ease-of-monitoring, individual uniqueness as well as important clinical value. This study proposes a method of dynamic threshold setting to extract the most stable ECG waveform as the template for the consequent ECG identification process. With the proposed method, the accuracy of ECG biometrics using the dynamic time wraping for difference measures has been significantly improved. Analysis results with the self-built electrocardiogram database show that the deployment of the proposed method was able to reduce the half total error rate of the ECG biometric system from 3.35% to 1.45%. Its average running time on the platform of android mobile terminal was around 0.06 seconds, and thus demonstrates acceptable real-time performance.

Molecular dynamics in principal component space.

PubMed

Michielssens, Servaas; van Erp, Titus S; Kutzner, Carsten; Ceulemans, Arnout; de Groot, Bert L

2012-07-26

A molecular dynamics algorithm in principal component space is presented. It is demonstrated that sampling can be improved without changing the ensemble by assigning masses to the principal components proportional to the inverse square root of the eigenvalues. The setup of the simulation requires no prior knowledge of the system; a short initial MD simulation to extract the eigenvectors and eigenvalues suffices. Independent measures indicated a 6-7 times faster sampling compared to a regular molecular dynamics simulation.

Simultaneous measurement of temperature and emissivity of lunar regolith simulant using dual-channel millimeter-wave radiometry

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

McCloy, J. S.; Sundaram, S. K.; Matyas, J.

Millimeter wave (MMW) radiometry can be used for simultaneous measurement of emissivity and temperature of materials under extreme environments (high temperature, pressure, and corrosive environments). The state-of-the-art dual channel MMW passive radiometer with active interferometric capabilities at 137 GHz described here allows for radiometric measurements of sample temperature and emissivity up to at least 1600 °C with simultaneous measurement of sample surface dynamics. These capabilities have been used to demonstrate dynamic measurement of melting of powders of simulated lunar regolith and static measurement of emissivity of solid samples. The paper presents the theoretical background and basis for the dual-receiver system,more » describes the hardware in detail, and demonstrates the data analysis. Post-experiment analysis of emissivity versus temperature allows further extraction from the radiometric data of millimeter wave viewing beam coupling factors, which provide corroboratory evidence to the interferometric data of the process dynamics observed. Finally, these results show the promise of the MMW system for extracting quantitative and qualitative process parameters for industrial processes and access to real-time dynamics of materials behavior in extreme environments.« less

Ocular dynamics of systemic aqueous extracts of Xylopia aethiopica (African guinea pepper) seeds on visually active volunteers.

PubMed

Igwe, S A; Afonne, J C; Ghasi, S I

2003-06-01

Xylopia aethiopica, African guinea pepper, is an angiosperm belonging to the family Annonecae, and used mainly as spice and in traditional medicine. The ocular dynamics of bolus consumption of 300 mg total dose was undertaken on visually active volunteers with a view to finding its ocular effects or complications. Results showed that the aqueous extract of X. aethiopica was neither a miotic nor a mydriatic, but lowered the intraocular pressure (17.48%), reduced the near point of convergence (31.1%) and increased the amplitude of accommodation (8.98%) which are positively correlated (r=0.95). On the other hand, the systemic extract had no effect on the visual acuity at far and near as well as the phoria status at the appropriate distances. The convergence excess resulted in esophoria and the increased amplitude of accommodation placed greater demand on accommodation mechanism without any discomfort. The nonspecific mechanism of action makes it a safer spice which can be exploited in the management of exophoria and raised intraocular pressure (glaucoma) in instances where the efficacy of the older conventional drugs is insufficient.

Model and Data Reduction for Control, Identification and Compressed Sensing

NASA Astrophysics Data System (ADS)

Kramer, Boris

This dissertation focuses on problems in design, optimization and control of complex, large-scale dynamical systems from different viewpoints. The goal is to develop new algorithms and methods, that solve real problems more efficiently, together with providing mathematical insight into the success of those methods. There are three main contributions in this dissertation. In Chapter 3, we provide a new method to solve large-scale algebraic Riccati equations, which arise in optimal control, filtering and model reduction. We present a projection based algorithm utilizing proper orthogonal decomposition, which is demonstrated to produce highly accurate solutions at low rank. The method is parallelizable, easy to implement for practitioners, and is a first step towards a matrix free approach to solve AREs. Numerical examples for n ≥ 106 unknowns are presented. In Chapter 4, we develop a system identification method which is motivated by tangential interpolation. This addresses the challenge of fitting linear time invariant systems to input-output responses of complex dynamics, where the number of inputs and outputs is relatively large. The method reduces the computational burden imposed by a full singular value decomposition, by carefully choosing directions on which to project the impulse response prior to assembly of the Hankel matrix. The identification and model reduction step follows from the eigensystem realization algorithm. We present three numerical examples, a mass spring damper system, a heat transfer problem, and a fluid dynamics system. We obtain error bounds and stability results for this method. Chapter 5 deals with control and observation design for parameter dependent dynamical systems. We address this by using local parametric reduced order models, which can be used online. Data available from simulations of the system at various configurations (parameters, boundary conditions) is used to extract a sparse basis to represent the dynamics (via dynamic mode decomposition). Subsequently, a new, compressed sensing based classification algorithm is developed which incorporates the extracted dynamic information into the sensing basis. We show that this augmented classification basis makes the method more robust to noise, and results in superior identification of the correct parameter. Numerical examples consist of a Navier-Stokes, as well as a Boussinesq flow application.

Single neuron computation: from dynamical system to feature detector.

PubMed

Hong, Sungho; Agüera y Arcas, Blaise; Fairhall, Adrienne L

2007-12-01

White noise methods are a powerful tool for characterizing the computation performed by neural systems. These methods allow one to identify the feature or features that a neural system extracts from a complex input and to determine how these features are combined to drive the system's spiking response. These methods have also been applied to characterize the input-output relations of single neurons driven by synaptic inputs, simulated by direct current injection. To interpret the results of white noise analysis of single neurons, we would like to understand how the obtained feature space of a single neuron maps onto the biophysical properties of the membrane, in particular, the dynamics of ion channels. Here, through analysis of a simple dynamical model neuron, we draw explicit connections between the output of a white noise analysis and the underlying dynamical system. We find that under certain assumptions, the form of the relevant features is well defined by the parameters of the dynamical system. Further, we show that under some conditions, the feature space is spanned by the spike-triggered average and its successive order time derivatives.

Experimental Determination of Dynamical Lee-Yang Zeros

NASA Astrophysics Data System (ADS)

Brandner, Kay; Maisi, Ville F.; Pekola, Jukka P.; Garrahan, Juan P.; Flindt, Christian

2017-05-01

Statistical physics provides the concepts and methods to explain the phase behavior of interacting many-body systems. Investigations of Lee-Yang zeros—complex singularities of the free energy in systems of finite size—have led to a unified understanding of equilibrium phase transitions. The ideas of Lee and Yang, however, are not restricted to equilibrium phenomena. Recently, Lee-Yang zeros have been used to characterize nonequilibrium processes such as dynamical phase transitions in quantum systems after a quench or dynamic order-disorder transitions in glasses. Here, we experimentally realize a scheme for determining Lee-Yang zeros in such nonequilibrium settings. We extract the dynamical Lee-Yang zeros of a stochastic process involving Andreev tunneling between a normal-state island and two superconducting leads from measurements of the dynamical activity along a trajectory. From the short-time behavior of the Lee-Yang zeros, we predict the large-deviation statistics of the activity which is typically difficult to measure. Our method paves the way for further experiments on the statistical mechanics of many-body systems out of equilibrium.

Rigging Test Bed Development for Validation of Multi-Stage Decelerator Extractions

NASA Technical Reports Server (NTRS)

Kenig, Sivan J.; Gallon, John C.; Adams, Douglas S.; Rivellini, Tommaso P.

2013-01-01

The Low Density Supersonic Decelerator project is developing new decelerator systems for Mars entry which would include testing with a Supersonic Flight Dynamics Test Vehicle. One of the decelerator systems being developed is a large supersonic ringsail parachute. Due to the configuration of the vehicle it is not possible to deploy the parachute with a mortar which would be the preferred method for a spacecraft in a supersonic flow. Alternatively, a multi-stage extraction process using a ballute as a pilot is being developed for the test vehicle. The Rigging Test Bed is a test venue being constructed to perform verification and validation of this extraction process. The test bed consists of a long pneumatic piston device capable of providing a constant force simulating the ballute drag force during the extraction events. The extraction tests will take place both inside a high-bay for frequent tests of individual extraction stages and outdoors using a mobile hydraulic crane for complete deployment tests from initial pack pull out to canopy extraction. These tests will measure line tensions and use photogrammetry to track motion of the elements involved. The resulting data will be used to verify packing and rigging as well, as validate models and identify potential failure modes in order to finalize the design of the extraction system.

Chiral dynamics with (non)strange quarks

NASA Astrophysics Data System (ADS)

Kubis, Bastian; Meißner, Ulf-G.

2017-01-01

We review the results and achievements of the project B.3. Topics addressed include pion photoproduction off the proton and off deuterium, three-flavor chiral perturbation theory studies, chiral symmetry tests in Goldstone boson decays, the development of unitarized chiral perturbation theory to next-to-leading order, the two-pole structure of the Λ(1405), the dynamical generation of the lowest S11 resonances, the theory of hadronic atoms and its application to various systems, precision studies in light-meson decays based on dispersion theory, the Roy-Steiner analysis of pion-nucleon scattering, a high-precision extraction of the elusive pion-nucleon σ-term, and aspects of chiral dynamics in few-nucleon systems.

Compressive Information Extraction: A Dynamical Systems Approach

DTIC Science & Technology

2016-01-24

sparsely encoded in very large data streams. (a) Target tracking in an urban canyon; (b) and (c) sample frames showing contextually abnormal events: onset...extraction to identify contextually abnormal se- quences (see section 2.2.3). Formally, the problem of interest can be stated as establishing whether a noisy...relaxations with optimality guarantees can be obtained using tools from semi-algebraic geometry. 2.2 Application: Detecting Contextually Abnormal Events

Observer properties for understanding dynamical displays: Capacities, limitations, and defaults

NASA Technical Reports Server (NTRS)

Proffitt, Dennis R.; Kaiser, Mary K.

1991-01-01

People's ability to extract relevant information while viewing ongoing events is discussed in terms of human capabilities, limitations, and defaults. A taxonomy of event complexity is developed which predicts which dynamical events people can and cannot construe. This taxonomy is related to the distinction drawn in classical mechanics between particle and extended body motions. People's commonsense understandings of simple mechanical systems are impacted little by formal training, but rather reflect heuristical simplifications that focus on a single dimension of perceived dynamical relevance.

Improved GART neural network model for pattern classification and rule extraction with application to power systems.

PubMed

Yap, Keem Siah; Lim, Chee Peng; Au, Mau Teng

2011-12-01

Generalized adaptive resonance theory (GART) is a neural network model that is capable of online learning and is effective in tackling pattern classification tasks. In this paper, we propose an improved GART model (IGART), and demonstrate its applicability to power systems. IGART enhances the dynamics of GART in several aspects, which include the use of the Laplacian likelihood function, a new vigilance function, a new match-tracking mechanism, an ordering algorithm for determining the sequence of training data, and a rule extraction capability to elicit if-then rules from the network. To assess the effectiveness of IGART and to compare its performances with those from other methods, three datasets that are related to power systems are employed. The experimental results demonstrate the usefulness of IGART with the rule extraction capability in undertaking classification problems in power systems engineering.

Evaluation of human dynamic balance in Grassmann manifold

NASA Astrophysics Data System (ADS)

Michalczuk, Agnieszka; Wereszczyński, Kamil; Mucha, Romualda; Świtoński, Adam; Josiński, Henryk; Wojciechowski, Konrad

2017-07-01

The authors present an application of Grassmann manifold to the evaluation of human dynamic balance based on the time series representing movements of hip, knee and ankle joints in the sagittal, frontal and transverse planes. Time series were extracted from gait sequences which were recorded in the Human Motion Laboratory (HML) of the Polish-Japanese Academy of Information Technology in Bytom, Poland using the Vicon system.

Tropical forest harvesting and taxation: a dynamic model of harvesting behavior under selective extraction systems

Treesearch

Robert F. Conrad; Malcolm Gillis; D. Evan Mercer

2005-01-01

A dynamic model of selective harvesting in multi-species,multi-age tropical forests is developed. Forests are predicted to exhibit different optimal harvesting profiles depending on the nature of their joint cost functions and own or cross-species stock effects. The model is applied to the controversy about incentives produced by various taxes. The impacts of specific...

An assessment of the liquid-gas partitioning behavior of major wastewater odorants using two comparative experimental approaches: liquid sample-based vaporization vs. impinger-based dynamic headspace extraction into sorbent tubes.

PubMed

Iqbal, Mohammad Asif; Kim, Ki-Hyun; Szulejko, Jan E; Cho, Jinwoo

2014-01-01

The gas-liquid partitioning behavior of major odorants (acetic acid, propionic acid, isobutyric acid, n-butyric acid, i-valeric acid, n-valeric acid, hexanoic acid, phenol, p-cresol, indole, skatole, and toluene (as a reference)) commonly found in microbially digested wastewaters was investigated by two experimental approaches. Firstly, a simple vaporization method was applied to measure the target odorants dissolved in liquid samples with the aid of sorbent tube/thermal desorption/gas chromatography/mass spectrometry. As an alternative method, an impinger-based dynamic headspace sampling method was also explored to measure the partitioning of target odorants between the gas and liquid phases with the same detection system. The relative extraction efficiency (in percent) of the odorants by dynamic headspace sampling was estimated against the calibration results derived by the vaporization method. Finally, the concentrations of the major odorants in real digested wastewater samples were also analyzed using both analytical approaches. Through a parallel application of the two experimental methods, we intended to develop an experimental approach to be able to assess the liquid-to-gas phase partitioning behavior of major odorants in a complex wastewater system. The relative sensitivity of the two methods expressed in terms of response factor ratios (RFvap/RFimp) of liquid standard calibration between vaporization and impinger-based calibrations varied widely from 981 (skatole) to 6,022 (acetic acid). Comparison of this relative sensitivity thus highlights the rather low extraction efficiency of the highly soluble and more acidic odorants from wastewater samples in dynamic headspace sampling.

An integrated automatic system to evaluate U and Th dynamic lixiviation from solid matrices, and to extract/pre-concentrate leached analytes previous ICP-MS detection.

PubMed

Ceballos, Melisa Rodas; García-Tenorio, Rafael; Estela, José Manuel; Cerdà, Víctor; Ferrer, Laura

2017-12-01

Leached fractions of U and Th from different environmental solid matrices were evaluated by an automatic system enabling the on-line lixiviation and extraction/pre-concentration of these two elements previous ICP-MS detection. UTEVA resin was used as selective extraction material. Ten leached fraction, using artificial rainwater (pH 5.4) as leaching agent, and a residual fraction were analyzed for each sample, allowing the study of behavior of U and Th in dynamic lixiviation conditions. Multivariate techniques have been employed for the efficient optimization of the independent variables that affect the lixiviation process. The system reached LODs of 0.1 and 0.7ngkg -1 of U and Th, respectively. The method was satisfactorily validated for three solid matrices, by the analysis of a soil reference material (IAEA-375), a certified sediment reference material (BCR- 320R) and a phosphogypsum reference material (MatControl CSN-CIEMAT 2008). Besides, environmental samples were analyzed, showing a similar behavior, i.e. the content of radionuclides decreases with the successive extractions. In all cases, the accumulative leached fraction of U and Th for different solid matrices studied (soil, sediment and phosphogypsum) were extremely low, up to 0.05% and 0.005% of U and Th, respectively. However, a great variability was observed in terms of mass concentration released, e.g. between 44 and 13,967ngUkg -1 . Copyright © 2017 Elsevier B.V. All rights reserved.

Estimation Method of Center of Inertia Frequency based on Multiple Synchronized Phasor Measurement Data

NASA Astrophysics Data System (ADS)

Hashiguchi, Takuhei; Watanabe, Masayuki; Goda, Tadahiro; Mitani, Yasunori; Saeki, Osamu; Hojo, Masahide; Ukai, Hiroyuki

Open access and deregulation have been introduced into Japan and some independent power producers (IPP) and power producer and suppliers (PPS) are participating in the power generation business, which is possible to makes power system dynamics more complex. To maintain power system condition under various situations, it is essential that a real time measurement system over wide area is available. Therefore we started a project to construct an original measurement system by the use of phasor measurement units (PMU) in Japan. This paper describes the estimation method of a center of inertia frequency by applying actual measurement data. The application of this method enables us to extract power system oscillations from measurement data appropriately. Moreover, the analysis of power system dynamics for power system oscillations occurring in western Japan 60Hz system is shown. These results will lead to the clarification of power system dynamics and may make it possible to realize the monitoring of power system oscillations associated with power system stability.

Studying Climate Response to Forcing by the Nonlinear Dynamical Mode Decomposition

NASA Astrophysics Data System (ADS)

Mukhin, Dmitry; Gavrilov, Andrey; Loskutov, Evgeny; Feigin, Alexander

2017-04-01

An analysis of global climate response to external forcing, both anthropogenic (mainly, CO2 and aerosol) and natural (solar and volcanic), is needed for adequate predictions of global climate change. Being complex dynamical system, the climate reacts to external perturbations exciting feedbacks (both positive and negative) making the response non-trivial and poorly predictable. Thus an extraction of internal modes of climate system, investigation of their interaction with external forcings and further modeling and forecast of their dynamics, are all the problems providing the success of climate modeling. In the report the new method for principal mode extraction from climate data is presented. The method is based on the Nonlinear Dynamical Mode (NDM) expansion [1,2], but takes into account a number of external forcings applied to the system. Each NDM is represented by hidden time series governing the observed variability, which, together with external forcing time series, are mapped onto data space. While forcing time series are considered to be known, the hidden unknown signals underlying the internal climate dynamics are extracted from observed data by the suggested method. In particular, it gives us an opportunity to study the evolution of principal system's mode structure in changing external conditions and separate the internal climate variability from trends forced by external perturbations. Furthermore, the modes so obtained can be extrapolated beyond the observational time series, and long-term prognosis of modes' structure including characteristics of interconnections and responses to external perturbations, can be carried out. In this work the method is used for reconstructing and studying the principal modes of climate variability on inter-annual and decadal time scales accounting the external forcings such as anthropogenic emissions, variations of the solar activity and volcanic activity. The structure of the obtained modes as well as their response to external factors, e.g. forecast their change in 21 century under different CO2 emission scenarios, are discussed. [1] Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510 [2] Gavrilov, A., Mukhin, D., Loskutov, E., Volodin, E., Feigin, A., & Kurths, J. (2016). Method for reconstructing nonlinear modes with adaptive structure from multidimensional data. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(12), 123101. http://doi.org/10.1063/1.4968852

78 FR 70075 - Notice of Permit Applications Received Under the Antarctic Conservation Act of 1978 (Public Law...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-22

... establishment of a permit system for various activities in Antarctica and designation of certain animals and certain geographic areas a requiring special protection. The regulations establish such a permit system to..., stable isotope analysis, and DNA extraction. Data would be used to reconstruct seal population dynamics...

Practical limits for reverse engineering of dynamical systems: a statistical analysis of sensitivity and parameter inferability in systems biology models.

PubMed

Erguler, Kamil; Stumpf, Michael P H

2011-05-01

The size and complexity of cellular systems make building predictive models an extremely difficult task. In principle dynamical time-course data can be used to elucidate the structure of the underlying molecular mechanisms, but a central and recurring problem is that many and very different models can be fitted to experimental data, especially when the latter are limited and subject to noise. Even given a model, estimating its parameters remains challenging in real-world systems. Here we present a comprehensive analysis of 180 systems biology models, which allows us to classify the parameters with respect to their contribution to the overall dynamical behaviour of the different systems. Our results reveal candidate elements of control in biochemical pathways that differentially contribute to dynamics. We introduce sensitivity profiles that concisely characterize parameter sensitivity and demonstrate how this can be connected to variability in data. Systematically linking data and model sloppiness allows us to extract features of dynamical systems that determine how well parameters can be estimated from time-course measurements, and associates the extent of data required for parameter inference with the model structure, and also with the global dynamical state of the system. The comprehensive analysis of so many systems biology models reaffirms the inability to estimate precisely most model or kinetic parameters as a generic feature of dynamical systems, and provides safe guidelines for performing better inferences and model predictions in the context of reverse engineering of mathematical models for biological systems.

Xenopus extract approaches to studying microtubule organization and signaling in cytokinesis

PubMed Central

Field, Christine M.; Pelletier, James F.; Mitchison, Timothy J.

2017-01-01

We report optimized methods for preparing actin-intact Xenopus egg extract. This extract is minimally perturbed, undiluted egg cytoplasm where the cell cycle can be experimentally controlled. It contains abundant organelles and glycogen, and supports active metabolism and cytoskeletal dynamics that closely mimic egg physiology. The concentration of the most abundant ~11,000 proteins is known from mass spectrometry. Actin-intact egg extract can be used for analysis of actin dynamics and interaction of actin with other cytoplasmic systems, as well as microtubule organization. It can be spread as thin layers, and naturally depletes oxygen though mitochondrial metabolism, which makes it ideal for fluorescence imaging. When combined with artificial lipid bilayers, it allows reconstitution and analysis of the spatially controlled signaling that positions the cleavage furrow during early cytokinesis. Actin-intact extract is generally useful for probing the biochemistry and biophysics of the large Xenopus egg. Protocols are provided for preparation of actin-intact egg extract, control of the cell cycle, fluorescent probes for cytoskeleton and cytoskeleton-dependent signaling, preparation of glass surfaces for imaging experiments, and immunodepletion to probe the role of specific proteins and protein complexes. We also describe methods for adding supported lipid bilayers to mimic the plasma membrane and for confining in microfluidic droplets to explore size scaling issues. PMID:28065319

Optimal Control Strategy Design Based on Dynamic Programming for a Dual-Motor Coupling-Propulsion System

PubMed Central

Zhang, Shuo; Zhang, Chengning; Han, Guangwei; Wang, Qinghui

2014-01-01

A dual-motor coupling-propulsion electric bus (DMCPEB) is modeled, and its optimal control strategy is studied in this paper. The necessary dynamic features of energy loss for subsystems is modeled. Dynamic programming (DP) technique is applied to find the optimal control strategy including upshift threshold, downshift threshold, and power split ratio between the main motor and auxiliary motor. Improved control rules are extracted from the DP-based control solution, forming near-optimal control strategies. Simulation results demonstrate that a significant improvement in reducing energy loss due to the dual-motor coupling-propulsion system (DMCPS) running is realized without increasing the frequency of the mode switch. PMID:25540814

Optimal control strategy design based on dynamic programming for a dual-motor coupling-propulsion system.

PubMed

Zhang, Shuo; Zhang, Chengning; Han, Guangwei; Wang, Qinghui

2014-01-01

A dual-motor coupling-propulsion electric bus (DMCPEB) is modeled, and its optimal control strategy is studied in this paper. The necessary dynamic features of energy loss for subsystems is modeled. Dynamic programming (DP) technique is applied to find the optimal control strategy including upshift threshold, downshift threshold, and power split ratio between the main motor and auxiliary motor. Improved control rules are extracted from the DP-based control solution, forming near-optimal control strategies. Simulation results demonstrate that a significant improvement in reducing energy loss due to the dual-motor coupling-propulsion system (DMCPS) running is realized without increasing the frequency of the mode switch.

The influence of organic-mineral complexes on micro-elements dynamic in ecological systems of vegetables cultivation

NASA Astrophysics Data System (ADS)

Bulgariu, D.; Buzgar, N.; Bulgariu, L.; Rusu, C.; Munteanu, N.

2009-04-01

In ecological systems of vegetable cultivation (hortic antrosols; soils from greenhouses), exists an ensemble of equilibriums between organic-mineral combinations, very sensitive even to relatively small variations of physical-chemical conditions in soils. As such, these can manifest a strong influence on organic matter, clay minerals and microelements from soil, which in turn impacts on the productivity of these soils and the quality of obtained products (vegetables, fruit). Although many studies consider these organic-mineral combinations are meta-stable combinations, our work has shown that the stability of organic-mineral combinations in hortic antrosols (especially for clay-humic, clay-ironhumic combinations and chelates) is higher. We believe that this is due to the higher flexibility of these combinations' structures with the variation of chemical-mineralogical composition and physical-chemical conditions in soil. This paper highlights the results of our research on the differentiation possibility of organic-mineral complexes, depending on their structure and composition (using Raman and FT-IR spectrometry) and the influences manifested by the organic-mineral complexes on the micro-elements dynamic from ecological systems of fresh vegetable cultivation. The non-destructive separation of organic-mineral compounds from soil samples was carried out through iso-dynamic magnetic separation and extraction in aqueous two-phase systems (PEG-based). The Raman and FT-IR spectrometry analyses on raw soil samples, extracts obtained from soil samples and separated mineral fractions have been supplemented by the results obtained through chemical, microscopic and thermal analyses and by UV-VIS absorption spectrometry. Ours experimental studies have been done on representative samples of hortic antrosol from Copou glasshouse (Iasi, Romania), and was studied five micro-elements: Zn, Ni, Cu, Mn, Cr and P. The total contents of the five microelements and their fractions differential bonded on mineral and organic components of hortic antrosols, have been determined by atomic absorption spectrometry after combined sequential extraction in solid phase extraction - aqueous biphasic (PEG based) systems. The specific mechanisms of the microelements interaction with organic components have been estimated on the basis of studies realized on fractions obtained after each extraction step by Raman and FTIR spectrometry. These data have been correlated with those obtained by chemical analysis and UV-VIS spectrometry. In conditions of hortic antrosol, from total contents of Zn, Ni, Cu, Mn and Cr, more than 65 % are binding on organic components. A specific phenomenon of hortic antrosols is the microelements complexation exclusively with the functional groups of organic macromolecules. This phenomenon has two important consequences: (i) the strong fixation of microelements (these can be extracted only in very extremely conditions, which implied the organic part destroying) and (ii) their presence determined major modifications in the structure, conformation and stability of organic macromolecules. Under these conditions, the type and structure of organic-mineral compounds represent determinant factors for the dynamic of micro-elements and organic compounds in ecological systems of vegetables cultivation. Acknowledgments The authors would like to acknowledge the financial support from Romanian Ministry of Education and Research (Project PNCDI 2-D5 no. 51045/07 an Project PNCDI 2-D5 no. 52141 / 08).

A Novel Dynamic Update Framework for Epileptic Seizure Prediction

PubMed Central

Wang, Minghui; Hong, Xiaojun; Han, Jie

2014-01-01

Epileptic seizure prediction is a difficult problem in clinical applications, and it has the potential to significantly improve the patients' daily lives whose seizures cannot be controlled by either drugs or surgery. However, most current studies of epileptic seizure prediction focus on high sensitivity and low false-positive rate only and lack the flexibility for a variety of epileptic seizures and patients' physical conditions. Therefore, a novel dynamic update framework for epileptic seizure prediction is proposed in this paper. In this framework, two basic sample pools are constructed and updated dynamically. Furthermore, the prediction model can be updated to be the most appropriate one for the prediction of seizures' arrival. Mahalanobis distance is introduced in this part to solve the problem of side information, measuring the distance between two data sets. In addition, a multichannel feature extraction method based on Hilbert-Huang transform and extreme learning machine is utilized to extract the features of a patient's preseizure state against the normal state. At last, a dynamic update epileptic seizure prediction system is built up. Simulations on Freiburg database show that the proposed system has a better performance than the one without update. The research of this paper is significantly helpful for clinical applications, especially for the exploitation of online portable devices. PMID:25050381

A novel dynamic update framework for epileptic seizure prediction.

PubMed

Han, Min; Ge, Sunan; Wang, Minghui; Hong, Xiaojun; Han, Jie

2014-01-01

Epileptic seizure prediction is a difficult problem in clinical applications, and it has the potential to significantly improve the patients' daily lives whose seizures cannot be controlled by either drugs or surgery. However, most current studies of epileptic seizure prediction focus on high sensitivity and low false-positive rate only and lack the flexibility for a variety of epileptic seizures and patients' physical conditions. Therefore, a novel dynamic update framework for epileptic seizure prediction is proposed in this paper. In this framework, two basic sample pools are constructed and updated dynamically. Furthermore, the prediction model can be updated to be the most appropriate one for the prediction of seizures' arrival. Mahalanobis distance is introduced in this part to solve the problem of side information, measuring the distance between two data sets. In addition, a multichannel feature extraction method based on Hilbert-Huang transform and extreme learning machine is utilized to extract the features of a patient's preseizure state against the normal state. At last, a dynamic update epileptic seizure prediction system is built up. Simulations on Freiburg database show that the proposed system has a better performance than the one without update. The research of this paper is significantly helpful for clinical applications, especially for the exploitation of online portable devices.

The development of a dynamic software for the user interaction from the geographic information system environment with the database of the calibration site of the satellite remote electro-optic sensors

NASA Astrophysics Data System (ADS)

Zyelyk, Ya. I.; Semeniv, O. V.

2015-12-01

The state of the problem of the post-launch calibration of the satellite electro-optic remote sensors and its solutions in Ukraine is analyzed. The database is improved and dynamic services for user interaction with database from the environment of open geographical information system Quantum GIS for information support of calibration activities are created. A dynamic application under QGIS is developed, implementing these services in the direction of the possibility of data entering, editing and extraction from the database, using the technology of object-oriented programming and of modern complex program design patterns. The functional and algorithmic support of this dynamic software and its interface are developed.

Operational Modal Analysis of Bridge Structures with Data from GNSS/Accelerometer Measurements.

PubMed

Xiong, Chunbao; Lu, Huali; Zhu, Jinsong

2017-02-23

Real-time dynamic displacement and acceleration responses of the main span section of the Tianjin Fumin Bridge in China under ambient excitation were tested using a Global Navigation Satellite System (GNSS) dynamic deformation monitoring system and an acceleration sensor vibration test system. Considering the close relationship between the GNSS multipath errors and measurement environment in combination with the noise reduction characteristics of different filtering algorithms, the researchers proposed an AFEC mixed filtering algorithm, which is an combination of autocorrelation function-based empirical mode decomposition (EMD) and Chebyshev mixed filtering to extract the real vibration displacement of the bridge structure after system error correction and filtering de-noising of signals collected by the GNSS. The proposed AFEC mixed filtering algorithm had high accuracy (1 mm) of real displacement at the elevation direction. Next, the traditional random decrement technique (used mainly for stationary random processes) was expanded to non-stationary random processes. Combining the expanded random decrement technique (RDT) and autoregressive moving average model (ARMA), the modal frequency of the bridge structural system was extracted using an expanded ARMA_RDT modal identification method, which was compared with the power spectrum analysis results of the acceleration signal and finite element analysis results. Identification results demonstrated that the proposed algorithm is applicable to analyze the dynamic displacement monitoring data of real bridge structures under ambient excitation and could identify the first five orders of the inherent frequencies of the structural system accurately. The identification error of the inherent frequency was smaller than 6%, indicating the high identification accuracy of the proposed algorithm. Furthermore, the GNSS dynamic deformation monitoring method can be used to monitor dynamic displacement and identify the modal parameters of bridge structures. The GNSS can monitor the working state of bridges effectively and accurately. Research results can provide references to evaluate the bearing capacity, safety performance, and durability of bridge structures during operation.

Operational Modal Analysis of Bridge Structures with Data from GNSS/Accelerometer Measurements

PubMed Central

Xiong, Chunbao; Lu, Huali; Zhu, Jinsong

2017-01-01

Real-time dynamic displacement and acceleration responses of the main span section of the Tianjin Fumin Bridge in China under ambient excitation were tested using a Global Navigation Satellite System (GNSS) dynamic deformation monitoring system and an acceleration sensor vibration test system. Considering the close relationship between the GNSS multipath errors and measurement environment in combination with the noise reduction characteristics of different filtering algorithms, the researchers proposed an AFEC mixed filtering algorithm, which is an combination of autocorrelation function-based empirical mode decomposition (EMD) and Chebyshev mixed filtering to extract the real vibration displacement of the bridge structure after system error correction and filtering de-noising of signals collected by the GNSS. The proposed AFEC mixed filtering algorithm had high accuracy (1 mm) of real displacement at the elevation direction. Next, the traditional random decrement technique (used mainly for stationary random processes) was expanded to non-stationary random processes. Combining the expanded random decrement technique (RDT) and autoregressive moving average model (ARMA), the modal frequency of the bridge structural system was extracted using an expanded ARMA_RDT modal identification method, which was compared with the power spectrum analysis results of the acceleration signal and finite element analysis results. Identification results demonstrated that the proposed algorithm is applicable to analyze the dynamic displacement monitoring data of real bridge structures under ambient excitation and could identify the first five orders of the inherent frequencies of the structural system accurately. The identification error of the inherent frequency was smaller than 6%, indicating the high identification accuracy of the proposed algorithm. Furthermore, the GNSS dynamic deformation monitoring method can be used to monitor dynamic displacement and identify the modal parameters of bridge structures. The GNSS can monitor the working state of bridges effectively and accurately. Research results can provide references to evaluate the bearing capacity, safety performance, and durability of bridge structures during operation. PMID:28241472

Intelligent classifier for dynamic fault patterns based on hidden Markov model

NASA Astrophysics Data System (ADS)

Xu, Bo; Feng, Yuguang; Yu, Jinsong

2006-11-01

It's difficult to build precise mathematical models for complex engineering systems because of the complexity of the structure and dynamics characteristics. Intelligent fault diagnosis introduces artificial intelligence and works in a different way without building the analytical mathematical model of a diagnostic object, so it's a practical approach to solve diagnostic problems of complex systems. This paper presents an intelligent fault diagnosis method, an integrated fault-pattern classifier based on Hidden Markov Model (HMM). This classifier consists of dynamic time warping (DTW) algorithm, self-organizing feature mapping (SOFM) network and Hidden Markov Model. First, after dynamic observation vector in measuring space is processed by DTW, the error vector including the fault feature of being tested system is obtained. Then a SOFM network is used as a feature extractor and vector quantization processor. Finally, fault diagnosis is realized by fault patterns classifying with the Hidden Markov Model classifier. The importing of dynamic time warping solves the problem of feature extracting from dynamic process vectors of complex system such as aeroengine, and makes it come true to diagnose complex system by utilizing dynamic process information. Simulating experiments show that the diagnosis model is easy to extend, and the fault pattern classifier is efficient and is convenient to the detecting and diagnosing of new faults.

Are galaxy distributions scale invariant? A perspective from dynamical systems theory

NASA Astrophysics Data System (ADS)

McCauley, J. L.

2002-06-01

Unless there is an evidence for fractal scaling with a single exponent over distances 0.1<=r<=100h-1Mpc, then the widely accepted notion of scale invariance of the correlation integral for 0.1<=r<=10h-1Mpc must be questioned. The attempt to extract a scaling exponent /ν from the correlation integral /n(r) by plotting /log(n(r)) vs. /log(r) is unreliable unless the underlying point set is approximately monofractal. The extraction of a spectrum of generalized dimensions νq from a plot of the correlation integral generating function Gn(q) by a similar procedure is probably an indication that Gn(q) does not scale at all. We explain these assertions after defining the term multifractal, mutually inconsistent definitions having been confused together in the cosmology literature. Part of this confusion is traced to the confusion in interpreting a measure-theoretic formula written down by Hentschel and Procaccia in the dynamical systems theory literature, while other errors follow from confusing together entirely different definitions of multifractal from two different schools of thought. Most important are serious errors in data analysis that follow from taking for granted a largest term approximation that is inevitably advertised in the literature on both fractals and dynamical systems theory.

System-size and beam energy dependence of the space-time extent of the pion emission source

NASA Astrophysics Data System (ADS)

Pak, Robert; Phenix Collaboration

2014-09-01

Two-pion interferometry measurements are used to extract the Gaussian source radii Rout ,Rside and Rlong , of the pion emission sources produced in d + Au, Cu +Cu and Au +Au collisions for several beam collision energies at PHENIX experiment. The extracted radii, which are compared to recent STAR and ALICE data, show characteristic scaling patterns as a function of the initial transverse geometric size of the collision system, and the transverse mass of the emitted pion pairs. These scaling patterns indicate a linear dependence of Rside on the initial transverse size, as well as a smaller freeze-out size for the d + Au system. Mathematical combinations of the extracted radii generally associated with the emission source duration and expansion rate exhibit non-monotonic behavior, suggesting a change in the expansion dynamics over this beam energy range.

Thermal machines beyond the weak coupling regime

NASA Astrophysics Data System (ADS)

Gallego, R.; Riera, A.; Eisert, J.

2014-12-01

How much work can be extracted from a heat bath using a thermal machine? The study of this question has a very long history in statistical physics in the weak-coupling limit, when applied to macroscopic systems. However, the assumption that thermal heat baths remain uncorrelated with associated physical systems is less reasonable on the nano-scale and in the quantum setting. In this work, we establish a framework of work extraction in the presence of quantum correlations. We show in a mathematically rigorous and quantitative fashion that quantum correlations and entanglement emerge as limitations to work extraction compared to what would be allowed by the second law of thermodynamics. At the heart of the approach are operations that capture the naturally non-equilibrium dynamics encountered when putting physical systems into contact with each other. We discuss various limits that relate to known results and put our work into the context of approaches to finite-time quantum thermodynamics.

Model-based restoration using light vein for range-gated imaging systems.

PubMed

Wang, Canjin; Sun, Tao; Wang, Tingfeng; Wang, Rui; Guo, Jin; Tian, Yuzhen

2016-09-10

The images captured by an airborne range-gated imaging system are degraded by many factors, such as light scattering, noise, defocus of the optical system, atmospheric disturbances, platform vibrations, and so on. The characteristics of low illumination, few details, and high noise make the state-of-the-art restoration method fail. In this paper, we present a restoration method especially for range-gated imaging systems. The degradation process is divided into two parts: the static part and the dynamic part. For the static part, we establish the physical model of the imaging system according to the laser transmission theory, and estimate the static point spread function (PSF). For the dynamic part, a so-called light vein feature extraction method is presented to estimate the fuzzy parameter of the atmospheric disturbance and platform movement, which make contributions to the dynamic PSF. Finally, combined with the static and dynamic PSF, an iterative updating framework is used to restore the image. Compared with the state-of-the-art methods, the proposed method can effectively suppress ringing artifacts and achieve better performance in a range-gated imaging system.

On solitons: the biomolecular nonlinear transmission line models with constant and time variable coefficients

NASA Astrophysics Data System (ADS)

Raza, Nauman; Murtaza, Isma Ghulam; Sial, Sultan; Younis, Muhammad

2018-07-01

The article studies the dynamics of solitons in electrical microtubule ? model, which describes the propagation of waves in nonlinear dynamical system. Microtubules are not only a passive support of a cell but also they have highly dynamic structures involved in cell motility, intracellular transport and signaling. The underlying model has been considered with constant and variable coefficients of time function. The solitary wave ansatz has been applied successfully to extract these solitons. The corresponding integrability criteria, also known as constraint conditions, naturally emerge from the analysis of these models.

Extraction and Separation Modeling of Orion Test Vehicles with ADAMS Simulation

NASA Technical Reports Server (NTRS)

Fraire, Usbaldo, Jr.; Anderson, Keith; Cuthbert, Peter A.

2013-01-01

The Capsule Parachute Assembly System (CPAS) project has increased efforts to demonstrate the performance of fully integrated parachute systems at both higher dynamic pressures and in the presence of wake fields using a Parachute Compartment Drop Test Vehicle (PCDTV) and a Parachute Test Vehicle (PTV), respectively. Modeling the extraction and separation events has proven challenging and an understanding of the physics is required to reduce the risk of separation malfunctions. The need for extraction and separation modeling is critical to a successful CPAS test campaign. Current PTV-alone simulations, such as Decelerator System Simulation (DSS), require accurate initial conditions (ICs) drawn from a separation model. Automatic Dynamic Analysis of Mechanical Systems (ADAMS), a Commercial off the Shelf (COTS) tool, was employed to provide insight into the multi-body six degree of freedom (DOF) interaction between parachute test hardware and external and internal forces. Components of the model include a composite extraction parachute, primary vehicle (PTV or PCDTV), platform cradle, a release mechanism, aircraft ramp, and a programmer parachute with attach points. Independent aerodynamic forces were applied to the mated test vehicle/platform cradle and the separated test vehicle and platform cradle. The aero coefficients were determined from real time lookup tables which were functions of both angle of attack ( ) and sideslip ( ). The atmospheric properties were also determined from a real time lookup table characteristic of the Yuma Proving Grounds (YPG) atmosphere relative to the planned test month. Representative geometries were constructed in ADAMS with measured mass properties generated for each independent vehicle. Derived smart separation parameters were included in ADAMS as sensors with defined pitch and pitch rate criteria used to refine inputs to analogous avionics systems for optimal separation conditions. Key design variables were dispersed in a Monte Carlo analysis to provide the maximum expected range of the state variables at programmer deployment to be used as ICs in DSS. Extensive comparisons were made with Decelerator System Simulation Application (DSSA) to validate the mated portion of the ADAMS extraction trajectory. Results of the comparisons improved the fidelity of ADAMS with a ramp pitch profile update from DSSA. Post-test reconstructions resulted in improvements to extraction parachute drag area knock-down factors, extraction line modeling, and the inclusion of ball-to-socket attachments used as a release mechanism on the PTV. Modeling of two Extraction parachutes was based on United States Air Force (USAF) tow test data and integrated into ADAMS for nominal and Monte Carlo trajectory assessments. Video overlay of ADAMS animations and actual C-12 chase plane test videos supported analysis and observation efforts of extraction and separation events. The COTS ADAMS simulation has been integrated with NASA based simulations to provide complete end to end trajectories with a focus on the extraction, separation, and programmer deployment sequence. The flexibility of modifying ADAMS inputs has proven useful for sensitivity studies and extraction/separation modeling efforts. 1

Untangling the proximate causes and underlying drivers of deforestation and forest degradation in Myanmar.

PubMed

Lim, Cheng Ling; Prescott, Graham W; De Alban, Jose Don T; Ziegler, Alan D; Webb, Edward L

2017-12-01

Political transitions often trigger substantial environmental changes. In particular, deforestation can result from the complex interplay among the components of a system-actors, institutions, and existing policies-adapting to new opportunities. A dynamic conceptual map of system components is particularly useful for systems in which multiple actors, each with different worldviews and motivations, may be simultaneously trying to alter different facets of the system, unaware of the impacts on other components. In Myanmar, a global biodiversity hotspot with the largest forest area in mainland Southeast Asia, ongoing political and economic reforms are likely to change the dynamics of deforestation drivers. A fundamental conceptual map of these dynamics is therefore a prerequisite for interventions to reduce deforestation. We used a system-dynamics approach and causal-network analysis to determine the proximate causes and underlying drivers of forest loss and degradation in Myanmar from 1995 to 2016 and to articulate the linkages among them. Proximate causes included infrastructure development, timber extraction, and agricultural expansion. These were stimulated primarily by formal agricultural, logging, mining, and hydropower concessions and economic investment and social issues relating to civil war and land tenure. Reform of land laws, the link between natural resource extraction and civil war, and the allocation of agricultural concessions will influence the extent of future forest loss and degradation in Myanmar. The causal-network analysis identified priority areas for policy interventions, for example, creating a public registry of land-concession holders to deter corruption in concession allocation. We recommend application of this analytical approach to other countries, particularly those undergoing political transition, to inform policy interventions to reduce forest loss and degradation. © 2017 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Large-area photogrammetry based testing of wind turbine blades

NASA Astrophysics Data System (ADS)

Poozesh, Peyman; Baqersad, Javad; Niezrecki, Christopher; Avitabile, Peter; Harvey, Eric; Yarala, Rahul

2017-03-01

An optically based sensing system that can measure the displacement and strain over essentially the entire area of a utility-scale blade leads to a measurement system that can significantly reduce the time and cost associated with traditional instrumentation. This paper evaluates the performance of conventional three dimensional digital image correlation (3D DIC) and three dimensional point tracking (3DPT) approaches over the surface of wind turbine blades and proposes a multi-camera measurement system using dynamic spatial data stitching. The potential advantages for the proposed approach include: (1) full-field measurement distributed over a very large area, (2) the elimination of time-consuming wiring and expensive sensors, and (3) the need for large-channel data acquisition systems. There are several challenges associated with extending the capability of a standard 3D DIC system to measure entire surface of utility scale blades to extract distributed strain, deflection, and modal parameters. This paper only tries to address some of the difficulties including: (1) assessing the accuracy of the 3D DIC system to measure full-field distributed strain and displacement over the large area, (2) understanding the geometrical constraints associated with a wind turbine testing facility (e.g. lighting, working distance, and speckle pattern size), (3) evaluating the performance of the dynamic stitching method to combine two different fields of view by extracting modal parameters from aligned point clouds, and (4) determining the feasibility of employing an output-only system identification to estimate modal parameters of a utility scale wind turbine blade from optically measured data. Within the current work, the results of an optical measurement (one stereo-vision system) performed on a large area over a 50-m utility-scale blade subjected to quasi-static and cyclic loading are presented. The blade certification and testing is typically performed using International Electro-Technical Commission standard (IEC 61400-23). For static tests, the blade is pulled in either flap-wise or edge-wise directions to measure deflection or distributed strain at a few limited locations of a large-sized blade. Additionally, the paper explores the error associated with using a multi-camera system (two stereo-vision systems) in measuring 3D displacement and extracting structural dynamic parameters on a mock set up emulating a utility-scale wind turbine blade. The results obtained in this paper reveal that the multi-camera measurement system has the potential to identify the dynamic characteristics of a very large structure.

Combining Experiments and Simulations of Extraction Kinetics and Thermodynamics in Advanced Separation Processes for Used Nuclear Fuel

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

Nilsson, Mikael

This 3-year project was a collaboration between University of California Irvine (UC Irvine), Pacific Northwest National Laboratory (PNNL), Idaho National Laboratory (INL), Argonne National Laboratory (ANL) and with an international collaborator at ForschungZentrum Jülich (FZJ). The project was led from UC Irvine under the direction of Profs. Mikael Nilsson and Hung Nguyen. The leads at PNNL, INL, ANL and FZJ were Dr. Liem Dang, Dr. Peter Zalupski, Dr. Nathaniel Hoyt and Dr. Giuseppe Modolo, respectively. Involved in this project at UC Irvine were three full time PhD graduate students, Tro Babikian, Ted Yoo, and Quynh Vo, and one MS student,more » Alba Font Bosch. The overall objective of this project was to study how the kinetics and thermodynamics of metal ion extraction can be described by molecular dynamic (MD) simulations and how the simulations can be validated by experimental data. Furthermore, the project includes the applied separation by testing the extraction systems in a single stage annular centrifugal contactor and coupling the experimental data with computational fluid dynamic (CFD) simulations. Specific objectives of the proposed research were: Study and establish a rigorous connection between MD simulations based on polarizable force fields and extraction thermodynamic and kinetic data. Compare and validate CFD simulations of extraction processes for An/Ln separation using different sizes (and types) of annular centrifugal contactors. Provide a theoretical/simulation and experimental base for scale-up of batch-wise extraction to continuous contactors. We approached objective 1 and 2 in parallel. For objective 1 we started by studying a well established extraction system with a relatively simple extraction mechanism, namely tributyl phosphate. What we found was that well optimized simulations can inform experiments and new information on TBP behavior was presented in this project, as well be discussed below. The second objective proved a larger challenge and most of the efforts were devoted to experimental studies.« less

Role of core excitation in (d ,p ) transfer reactions

NASA Astrophysics Data System (ADS)

Deltuva, A.; Ross, A.; Norvaišas, E.; Nunes, F. M.

2016-10-01

Background: Recent work found that core excitations can be important in extracting structure information from (d ,p ) reactions. Purpose: Our objective is to systematically explore the role of core excitation in (d ,p ) reactions and to understand the origin of the dynamical effects. Method: Based on the particle-rotor model of n +10Be , we generate a number of models with a range of separation energies (Sn=0.1 -5.0 MeV), while maintaining a significant core excited component. We then apply the latest extension of the momentum-space-based Faddeev method, including dynamical core excitation in the reaction mechanism to all orders, to the 10Be(d ,p )11Be -like reactions, and study the excitation effects for beam energies Ed=15 -90 MeV. Results: We study the resulting angular distributions and the differences between the spectroscopic factor that would be extracted from the cross sections, when including dynamical core excitation in the reaction, and that of the original structure model. We also explore how different partial waves affect the final cross section. Conclusions: Our results show a strong beam-energy dependence of the extracted spectroscopic factors that become smaller for intermediate beam energies. This dependence increases for loosely bound systems.

Preparation and use of Xenopus egg extracts to study DNA replication and chromatin associated proteins

PubMed Central

Gillespie, Peter J.; Gambus, Agnieszka; Blow, J. Julian

2012-01-01

The use of cell-free extracts prepared from eggs of the South African clawed toad, Xenopus laevis, has led to many important discoveries in cell cycle research. These egg extracts recapitulate the key nuclear transitions of the eukaryotic cell cycle in vitro under apparently the same controls that exist in vivo. DNA added to the extract is first assembled into a nucleus and is then efficiently replicated. Progression of the extract into mitosis then allows the separation of paired sister chromatids. The Xenopus cell-free system is therefore uniquely suited to the study of the mechanisms, dynamics and integration of cell cycle regulated processes at a biochemical level. In this article we describe methods currently in use in our laboratory for the preparation of Xenopus egg extracts and demembranated sperm nuclei for the study of DNA replication in vitro. We also detail how DNA replication can be quantified in this system. In addition, we describe methods for isolating chromatin and chromatin-bound protein complexes from egg extracts. These recently developed and revised techniques provide a practical starting point for investigating the function of proteins involved in DNA replication. PMID:22521908

Development and characterization of a green procedure for apigenin extraction from Scutellaria barbata D. Don.

PubMed

Yang, Yu-Chiao; Wei, Ming-Chi

2018-06-30

This study compared the use of ultrasound-assisted supercritical CO 2 (USC-CO 2 ) extraction to obtain apigenin-rich extracts from Scutellaria barbata D. Don with that of conventional supercritical CO 2 (SC-CO 2 ) extraction and heat-reflux extraction (HRE), conducted in parallel. This green procedure yielded 20.1% and 31.6% more apigenin than conventional SC-CO 2 extraction and HRE, respectively. Moreover, the extraction time required by the USC-CO 2 procedure, which used milder conditions, was approximately 1.9 times and 2.4 times shorter than that required by conventional SC-CO 2 extraction and HRE, respectively. Furthermore, the theoretical solubility of apigenin in the supercritical fluid system was obtained from the USC-CO 2 dynamic extraction curves and was in good agreement with the calculated values for the three empirical density-based models. The second-order kinetics model was further applied to evaluate the kinetics of USC-CO 2 extraction. The results demonstrated that the selected model allowed the evaluation of the extraction rate and extent of USC-CO 2 extraction. Copyright © 2017 Elsevier Ltd. All rights reserved.

Investigation of High Linearity DFB Lasers for Analog Communications

DTIC Science & Technology

1998-02-01

personal communication systems (PCS) service and phased array radar. In this thesis, we examine the dynamic range and distortion for a Fujitsu DFB laser. We...PCS) service and phased array radar. In this thesis, we examine the dynamic range and distortion for a Fujitsu DFB laser. We extract parameters from...is dependent upon the coupling coefficient, as discussed in Chapter 3. Spatial hole burning is more important at lower frequencies (owing to finite

Dynamic fiber Bragg gratings based health monitoring system of composite aerospace structures

NASA Astrophysics Data System (ADS)

Panopoulou, A.; Loutas, T.; Roulias, D.; Fransen, S.; Kostopoulos, V.

2011-09-01

The main purpose of the current work is to develop a new system for structural health monitoring of composite aerospace structures based on real-time dynamic measurements, in order to identify the structural state condition. Long-gauge Fibre Bragg Grating (FBG) optical sensors were used for monitoring the dynamic response of the composite structure. The algorithm that was developed for structural damage detection utilizes the collected dynamic response data, analyzes them in various ways and through an artificial neural network identifies the damage state and its location. Damage was simulated by slightly varying locally the mass of the structure (by adding a known mass) at different zones of the structure. Lumped masses in different locations upon the structure alter the eigen-frequencies in a way similar to actual damage. The structural dynamic behaviour has been numerically simulated and experimentally verified by means of modal testing on two different composite aerospace structures. Advanced digital signal processing techniques, e.g. the wavelet transform (WT), were used for the analysis of the dynamic response for feature extraction. WT's capability of separating the different frequency components in the time domain without loosing frequency information makes it a versatile tool for demanding signal processing applications. The use of WT is also suggested by the no-stationary nature of dynamic response signals and the opportunity of evaluating the temporal evolution of their frequency contents. Feature extraction is the first step of the procedure. The extracted features are effective indices of damage size and location. The classification step comprises of a feed-forward back propagation network, whose output determines the simulated damage location. Finally, dedicated training and validation activities were carried out by means of numerical simulations and experimental procedures. Experimental validation was performed initially on a flat stiffened panel, representing a section of a typical aeronautical structure, manufactured and tested in the lab and, as a second step, on a scaled up space oriented structure, which is a composite honeycomb plate, used as a deployment base for antenna arrays. An integrated FBG sensor network, based on the advantage of multiplexing, was mounted on both structures and different excitation positions and boundary conditions were used. The analysis of operational dynamic responses was employed to identify both the damage and its position. The system that was designed and tested initially on the thin composite panel, was successfully validated on the larger honeycomb structure. Numerical simulation of both structures was used as a support tool at all the steps of the work providing among others the location of the optical sensors used. The proposed work will be the base for the whole system qualification and validation on an antenna reflector in future work.

Using nonequilibrium dynamics to probe competing orders in a Mott-Peierls system

DOE PAGES

Wang, Y.; Moritz, B.; Chen, C. -C.; ...

2016-02-24

Competition between ordered phases, and their associated phase transitions, are significant in the study of strongly correlated systems. Here, we examine one aspect, the nonequilibrium dynamics of a photoexcited Mott-Peierls system, using an effective Peierls-Hubbard model and exact diagonalization. Near a transition where spin and charge become strongly intertwined, we observe antiphase dynamics and a coupling-strength-dependent suppression or enhancement in the static structure factors. The renormalized bosonic excitations coupled to a particular photoexcited electron can be extracted, which provides an approach for characterizing the underlying bosonic modes. The results from this analysis for different electronic momenta show an uneven softeningmore » due to a stronger coupling near k F. As a result, this behavior reflects the strong link between the fermionic momenta, the coupling vertices, and ultimately, the bosonic susceptibilities when multiple phases compete for the ground state of the system.« less

Within- and across-trial dynamics of human EEG reveal cooperative interplay between reinforcement learning and working memory.

PubMed

Collins, Anne G E; Frank, Michael J

2018-03-06

Learning from rewards and punishments is essential to survival and facilitates flexible human behavior. It is widely appreciated that multiple cognitive and reinforcement learning systems contribute to decision-making, but the nature of their interactions is elusive. Here, we leverage methods for extracting trial-by-trial indices of reinforcement learning (RL) and working memory (WM) in human electro-encephalography to reveal single-trial computations beyond that afforded by behavior alone. Neural dynamics confirmed that increases in neural expectation were predictive of reduced neural surprise in the following feedback period, supporting central tenets of RL models. Within- and cross-trial dynamics revealed a cooperative interplay between systems for learning, in which WM contributes expectations to guide RL, despite competition between systems during choice. Together, these results provide a deeper understanding of how multiple neural systems interact for learning and decision-making and facilitate analysis of their disruption in clinical populations.

Extracting aerobic system dynamics during unsupervised activities of daily living using wearable sensor machine learning models.

PubMed

Beltrame, Thomas; Amelard, Robert; Wong, Alexander; Hughson, Richard L

2018-02-01

Physical activity levels are related through algorithms to the energetic demand, with no information regarding the integrity of the multiple physiological systems involved in the energetic supply. Longitudinal analysis of the oxygen uptake (V̇o 2 ) by wearable sensors in realistic settings might permit development of a practical tool for the study of the longitudinal aerobic system dynamics (i.e., V̇o 2 kinetics). This study evaluated aerobic system dynamics based on predicted V̇o 2 data obtained from wearable sensors during unsupervised activities of daily living (μADL). Thirteen healthy men performed a laboratory-controlled moderate exercise protocol and were monitored for ≈6 h/day for 4 days (μADL data). Variables derived from hip accelerometer (ACC HIP ), heart rate monitor, and respiratory bands during μADL were extracted and processed by a validated random forest regression model to predict V̇o 2 . The aerobic system analysis was based on the frequency-domain analysis of ACC HIP and predicted V̇o 2 data obtained during μADL. Optimal samples for frequency domain analysis (constrained to ≤0.01 Hz) were selected when ACC HIP was higher than 0.05 g at a given frequency (i.e., participants were active). The temporal characteristics of predicted V̇o 2 data during μADL correlated with the temporal characteristics of measured V̇o 2 data during laboratory-controlled protocol ([Formula: see text] = 0.82, P < 0.001, n = 13). In conclusion, aerobic system dynamics can be investigated during unsupervised activities of daily living by wearable sensors. Although speculative, these algorithms have the potential to be incorporated into wearable systems for early detection of changes in health status in realistic environments by detecting changes in aerobic response dynamics. NEW & NOTEWORTHY The early detection of subclinical aerobic system impairments might be indicative of impaired physiological reserves that impact the capacity for physical activity. This study is the first to use wearable sensors in unsupervised activities of daily living in combination with novel machine learning algorithms to investigate the aerobic system dynamics with the potential to contribute to models of functional health status and guide future individualized health care in the normal population.

Temperature Measurements in Dynamically-loaded Systems Using Neutron Resonance Spectroscopy (NRS) at LANSCE

NASA Astrophysics Data System (ADS)

Yuan, V. W.

2002-12-01

In previous attempts to determine the internal temperature in systems subjected to dynamic loading, experimenters have usually relied on surface-based optical techniques that are often hampered by insufficient information regarding the emissivity of the surfaces under study. Neutron Resonance Spectroscopy (NRS) is a technique that uses Doppler-broadened neutron resonances to measure internal temperatures in dynamically-loaded samples. NRS has developed its own target-moderator assembly to provide single pulses with an order of magnitude higher brightness than the Lujan production target. The resonance line shapes from which temperature information is extracted are also influenced by non-temperature-dependent broadening from the moderator and detector phosphorescence. Dynamic NRS experiments have been performed to measure the temperature in a silver sheet jet and behind the passage of a shock wave in molybdenum.

The optimization of essential oils supercritical CO2 extraction from Lavandula hybrida through static-dynamic steps procedure and semi-continuous technique using response surface method

PubMed Central

Kamali, Hossein; Aminimoghadamfarouj, Noushin; Golmakani, Ebrahim; Nematollahi, Alireza

2015-01-01

Aim: The aim of this study was to examine and evaluate crucial variables in essential oils extraction process from Lavandula hybrida through static-dynamic and semi-continuous techniques using response surface method. Materials and Methods: Essential oil components were extracted from Lavandula hybrida (Lavandin) flowers using supercritical carbon dioxide via static-dynamic steps (SDS) procedure, and semi-continuous (SC) technique. Results: Using response surface method the optimum extraction yield (4.768%) was obtained via SDS at 108.7 bar, 48.5°C, 120 min (static: 8×15), 24 min (dynamic: 8×3 min) in contrast to the 4.620% extraction yield for the SC at 111.6 bar, 49.2°C, 14 min (static), 121.1 min (dynamic). Conclusion: The results indicated that a substantial reduction (81.56%) solvent usage (kg CO2/g oil) is observed in the SDS method versus the conventional SC method. PMID:25598636

Collective Langevin dynamics of conformational motions in proteins

NASA Astrophysics Data System (ADS)

Lange, Oliver F.; Grubmüller, Helmut

2006-06-01

Functionally relevant slow conformational motions of proteins are, at present, in most cases inaccessible to molecular dynamics (MD) simulations. The main reason is that the major part of the computational effort is spend for the accurate description of a huge number of high frequency motions of the protein and the surrounding solvent. The accumulated influence of these fluctuations is crucial for a correct treatment of the conformational dynamics; however, their details can be considered irrelevant for most purposes. To accurately describe long time protein dynamics we here propose a reduced dimension approach, collective Langevin dynamics (CLD), which evolves the dynamics of the system within a small subspace of relevant collective degrees of freedom. The dynamics within the low-dimensional conformational subspace is evolved via a generalized Langevin equation which accounts for memory effects via memory kernels also extracted from short explicit MD simulations. To determine the memory kernel with differing levels of regularization, we propose and evaluate two methods. As a first test, CLD is applied to describe the conformational motion of the peptide neurotensin. A drastic dimension reduction is achieved by considering one single curved conformational coordinate. CLD yielded accurate thermodynamical and dynamical behaviors. In particular, the rate of transitions between two conformational states agreed well with a rate obtained from a 150ns reference molecular dynamics simulation, despite the fact that the time scale of the transition (˜50ns) was much longer than the 1ns molecular dynamics simulation from which the memory kernel was extracted.

Superlattice Structures, Electronic Properties, and Spin Dynamics of the Partially Cu-Extracted Phase for the Composite Crystal System CuxV4O11

NASA Astrophysics Data System (ADS)

Onoda, Masashige; Tamura, Asato

2017-02-01

The crystal structures, electronic properties, and spin dynamics of CuxV4O11 with 1.2 ≤ x < 2, classified as the partially Cu-extracted phase for the composite crystal system, are explored through measurements of x-ray four-circle diffraction, electrochemistry, electrical resistivity, thermoelectric power, magnetization, and electron paramagnetic resonance. This system has superlattice structures mainly ascribed to the partial ordering of Cu ions. Cu1.78V4O11 is triclinic with space group Pbar{1} and the double supercell of the V4O11 substructure of the composite crystal. The significantly Cu-extracted crystal Cu1.40V4O11 has a quadruple supercell with space group P1. The electron transport for V ions is nonmetallic owing to the polaronic nature and/or phonon softening and to the random potential of Cu ions. The Curie-Weiss-type paramagnetism basically originates from the Cu2+ chain coordinated octahedrally, and the EPR relaxation at low temperatures is understood through the exchange mechanism for the dipole-dipole and anisotropic exchange interactions. The near absence of paramagnetic behaviors of V4+ ions might be due to the spin-singlet ladder model or alternating-exchange chain model depending on the superlattice structure and valence distribution. The electrochemical performance of Li rechargeable batteries using this superlattice system is about 300 A h kg-1 at voltages above 2 V.

Extracting Leading Nonlinear Modes of Changing Climate From Global SST Time Series

NASA Astrophysics Data System (ADS)

Mukhin, D.; Gavrilov, A.; Loskutov, E. M.; Feigin, A. M.; Kurths, J.

2017-12-01

Data-driven modeling of climate requires adequate principal variables extracted from observed high-dimensional data. For constructing such variables it is needed to find spatial-temporal patterns explaining a substantial part of the variability and comprising all dynamically related time series from the data. The difficulties of this task rise from the nonlinearity and non-stationarity of the climate dynamical system. The nonlinearity leads to insufficiency of linear methods of data decomposition for separating different processes entangled in the observed time series. On the other hand, various forcings, both anthropogenic and natural, make the dynamics non-stationary, and we should be able to describe the response of the system to such forcings in order to separate the modes explaining the internal variability. The method we present is aimed to overcome both these problems. The method is based on the Nonlinear Dynamical Mode (NDM) decomposition [1,2], but takes into account external forcing signals. An each mode depends on hidden, unknown a priori, time series which, together with external forcing time series, are mapped onto data space. Finding both the hidden signals and the mapping allows us to study the evolution of the modes' structure in changing external conditions and to compare the roles of the internal variability and forcing in the observed behavior. The method is used for extracting of the principal modes of SST variability on inter-annual and multidecadal time scales accounting the external forcings such as CO2, variations of the solar activity and volcanic activity. The structure of the revealed teleconnection patterns as well as their forecast under different CO2 emission scenarios are discussed.[1] Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. [2] Gavrilov, A., Mukhin, D., Loskutov, E., Volodin, E., Feigin, A., & Kurths, J. (2016). Method for reconstructing nonlinear modes with adaptive structure from multidimensional data. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(12), 123101.

Multidimensional biochemical information processing of dynamical patterns

NASA Astrophysics Data System (ADS)

Hasegawa, Yoshihiko

2018-02-01

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

Multidimensional biochemical information processing of dynamical patterns.

PubMed

Hasegawa, Yoshihiko

2018-02-01

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

Potential-based dynamical reweighting for Markov state models of protein dynamics.

PubMed

Weber, Jeffrey K; Pande, Vijay S

2015-06-09

As simulators attempt to replicate the dynamics of large cellular components in silico, problems related to sampling slow, glassy degrees of freedom in molecular systems will be amplified manyfold. It is tempting to augment simulation techniques with external biases to overcome such barriers with ease; biased simulations, however, offer little utility unless equilibrium properties of interest (both kinetic and thermodynamic) can be recovered from the data generated. In this Article, we present a general scheme that harnesses the power of Markov state models (MSMs) to extract equilibrium kinetic properties from molecular dynamics trajectories collected on biased potential energy surfaces. We first validate our reweighting protocol on a simple two-well potential, and we proceed to test our method on potential-biased simulations of the Trp-cage miniprotein. In both cases, we find that equilibrium populations, time scales, and dynamical processes are reliably reproduced as compared to gold standard, unbiased data sets. We go on to discuss the limitations of our dynamical reweighting approach, and we suggest auspicious target systems for further application.

A modal parameter extraction procedure applicable to linear time-invariant dynamic systems

NASA Technical Reports Server (NTRS)

Kurdila, A. J.; Craig, R. R., Jr.

1985-01-01

Modal analysis has emerged as a valuable tool in many phases of the engineering design process. Complex vibration and acoustic problems in new designs can often be remedied through use of the method. Moreover, the technique has been used to enhance the conceptual understanding of structures by serving to verify analytical models. A new modal parameter estimation procedure is presented. The technique is applicable to linear, time-invariant systems and accommodates multiple input excitations. In order to provide a background for the derivation of the method, some modal parameter extraction procedures currently in use are described. Key features implemented in the new technique are elaborated upon.

Research and application of thermal power unit’s load dynamic adjustment based on extraction steam

NASA Astrophysics Data System (ADS)

Li, Jun; Li, Huicong; Li, Weiwei

2018-02-01

The rapid development of heat and power generation in large power plant has caused tremendous constraints on the load adjustment of power grids and power plants. By introducing the thermodynamic system of thermal power unit, the relationship between thermal power extraction steam and unit’s load has analyzed and calculated. The practical application results show that power capability of the unit affected by extraction and it is not conducive to adjust the grid frequency. By monitoring the load adjustment capacity of thermal power units, especially the combined heat and power generating units, the upper and lower limits of the unit load can be dynamically adjusted by the operator on the grid side. The grid regulation and control departments can effectively control the load adjustable intervals of the operating units and provide reliable for the cooperative action of the power grid and power plants, to ensure the safety and stability of the power grid.

Radiation crosslinking of highly plasticized PVC

NASA Astrophysics Data System (ADS)

Mendizabal, E.; Cruz, L.; Jasso, C. F.; Burillo, G.; Dakin, V. I.

1996-02-01

To improve the physical properties of highly plasticized PVC, the polymer was crosslinked by gamma irradiation using a dose rate of 91 kGy/h. The effect of plasticizer type was studied by using three different plasticizers, 2,2,4-trimethyl-1,3-pentanediol diisobutyrate (TXIB), di(2-ethyl hexyl) phthalate (DOP), and di(2-ethylhexyl terephthalate) (DOTP), and varying irradiation doses. Gel content was determined by soxhlet extraction, tensile measurements were made on a universal testing machine and the mechano-dynamic measurements were made in a dynamic rheometer. It was found that a considerable bonding of plasticizer molecules to macromolelcules takes place along with crosslinking, so that the use of the solvent extraction method for measuring the degree of crosslinking can give erroneous information. Radiation-chemical crosslinking yield ( Gc) and molecular weight of interjunctions chains ( Mc), were calculated for different systems studied. Addition of ethylene glycol dimethacrylate (EGDM) as a crosslinking coagent and dioctyl tin oxide (DOTO) as a stabilizer was also studied. Plasticizers extraction resistance was increased by irradiation treatment.

Development of Availability and Sustainability Spares Optimization Models for Aircraft Reparables

DTIC Science & Technology

2013-09-01

the integrated SAP ® Enterprise Resource Planning ( ERP ) information system of the RSAF. A more in-depth review of OPUS10 capabilities will be provided...Dynamic Multi-Echelon Technique for Recoverable Item Control EBO: Expected Backorder EOQ: Economic Order Quantity ERP : Enterprise Resource...particular, the propulsion sub-system was expanded to include SSRUs. Spares information are extracted from the RSAF ERP system and include: 22

Ares I-X In-Flight Modal Identification

NASA Technical Reports Server (NTRS)

Bartkowicz, Theodore J.; James, George H., III

2011-01-01

Operational modal analysis is a procedure that allows the extraction of modal parameters of a structure in its operating environment. It is based on the idealized premise that input to the structure is white noise. In some cases, when free decay responses are corrupted by unmeasured random disturbances, the response data can be processed into cross-correlation functions that approximate free decay responses. Modal parameters can be computed from these functions by time domain identification methods such as the Eigenvalue Realization Algorithm (ERA). The extracted modal parameters have the same characteristics as impulse response functions of the original system. Operational modal analysis is performed on Ares I-X in-flight data. Since the dynamic system is not stationary due to propellant mass loss, modal identification is only possible by analyzing the system as a series of linearized models over short periods of time via a sliding time-window of short time intervals. A time-domain zooming technique was also employed to enhance the modal parameter extraction. Results of this study demonstrate that free-decay time domain modal identification methods can be successfully employed for in-flight launch vehicle modal extraction.

Sex differences in the oxygen delivery, extraction, and uptake during moderate-walking exercise transition.

PubMed

Beltrame, Thomas; Villar, Rodrigo; Hughson, Richard L

2017-09-01

Previous studies in children and older adults demonstrated faster oxygen uptake (V̇O 2 ) kinetics in males compared with females, but young healthy adults have not been studied. We hypothesized that young men would have faster aerobic system dynamics in response to the onset of exercise than women. Interactions between oxygen supply and utilization were characterized by the dynamics of V̇O 2 , deoxyhemoglobin (HHb), tissue saturation index (TSI), cardiac output (Q̇), and calculated arteriovenous O 2 difference (a-vO 2 diff ) in women and men. Eighteen healthy active young women and men (9 of each sex) with similar aerobic fitness levels volunteered for this study. Participants performed an incremental cardiopulmonary treadmill exercise test and 3 moderate-intensity treadmill exercise tests (at 80% V̇O 2 of gas exchange threshold). Data related to the moderate exercise were submitted to exponential data modelling to obtain parameters related to the aerobic system dynamics. The time constants of V̇O 2 , a-vO 2 diff , HHb, and TSI (30 ± 6, 29 ± 1, 16 ± 1, and 15 ± 2 s, respectively) in women were statistically (p < 0.05) faster than the time constants in men (42 ± 10, 49 ± 21, 19 ± 3, and 20 ± 4 s, respectively). Although Q̇ dynamics were not statistically different (p = 0.06) between groups, there was a trend to slower Q̇ dynamics in men corresponding with the slower V̇O 2 kinetics. These results indicated that the peripheral and pulmonary oxygen extraction dynamics were remarkably faster in women. Thus, contrary to the hypothesis, V̇O 2 dynamics measured at the mouth at the onset of submaximal treadmill walking were faster in women compared with men.

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

Islam, Md. Shafiqul, E-mail: shafique@eng.ukm.my; Hannan, M.A., E-mail: hannan@eng.ukm.my; Basri, Hassan

Highlights: • Solid waste bin level detection using Dynamic Time Warping (DTW). • Gabor wavelet filter is used to extract the solid waste image features. • Multi-Layer Perceptron classifier network is used for bin image classification. • The classification performance evaluated by ROC curve analysis. - Abstract: The increasing requirement for Solid Waste Management (SWM) has become a significant challenge for municipal authorities. A number of integrated systems and methods have introduced to overcome this challenge. Many researchers have aimed to develop an ideal SWM system, including approaches involving software-based routing, Geographic Information Systems (GIS), Radio-frequency Identification (RFID), or sensormore » intelligent bins. Image processing solutions for the Solid Waste (SW) collection have also been developed; however, during capturing the bin image, it is challenging to position the camera for getting a bin area centralized image. As yet, there is no ideal system which can correctly estimate the amount of SW. This paper briefly discusses an efficient image processing solution to overcome these problems. Dynamic Time Warping (DTW) was used for detecting and cropping the bin area and Gabor wavelet (GW) was introduced for feature extraction of the waste bin image. Image features were used to train the classifier. A Multi-Layer Perceptron (MLP) classifier was used to classify the waste bin level and estimate the amount of waste inside the bin. The area under the Receiver Operating Characteristic (ROC) curves was used to statistically evaluate classifier performance. The results of this developed system are comparable to previous image processing based system. The system demonstration using DTW with GW for feature extraction and an MLP classifier led to promising results with respect to the accuracy of waste level estimation (98.50%). The application can be used to optimize the routing of waste collection based on the estimated bin level.« less

Dynamic ultrasonic nebulisation extraction coupled with headspace ionic liquid-based single-drop microextraction for the analysis of the essential oil in Forsythia suspensa.

PubMed

Yang, Jinjuan; Wei, Hongmin; Teng, Xiane; Zhang, Hanqi; Shi, Yuhua

2014-01-01

Ionic liquids have attracted much attention as an extraction solvent instead of traditional organic solvent in single-drop microextraction. However, non-volatile ionic liquids are difficult to couple with gas chromatography. Thus, the following injection system for the determination of organic compounds is described. To establish an environmentally friendly, simple, and effective extraction method for preparation and analysis of the essential oil from aromatic plants. The dynamic ultrasonic nebulisation extraction was coupled with headspace ionic liquid-based single-drop microextraction(UNE-HS/IL/SDME)for the extraction of essential oils from Forsythia suspense fruits. After 13 min of extraction for 50 mg sample, the extracts in ionic liquid were evaporated rapidly in the gas chromatography injector through a thermal desorption unit (5 s). The traditional extraction method was carried out for comparative study. The optimum conditions were: 3 μL of 1-methyl-3-octylimidazolium hexafluorophosphate was selected as the extraction solvent, the sample amount was 50 mg, the flow rate of purging gas was 200 mL/min, the extraction time was 13 min, the injection volume was 2 μL, and the thermal desorption temperature and time were 240 °C and 5 s respectively. Comparing with hydrodistillation (HD), the proposed method was environment friendly and efficient. The proposed method is environmentally friendly, time saving, with high efficiency and low consumption. It would extend the application range of the HS/SDME and would be useful especially for aromatic plants analysis. Copyright © 2013 John Wiley & Sons, Ltd.

A comparison of two types of neural network for weld quality prediction in small scale resistance spot welding

NASA Astrophysics Data System (ADS)

Wan, Xiaodong; Wang, Yuanxun; Zhao, Dawei; Huang, YongAn

2017-09-01

Our study aims at developing an effective quality monitoring system in small scale resistance spot welding of titanium alloy. The measured electrical signals were interpreted in combination with the nugget development. Features were extracted from the dynamic resistance and electrode voltage curve. A higher welding current generally indicated a lower overall dynamic resistance level. A larger electrode voltage peak and higher change rate of electrode voltage could be detected under a smaller electrode force or higher welding current condition. Variation of the extracted features and weld quality was found more sensitive to the change of welding current than electrode force. Different neural network model were proposed for weld quality prediction. The back propagation neural network was more proper in failure load estimation. The probabilistic neural network model was more appropriate to be applied in quality level classification. A real-time and on-line weld quality monitoring system may be developed by taking advantages of both methods.

Extracting neuronal functional network dynamics via adaptive Granger causality analysis.

PubMed

Sheikhattar, Alireza; Miran, Sina; Liu, Ji; Fritz, Jonathan B; Shamma, Shihab A; Kanold, Patrick O; Babadi, Behtash

2018-04-24

Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca 2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.

Controlling transient chaos in deterministic flows with applications to electrical power systems and ecology

NASA Astrophysics Data System (ADS)

Dhamala, Mukeshwar; Lai, Ying-Cheng

1999-02-01

Transient chaos is a common phenomenon in nonlinear dynamics of many physical, biological, and engineering systems. In applications it is often desirable to maintain sustained chaos even in parameter regimes of transient chaos. We address how to sustain transient chaos in deterministic flows. We utilize a simple and practical method, based on extracting the fundamental dynamics from time series, to maintain chaos. The method can result in control of trajectories from almost all initial conditions in the original basin of the chaotic attractor from which transient chaos is created. We apply our method to three problems: (1) voltage collapse in electrical power systems, (2) species preservation in ecology, and (3) elimination of undesirable bursting behavior in a chemical reaction system.

Extracting heading and temporal range from optic flow: Human performance issues

NASA Technical Reports Server (NTRS)

Kaiser, Mary K.; Perrone, John A.; Stone, Leland; Banks, Martin S.; Crowell, James A.

1993-01-01

Pilots are able to extract information about their vehicle motion and environmental structure from dynamic transformations in the out-the-window scene. In this presentation, we focus on the information in the optic flow which specifies vehicle heading and distance to objects in the environment, scaled to a temporal metric. In particular, we are concerned with modeling how the human operators extract the necessary information, and what factors impact their ability to utilize the critical information. In general, the psychophysical data suggest that the human visual system is fairly robust to degradations in the visual display, e.g., reduced contrast and resolution or restricted field of view. However, extraneous motion flow, i.e., introduced by sensor rotation, greatly compromises human performance. The implications of these models and data for enhanced/synthetic vision systems are discussed.

Combined impacts of tidal energy extraction and sea level rise in the Gulf of Maine

NASA Astrophysics Data System (ADS)

Hashemi, M. R.; Kresning, B.

2016-12-01

The objective of this study was to assess the combined effects of SLR and tidal energy extraction on the dynamics of tides in the Gulf of Maine in both US and Canadian waters. The dynamics of tides in the Gulf of Maine is dominated by tidal resonance, which generates one of the largest tidal ranges in the world. Further, sea level rise (SLR) is affecting tidal circulations globally, and in the Gulf of Maine. A large tidal energy resource is available in the Gulf of Maine, particularly in the Bay of Fundy, and is expected to be harvested in the future. Currently, more than 6 projects are operational or under development in this region (in both US and Canadian waters). Understanding the far-field impacts of tidal-stream arrays is important for future development of tidal energy extraction. The impacts include possible changes in water elevation, which can potentially increase flooding in coastal areas. Further, SLR can affect tidal energy resources and the impacts of tidal energy extraction during the project lifetime - which is usually more than 25 years. A tidal model of the Gulf of Maine was developed using Regional Ocean Model System (ROMS) at one arcminute scale. An array of turbines were simulated in the model. After validation of the model at NOAA tidal gauge stations and NERACOOS buoys, several scenarios; including SLR scenario, and tidal extraction scenario, were examined. In particular, the results of a recent research was used to assess the impacts of SLR on the boundary of the model domain, which was neglected in previous studies. The results of the impacts of the tidal energy extraction with and without the SLR were presented, and compared with those from literature. This includes the decrease of tidal range and M2 amplitude in Minas Basin due to the 2.5 GW extraction scenario, and possible changes in Massachusetts coastal area. The impacts were compared with the level of uncertainty in the model. It was shown that the impact of SLR on the dynamics of tides is more than those from energy extraction assuming 2.5 GW extraction in Minas Passage.

Assessing pharmacokinetics of indocyanine green-loaded nanoparticle in tumor with a dynamic diffuse fluorescence tomography system

NASA Astrophysics Data System (ADS)

Zhang, Yanqi; Yin, Guoyan; Zhao, Huijuan; Ma, Wenjuan; Gao, Feng; Zhang, Limin

2018-02-01

Real-time and continuous monitoring of drug release in vivo is an important task in pharmaceutical development. Here, we devoted to explore a real-time continuous study of the pharmacokinetics of free indocyanine green (ICG) and ICG loaded in the shell-sheddable nanoparticles in tumor based on a dynamic diffuse fluorescence tomography (DFT) system: A highly-sensitive dynamic DFT system of CT-scanning mode generates informative and instantaneous sampling datasets; An analysis procedure extracts the pharmacokinetic parameters from the reconstructed time curves of the mean ICG concentration in tumor, using the Gauss-Newton scheme based on two-compartment model. Compared with the pharmacokinetic parameters of free ICG in tumor, the ICG loaded in the shell-sheddable nanoparticles shows efficient accumulation in tumor. The results demonstrate our proposed dynamic-DFT can provide an integrated and continuous view of the drug delivery of the injected agents in different formulations, which is helpful for the development of diagnosis and therapy for tumors.

Self-similarity in nature

NASA Astrophysics Data System (ADS)

Timashev, S. F.

2000-02-01

A general phenomenological approach to the analysis of experimental temporal, spatial and energetic series for extracting truly physical non-model parameters ("passport data") is presented, which may be used to characterize and distinguish the evolution as well as the spatial and energetic structure of any open nonlinear dissipative system. This methodology is based on a postulate concerning the crucial information contained in the sequences of non-regularities of the measured dynamic variable (temporal, spatial, energetic). In accordance with this approach, multi-parametric formulas for dynamic variable power spectra as well as for structural functions of different orders are identical for every spatial-temporal-energetic level of the system under consideration. In effect, this entails the introduction of a new kind of self-similarity in Nature. An algorithm has been developed for obtaining as many "passport data" as are necessary for the characterization of a dynamic system. Applications of this approach in the analysis of various experimental series (temporal, spatial, energetic) demonstrate its potential for defining adequate phenomenological parameters of different dynamic processes and structures.

Detecting, anticipating, and predicting critical transitions in spatially extended systems.

PubMed

Kwasniok, Frank

2018-03-01

A data-driven linear framework for detecting, anticipating, and predicting incipient bifurcations in spatially extended systems based on principal oscillation pattern (POP) analysis is discussed. The dynamics are assumed to be governed by a system of linear stochastic differential equations which is estimated from the data. The principal modes of the system together with corresponding decay or growth rates and oscillation frequencies are extracted as the eigenvectors and eigenvalues of the system matrix. The method can be applied to stationary datasets to identify the least stable modes and assess the proximity to instability; it can also be applied to nonstationary datasets using a sliding window approach to track the changing eigenvalues and eigenvectors of the system. As a further step, a genuinely nonstationary POP analysis is introduced. Here, the system matrix of the linear stochastic model is time-dependent, allowing for extrapolation and prediction of instabilities beyond the learning data window. The methods are demonstrated and explored using the one-dimensional Swift-Hohenberg equation as an example, focusing on the dynamics of stochastic fluctuations around the homogeneous stable state prior to the first bifurcation. The POP-based techniques are able to extract and track the least stable eigenvalues and eigenvectors of the system; the nonstationary POP analysis successfully predicts the timing of the first instability and the unstable mode well beyond the learning data window.

Detecting, anticipating, and predicting critical transitions in spatially extended systems

NASA Astrophysics Data System (ADS)

Kwasniok, Frank

2018-03-01

A data-driven linear framework for detecting, anticipating, and predicting incipient bifurcations in spatially extended systems based on principal oscillation pattern (POP) analysis is discussed. The dynamics are assumed to be governed by a system of linear stochastic differential equations which is estimated from the data. The principal modes of the system together with corresponding decay or growth rates and oscillation frequencies are extracted as the eigenvectors and eigenvalues of the system matrix. The method can be applied to stationary datasets to identify the least stable modes and assess the proximity to instability; it can also be applied to nonstationary datasets using a sliding window approach to track the changing eigenvalues and eigenvectors of the system. As a further step, a genuinely nonstationary POP analysis is introduced. Here, the system matrix of the linear stochastic model is time-dependent, allowing for extrapolation and prediction of instabilities beyond the learning data window. The methods are demonstrated and explored using the one-dimensional Swift-Hohenberg equation as an example, focusing on the dynamics of stochastic fluctuations around the homogeneous stable state prior to the first bifurcation. The POP-based techniques are able to extract and track the least stable eigenvalues and eigenvectors of the system; the nonstationary POP analysis successfully predicts the timing of the first instability and the unstable mode well beyond the learning data window.

Phonon-magnon interaction in low dimensional quantum magnets observed by dynamic heat transport measurements.

PubMed

Montagnese, Matteo; Otter, Marian; Zotos, Xenophon; Fishman, Dmitry A; Hlubek, Nikolai; Mityashkin, Oleg; Hess, Christian; Saint-Martin, Romuald; Singh, Surjeet; Revcolevschi, Alexandre; van Loosdrecht, Paul H M

2013-04-05

Thirty-five years ago, Sanders and Walton [Phys. Rev. B 15, 1489 (1977)] proposed a method to measure the phonon-magnon interaction in antiferromagnets through thermal transport which so far has not been verified experimentally. We show that a dynamical variant of this approach allows direct extraction of the phonon-magnon equilibration time, yielding 400 μs for the cuprate spin-ladder system Ca(9)La(5)Cu(24)O(41). The present work provides a general method to directly address the spin-phonon interaction by means of dynamical transport experiments.

Multiobjective Optimization of Low-Energy Trajectories Using Optimal Control on Dynamical Channels

NASA Technical Reports Server (NTRS)

Coffee, Thomas M.; Anderson, Rodney L.; Lo, Martin W.

2011-01-01

We introduce a computational method to design efficient low-energy trajectories by extracting initial solutions from dynamical channels formed by invariant manifolds, and improving these solutions through variational optimal control. We consider trajectories connecting two unstable periodic orbits in the circular restricted 3-body problem (CR3BP). Our method leverages dynamical channels to generate a range of solutions, and approximates the areto front for impulse and time of flight through a multiobjective optimization of these solutions based on primer vector theory. We demonstrate the application of our method to a libration orbit transfer in the Earth-Moon system.

Effective Information Extraction Framework for Heterogeneous Clinical Reports Using Online Machine Learning and Controlled Vocabularies

PubMed Central

Zheng, Shuai; Ghasemzadeh, Nima; Hayek, Salim S; Quyyumi, Arshed A

2017-01-01

Background Extracting structured data from narrated medical reports is challenged by the complexity of heterogeneous structures and vocabularies and often requires significant manual effort. Traditional machine-based approaches lack the capability to take user feedbacks for improving the extraction algorithm in real time. Objective Our goal was to provide a generic information extraction framework that can support diverse clinical reports and enables a dynamic interaction between a human and a machine that produces highly accurate results. Methods A clinical information extraction system IDEAL-X has been built on top of online machine learning. It processes one document at a time, and user interactions are recorded as feedbacks to update the learning model in real time. The updated model is used to predict values for extraction in subsequent documents. Once prediction accuracy reaches a user-acceptable threshold, the remaining documents may be batch processed. A customizable controlled vocabulary may be used to support extraction. Results Three datasets were used for experiments based on report styles: 100 cardiac catheterization procedure reports, 100 coronary angiographic reports, and 100 integrated reports—each combines history and physical report, discharge summary, outpatient clinic notes, outpatient clinic letter, and inpatient discharge medication report. Data extraction was performed by 3 methods: online machine learning, controlled vocabularies, and a combination of these. The system delivers results with F1 scores greater than 95%. Conclusions IDEAL-X adopts a unique online machine learning–based approach combined with controlled vocabularies to support data extraction for clinical reports. The system can quickly learn and improve, thus it is highly adaptable. PMID:28487265

Construction of Green Tide Monitoring System and Research on its Key Techniques

NASA Astrophysics Data System (ADS)

Xing, B.; Li, J.; Zhu, H.; Wei, P.; Zhao, Y.

2018-04-01

As a kind of marine natural disaster, Green Tide has been appearing every year along the Qingdao Coast, bringing great loss to this region, since the large-scale bloom in 2008. Therefore, it is of great value to obtain the real time dynamic information about green tide distribution. In this study, methods of optical remote sensing and microwave remote sensing are employed in Green Tide Monitoring Research. A specific remote sensing data processing flow and a green tide information extraction algorithm are designed, according to the optical and microwave data of different characteristics. In the aspect of green tide spatial distribution information extraction, an automatic extraction algorithm of green tide distribution boundaries is designed based on the principle of mathematical morphology dilation/erosion. And key issues in information extraction, including the division of green tide regions, the obtaining of basic distributions, the limitation of distribution boundary, and the elimination of islands, have been solved. The automatic generation of green tide distribution boundaries from the results of remote sensing information extraction is realized. Finally, a green tide monitoring system is built based on IDL/GIS secondary development in the integrated environment of RS and GIS, achieving the integration of RS monitoring and information extraction.

Integrated microwave processing system for the extraction of organophosphorus pesticides in fresh vegetables.

PubMed

Wu, Lijie; Song, Ying; Hu, Mingzhu; Xu, Xu; Zhang, Hanqi; Yu, Aimin; Ma, Qiang; Wang, Ziming

2015-03-01

A simple and efficient integrated microwave processing system (IMPS) was firstly assembled and validated for the extraction of organophosphorus pesticides in fresh vegetables. Two processes under microwave irradiation, dynamic microwave-assisted extraction (DMAE) and microwave-accelerated solvent elution (MASE), were integrated for simplifying the pretreatment of the sample. Extraction, separation, enrichment and elution were finished in a simple step. The organophosphorus pesticides were extracted from the fresh vegetables into hexane with DMAE, and then the extract was directly introduced into the enrichment column packed with active carbon fiber (ACF). Subsequently, the organophosphorus pesticides trapped on the ACF were eluted with ethyl acetate under microwave irradiation. No further filtration or cleanup was required before analysis of the eluate by gas chromatography-mass spectrometry. Some experimental parameters affecting extraction efficiency were investigated and optimized, such as microwave output power, kind and volume of extraction solvent, extraction time, amount of sorbent, elution microwave power, kind and volume of elution solvent, elution solvent flow rate. Under the optimized conditions, the recoveries were in the range of 71.5-105.2%, and the relative standard deviations were lower than 11.6%. The experiment results prove that the present method is a simple and effective sample preparation method for the determination of pesticides in solid samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Development of green betaine-based deep eutectic solvent aqueous two-phase system for the extraction of protein.

PubMed

Li, Na; Wang, Yuzhi; Xu, Kaijia; Huang, Yanhua; Wen, Qian; Ding, Xueqin

2016-05-15

Six kinds of new type of green betaine-based deep eutectic solvents (DESs) have been synthesized. Deep eutectic solvent aqueous two-phase systems (DES-ATPS) were established and successfully applied in the extraction of protein. Betaine-urea (Be-U) was selected as the suitable extractant. Single factor experiments were carried out to determine the optimum conditions of the extraction process, such as the salt concentration, the mass of DES, the separation time, the amount of protein, the temperature and the pH value. The extraction efficiency could achieve to 99.82% under the optimum conditions. Mixed sample and practical sample analysis were discussed. The back extraction experiment was implemented and the back extraction efficiency could reach to 32.66%. The precision experiment, repeatability experiment and stability experiment were investigated. UV-vis, FT-IR and circular dichroism (CD) spectra confirmed that the conformation of protein was not changed during the process of extraction. The mechanisms of extraction were researched by dynamic light scattering (DLS), the measurement of the conductivity and transmission electron microscopy (TEM). DES-protein aggregates and embraces phenomenon play considerable roles in the separation process. All of these results indicated that betaine-based DES-ATPS may provide a potential substitute new method for the separation of proteins. Copyright © 2016 Elsevier B.V. All rights reserved.

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures

PubMed Central

Pi, Yiming

2017-01-01

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar. PMID:29267249

Space shuttle flying qualities and criteria assessment

NASA Technical Reports Server (NTRS)

Myers, T. T.; Johnston, D. E.; Mcruer, Duane T.

1987-01-01

Work accomplished under a series of study tasks for the Flying Qualities and Flight Control Systems Design Criteria Experiment (OFQ) of the Shuttle Orbiter Experiments Program (OEX) is summarized. The tasks involved review of applicability of existing flying quality and flight control system specification and criteria for the Shuttle; identification of potentially crucial flying quality deficiencies; dynamic modeling of the Shuttle Orbiter pilot/vehicle system in the terminal flight phases; devising a nonintrusive experimental program for extraction and identification of vehicle dynamics, pilot control strategy, and approach and landing performance metrics, and preparation of an OEX approach to produce a data archive and optimize use of the data to develop flying qualities for future space shuttle craft in general. Analytic modeling of the Orbiter's unconventional closed-loop dynamics in landing, modeling pilot control strategies, verification of vehicle dynamics and pilot control strategy from flight data, review of various existent or proposed aircraft flying quality parameters and criteria in comparison with the unique dynamic characteristics and control aspects of the Shuttle in landing; and finally a summary of conclusions and recommendations for developing flying quality criteria and design guides for future Shuttle craft.

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures.

PubMed

Zhou, Zhi; Cao, Zongjie; Pi, Yiming

2017-12-21

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar.

Velocity measurements of heterogeneous RBC flow in capillary vessels using dynamic laser speckle signal.

PubMed

Li, Chenxi; Wang, Ruikang

2017-04-01

We propose an approach to measure heterogeneous velocities of red blood cells (RBCs) in capillary vessels using full-field time-varying dynamic speckle signals. The approach utilizes a low coherent laser speckle imaging system to record the instantaneous speckle pattern, followed by an eigen-decomposition-based filtering algorithm to extract dynamic speckle signal due to the moving RBCs. The velocity of heterogeneous RBC flows is determined by cross-correlating the temporal dynamic speckle signals obtained at adjacent locations. We verify the approach by imaging mouse pinna in vivo, demonstrating its capability for full-field RBC flow mapping and quantifying flow pattern with high resolution. It is expected to investigate the dynamic action of RBCs flow in capillaries under physiological changes.

Dynamic Visualization of Co-expression in Systems Genetics Data

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

New, Joshua Ryan; Huang, Jian; Chesler, Elissa J

2008-01-01

Biologists hope to address grand scientific challenges by exploring the abundance of data made available through modern microarray technology and other high-throughput techniques. The impact of this data, however, is limited unless researchers can effectively assimilate such complex information and integrate it into their daily research; interactive visualization tools are called for to support the effort. Specifically, typical studies of gene co-expression require novel visualization tools that enable the dynamic formulation and fine-tuning of hypotheses to aid the process of evaluating sensitivity of key parameters. These tools should allow biologists to develop an intuitive understanding of the structure of biologicalmore » networks and discover genes which reside in critical positions in networks and pathways. By using a graph as a universal data representation of correlation in gene expression data, our novel visualization tool employs several techniques that when used in an integrated manner provide innovative analytical capabilities. Our tool for interacting with gene co-expression data integrates techniques such as: graph layout, qualitative subgraph extraction through a novel 2D user interface, quantitative subgraph extraction using graph-theoretic algorithms or by querying an optimized b-tree, dynamic level-of-detail graph abstraction, and template-based fuzzy classification using neural networks. We demonstrate our system using a real-world workflow from a large-scale, systems genetics study of mammalian gene co-expression.« less

Dynamic RGB-D Mapping

DTIC Science & Technology

2012-01-01

by David Lowe, extracts and matches visual features and their associ- ated descriptors between frames, it is described in sec- tion 3.1. The putative...Science and Systems, 2009. [25] J. Sturm, S. Magnenat, N. Engelhard, F. Pomerleau, F. Colas, W. Burgard, D. Cremers , and R. Siegwart, “Towards a benchmark

Low-dimensional dynamical characterization of human performance of cancer patients using motion data.

PubMed

Hasnain, Zaki; Li, Ming; Dorff, Tanya; Quinn, David; Ueno, Naoto T; Yennu, Sriram; Kolatkar, Anand; Shahabi, Cyrus; Nocera, Luciano; Nieva, Jorge; Kuhn, Peter; Newton, Paul K

2018-05-18

Biomechanical characterization of human performance with respect to fatigue and fitness is relevant in many settings, however is usually limited to either fully qualitative assessments or invasive methods which require a significant experimental setup consisting of numerous sensors, force plates, and motion detectors. Qualitative assessments are difficult to standardize due to their intrinsic subjective nature, on the other hand, invasive methods provide reliable metrics but are not feasible for large scale applications. Presented here is a dynamical toolset for detecting performance groups using a non-invasive system based on the Microsoft Kinect motion capture sensor, and a case study of 37 cancer patients performing two clinically monitored tasks before and after therapy regimens. Dynamical features are extracted from the motion time series data and evaluated based on their ability to i) cluster patients into coherent fitness groups using unsupervised learning algorithms and to ii) predict Eastern Cooperative Oncology Group performance status via supervised learning. The unsupervised patient clustering is comparable to clustering based on physician assigned Eastern Cooperative Oncology Group status in that they both have similar concordance with change in weight before and after therapy as well as unexpected hospitalizations throughout the study. The extracted dynamical features can predict physician, coordinator, and patient Eastern Cooperative Oncology Group status with an accuracy of approximately 80%. The non-invasive Microsoft Kinect sensor and the proposed dynamical toolset comprised of data preprocessing, feature extraction, dimensionality reduction, and machine learning offers a low-cost and general method for performance segregation and can complement existing qualitative clinical assessments. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comparative Analysis of Volcanic Inflation—Deflation Cycles

NASA Astrophysics Data System (ADS)

Walwer, D.; Ghil, M.; Calais, E.

2016-12-01

GPS geodetic data together with INSAR images are often used to formulate kinematic models of the sources of volcanic deformations. The increasing amount of data now available allows one to produce time series that are several years long and thus capture continuously the history of volcanic deformations, in particular their nonlinear behavior. This information is highly valuable in helping understand the dynamics of volcanic systems.Nonlinear deformation signals are, however, difficult to extract from the background noise inherent in the GPS time series. It is also arduous to unravel the signal of interest from other nonlinear signals, such as the seasonal oscillations associated with mass variations in the atmosphere, the ocean, and the hydrological reservoirs. Here we use Multichannel Singular Spectrum Analysis (M-SSA) — an advanced, data-adaptive method for time series analysis that exploits simultaneously the temporal and spatial correlations of geophysical fields — to extract such deformation signals.We apply M-SSA to GPS data sets from four volcanoes: Akutan, Alaska; Okmok, Alaska; Westdahl, Alaska; and Piton de la Fournaise, La Reunion. Our analyses show that all four volcanoes share similar features in their deformation history, suggesting similarities in the dynamics that generate the inflation-deflation cycles. In particular, all four volcanic systems exhibit sawtooth-shaped oscillations with slow inflations followed by slower deflations, with time scales that vary from 6 months to 4 years. This relation of dynamical similarity is further highlighted by the phase portrait reconstruction of the four systems in the plane of deformation vs. rate-of-deformation, as obtained from the deformation signals extracted from the GPS time series using M-SSA.The inflating phase of these oscillations is followed by eruptions at Okmok volcano and at Piton de la Fournaise. These analysis results suggest that these volcanic inflation—deflation cycles are associated with the destabilization of a volcanic system and may lead to the identification of premonitory signals for an eruptive regime.

U(VI) Reduction by Biogenic and Abiotic Hydroxycarbonate Green Rusts: Impacts on U(IV) Speciation and Stability Over Time

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

Yan, Sen; Boyanov, Maxim I.; Mishra, Bhoopesh

Green rusts (GRs) are redox active Fe II-Fe III minerals that form in the environment via various biotic and abiotic processes. Although both biogenic (BioGR) and abiotic (ChemGR) GRs have been shown to reduce U VI, the dynamics of the transformations and the speciation and stability of the resulting U IV phases are poorly understood. We used carbonate extraction and XAFS spectroscopy to investigate the products of U VI reduction by BioGR and ChemGR. The results show that both GRs can rapidly remove U VI from synthetic groundwater via reduction to U IV. The initial products in the ChemGR systemmore » are solids-associated U IV-carbonate complexes that gradually transform to nanocrystalline uraninite over time, leading to a decrease in the proportion of carbonate-extractable U from ~95% to ~10%. In contrast, solid-phase U IV atoms in the BioGR system remain relatively extractable, non-uraninite U IV species over the same reaction period. The presence of calcium and carbonate in groundwater significantly increase the extractability of U IV in the BioGR system. Furthermore, these data provide new insights into the transformations of U under anoxic conditions in groundwater that contains calcium and carbonate, and have major implications for predicting uranium stability within redox dynamic environments and designing approaches for the remediation of uranium-contaminated groundwater.« less

U(VI) Reduction by Biogenic and Abiotic Hydroxycarbonate Green Rusts: Impacts on U(IV) Speciation and Stability Over Time

DOE PAGES

Yan, Sen; Boyanov, Maxim I.; Mishra, Bhoopesh; ...

2018-04-09

Green rusts (GRs) are redox active Fe II-Fe III minerals that form in the environment via various biotic and abiotic processes. Although both biogenic (BioGR) and abiotic (ChemGR) GRs have been shown to reduce U VI, the dynamics of the transformations and the speciation and stability of the resulting U IV phases are poorly understood. We used carbonate extraction and XAFS spectroscopy to investigate the products of U VI reduction by BioGR and ChemGR. The results show that both GRs can rapidly remove U VI from synthetic groundwater via reduction to U IV. The initial products in the ChemGR systemmore » are solids-associated U IV-carbonate complexes that gradually transform to nanocrystalline uraninite over time, leading to a decrease in the proportion of carbonate-extractable U from ~95% to ~10%. In contrast, solid-phase U IV atoms in the BioGR system remain relatively extractable, non-uraninite U IV species over the same reaction period. The presence of calcium and carbonate in groundwater significantly increase the extractability of U IV in the BioGR system. Furthermore, these data provide new insights into the transformations of U under anoxic conditions in groundwater that contains calcium and carbonate, and have major implications for predicting uranium stability within redox dynamic environments and designing approaches for the remediation of uranium-contaminated groundwater.« less

Aqueous biphasic systems containing PEG-based deep eutectic solvents for high-performance partitioning of RNA.

PubMed

Zhang, Hongmei; Wang, Yuzhi; Zhou, Yigang; Xu, Kaijia; Li, Na; Wen, Qian; Yang, Qin

2017-08-01

In this work, 16 kinds of novel deep eutectic solvents (DESs) composed of polyethylene glycol (PEG) and quaternary ammonium salts, were coupled with Aqueous Biphasic Systems (ABSs) to extract RNA. The phase forming ability of ABSs were comprehensively evaluated, involving the effects of various proportions of DESs' components, carbon chain length and anions species of quaternary ammonium salts, average molecular weights of PEG and inorganic salts nature. Then the systems were applied in RNA extraction, and the results revealed that the extraction efficiency values were distinctly enhanced by relatively lower PEG content in DESs, smaller PEG molecular weights, longer carbon chain of quaternary ammonium salts and more hydrophobic inorganic salts. Then the systems composed of [TBAB][PEG600] and Na 2 SO 4 were utilized in the influence factor experiments, proving that the electrostatic interaction was the dominant force for RNA extraction. Therefore, back-extraction efficiency values ranging between 85.19% and 90.78% were obtained by adjusting the ionic strength. Besides, the selective separation of RNA and tryptophane (Trp) was successfully accomplished. It was found that 86.19% RNA was distributed in the bottom phase, while 72.02% Trp was enriched in the top phase in the novel ABSs. Finally, dynamic light scattering (DLS) and transmission electron microscope (TEM) were used to further investigate the extraction mechanism. The proposed method reveals the outstanding feasibility of the newly developed ABSs formed by PEG-based DESs and inorganic salts for the green extraction of RNA. Copyright © 2017 Elsevier B.V. All rights reserved.

Validation of a Statistical Methodology for Extracting Vegetation Feedbacks: Focus on North African Ecosystems in the Community Earth System Model

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

Yu, Yan; Notaro, Michael; Wang, Fuyao

Generalized equilibrium feedback assessment (GEFA) is a potentially valuable multivariate statistical tool for extracting vegetation feedbacks to the atmosphere in either observations or coupled Earth system models. The reliability of GEFA at capturing the terrestrial impacts on regional climate is demonstrated in this paper using the National Center for Atmospheric Research Community Earth System Model (CESM), with focus on North Africa. The feedback is assessed statistically by applying GEFA to output from a fully coupled control run. To reduce the sampling error caused by short data records, the traditional or full GEFA is refined through stepwise GEFA by dropping unimportantmore » forcings. Two ensembles of dynamical experiments are developed for the Sahel or West African monsoon region against which GEFA-based vegetation feedbacks are evaluated. In these dynamical experiments, regional leaf area index (LAI) is modified either alone or in conjunction with soil moisture, with the latter runs motivated by strong regional soil moisture–LAI coupling. Stepwise GEFA boasts higher consistency between statistically and dynamically assessed atmospheric responses to land surface anomalies than full GEFA, especially with short data records. GEFA-based atmospheric responses are more consistent with the coupled soil moisture–LAI experiments, indicating that GEFA is assessing the combined impacts of coupled vegetation and soil moisture. Finally, both the statistical and dynamical assessments reveal a negative vegetation–rainfall feedback in the Sahel associated with an atmospheric stability mechanism in CESM versus a weaker positive feedback in the West African monsoon region associated with a moisture recycling mechanism in CESM.« less

Sequential reconstruction of driving-forces from nonlinear nonstationary dynamics

NASA Astrophysics Data System (ADS)

Güntürkün, Ulaş

2010-07-01

This paper describes a functional analysis-based method for the estimation of driving-forces from nonlinear dynamic systems. The driving-forces account for the perturbation inputs induced by the external environment or the secular variations in the internal variables of the system. The proposed algorithm is applicable to the problems for which there is too little or no prior knowledge to build a rigorous mathematical model of the unknown dynamics. We derive the estimator conditioned on the differentiability of the unknown system’s mapping, and smoothness of the driving-force. The proposed algorithm is an adaptive sequential realization of the blind prediction error method, where the basic idea is to predict the observables, and retrieve the driving-force from the prediction error. Our realization of this idea is embodied by predicting the observables one-step into the future using a bank of echo state networks (ESN) in an online fashion, and then extracting the raw estimates from the prediction error and smoothing these estimates in two adaptive filtering stages. The adaptive nature of the algorithm enables to retrieve both slowly and rapidly varying driving-forces accurately, which are illustrated by simulations. Logistic and Moran-Ricker maps are studied in controlled experiments, exemplifying chaotic state and stochastic measurement models. The algorithm is also applied to the estimation of a driving-force from another nonlinear dynamic system that is stochastic in both state and measurement equations. The results are judged by the posterior Cramer-Rao lower bounds. The method is finally put into test on a real-world application; extracting sun’s magnetic flux from the sunspot time series.

Validation of a Statistical Methodology for Extracting Vegetation Feedbacks: Focus on North African Ecosystems in the Community Earth System Model

DOE PAGES

Yu, Yan; Notaro, Michael; Wang, Fuyao; ...

2018-02-05

Generalized equilibrium feedback assessment (GEFA) is a potentially valuable multivariate statistical tool for extracting vegetation feedbacks to the atmosphere in either observations or coupled Earth system models. The reliability of GEFA at capturing the terrestrial impacts on regional climate is demonstrated in this paper using the National Center for Atmospheric Research Community Earth System Model (CESM), with focus on North Africa. The feedback is assessed statistically by applying GEFA to output from a fully coupled control run. To reduce the sampling error caused by short data records, the traditional or full GEFA is refined through stepwise GEFA by dropping unimportantmore » forcings. Two ensembles of dynamical experiments are developed for the Sahel or West African monsoon region against which GEFA-based vegetation feedbacks are evaluated. In these dynamical experiments, regional leaf area index (LAI) is modified either alone or in conjunction with soil moisture, with the latter runs motivated by strong regional soil moisture–LAI coupling. Stepwise GEFA boasts higher consistency between statistically and dynamically assessed atmospheric responses to land surface anomalies than full GEFA, especially with short data records. GEFA-based atmospheric responses are more consistent with the coupled soil moisture–LAI experiments, indicating that GEFA is assessing the combined impacts of coupled vegetation and soil moisture. Finally, both the statistical and dynamical assessments reveal a negative vegetation–rainfall feedback in the Sahel associated with an atmospheric stability mechanism in CESM versus a weaker positive feedback in the West African monsoon region associated with a moisture recycling mechanism in CESM.« less

Discovering governing equations from data by sparse identification of nonlinear dynamical systems

PubMed Central

Brunton, Steven L.; Proctor, Joshua L.; Kutz, J. Nathan

2016-01-01

Extracting governing equations from data is a central challenge in many diverse areas of science and engineering. Data are abundant whereas models often remain elusive, as in climate science, neuroscience, ecology, finance, and epidemiology, to name only a few examples. In this work, we combine sparsity-promoting techniques and machine learning with nonlinear dynamical systems to discover governing equations from noisy measurement data. The only assumption about the structure of the model is that there are only a few important terms that govern the dynamics, so that the equations are sparse in the space of possible functions; this assumption holds for many physical systems in an appropriate basis. In particular, we use sparse regression to determine the fewest terms in the dynamic governing equations required to accurately represent the data. This results in parsimonious models that balance accuracy with model complexity to avoid overfitting. We demonstrate the algorithm on a wide range of problems, from simple canonical systems, including linear and nonlinear oscillators and the chaotic Lorenz system, to the fluid vortex shedding behind an obstacle. The fluid example illustrates the ability of this method to discover the underlying dynamics of a system that took experts in the community nearly 30 years to resolve. We also show that this method generalizes to parameterized systems and systems that are time-varying or have external forcing. PMID:27035946

Discovering governing equations from data by sparse identification of nonlinear dynamical systems.

PubMed

Brunton, Steven L; Proctor, Joshua L; Kutz, J Nathan

2016-04-12

Extracting governing equations from data is a central challenge in many diverse areas of science and engineering. Data are abundant whereas models often remain elusive, as in climate science, neuroscience, ecology, finance, and epidemiology, to name only a few examples. In this work, we combine sparsity-promoting techniques and machine learning with nonlinear dynamical systems to discover governing equations from noisy measurement data. The only assumption about the structure of the model is that there are only a few important terms that govern the dynamics, so that the equations are sparse in the space of possible functions; this assumption holds for many physical systems in an appropriate basis. In particular, we use sparse regression to determine the fewest terms in the dynamic governing equations required to accurately represent the data. This results in parsimonious models that balance accuracy with model complexity to avoid overfitting. We demonstrate the algorithm on a wide range of problems, from simple canonical systems, including linear and nonlinear oscillators and the chaotic Lorenz system, to the fluid vortex shedding behind an obstacle. The fluid example illustrates the ability of this method to discover the underlying dynamics of a system that took experts in the community nearly 30 years to resolve. We also show that this method generalizes to parameterized systems and systems that are time-varying or have external forcing.

Prediction of dynamical systems by symbolic regression

NASA Astrophysics Data System (ADS)

Quade, Markus; Abel, Markus; Shafi, Kamran; Niven, Robert K.; Noack, Bernd R.

2016-07-01

We study the modeling and prediction of dynamical systems based on conventional models derived from measurements. Such algorithms are highly desirable in situations where the underlying dynamics are hard to model from physical principles or simplified models need to be found. We focus on symbolic regression methods as a part of machine learning. These algorithms are capable of learning an analytically tractable model from data, a highly valuable property. Symbolic regression methods can be considered as generalized regression methods. We investigate two particular algorithms, the so-called fast function extraction which is a generalized linear regression algorithm, and genetic programming which is a very general method. Both are able to combine functions in a certain way such that a good model for the prediction of the temporal evolution of a dynamical system can be identified. We illustrate the algorithms by finding a prediction for the evolution of a harmonic oscillator based on measurements, by detecting an arriving front in an excitable system, and as a real-world application, the prediction of solar power production based on energy production observations at a given site together with the weather forecast.

Comparison of salivary collection and processing methods for quantitative HHV-8 detection.

PubMed

Speicher, D J; Johnson, N W

2014-10-01

Saliva is a proved diagnostic fluid for the qualitative detection of infectious agents, but the accuracy of viral load determinations is unknown. Stabilising fluids impede nucleic acid degradation, compared with collection onto ice and then freezing, and we have shown that the DNA Genotek P-021 prototype kit (P-021) can produce high-quality DNA after 14 months of storage at room temperature. Here we evaluate the quantitative capability of 10 collection/processing methods. Unstimulated whole mouth fluid was spiked with a mixture of HHV-8 cloned constructs, 10-fold serial dilutions were produced, and samples were extracted and then examined with quantitative PCR (qPCR). Calibration curves were compared by linear regression and qPCR dynamics. All methods extracted with commercial spin columns produced linear calibration curves with large dynamic range and gave accurate viral loads. Ethanol precipitation of the P-021 does not produce a linear standard curve, and virus is lost in the cell pellet. DNA extractions from the P-021 using commercial spin columns produced linear standard curves with wide dynamic range and excellent limit of detection. When extracted with spin columns, the P-021 enables accurate viral loads down to 23 copies μl(-1) DNA. The quantitative and long-term storage capability of this system makes it ideal for study of salivary DNA viruses in resource-poor settings. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Toward On-Demand Deep Brain Stimulation Using Online Parkinson's Disease Prediction Driven by Dynamic Detection.

PubMed

Mohammed, Ameer; Zamani, Majid; Bayford, Richard; Demosthenous, Andreas

2017-12-01

In Parkinson's disease (PD), on-demand deep brain stimulation is required so that stimulation is regulated to reduce side effects resulting from continuous stimulation and PD exacerbation due to untimely stimulation. Also, the progressive nature of PD necessitates the use of dynamic detection schemes that can track the nonlinearities in PD. This paper proposes the use of dynamic feature extraction and dynamic pattern classification to achieve dynamic PD detection taking into account the demand for high accuracy, low computation, and real-time detection. The dynamic feature extraction and dynamic pattern classification are selected by evaluating a subset of feature extraction, dimensionality reduction, and classification algorithms that have been used in brain-machine interfaces. A novel dimensionality reduction technique, the maximum ratio method (MRM) is proposed, which provides the most efficient performance. In terms of accuracy and complexity for hardware implementation, a combination having discrete wavelet transform for feature extraction, MRM for dimensionality reduction, and dynamic k-nearest neighbor for classification was chosen as the most efficient. It achieves a classification accuracy of 99.29%, an F1-score of 97.90%, and a choice probability of 99.86%.

Learning of spatio-temporal codes in a coupled oscillator system.

PubMed

Orosz, Gábor; Ashwin, Peter; Townley, Stuart

2009-07-01

In this paper, we consider a learning strategy that allows one to transmit information between two coupled phase oscillator systems (called teaching and learning systems) via frequency adaptation. The dynamics of these systems can be modeled with reference to a number of partially synchronized cluster states and transitions between them. Forcing the teaching system by steady but spatially nonhomogeneous inputs produces cyclic sequences of transitions between the cluster states, that is, information about inputs is encoded via a "winnerless competition" process into spatio-temporal codes. The large variety of codes can be learned by the learning system that adapts its frequencies to those of the teaching system. We visualize the dynamics using "weighted order parameters (WOPs)" that are analogous to "local field potentials" in neural systems. Since spatio-temporal coding is a mechanism that appears in olfactory systems, the developed learning rules may help to extract information from these neural ensembles.

Quantification of groundwater extraction-induced subsidence in the Mekong delta, Vietnam: 3D process-based numerical modeling

NASA Astrophysics Data System (ADS)

Minderhoud, Philip S. J.; Erkens, Gilles; Pham, Hung V.; Bui, Vuong T.; Kooi, Henk; Erban, Laura; Stouthamer, Esther

2017-04-01

The demand for groundwater in the Vietnamese Mekong delta has steadily risen over the past decades. As a result, hydraulic heads in the aquifers dropped on average 0.3-0.7 m/yr-1, potentially causing aquifer-system compaction. At present, the delta is experiencing subsidence rates up to several centimeters per year that outpace global sea level rise by an order of magnitude. However, the exact contribution of groundwater extraction to total subsidence in the delta has not been assessed yet. The objective of our study is to quantify the impact of 25 years of groundwater extraction on subsidence. We built a 3D numerical hydrogeological model comprising the multi-aquifer system of the entire Vietnamese Mekong delta. Groundwater dynamics in the aquifers was simulated over the past quarter-century based on the known extraction history and measured time series of hydraulic head. Subsequently, we calculated corresponding aquifer system compaction using a coupled land subsidence module, which includes a direct, elastic component and a secular, viscous component (i.e. creep). The hydrogeological model is able to reproduce the measured drawdowns in the multi-aquifer system of the past 25 years. Corresponding subsidence rates resulting from aquifer system compaction show a gradual increase over the past two decades to significant annual rates up to several centimeters. Groundwater extraction seems to be a dominant driver of subsidence in the delta, but does not explain the total measured subsidence. This process-based modeling approach can be used to quantify groundwater extraction-induced subsidence for coastal areas and at delta-scale worldwide.

Insight into the time-resolved extraction of aroma compounds during espresso coffee preparation: online monitoring by PTR-ToF-MS.

PubMed

Sánchez-López, José A; Zimmermann, Ralf; Yeretzian, Chahan

2014-12-02

Using proton-transfer-reaction time-of-flight mass-spectrometry (PTR-ToF-MS), we investigated the extraction dynamic of 95 ion traces in real time (time resolution = 1 s) during espresso coffee preparation. Fifty-two of these ions were tentatively identified. This was achieved by online sampling of the volatile organic compounds (VOCs) in close vicinity to the coffee flow, at the exit of the extraction hose of the espresso machine (single serve capsules). Ten replicates of six different single serve coffee types were extracted to a final weight between 20-120 g, according to the recommended cup size of the respective coffee capsule (Ristretto, Espresso, and Lungo), and analyzed. The results revealed considerable differences in the extraction kinetics between compounds, which led to a fast evolution of the volatile profiles in the extract flow and consequently to an evolution of the final aroma balance in the cup. Besides exploring the time-resolved extraction dynamics of VOCs, the dynamic data also allowed the coffees types (capsules) to be distinguished from one another. Both hierarchical cluster analysis (HCA) and principal component analysis (PCA) showed full separation between the coffees types. The methodology developed provides a fast and simple means of studying the extraction dynamics of VOCs and differentiating between different coffee types.

Role of core excitation in ( d , p ) transfer reactions

DOE PAGES

Deltuva, A.; Ross, A.; Norvaišas, E.; ...

2016-10-24

In our recent work we found that core excitations can be important in extracting structure information from (d,p) reactions. Our objective is to systematically explore the role of core excitation in (d,p) reactions and to understand the origin of the dynamical effects. Based on the particle-rotor model of n+Be 10, we generate a number of models with a range of separation energies (S n=0.1–5.0 MeV), while maintaining a significant core excited component. We then apply the latest extension of the momentum-space-based Faddeev method, including dynamical core excitation in the reaction mechanism to all orders, to the Be 10(d,p)Be 11-like reactions,more » and study the excitation effects for beam energies E d=15–90 MeV. We study the resulting angular distributions and the differences between the spectroscopic factor that would be extracted from the cross sections, when including dynamical core excitation in the reaction, and that of the original structure model. We also explore how different partial waves affect the final cross section. Our results show a strong beam-energy dependence of the extracted spectroscopic factors that become smaller for intermediate beam energies. Finally, this dependence increases for loosely bound systems.« less

Knowledge discovery and system biology in molecular medicine: an application on neurodegenerative diseases.

PubMed

Fattore, Matteo; Arrigo, Patrizio

2005-01-01

The possibility to study an organism in terms of system theory has been proposed in the past, but only the advancement of molecular biology techniques allow us to investigate the dynamical properties of a biological system in a more quantitative and rational way than before . These new techniques can gave only the basic level view of an organisms functionality. The comprehension of its dynamical behaviour depends on the possibility to perform a multiple level analysis. Functional genomics has stimulated the interest in the investigation the dynamical behaviour of an organism as a whole. These activities are commonly known as System Biology, and its interests ranges from molecules to organs. One of the more promising applications is the 'disease modeling'. The use of experimental models is a common procedure in pharmacological and clinical researches; today this approach is supported by 'in silico' predictive methods. This investigation can be improved by a combination of experimental and computational tools. The Machine Learning (ML) tools are able to process different heterogeneous data sources, taking into account this peculiarity, they could be fruitfully applied to support a multilevel data processing (molecular, cellular and morphological) that is the prerequisite for the formal model design; these techniques can allow us to extract the knowledge for mathematical model development. The aim of our work is the development and implementation of a system that combines ML and dynamical models simulations. The program is addressed to the virtual analysis of the pathways involved in neurodegenerative diseases. These pathologies are multifactorial diseases and the relevance of the different factors has not yet been well elucidated. This is a very complex task; in order to test the integrative approach our program has been limited to the analysis of the effects of a specific protein, the Cyclin dependent kinase 5 (CDK5) which relies on the induction of neuronal apoptosis. The system has a modular structure centred on a textual knowledge discovery approach. The text mining is the only way to enhance the capability to extract ,from multiple data sources, the information required for the dynamical simulator. The user may access the publically available modules through the following site: http://biocomp.ge.ismac.cnr.it.

Complexity in Dynamical Systems

NASA Astrophysics Data System (ADS)

Moore, Cristopher David

The study of chaos has shown us that deterministic systems can have a kind of unpredictability, based on a limited knowledge of their initial conditions; after a finite time, the motion appears essentially random. This observation has inspired a general interest in the subject of unpredictability, and more generally, complexity; how can we characterize how "complex" a dynamical system is?. In this thesis, we attempt to answer this question with a paradigm of complexity that comes from computer science, we extract sets of symbol sequences, or languages, from a dynamical system using standard methods of symbolic dynamics; we then ask what kinds of grammars or automata are needed a generate these languages. This places them in the Chomsky heirarchy, which in turn tells us something about how subtle and complex the dynamical system's behavior is. This gives us insight into the question of unpredictability, since these automata can also be thought of as computers attempting to predict the system. In the culmination of the thesis, we find a class of smooth, two-dimensional maps which are equivalent to the highest class in the Chomsky heirarchy, the turning machine; they are capable of universal computation. Therefore, these systems possess a kind of unpredictability qualitatively different from the usual "chaos": even if the initial conditions are known exactly, questions about the system's long-term dynamics are undecidable. No algorithm exists to answer them. Although this kind of unpredictability has been discussed in the context of distributed, many-degree-of -freedom systems (for instance, cellular automata) we believe this is the first example of such phenomena in a smooth, finite-degree-of-freedom system.

The Temporal Dynamics of Regularity Extraction in Non-Human Primates

ERIC Educational Resources Information Center

Minier, Laure; Fagot, Joël; Rey, Arnaud

2016-01-01

Extracting the regularities of our environment is one of our core cognitive abilities. To study the fine-grained dynamics of the extraction of embedded regularities, a method combining the advantages of the artificial language paradigm (Saffran, Aslin, & Newport, [Saffran, J. R., 1996]) and the serial response time task (Nissen & Bullemer,…

Thermally induced magnetic relaxation in square artificial spin ice.

PubMed

Andersson, M S; Pappas, S D; Stopfel, H; Östman, E; Stein, A; Nordblad, P; Mathieu, R; Hjörvarsson, B; Kapaklis, V

2016-11-24

The properties of natural and artificial assemblies of interacting elements, ranging from Quarks to Galaxies, are at the heart of Physics. The collective response and dynamics of such assemblies are dictated by the intrinsic dynamical properties of the building blocks, the nature of their interactions and topological constraints. Here we report on the relaxation dynamics of the magnetization of artificial assemblies of mesoscopic spins. In our model nano-magnetic system - square artificial spin ice - we are able to control the geometrical arrangement and interaction strength between the magnetically interacting building blocks by means of nano-lithography. Using time resolved magnetometry we show that the relaxation process can be described using the Kohlrausch law and that the extracted temperature dependent relaxation times of the assemblies follow the Vogel-Fulcher law. The results provide insight into the relaxation dynamics of mesoscopic nano-magnetic model systems, with adjustable energy and time scales, and demonstrates that these can serve as an ideal playground for the studies of collective dynamics and relaxations.

Thermally induced magnetic relaxation in square artificial spin ice

NASA Astrophysics Data System (ADS)

Andersson, M. S.; Pappas, S. D.; Stopfel, H.; Östman, E.; Stein, A.; Nordblad, P.; Mathieu, R.; Hjörvarsson, B.; Kapaklis, V.

2016-11-01

The properties of natural and artificial assemblies of interacting elements, ranging from Quarks to Galaxies, are at the heart of Physics. The collective response and dynamics of such assemblies are dictated by the intrinsic dynamical properties of the building blocks, the nature of their interactions and topological constraints. Here we report on the relaxation dynamics of the magnetization of artificial assemblies of mesoscopic spins. In our model nano-magnetic system - square artificial spin ice - we are able to control the geometrical arrangement and interaction strength between the magnetically interacting building blocks by means of nano-lithography. Using time resolved magnetometry we show that the relaxation process can be described using the Kohlrausch law and that the extracted temperature dependent relaxation times of the assemblies follow the Vogel-Fulcher law. The results provide insight into the relaxation dynamics of mesoscopic nano-magnetic model systems, with adjustable energy and time scales, and demonstrates that these can serve as an ideal playground for the studies of collective dynamics and relaxations.

Topological Principles of Control in Dynamical Networks

NASA Astrophysics Data System (ADS)

Kim, Jason; Pasqualetti, Fabio; Bassett, Danielle

Networked biological systems, such as the brain, feature complex patterns of interactions. To predict and correct the dynamic behavior of such systems, it is imperative to understand how the underlying topological structure affects and limits the function of the system. Here, we use network control theory to extract topological features that favor or prevent network controllability, and to understand the network-wide effect of external stimuli on large-scale brain systems. Specifically, we treat each brain region as a dynamic entity with real-valued state, and model the time evolution of all interconnected regions using linear, time-invariant dynamics. We propose a simplified feed-forward scheme where the effect of upstream regions (drivers) on the connected downstream regions (non-drivers) is characterized in closed-form. Leveraging this characterization of the simplified model, we derive topological features that predict the controllability properties of non-simplified networks. We show analytically and numerically that these predictors are accurate across a large range of parameters. Among other contributions, our analysis shows that heterogeneity in the network weights facilitate controllability, and allows us to implement targeted interventions that profoundly improve controllability. By assuming an underlying dynamical mechanism, we are able to understand the complex topology of networked biological systems in a functionally meaningful way.

Hot-hole extraction from quantum dot to molecular adsorbate.

PubMed

Singhal, Pallavi; Ghosh, Hirendra N

2015-03-09

Ultrafast thermalized and hot-hole-transfer processes have been investigated in CdSe quantum dot (QD)/catechol composite systems in which hole transfer from photoexcited QDs to the catechols is thermodynamically favorable. A series of catechol derivatives were selected with different electron-donating and -withdrawing groups, and the effect of these groups on hole transfer and charge recombination (CR) dynamics has been investigated. The hole-transfer time was determined using the fluorescence upconversion technique and found to be 2-10 ps depending on the molecular structure of the catechol derivatives. The hot-hole-transfer process was followed after monitoring 2S luminescence of CdSe QDs. Interestingly, hot-hole extraction was observed only in the CdSe/3-methoxycatechol (3-OCH3) composite system owing to the higher electron-donating property of the 3-methoxy group. To confirm the extraction of the hot hole and to monitor the CR reaction in CdSe QD/catechol composite systems, ultrafast transient absorption studies have been carried out. Ultrafast transient-absorption studies show that the bleach recovery kinetics of CdSe QD at the 2S excitonic position is much faster in the presence of 3-OCH3. This faster bleach recovery at the 2S position in CdSe/3-OCH3 suggests hot-hole transfer from CdSe QD to 3-OCH3. CR dynamics in CdSe QD/catechol composite systems was followed by monitoring the excitonic bleach at the 1S position and was found to decrease with free energy of the CR reaction. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

First- and second-order processing in transient stereopsis.

PubMed

Edwards, M; Pope, D R; Schor, C M

2000-01-01

Large-field stimuli were used to investigate the interaction of first- and second-order pathways in transient-stereo processing. Stimuli consisted of sinewave modulations in either the mean luminance (first-order stimulus) or the contrast (second-order stimulus) of a dynamic-random-dot field. The main results of the present study are that: (1) Depth could be extracted with both the first-order and second-order stimuli; (2) Depth could be extracted from dichoptically mixed first- and second-order stimuli, however, the same stimuli, when presented as a motion sequence, did not result in a motion percept. Based upon these findings we conclude that the transient-stereo system processes both first- and second-order signals, and that these two signals are pooled prior to the extraction of transient depth. This finding of interaction between first- and second-order stereoscopic processing is different from the independence that has been found with the motion system.

Simulation-based Extraction of Key Material Parameters from Atomic Force Microscopy

NASA Astrophysics Data System (ADS)

Alsafi, Huseen; Peninngton, Gray

Models for the atomic force microscopy (AFM) tip and sample interaction contain numerous material parameters that are often poorly known. This is especially true when dealing with novel material systems or when imaging samples that are exposed to complicated interactions with the local environment. In this work we use Monte Carlo methods to extract sample material parameters from the experimental AFM analysis of a test sample. The parameterized theoretical model that we use is based on the Virtual Environment for Dynamic AFM (VEDA) [1]. The extracted material parameters are then compared with the accepted values for our test sample. Using this procedure, we suggest a method that can be used to successfully determine unknown material properties in novel and complicated material systems. We acknowledge Fisher Endowment Grant support from the Jess and Mildred Fisher College of Science and Mathematics,Towson University.

Automated ancillary cancer history classification for mesothelioma patients from free-text clinical reports

PubMed Central

Wilson, Richard A.; Chapman, Wendy W.; DeFries, Shawn J.; Becich, Michael J.; Chapman, Brian E.

2010-01-01

Background: Clinical records are often unstructured, free-text documents that create information extraction challenges and costs. Healthcare delivery and research organizations, such as the National Mesothelioma Virtual Bank, require the aggregation of both structured and unstructured data types. Natural language processing offers techniques for automatically extracting information from unstructured, free-text documents. Methods: Five hundred and eight history and physical reports from mesothelioma patients were split into development (208) and test sets (300). A reference standard was developed and each report was annotated by experts with regard to the patient’s personal history of ancillary cancer and family history of any cancer. The Hx application was developed to process reports, extract relevant features, perform reference resolution and classify them with regard to cancer history. Two methods, Dynamic-Window and ConText, for extracting information were evaluated. Hx’s classification responses using each of the two methods were measured against the reference standard. The average Cohen’s weighted kappa served as the human benchmark in evaluating the system. Results: Hx had a high overall accuracy, with each method, scoring 96.2%. F-measures using the Dynamic-Window and ConText methods were 91.8% and 91.6%, which were comparable to the human benchmark of 92.8%. For the personal history classification, Dynamic-Window scored highest with 89.2% and for the family history classification, ConText scored highest with 97.6%, in which both methods were comparable to the human benchmark of 88.3% and 97.2%, respectively. Conclusion: We evaluated an automated application’s performance in classifying a mesothelioma patient’s personal and family history of cancer from clinical reports. To do so, the Hx application must process reports, identify cancer concepts, distinguish the known mesothelioma from ancillary cancers, recognize negation, perform reference resolution and determine the experiencer. Results indicated that both information extraction methods tested were dependant on the domain-specific lexicon and negation extraction. We showed that the more general method, ConText, performed as well as our task-specific method. Although Dynamic- Window could be modified to retrieve other concepts, ConText is more robust and performs better on inconclusive concepts. Hx could greatly improve and expedite the process of extracting data from free-text, clinical records for a variety of research or healthcare delivery organizations. PMID:21031012

A Fiber Bragg Grating Sensor Interrogation System Based on a Linearly Wavelength-Swept Thermo-Optic Laser Chip

PubMed Central

Lee, Hyung-Seok; Lee, Hwi Don; Kim, Hyo Jin; Cho, Jae Du; Jeong, Myung Yung; Kim, Chang-Seok

2014-01-01

A linearized wavelength-swept thermo-optic laser chip was applied to demonstrate a fiber Bragg grating (FBG) sensor interrogation system. A broad tuning range of 11.8 nm was periodically obtained from the laser chip for a sweep rate of 16 Hz. To measure the linear time response of the reflection signal from the FBG sensor, a programmed driving signal was directly applied to the wavelength-swept laser chip. The linear wavelength response of the applied strain was clearly extracted with an R-squared value of 0.99994. To test the feasibility of the system for dynamic measurements, the dynamic strain was successfully interrogated with a repetition rate of 0.2 Hz by using this FBG sensor interrogation system. PMID:25177803

Motion-seeded object-based attention for dynamic visual imagery

NASA Astrophysics Data System (ADS)

Huber, David J.; Khosla, Deepak; Kim, Kyungnam

2017-05-01

This paper† describes a novel system that finds and segments "objects of interest" from dynamic imagery (video) that (1) processes each frame using an advanced motion algorithm that pulls out regions that exhibit anomalous motion, and (2) extracts the boundary of each object of interest using a biologically-inspired segmentation algorithm based on feature contours. The system uses a series of modular, parallel algorithms, which allows many complicated operations to be carried out by the system in a very short time, and can be used as a front-end to a larger system that includes object recognition and scene understanding modules. Using this method, we show 90% accuracy with fewer than 0.1 false positives per frame of video, which represents a significant improvement over detection using a baseline attention algorithm.

A Low-Cost PC-Based Image Workstation for Dynamic Interactive Display of Three-Dimensional Anatomy

NASA Astrophysics Data System (ADS)

Barrett, William A.; Raya, Sai P.; Udupa, Jayaram K.

1989-05-01

A system for interactive definition, automated extraction, and dynamic interactive display of three-dimensional anatomy has been developed and implemented on a low-cost PC-based image workstation. An iconic display is used for staging predefined image sequences through specified increments of tilt and rotation over a solid viewing angle. Use of a fast processor facilitates rapid extraction and rendering of the anatomy into predefined image views. These views are formatted into a display matrix in a large image memory for rapid interactive selection and display of arbitrary spatially adjacent images within the viewing angle, thereby providing motion parallax depth cueing for efficient and accurate perception of true three-dimensional shape, size, structure, and spatial interrelationships of the imaged anatomy. The visual effect is that of holding and rotating the anatomy in the hand.

The economic value of remote sensing of earth resources from space: An ERTS overview and the value of continuity of service. Volume 7: Nonreplenishable natural resources: Minerals, fossil fuels and geothermal energy sources

NASA Technical Reports Server (NTRS)

Lietzke, K. R.

1974-01-01

The application of remotely-sensed information to the mineral, fossil fuel, and geothermal energy extraction industry is investigated. Public and private cost savings are documented in geologic mapping activities. Benefits and capabilities accruing to the ERS system are assessed. It is shown that remote sensing aids in resource extraction, as well as the monitoring of several dynamic phenomena, including disturbed lands, reclamation, erosion, glaciation, and volcanic and seismic activity.

From fuzzy recurrence plots to scalable recurrence networks of time series

NASA Astrophysics Data System (ADS)

Pham, Tuan D.

2017-04-01

Recurrence networks, which are derived from recurrence plots of nonlinear time series, enable the extraction of hidden features of complex dynamical systems. Because fuzzy recurrence plots are represented as grayscale images, this paper presents a variety of texture features that can be extracted from fuzzy recurrence plots. Based on the notion of fuzzy recurrence plots, defuzzified, undirected, and unweighted recurrence networks are introduced. Network measures can be computed for defuzzified recurrence networks that are scalable to meet the demand for the network-based analysis of big data.

Future Directions of Nonlinear Dynamics in Physical and Biological Systems. (Physica D Nonlinear. Volume 68, Number 1)

DTIC Science & Technology

1993-09-15

and structure of the equations. The Lagrangian for- c and we can extract information for any speed of mulation gives us an extremum principle for the...Dueholm and N.F. Pedersen, J. Appi. [261 For references on this see e.g. N.F. Pedersen, in: Phys. 60 (1986) 1447. SQUID 80, eds. H. Hahlbohm and H...obtained for arbitrary initial conditions, and a number of physical How do we augment the DNLSE (4) to treat features have been extracted [121. The

A Standard-Compliant Virtual Meeting System with Active Video Object Tracking

NASA Astrophysics Data System (ADS)

Lin, Chia-Wen; Chang, Yao-Jen; Wang, Chih-Ming; Chen, Yung-Chang; Sun, Ming-Ting

2002-12-01

This paper presents an H.323 standard compliant virtual video conferencing system. The proposed system not only serves as a multipoint control unit (MCU) for multipoint connection but also provides a gateway function between the H.323 LAN (local-area network) and the H.324 WAN (wide-area network) users. The proposed virtual video conferencing system provides user-friendly object compositing and manipulation features including 2D video object scaling, repositioning, rotation, and dynamic bit-allocation in a 3D virtual environment. A reliable, and accurate scheme based on background image mosaics is proposed for real-time extracting and tracking foreground video objects from the video captured with an active camera. Chroma-key insertion is used to facilitate video objects extraction and manipulation. We have implemented a prototype of the virtual conference system with an integrated graphical user interface to demonstrate the feasibility of the proposed methods.

Extraction and evaluation of gas-flow-dependent features from dynamic measurements of gas sensors array

NASA Astrophysics Data System (ADS)

Kalinowski, Paweł; Woźniak, Łukasz; Jasiński, Grzegorz; Jasiński, Piotr

2016-11-01

Gas analyzers based on gas sensors are the devices which enable recognition of various kinds of volatile compounds. They have continuously been developed and investigated for over three decades, however there are still limitations which slow down the implementation of those devices in many applications. For example, the main drawbacks are the lack of selectivity, sensitivity and long term stability of those devices caused by the drift of utilized sensors. This implies the necessity of investigations not only in the field of development of gas sensors construction, but also the development of measurement procedures or methods of analysis of sensor responses which compensate the limitations of sensors devices. One of the fields of investigations covers the dynamic measurements of sensors or sensor-arrays response with the utilization of flow modulation techniques. Different gas delivery patterns enable the possibility of extraction of unique features which improves the stability and selectivity of gas detecting systems. In this article three utilized flow modulation techniques are presented, together with the proposition of the evaluation method of their usefulness and robustness in environmental pollutants detecting systems. The results of dynamic measurements of an commercially available TGS sensor array in the presence of nitrogen dioxide and ammonia are shown.

Dynamic Mass Transfer of Hemoglobin at the Aqueous/Ionic-Liquid Interface Monitored with Liquid Core Optical Waveguide.

PubMed

Chen, Xuwei; Yang, Xu; Zeng, Wanying; Wang, Jianhua

2015-08-04

Protein transfer from aqueous medium into ionic liquid is an important approach for the isolation of proteins of interest from complex biological samples. We hereby report a solid-cladding/liquid-core/liquid-cladding sandwich optical waveguide system for the purpose of monitoring the dynamic mass-transfer behaviors of hemoglobin (Hb) at the aqueous/ionic liquid interface. The optical waveguide system is fabricated by using a hydrophobic IL (1,3-dibutylimidazolium hexafluorophosphate, BBimPF6) as the core, and protein solution as one of the cladding layer. UV-vis spectra are recorded with a CCD spectrophotometer via optical fibers. The recorded spectra suggest that the mass transfer of Hb molecules between the aqueous and ionic liquid media involve accumulation of Hb on the aqueous/IL interface followed by dynamic extraction/transfer of Hb into the ionic liquid phase. A part of Hb molecules remain at the interface even after the accomplishment of the extraction/transfer process. Further investigations indicate that the mass transfer of Hb from aqueous medium into the ionic liquid phase is mainly driven by the coordination interaction between heme group of Hb and the cationic moiety of ionic liquid, for example, imidazolium cation in this particular case. In addition, hydrophobic interactions also contribute to the transfer of Hb.

G-Consistent Subsets and Reduced Dynamical Quantum Maps

NASA Astrophysics Data System (ADS)

Ceballos, Russell R.

A quantum system which evolves in time while interacting with an external environ- ment is said to be an open quantum system (OQS), and the influence of the environment on the unperturbed unitary evolution of the system generally leads to non-unitary dynamics. This kind of open system dynamical evolution has been typically modeled by a Standard Prescription (SP) which assumes that the state of the OQS is initially uncorrelated with the environment state. It is here shown that when a minimal set of physically motivated assumptions are adopted, not only does there exist constraints on the reduced dynamics of an OQS such that this SP does not always accurately describe the possible initial cor- relations existing between the OQS and environment, but such initial correlations, and even entanglement, can be witnessed when observing a particular class of reduced state transformations termed purity extractions are observed. Furthermore, as part of a more fundamental investigation to better understand the minimal set of assumptions required to formulate well defined reduced dynamical quantum maps, it is demonstrated that there exists a one-to-one correspondence between the set of initial reduced states and the set of admissible initial system-environment composite states when G-consistency is enforced. Given the discussions surrounding the requirement of complete positivity and the reliance on the SP, the results presented here may well be found valuable for determining the ba- sic properties of reduced dynamical maps, and when restrictions on the OQS dynamics naturally emerge.

Effects of cockpit lateral stick characteristics on handling qualities and pilot dynamics

NASA Technical Reports Server (NTRS)

Mitchell, David G.; Aponso, Bimal L.; Klyde, David H.

1992-01-01

This report presents the results of analysis of cockpit lateral control feel-system studies. Variations in feel-system natural frequency, damping, and command sensing reference (force and position) were investigated, in combination with variations in the aircraft response characteristics. The primary data for the report were obtained from a flight investigation conducted with a variable-stability airplane, with additional information taken from other flight experiments and ground-based simulations for both airplanes and helicopters . The study consisted of analysis of handling qualities ratings and extraction of open-loop, pilot-vehicle describing functions from sum-of-sines tracking data, including, for a limited subset of these data, the development of pilot models. The study confirms the findings of other investigators that the effects on pilot opinion of cockpit feel-system dynamics are not equivalent to a comparable level of added time delay, and until a more comprehensive set of criteria are developed, it is recommended that feel-system dynamics be considered a delay-inducing element in the aircraft response. The best correlation with time-delay requirements was found when the feel-system dynamics were included in the delay measurements, regardless of the command reference. This is a radical departure from past approaches.

Quantification of the ciliary muscle and crystalline lens interaction during accommodation with synchronous OCT imaging

PubMed Central

Ruggeri, Marco; de Freitas, Carolina; Williams, Siobhan; Hernandez, Victor M.; Cabot, Florence; Yesilirmak, Nilufer; Alawa, Karam; Chang, Yu-Cherng; Yoo, Sonia H.; Gregori, Giovanni; Parel, Jean-Marie; Manns, Fabrice

2016-01-01

Abstract: Two SD-OCT systems and a dual channel accommodation target were combined and precisely synchronized to simultaneously image the anterior segment and the ciliary muscle during dynamic accommodation. The imaging system simultaneously generates two synchronized OCT image sequences of the anterior segment and ciliary muscle with an imaging speed of 13 frames per second. The system was used to acquire OCT image sequences of a non-presbyopic and a pre-presbyopic subject accommodating in response to step changes in vergence. The image sequences were processed to extract dynamic morphological data from the crystalline lens and the ciliary muscle. The synchronization between the OCT systems allowed the precise correlation of anatomical changes occurring in the crystalline lens and ciliary muscle at identical time points during accommodation. To describe the dynamic interaction between the crystalline lens and ciliary muscle, we introduce accommodation state diagrams that display the relation between anatomical changes occurring in the accommodating crystalline lens and ciliary muscle. PMID:27446660

Asymptotic safety of gravity-matter systems

NASA Astrophysics Data System (ADS)

Meibohm, J.; Pawlowski, J. M.; Reichert, M.

2016-04-01

We study the ultraviolet stability of gravity-matter systems for general numbers of minimally coupled scalars and fermions. This is done within the functional renormalization group setup put forward in [N. Christiansen, B. Knorr, J. Meibohm, J. M. Pawlowski, and M. Reichert, Phys. Rev. D 92, 121501 (2015).] for pure gravity. It includes full dynamical propagators and a genuine dynamical Newton's coupling, which is extracted from the graviton three-point function. We find ultraviolet stability of general gravity-fermion systems. Gravity-scalar systems are also found to be ultraviolet stable within validity bounds for the chosen generic class of regulators, based on the size of the anomalous dimension. Remarkably, the ultraviolet fixed points for the dynamical couplings are found to be significantly different from those of their associated background counterparts, once matter fields are included. In summary, the asymptotic safety scenario does not put constraints on the matter content of the theory within the validity bounds for the chosen generic class of regulators.

Quantification of the ciliary muscle and crystalline lens interaction during accommodation with synchronous OCT imaging.

PubMed

Ruggeri, Marco; de Freitas, Carolina; Williams, Siobhan; Hernandez, Victor M; Cabot, Florence; Yesilirmak, Nilufer; Alawa, Karam; Chang, Yu-Cherng; Yoo, Sonia H; Gregori, Giovanni; Parel, Jean-Marie; Manns, Fabrice

2016-04-01

Two SD-OCT systems and a dual channel accommodation target were combined and precisely synchronized to simultaneously image the anterior segment and the ciliary muscle during dynamic accommodation. The imaging system simultaneously generates two synchronized OCT image sequences of the anterior segment and ciliary muscle with an imaging speed of 13 frames per second. The system was used to acquire OCT image sequences of a non-presbyopic and a pre-presbyopic subject accommodating in response to step changes in vergence. The image sequences were processed to extract dynamic morphological data from the crystalline lens and the ciliary muscle. The synchronization between the OCT systems allowed the precise correlation of anatomical changes occurring in the crystalline lens and ciliary muscle at identical time points during accommodation. To describe the dynamic interaction between the crystalline lens and ciliary muscle, we introduce accommodation state diagrams that display the relation between anatomical changes occurring in the accommodating crystalline lens and ciliary muscle.

Vision-based system identification technique for building structures using a motion capture system

NASA Astrophysics Data System (ADS)

Oh, Byung Kwan; Hwang, Jin Woo; Kim, Yousok; Cho, Tongjun; Park, Hyo Seon

2015-11-01

This paper presents a new vision-based system identification (SI) technique for building structures by using a motion capture system (MCS). The MCS with outstanding capabilities for dynamic response measurements can provide gage-free measurements of vibrations through the convenient installation of multiple markers. In this technique, from the dynamic displacement responses measured by MCS, the dynamic characteristics (natural frequency, mode shape, and damping ratio) of building structures are extracted after the processes of converting the displacement from MCS to acceleration and conducting SI by frequency domain decomposition. A free vibration experiment on a three-story shear frame was conducted to validate the proposed technique. The SI results from the conventional accelerometer-based method were compared with those from the proposed technique and showed good agreement, which confirms the validity and applicability of the proposed vision-based SI technique for building structures. Furthermore, SI directly employing MCS measured displacements to FDD was performed and showed identical results to those of conventional SI method.

Measuring the dynamic structure factor of a quantum gas undergoing a structural phase transition

PubMed Central

Landig, Renate; Brennecke, Ferdinand; Mottl, Rafael; Donner, Tobias; Esslinger, Tilman

2015-01-01

The dynamic structure factor is a central quantity describing the physics of quantum many-body systems, capturing structure and collective excitations of a material. In condensed matter, it can be measured via inelastic neutron scattering, which is an energy-resolving probe for the density fluctuations. In ultracold atoms, a similar approach could so far not be applied because of the diluteness of the system. Here we report on a direct, real-time and nondestructive measurement of the dynamic structure factor of a quantum gas exhibiting cavity-mediated long-range interactions. The technique relies on inelastic scattering of photons, stimulated by the enhanced vacuum field inside a high finesse optical cavity. We extract the density fluctuations, their energy and lifetime while the system undergoes a structural phase transition. We observe an occupation of the relevant quasi-particle mode on the level of a few excitations, and provide a theoretical description of this dissipative quantum many-body system. PMID:25944151

Low-Rank Linear Dynamical Systems for Motor Imagery EEG.

PubMed

Zhang, Wenchang; Sun, Fuchun; Tan, Chuanqi; Liu, Shaobo

2016-01-01

The common spatial pattern (CSP) and other spatiospectral feature extraction methods have become the most effective and successful approaches to solve the problem of motor imagery electroencephalography (MI-EEG) pattern recognition from multichannel neural activity in recent years. However, these methods need a lot of preprocessing and postprocessing such as filtering, demean, and spatiospectral feature fusion, which influence the classification accuracy easily. In this paper, we utilize linear dynamical systems (LDSs) for EEG signals feature extraction and classification. LDSs model has lots of advantages such as simultaneous spatial and temporal feature matrix generation, free of preprocessing or postprocessing, and low cost. Furthermore, a low-rank matrix decomposition approach is introduced to get rid of noise and resting state component in order to improve the robustness of the system. Then, we propose a low-rank LDSs algorithm to decompose feature subspace of LDSs on finite Grassmannian and obtain a better performance. Extensive experiments are carried out on public dataset from "BCI Competition III Dataset IVa" and "BCI Competition IV Database 2a." The results show that our proposed three methods yield higher accuracies compared with prevailing approaches such as CSP and CSSP.

Effective Information Extraction Framework for Heterogeneous Clinical Reports Using Online Machine Learning and Controlled Vocabularies.

PubMed

Zheng, Shuai; Lu, James J; Ghasemzadeh, Nima; Hayek, Salim S; Quyyumi, Arshed A; Wang, Fusheng

2017-05-09

Extracting structured data from narrated medical reports is challenged by the complexity of heterogeneous structures and vocabularies and often requires significant manual effort. Traditional machine-based approaches lack the capability to take user feedbacks for improving the extraction algorithm in real time. Our goal was to provide a generic information extraction framework that can support diverse clinical reports and enables a dynamic interaction between a human and a machine that produces highly accurate results. A clinical information extraction system IDEAL-X has been built on top of online machine learning. It processes one document at a time, and user interactions are recorded as feedbacks to update the learning model in real time. The updated model is used to predict values for extraction in subsequent documents. Once prediction accuracy reaches a user-acceptable threshold, the remaining documents may be batch processed. A customizable controlled vocabulary may be used to support extraction. Three datasets were used for experiments based on report styles: 100 cardiac catheterization procedure reports, 100 coronary angiographic reports, and 100 integrated reports-each combines history and physical report, discharge summary, outpatient clinic notes, outpatient clinic letter, and inpatient discharge medication report. Data extraction was performed by 3 methods: online machine learning, controlled vocabularies, and a combination of these. The system delivers results with F1 scores greater than 95%. IDEAL-X adopts a unique online machine learning-based approach combined with controlled vocabularies to support data extraction for clinical reports. The system can quickly learn and improve, thus it is highly adaptable. ©Shuai Zheng, James J Lu, Nima Ghasemzadeh, Salim S Hayek, Arshed A Quyyumi, Fusheng Wang. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 09.05.2017.

Velocity measurements of heterogeneous RBC flow in capillary vessels using dynamic laser speckle signal

PubMed Central

Li, Chenxi; Wang, Ruikang

2017-01-01

Abstract. We propose an approach to measure heterogeneous velocities of red blood cells (RBCs) in capillary vessels using full-field time-varying dynamic speckle signals. The approach utilizes a low coherent laser speckle imaging system to record the instantaneous speckle pattern, followed by an eigen-decomposition-based filtering algorithm to extract dynamic speckle signal due to the moving RBCs. The velocity of heterogeneous RBC flows is determined by cross-correlating the temporal dynamic speckle signals obtained at adjacent locations. We verify the approach by imaging mouse pinna in vivo, demonstrating its capability for full-field RBC flow mapping and quantifying flow pattern with high resolution. It is expected to investigate the dynamic action of RBCs flow in capillaries under physiological changes. PMID:28384709

Algorithm for Stabilizing a POD-Based Dynamical System

NASA Technical Reports Server (NTRS)

Kalb, Virginia L.

2010-01-01

This algorithm provides a new way to improve the accuracy and asymptotic behavior of a low-dimensional system based on the proper orthogonal decomposition (POD). Given a data set representing the evolution of a system of partial differential equations (PDEs), such as the Navier-Stokes equations for incompressible flow, one may obtain a low-dimensional model in the form of ordinary differential equations (ODEs) that should model the dynamics of the flow. Temporal sampling of the direct numerical simulation of the PDEs produces a spatial time series. The POD extracts the temporal and spatial eigenfunctions of this data set. Truncated to retain only the most energetic modes followed by Galerkin projection of these modes onto the PDEs obtains a dynamical system of ordinary differential equations for the time-dependent behavior of the flow. In practice, the steps leading to this system of ODEs entail numerically computing first-order derivatives of the mean data field and the eigenfunctions, and the computation of many inner products. This is far from a perfect process, and often results in the lack of long-term stability of the system and incorrect asymptotic behavior of the model. This algorithm describes a new stabilization method that utilizes the temporal eigenfunctions to derive correction terms for the coefficients of the dynamical system to significantly reduce these errors.

Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation.

PubMed

Villaverde, Alejandro F; Banga, Julio R

2017-11-01

The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. However, the original definition of dynamical compensation amounts to lack of structural identifiability. This is relevant if model parameters need to be estimated, as is often the case in biological modelling. Care should we taken when using an unidentifiable model to extract biological insight: the estimated values of structurally unidentifiable parameters are meaningless, and model predictions about unmeasured state variables can be wrong. Taking this into account, we explore alternative definitions of dynamical compensation that do not necessarily imply structural unidentifiability. Accordingly, we show different ways in which a model can be made identifiable while exhibiting dynamical compensation. Our analyses enable the use of the new concept of dynamical compensation in the context of parameter identification, and reconcile it with the desirable property of structural identifiability.

Dynamic fabric phase sorptive extraction for a group of pharmaceuticals and personal care products from environmental waters.

PubMed

Lakade, Sameer S; Borrull, Francesc; Furton, Kenneth G; Kabir, Abuzar; Marcé, Rosa Maria; Fontanals, Núria

2016-07-22

This paper describes for the first time the use of a new extraction technique, based on fabric phase sorptive extraction (FPSE). This new mode proposes the extraction of the analytes in dynamic mode in order to reduce the extraction time. Dynamic fabric phase sorptive extraction (DFPSE) followed by liquid chromatography-tandem mass spectrometry was evaluated for the extraction of a group of pharmaceuticals and personal care products (PPCPs) from environmental water samples. Different parameters affecting the extraction were optimized and best conditions were achieved when 50mL of sample at pH 3 was passed through 3 disks and analytes retained were eluted with 10mL of ethyl acetate. The recoveries were higher than 60% for most of compounds with the exception of the most polar ones (between 8% and 38%). The analytical method was validated with environmental samples such as river water and effluent and influent wastewater, and good performance was obtained. The analysis of samples revealed the presence of some PPCPs at low ngL(-1) concentrations. Copyright © 2016 Elsevier B.V. All rights reserved.

Chaos of radiative heat-loss-induced flame front instability.

PubMed

Kinugawa, Hikaru; Ueda, Kazuhiro; Gotoda, Hiroshi

2016-03-01

We are intensively studying the chaos via the period-doubling bifurcation cascade in radiative heat-loss-induced flame front instability by analytical methods based on dynamical systems theory and complex networks. Significant changes in flame front dynamics in the chaotic region, which cannot be seen in the bifurcation diagrams, were successfully extracted from recurrence quantification analysis and nonlinear forecasting and from the network entropy. The temporal dynamics of the fuel concentration in the well-developed chaotic region is much more complicated than that of the flame front temperature. It exhibits self-affinity as a result of the scale-free structure in the constructed visibility graph.

An Energy-Aware Trajectory Optimization Layer for sUAS

NASA Astrophysics Data System (ADS)

Silva, William A.

The focus of this work is the implementation of an energy-aware trajectory optimization algorithm that enables small unmanned aircraft systems (sUAS) to operate in unknown, dynamic severe weather environments. The software is designed as a component of an Energy-Aware Dynamic Data Driven Application System (EA-DDDAS) for sUAS. This work addresses the challenges of integrating and executing an online trajectory optimization algorithm during mission operations in the field. Using simplified aircraft kinematics, the energy-aware algorithm enables extraction of kinetic energy from measured winds to optimize thrust use and endurance during flight. The optimization layer, based upon a nonlinear program formulation, extracts energy by exploiting strong wind velocity gradients in the wind field, a process known as dynamic soaring. The trajectory optimization layer extends the energy-aware path planner developed by Wenceslao Shaw-Cortez te{Shaw-cortez2013} to include additional mission configurations, simulations with a 6-DOF model, and validation of the system with flight testing in June 2015 in Lubbock, Texas. The trajectory optimization layer interfaces with several components within the EA-DDDAS to provide an sUAS with optimal flight trajectories in real-time during severe weather. As a result, execution timing, data transfer, and scalability are considered in the design of the software. Severe weather also poses a measure of unpredictability to the system with respect to communication between systems and available data resources during mission operations. A heuristic mission tree with different cost functions and constraints is implemented to provide a level of adaptability to the optimization layer. Simulations and flight experiments are performed to assess the efficacy of the trajectory optimization layer. The results are used to assess the feasibility of flying dynamic soaring trajectories with existing controllers as well as to verify the interconnections between EA-DDDAS components. Results also demonstrate the usage of the trajectory optimization layer in conjunction with a lattice-based path planner as a method of guiding the optimization layer and stitching together subsequent trajectories.

Microwave signal processing with photorefractive dynamic holography

NASA Astrophysics Data System (ADS)

Fotheringham, Edeline B.

Have you ever found yourself listening to the music playing from the closest stereo rather than to the bromidic (uninspiring) person speaking to you? Your ears receive information from two sources but your brain listens to only one. What if your cell phone could distinguish among signals sharing the same bandwidth too? There would be no "full" channels to stop you from placing or receiving a call. This thesis presents a nonlinear optical circuit capable of distinguishing uncorrelated signals that have overlapping temporal bandwidths. This so called autotuning filter is the size of a U.S. quarter dollar and requires less than 3 mW of optical power to operate. It is basically an oscillator in which the losses are compensated with dynamic holographic gain. The combination of two photorefractive crystals in the resonator governs the filter's winner-take-all dynamics through signal-competition for gain. This physical circuit extracts what is mathematically referred to as the largest principal component of its spatio-temporal input space. The circuit's practicality is demonstrated by its incorporation in an RF-photonic system. An unknown mixture of unknown microwave signals, received by an antenna array, constitutes the input to the system. The output electronically returns one of the original microwave signals. The front-end of the system down converts the 10 GHz microwave signals and amplifies them before the signals phase modulate optical beams. The optical carrier is suppressed from these beams so that it may not be considered as a signal itself to the autotuning filter. The suppression is achieved with two-beam coupling in a single photorefractive crystal. The filter extracts the more intense of the signals present on the carrier-suppressed input beams. The detection of the extracted signal restores the microwave signal to an electronic form. The system, without the receiving antenna array, is packaged in a 13 x 18 x 6″ briefcase. Its power consumption equals that of a regular 50 W household light bulb. The system was shipped to different parts of the country for real-time demonstrations of signal separation thus also validating its claim to robustness.

Dynamic Stability Analysis of Linear Time-varying Systems via an Extended Modal Identification Approach

NASA Astrophysics Data System (ADS)

Ma, Zhisai; Liu, Li; Zhou, Sida; Naets, Frank; Heylen, Ward; Desmet, Wim

2017-03-01

The problem of linear time-varying(LTV) system modal analysis is considered based on time-dependent state space representations, as classical modal analysis of linear time-invariant systems and current LTV system modal analysis under the "frozen-time" assumption are not able to determine the dynamic stability of LTV systems. Time-dependent state space representations of LTV systems are first introduced, and the corresponding modal analysis theories are subsequently presented via a stability-preserving state transformation. The time-varying modes of LTV systems are extended in terms of uniqueness, and are further interpreted to determine the system's stability. An extended modal identification is proposed to estimate the time-varying modes, consisting of the estimation of the state transition matrix via a subspace-based method and the extraction of the time-varying modes by the QR decomposition. The proposed approach is numerically validated by three numerical cases, and is experimentally validated by a coupled moving-mass simply supported beam experimental case. The proposed approach is capable of accurately estimating the time-varying modes, and provides a new way to determine the dynamic stability of LTV systems by using the estimated time-varying modes.

Improving the quality of extracting dynamics from interspike intervals via a resampling approach

NASA Astrophysics Data System (ADS)

Pavlova, O. N.; Pavlov, A. N.

2018-04-01

We address the problem of improving the quality of characterizing chaotic dynamics based on point processes produced by different types of neuron models. Despite the presence of embedding theorems for non-uniformly sampled dynamical systems, the case of short data analysis requires additional attention because the selection of algorithmic parameters may have an essential influence on estimated measures. We consider how the preliminary processing of interspike intervals (ISIs) can increase the precision of computing the largest Lyapunov exponent (LE). We report general features of characterizing chaotic dynamics from point processes and show that independently of the selected mechanism for spike generation, the performed preprocessing reduces computation errors when dealing with a limited amount of data.

Speed Limits: Orientation and Semantic Context Interactions Constrain Natural Scene Discrimination Dynamics

ERIC Educational Resources Information Center

Rieger, Jochem W.; Kochy, Nick; Schalk, Franziska; Gruschow, Marcus; Heinze, Hans-Jochen

2008-01-01

The visual system rapidly extracts information about objects from the cluttered natural environment. In 5 experiments, the authors quantified the influence of orientation and semantics on the classification speed of objects in natural scenes, particularly with regard to object-context interactions. Natural scene photographs were presented in an…

Channel disturbances and morpho-dynamics: linking hydraulics, topographic changes and human impacts in a highly dynamic wandering river at multiple temporal scales

NASA Astrophysics Data System (ADS)

Vericat, Damià; Llena, Manel; Muñoz, Efrén; Ramos, Ester; Béjar, María; Brasington, James; Gibbins, Chris; Batalla, Ramon J.; Tena, Álvaro; Martínez-Casasnovas, José A.; Wheaton, Joe

2015-04-01

Episodic erosion, transport and deposition of sediments produce changes in river's channel morphology. These changes, although are directly related to flow hydraulics and bed material availability, supply and transport, could also be highly influenced by structural and local human impacts. Dams cut the continuity of sediment transfer and alter flood magnitude and frequency. In-channel gravel mining, however, disturbs channel beds locally, with a direct influence in upstream and downstream reaches. In this paper we present some of the preliminary results obtained in the background of MorphSed (www.morphsed.es). Morphsed is analysing the morpho-sedimentary dynamics of a mountain fluvial system located in the foothills of the Pyrenees, Iberian Peninsula. The study system is suffering major local alterations due to gravel mining. Changes on bed topography along a 12-km river reach have been analysed at two temporal scales: (i) decadal or historical and (ii) flood-based or contemporary. The study reach has suffered natural and human channel disturbances (i.e. major flood events, and gravel extractions and channel embankments, respectively). Preliminary results show how gravel mining occurred after the large flood event registered in October 1982 created a sedimentary disequilibrium in the reach. Additionally, the channel was heavily constrained associated to channel narrowing by embankments. The river has reached a new dynamic equilibrium by means of bed coarsening and channel incision, and changing from a braided to a wandering pattern. Contemporary competent flood events, however, cause severe damages in some of the embankments (i.e. lateral erosion). Gravel extractions in these sites are performed to protect these infrastructures and, in turn, are influencing local channel morpho-dynamics, increasing the sedimentary disequilibrium, exacerbating local channel incision processes, and modifying channel roughness and sediment transport dynamics. 2d hydraulic models show as these contemporary extractions influence on the magnitude and variability of hydraulic forces and, in turn, modify the conveyance of water and sediments through the study reach. All these changes have a direct influence on the ecological status of the river at different temporal and spatial scales. These links will be a key goal for progress towards the understanding of the interactions between river bed disturbance and ecological responses at multiple scales, and provide the basis for an integrated methodology that can be used to aid prediction, management and restoration of human stressed fluvial systems.

Dynamic analysis and pattern visualization of forest fires.

PubMed

Lopes, António M; Tenreiro Machado, J A

2014-01-01

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

Dynamic Analysis and Pattern Visualization of Forest Fires

PubMed Central

Lopes, António M.; Tenreiro Machado, J. A.

2014-01-01

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns. PMID:25137393

Evolutionary Dynamics of Nitrogen Fixation in the Legume–Rhizobia Symbiosis

PubMed Central

Fujita, Hironori; Aoki, Seishiro; Kawaguchi, Masayoshi

2014-01-01

The stabilization of host–symbiont mutualism against the emergence of parasitic individuals is pivotal to the evolution of cooperation. One of the most famous symbioses occurs between legumes and their colonizing rhizobia, in which rhizobia extract nutrients (or benefits) from legume plants while supplying them with nitrogen resources produced by nitrogen fixation (or costs). Natural environments, however, are widely populated by ineffective rhizobia that extract benefits without paying costs and thus proliferate more efficiently than nitrogen-fixing cooperators. How and why this mutualism becomes stabilized and evolutionarily persists has been extensively discussed. To better understand the evolutionary dynamics of this symbiosis system, we construct a simple model based on the continuous snowdrift game with multiple interacting players. We investigate the model using adaptive dynamics and numerical simulations. We find that symbiotic evolution depends on the cost–benefit balance, and that cheaters widely emerge when the cost and benefit are similar in strength. In this scenario, the persistence of the symbiotic system is compatible with the presence of cheaters. This result suggests that the symbiotic relationship is robust to the emergence of cheaters, and may explain the prevalence of cheating rhizobia in nature. In addition, various stabilizing mechanisms, such as partner fidelity feedback, partner choice, and host sanction, can reinforce the symbiotic relationship by affecting the fitness of symbionts in various ways. This result suggests that the symbiotic relationship is cooperatively stabilized by various mechanisms. In addition, mixed nodule populations are thought to encourage cheater emergence, but our model predicts that, in certain situations, cheaters can disappear from such populations. These findings provide a theoretical basis of the evolutionary dynamics of legume–rhizobia symbioses, which is extendable to other single-host, multiple-colonizer systems. PMID:24691447

Quantum Quench Dynamics

NASA Astrophysics Data System (ADS)

Mitra, Aditi

2018-03-01

Quench dynamics is an active area of study encompassing condensed matter physics and quantum information, with applications to cold-atomic gases and pump-probe spectroscopy of materials. Recent theoretical progress in studying quantum quenches is reviewed. Quenches in interacting one-dimensional systems as well as systems in higher spatial dimensions are covered. The appearance of nontrivial steady states following a quench in exactly solvable models is discussed, and the stability of these states to perturbations is described. Proper conserving approximations needed to capture the onset of thermalization at long times are outlined. The appearance of universal scaling for quenches near critical points and the role of the renormalization group in capturing the transient regime are reviewed. Finally, the effect of quenches near critical points on the dynamics of entanglement entropy and entanglement statistics is discussed. The extraction of critical exponents from the entanglement statistics is outlined.

Experimental Modal Analysis and Dynaic Strain Fiber Bragg Gratings for Structural Health Monitoring of Composite Aerospace Structures

NASA Astrophysics Data System (ADS)

Panopoulou, A.; Fransen, S.; Gomez Molinero, V.; Kostopoulos, V.

2012-07-01

The objective of this work is to develop a new structural health monitoring system for composite aerospace structures based on dynamic response strain measurements and experimental modal analysis techniques. Fibre Bragg Grating (FBG) optical sensors were used for monitoring the dynamic response of the composite structure. The structural dynamic behaviour has been numerically simulated and experimentally verified by means of vibration testing. The hypothesis of all vibration tests was that actual damage in composites reduces their stiffness and produces the same result as mass increase produces. Thus, damage was simulated by slightly varying locally the mass of the structure at different zones. Experimental modal analysis based on the strain responses was conducted and the extracted strain mode shapes were the input for the damage detection expert system. A feed-forward back propagation neural network was the core of the damage detection system. The features-input to the neural network consisted of the strain mode shapes, extracted from the experimental modal analysis. Dedicated training and validation activities were carried out based on the experimental results. The system showed high reliability, confirmed by the ability of the neural network to recognize the size and the position of damage on the structure. The experiments were performed on a real structure i.e. a lightweight antenna sub- reflector, manufactured and tested at EADS CASA ESPACIO. An integrated FBG sensor network, based on the advantage of multiplexing, was mounted on the structure with optimum topology. Numerical simulation of both structures was used as a support tool at all the steps of the work. Potential applications for the proposed system are during ground qualification extensive tests of space structures and during the mission as modal analysis tool on board, being able via the FBG responses to identify a potential failure.

Development of emergent processing loops as a system of systems concept

NASA Astrophysics Data System (ADS)

Gainey, James C., Jr.; Blasch, Erik P.

1999-03-01

This paper describes an engineering approach toward implementing the current neuroscientific understanding of how the primate brain fuses, or integrates, 'information' in the decision-making process. We describe a System of Systems (SoS) design for improving the overall performance, capabilities, operational robustness, and user confidence in Identification (ID) systems and show how it could be applied to biometrics security. We use the Physio-associative temporal sensor integration algorithm (PATSIA) which is motivated by observed functions and interactions of the thalamus, hippocampus, and cortical structures in the brain. PATSIA utilizes signal theory mathematics to model how the human efficiently perceives and uses information from the environment. The hybrid architecture implements a possible SoS-level description of the Joint Directors of US Laboratories for Fusion Working Group's functional description involving 5 levels of fusion and their associated definitions. This SoS architecture propose dynamic sensor and knowledge-source integration by implementing multiple Emergent Processing Loops for predicting, feature extracting, matching, and Searching both static and dynamic database like MSTAR's PEMS loops. Biologically, this effort demonstrates these objectives by modeling similar processes from the eyes, ears, and somatosensory channels, through the thalamus, and to the cortices as appropriate while using the hippocampus for short-term memory search and storage as necessary. The particular approach demonstrated incorporates commercially available speaker verification and face recognition software and hardware to collect data and extract features to the PATSIA. The PATSIA maximizes the confidence levels for target identification or verification in dynamic situations using a belief filter. The proof of concept described here is easily adaptable and scaleable to other military and nonmilitary sensor fusion applications.

Combined non-parametric and parametric approach for identification of time-variant systems

NASA Astrophysics Data System (ADS)

Dziedziech, Kajetan; Czop, Piotr; Staszewski, Wieslaw J.; Uhl, Tadeusz

2018-03-01

Identification of systems, structures and machines with variable physical parameters is a challenging task especially when time-varying vibration modes are involved. The paper proposes a new combined, two-step - i.e. non-parametric and parametric - modelling approach in order to determine time-varying vibration modes based on input-output measurements. Single-degree-of-freedom (SDOF) vibration modes from multi-degree-of-freedom (MDOF) non-parametric system representation are extracted in the first step with the use of time-frequency wavelet-based filters. The second step involves time-varying parametric representation of extracted modes with the use of recursive linear autoregressive-moving-average with exogenous inputs (ARMAX) models. The combined approach is demonstrated using system identification analysis based on the experimental mass-varying MDOF frame-like structure subjected to random excitation. The results show that the proposed combined method correctly captures the dynamics of the analysed structure, using minimum a priori information on the model.

A Human Activity Recognition System Based on Dynamic Clustering of Skeleton Data.

PubMed

Manzi, Alessandro; Dario, Paolo; Cavallo, Filippo

2017-05-11

Human activity recognition is an important area in computer vision, with its wide range of applications including ambient assisted living. In this paper, an activity recognition system based on skeleton data extracted from a depth camera is presented. The system makes use of machine learning techniques to classify the actions that are described with a set of a few basic postures. The training phase creates several models related to the number of clustered postures by means of a multiclass Support Vector Machine (SVM), trained with Sequential Minimal Optimization (SMO). The classification phase adopts the X-means algorithm to find the optimal number of clusters dynamically. The contribution of the paper is twofold. The first aim is to perform activity recognition employing features based on a small number of informative postures, extracted independently from each activity instance; secondly, it aims to assess the minimum number of frames needed for an adequate classification. The system is evaluated on two publicly available datasets, the Cornell Activity Dataset (CAD-60) and the Telecommunication Systems Team (TST) Fall detection dataset. The number of clusters needed to model each instance ranges from two to four elements. The proposed approach reaches excellent performances using only about 4 s of input data (~100 frames) and outperforms the state of the art when it uses approximately 500 frames on the CAD-60 dataset. The results are promising for the test in real context.

A perspective on bridging scales and design of models using low-dimensional manifolds and data-driven model inference

PubMed Central

Zenil, Hector; Kiani, Narsis A.; Ball, Gordon; Gomez-Cabrero, David

2016-01-01

Systems in nature capable of collective behaviour are nonlinear, operating across several scales. Yet our ability to account for their collective dynamics differs in physics, chemistry and biology. Here, we briefly review the similarities and differences between mathematical modelling of adaptive living systems versus physico-chemical systems. We find that physics-based chemistry modelling and computational neuroscience have a shared interest in developing techniques for model reductions aiming at the identification of a reduced subsystem or slow manifold, capturing the effective dynamics. By contrast, as relations and kinetics between biological molecules are less characterized, current quantitative analysis under the umbrella of bioinformatics focuses on signal extraction, correlation, regression and machine-learning analysis. We argue that model reduction analysis and the ensuing identification of manifolds bridges physics and biology. Furthermore, modelling living systems presents deep challenges as how to reconcile rich molecular data with inherent modelling uncertainties (formalism, variables selection and model parameters). We anticipate a new generative data-driven modelling paradigm constrained by identified governing principles extracted from low-dimensional manifold analysis. The rise of a new generation of models will ultimately connect biology to quantitative mechanistic descriptions, thereby setting the stage for investigating the character of the model language and principles driving living systems. This article is part of the themed issue ‘Multiscale modelling at the physics–chemistry–biology interface’. PMID:27698038

Systems microscopy: an emerging strategy for the life sciences.

PubMed

Lock, John G; Strömblad, Staffan

2010-05-01

Dynamic cellular processes occurring in time and space are fundamental to all physiology and disease. To understand complex and dynamic cellular processes therefore demands the capacity to record and integrate quantitative multiparametric data from the four spatiotemporal dimensions within which living cells self-organize, and to subsequently use these data for the mathematical modeling of cellular systems. To this end, a raft of complementary developments in automated fluorescence microscopy, cell microarray platforms, quantitative image analysis and data mining, combined with multivariate statistics and computational modeling, now coalesce to produce a new research strategy, "systems microscopy", which facilitates systems biology analyses of living cells. Systems microscopy provides the crucial capacities to simultaneously extract and interrogate multiparametric quantitative data at resolution levels ranging from the molecular to the cellular, thereby elucidating a more comprehensive and richly integrated understanding of complex and dynamic cellular systems. The unique capacities of systems microscopy suggest that it will become a vital cornerstone of systems biology, and here we describe the current status and future prospects of this emerging field, as well as outlining some of the key challenges that remain to be overcome. Copyright 2010 Elsevier Inc. All rights reserved.

A green deep eutectic solvent-based aqueous two-phase system for protein extracting.

PubMed

Xu, Kaijia; Wang, Yuzhi; Huang, Yanhua; Li, Na; Wen, Qian

2015-03-15

As a new type of green solvent, deep eutectic solvent (DES) has been applied for the extraction of proteins with an aqueous two-phase system (ATPS) in this work. Four kinds of choline chloride (ChCl)-based DESs were synthesized to extract bovine serum albumin (BSA), and ChCl-glycerol was selected as the suitable extraction solvent. Single factor experiments have been done to investigate the effects of the extraction process, including the amount of DES, the concentration of salt, the mass of protein, the shaking time, the temperature and PH value. Experimental results show 98.16% of the BSA could be extracted into the DES-rich phase in a single-step extraction under the optimized conditions. A high extraction efficiency of 94.36% was achieved, while the conditions were applied to the extraction of trypsin (Try). Precision, repeatability and stability experiments were studied and the relative standard deviations (RSD) of the extraction efficiency were 0.4246% (n=3), 1.6057% (n=3) and 1.6132% (n=3), respectively. Conformation of BSA was not changed during the extraction process according to the investigation of UV-vis spectra, FT-IR spectra and CD spectra of BSA. The conductivity, dynamic light scattering (DLS) and transmission electron microscopy (TEM) were used to explore the mechanism of the extraction. It turned out that the formation of DES-protein aggregates play a significant role in the separation process. All the results suggest that ChCl-based DES-ATPS are supposed to have the potential to provide new possibilities in the separation of proteins. Copyright © 2015 Elsevier B.V. All rights reserved.

Principal component analysis of dynamic fluorescence images for diagnosis of diabetic vasculopathy

NASA Astrophysics Data System (ADS)

Seo, Jihye; An, Yuri; Lee, Jungsul; Ku, Taeyun; Kang, Yujung; Ahn, Chulwoo; Choi, Chulhee

2016-04-01

Indocyanine green (ICG) fluorescence imaging has been clinically used for noninvasive visualizations of vascular structures. We have previously developed a diagnostic system based on dynamic ICG fluorescence imaging for sensitive detection of vascular disorders. However, because high-dimensional raw data were used, the analysis of the ICG dynamics proved difficult. We used principal component analysis (PCA) in this study to extract important elements without significant loss of information. We examined ICG spatiotemporal profiles and identified critical features related to vascular disorders. PCA time courses of the first three components showed a distinct pattern in diabetic patients. Among the major components, the second principal component (PC2) represented arterial-like features. The explained variance of PC2 in diabetic patients was significantly lower than in normal controls. To visualize the spatial pattern of PCs, pixels were mapped with red, green, and blue channels. The PC2 score showed an inverse pattern between normal controls and diabetic patients. We propose that PC2 can be used as a representative bioimaging marker for the screening of vascular diseases. It may also be useful in simple extractions of arterial-like features.

Fusion of spectral models for dynamic modeling of sEMG and skeletal muscle force.

PubMed

Potluri, Chandrasekhar; Anugolu, Madhavi; Chiu, Steve; Urfer, Alex; Schoen, Marco P; Naidu, D Subbaram

2012-01-01

In this paper, we present a method of combining spectral models using a Kullback Information Criterion (KIC) data fusion algorithm. Surface Electromyographic (sEMG) signals and their corresponding skeletal muscle force signals are acquired from three sensors and pre-processed using a Half-Gaussian filter and a Chebyshev Type- II filter, respectively. Spectral models - Spectral Analysis (SPA), Empirical Transfer Function Estimate (ETFE), Spectral Analysis with Frequency Dependent Resolution (SPFRD) - are extracted from sEMG signals as input and skeletal muscle force as output signal. These signals are then employed in a System Identification (SI) routine to establish the dynamic models relating the input and output. After the individual models are extracted, the models are fused by a probability based KIC fusion algorithm. The results show that the SPFRD spectral models perform better than SPA and ETFE models in modeling the frequency content of the sEMG/skeletal muscle force data.

Phase-sensitive atomic dynamics in quantum light

NASA Astrophysics Data System (ADS)

Balybin, S. N.; Zakharov, R. V.; Tikhonova, O. V.

2018-05-01

Interaction between a quantum electromagnetic field and a model Ry atom with possible transitions to the continuum and to the low-lying resonant state is investigated. Strong sensitivity of atomic dynamics to the phase of applied coherent and squeezed vacuum light is found. Methods to extract the quantum field phase performing the measurements on the atomic system are proposed. In the case of the few-photon coherent state high accuracy of the phase determination is demonstrated, which appears to be much higher in comparison to the usually used quantum-optical methods such as homodyne detection.

Development of an image analysis screen for estrogen receptor alpha (ERα) ligands through measurement of nuclear translocation dynamics.

PubMed

Dull, Angie; Goncharova, Ekaterina; Hager, Gordon; McMahon, James B

2010-11-01

We have developed a robust high-content assay to screen for novel estrogen receptor alpha (ERα) agonists and antagonists by quantitation of cytoplasmic to nuclear translocation of an estrogen receptor chimera in 384-well plates. The screen utilizes a green fluorescent protein tagged-glucocorticoid/estrogen receptor (GFP-GRER) chimera which consisted of the N-terminus of the glucocorticoid receptor fused to the human ER ligand binding domain. The GFP-GRER exhibited cytoplasmic localization in the absence of ERα ligands, and translocated to the nucleus in response to stimulation with ERα agonists or antagonists. The BD Pathway 435 imaging system was used for image acquisition, analysis of translocation dynamics, and cytotoxicity measurements. The assay was validated with known ERα agonists and antagonists, and the Library of Pharmacologically Active Compounds (LOPAC 1280). Additionally, screening of crude natural product extracts demonstrated the robustness of the assay, and the ability to quantitate the effects of toxicity on nuclear translocation dynamics. The GFP-GRER nuclear translocation assay was very robust, with z' values >0.7, CVs <5%, and has been validated with known ER ligands, and inclusion of cytotoxicity filters will facilitate screening of natural product extracts. This assay has been developed for future primary screening of synthetic, pure natural products, and natural product extracts libraries available at the National Cancer Institute at Frederick. Copyright © 2010 Elsevier Ltd. All rights reserved.

Adaptive simplification of complex multiscale systems.

PubMed

Chiavazzo, Eliodoro; Karlin, Ilya

2011-03-01

A fully adaptive methodology is developed for reducing the complexity of large dissipative systems. This represents a significant step toward extracting essential physical knowledge from complex systems, by addressing the challenging problem of a minimal number of variables needed to exactly capture the system dynamics. Accurate reduced description is achieved, by construction of a hierarchy of slow invariant manifolds, with an embarrassingly simple implementation in any dimension. The method is validated with the autoignition of the hydrogen-air mixture where a reduction to a cascade of slow invariant manifolds is observed.

Mechatronics by Analogy and Application to Legged Locomotion

NASA Astrophysics Data System (ADS)

Ragusila, Victor

A new design methodology for mechatronic systems, dubbed as Mechatronics by Analogy (MbA), is introduced and applied to designing a leg mechanism. The new methodology argues that by establishing a similarity relation between a complex system and a number of simpler models it is possible to design the former using the analysis and synthesis means developed for the latter. The methodology provides a framework for concurrent engineering of complex systems while maintaining the transparency of the system behaviour through making formal analogies between the system and those with more tractable dynamics. The application of the MbA methodology to the design of a monopod robot leg, called the Linkage Leg, is also studied. A series of simulations show that the dynamic behaviour of the Linkage Leg is similar to that of a combination of a double pendulum and a spring-loaded inverted pendulum, based on which the system kinematic, dynamic, and control parameters can be designed concurrently. The first stage of Mechatronics by Analogy is a method of extracting significant features of system dynamics through simpler models. The goal is to determine a set of simpler mechanisms with similar dynamic behaviour to that of the original system in various phases of its motion. A modular bond-graph representation of the system is determined, and subsequently simplified using two simplification algorithms. The first algorithm determines the relevant dynamic elements of the system for each phase of motion, and the second algorithm finds the simple mechanism described by the remaining dynamic elements. In addition to greatly simplifying the controller for the system, using simpler mechanisms with similar behaviour provides a greater insight into the dynamics of the system. This is seen in the second stage of the new methodology, which concurrently optimizes the simpler mechanisms together with a control system based on their dynamics. Once the optimal configuration of the simpler system is determined, the original mechanism is optimized such that its dynamic behaviour is analogous. It is shown that, if this analogy is achieved, the control system designed based on the simpler mechanisms can be directly implemented to the more complex system, and their dynamic behaviours are close enough for the system performance to be effectively the same. Finally it is shown that, for the employed objective of fast legged locomotion, the proposed methodology achieves a better design than Reduction-by-Feedback, a competing methodology that uses control layers to simplify the dynamics of the system.

Characterization and classification of patients with different levels of cardiac death risk by using Poincaré plot analysis.

PubMed

Rodriguez, Javier; Voss, Andreas; Caminal, Pere; Bayes-Genis, Antoni; Giraldo, Beatriz F

2017-07-01

Cardiac death risk is still a big problem by an important part of the population, especially in elderly patients. In this study, we propose to characterize and analyze the cardiovascular and cardiorespiratory systems using the Poincaré plot. A total of 46 cardiomyopathy patients and 36 healthy subjets were analyzed. Left ventricular ejection fraction (LVEF) was used to stratify patients with low risk (LR: LVEF > 35%, 16 patients), and high risk (HR: LVEF ≤ 35%, 30 patients) of heart attack. RR, SBP and T Tot time series were extracted from the ECG, blood pressure and respiratory flow signals, respectively. Parameters that describe the scatterplott of Poincaré method, related to short- and long-term variabilities, acceleration and deceleration of the dynamic system, and the complex correlation index were extracted. The linear discriminant analysis (LDA) and the support vector machines (SVM) classification methods were used to analyze the results of the extracted parameters. The results showed that cardiac parameters were the best to discriminate between HR and LR groups, especially the complex correlation index (p = 0.009). Analising the interaction, the best result was obtained with the relation between the difference of the standard deviation of the cardiac and respiratory system (p = 0.003). When comparing HR vs LR groups, the best classification was obtained applying SVM method, using an ANOVA kernel, with an accuracy of 98.12%. An accuracy of 97.01% was obtained by comparing patients versus healthy, with a SVM classifier and Laplacian kernel. The morphology of Poincaré plot introduces parameters that allow the characterization of the cardiorespiratory system dynamics.

Synergistic effect of dicarbollide anions in liquid-liquid extraction: a molecular dynamics study at the octanol-water interface.

PubMed

Chevrot, G; Schurhammer, R; Wipff, G

2007-04-28

We report a molecular dynamics study of chlorinated cobalt bis(dicarbollide) anions [(B(9)C(2)H(8)Cl(3))(2)Co](-)"CCD(-)" in octanol and at the octanol-water interface, with the main aim to understand why these hydrophobic species act as strong synergists in assisted liquid-liquid cation extraction. Neat octanol is quite heterogeneous and is found to display dual solvation properties, allowing to well solubilize CCD(-), Cs(+) salts in the form of diluted pairs or oligomers, without displaying aggregation. At the aqueous interface, octanol behaves as an amphiphile, forming either monolayers or bilayers, depending on the initial state and confinement conditions. In biphasic octanol-water systems, CCD(-) anions are found to mainly partition to the organic phase, thus attracting Cs(+) or even more hydrophilic counterions like Eu(3+) into that phase. The remaining CCD(-) anions adsorb at the interface, but are less surface active than at the chloroform interface. Finally, we compare the interfacial behavior of the Eu(BTP)(3)(3+) complex in the absence and in the presence of CCD(-) anions and extractant molecules. It is found that when the CCD(-)'s are concentrated enough, the complex is extracted to the octanol phase. Otherwise, it is trapped at the interface, attracted by water. These results are compared to those obtained with chloroform as organic phase and discussed in the context of synergistic effect of CCD(-) in liquid-liquid extraction, pointing to the importance of dual solvation properties of octanol and of the hydrophobic character of CCD(-) for synergistic extraction of cations.

Design of distributed systems of hydrolithosphere processes management. A synthesis of distributed management systems

NASA Astrophysics Data System (ADS)

Pershin, I. M.; Pervukhin, D. A.; Ilyushin, Y. V.; Afanaseva, O. V.

2017-10-01

The paper considers an important problem of designing distributed systems of hydrolithosphere processes management. The control actions on the hydrolithosphere processes under consideration are implemented by a set of extractive wells. The article shows the method of defining the approximation links for description of the dynamic characteristics of hydrolithosphere processes. The structure of distributed regulators, used in the management systems by the considered processes, is presented. The paper analyses the results of the synthesis of the distributed management system and the results of modelling the closed-loop control system by the parameters of the hydrolithosphere process.

Tunable nonequilibrium dynamics of field quenches in spin ice

PubMed Central

Mostame, Sarah; Castelnovo, Claudio; Moessner, Roderich; Sondhi, Shivaji L.

2014-01-01

We present nonequilibrium physics in spin ice as a unique setting that combines kinematic constraints, emergent topological defects, and magnetic long-range Coulomb interactions. In spin ice, magnetic frustration leads to highly degenerate yet locally constrained ground states. Together, they form a highly unusual magnetic state—a “Coulomb phase”—whose excitations are point-like defects—magnetic monopoles—in the absence of which effectively no dynamics is possible. Hence, when they are sparse at low temperature, dynamics becomes very sluggish. When quenching the system from a monopole-rich to a monopole-poor state, a wealth of dynamical phenomena occur, the exposition of which is the subject of this article. Most notably, we find reaction diffusion behavior, slow dynamics owing to kinematic constraints, as well as a regime corresponding to the deposition of interacting dimers on a honeycomb lattice. We also identify potential avenues for detecting the magnetic monopoles in a regime of slow-moving monopoles. The interest in this model system is further enhanced by its large degree of tunability and the ease of probing it in experiment: With varying magnetic fields at different temperatures, geometric properties—including even the effective dimensionality of the system—can be varied. By monitoring magnetization, spin correlations or zero-field NMR, the dynamical properties of the system can be extracted in considerable detail. This establishes spin ice as a laboratory of choice for the study of tunable, slow dynamics. PMID:24379372

Thermally induced magnetic relaxation in square artificial spin ice

DOE PAGES

Andersson, M. S.; Pappas, S. D.; Stopfel, H.; ...

2016-11-24

The properties of natural and artificial assemblies of interacting elements, ranging from Quarks to Galaxies, are at the heart of Physics. The collective response and dynamics of such assemblies are dictated by the intrinsic dynamical properties of the building blocks, the nature of their interactions and topological constraints. Here in this paper, we report on the relaxation dynamics of the magnetization of artificial assemblies of mesoscopic spins. In our model nano-magnetic system $-$ square artificial spin ice $-$ we are able to control the geometrical arrangement and interaction strength between the magnetically interacting building blocks by means of nano-lithography. Usingmore » time resolved magnetometry we show that the relaxation process can be described using the Kohlrausch law and that the extracted temperature dependent relaxation times of the assemblies follow the Vogel-Fulcher law. The results provide insight into the relaxation dynamics of mesoscopic nano-magnetic model systems, with adjustable energy and time scales, and demonstrates that these can serve as an ideal playground for the studies of collective dynamics and relaxations.« less

Thermally induced magnetic relaxation in square artificial spin ice

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

Andersson, M. S.; Pappas, S. D.; Stopfel, H.

The properties of natural and artificial assemblies of interacting elements, ranging from Quarks to Galaxies, are at the heart of Physics. The collective response and dynamics of such assemblies are dictated by the intrinsic dynamical properties of the building blocks, the nature of their interactions and topological constraints. Here in this paper, we report on the relaxation dynamics of the magnetization of artificial assemblies of mesoscopic spins. In our model nano-magnetic system $-$ square artificial spin ice $-$ we are able to control the geometrical arrangement and interaction strength between the magnetically interacting building blocks by means of nano-lithography. Usingmore » time resolved magnetometry we show that the relaxation process can be described using the Kohlrausch law and that the extracted temperature dependent relaxation times of the assemblies follow the Vogel-Fulcher law. The results provide insight into the relaxation dynamics of mesoscopic nano-magnetic model systems, with adjustable energy and time scales, and demonstrates that these can serve as an ideal playground for the studies of collective dynamics and relaxations.« less

A model of gene expression based on random dynamical systems reveals modularity properties of gene regulatory networks.

PubMed

Antoneli, Fernando; Ferreira, Renata C; Briones, Marcelo R S

2016-06-01

Here we propose a new approach to modeling gene expression based on the theory of random dynamical systems (RDS) that provides a general coupling prescription between the nodes of any given regulatory network given the dynamics of each node is modeled by a RDS. The main virtues of this approach are the following: (i) it provides a natural way to obtain arbitrarily large networks by coupling together simple basic pieces, thus revealing the modularity of regulatory networks; (ii) the assumptions about the stochastic processes used in the modeling are fairly general, in the sense that the only requirement is stationarity; (iii) there is a well developed mathematical theory, which is a blend of smooth dynamical systems theory, ergodic theory and stochastic analysis that allows one to extract relevant dynamical and statistical information without solving the system; (iv) one may obtain the classical rate equations form the corresponding stochastic version by averaging the dynamic random variables (small noise limit). It is important to emphasize that unlike the deterministic case, where coupling two equations is a trivial matter, coupling two RDS is non-trivial, specially in our case, where the coupling is performed between a state variable of one gene and the switching stochastic process of another gene and, hence, it is not a priori true that the resulting coupled system will satisfy the definition of a random dynamical system. We shall provide the necessary arguments that ensure that our coupling prescription does indeed furnish a coupled regulatory network of random dynamical systems. Finally, the fact that classical rate equations are the small noise limit of our stochastic model ensures that any validation or prediction made on the basis of the classical theory is also a validation or prediction of our model. We illustrate our framework with some simple examples of single-gene system and network motifs. Copyright © 2016 Elsevier Inc. All rights reserved.

Experiment design for pilot identification in compensatory tracking tasks

NASA Technical Reports Server (NTRS)

Wells, W. R.

1976-01-01

A design criterion for input functions in laboratory tracking tasks resulting in efficient parameter estimation is formulated. The criterion is that the statistical correlations between pairs of parameters be reduced in order to minimize the problem of nonuniqueness in the extraction process. The effectiveness of the method is demonstrated for a lower order dynamic system.

Thermal analysis elements of liquefied gas storage tanks

NASA Astrophysics Data System (ADS)

Yanvarev, I. A.; Krupnikov, A. V.

2017-08-01

Tasks of solving energy and resource efficient usage problems, both for oil producing companies and for companies extracting and transporting natural gas, are associated with liquefied petroleum gas technology development. Improving the operation efficiency of liquefied products storages provides for conducting structural, functional, and appropriate thermal analysis of tank parks in the general case as complex dynamic thermal systems.

Interaction of spatially separated oscillating solitons in biased two-photon photorefractive materials

NASA Astrophysics Data System (ADS)

Asif, Noushin; Biswas, Anjan; Jovanoski, Z.; Konar, S.

2015-01-01

This paper presents the dynamics of two spatially separated optical solitons in two-photon photorefractive materials. The variational formalism has been employed to derive evolution equations of different parameters which characterize the dynamics of two interacting solitons. This approach yields a system of coupled ordinary differential equations for evolution of different parameters characterizing solitons such as amplitude, spatial width, chirp, center of gravity, etc., which have been subsequently solved adopting numerical method to extract information on their dynamics. Depending on their initial separation and power, solitons are shown to either disperse or compresses individually and attract each other. Dragging and trapping of a probe soliton by another pump have been discussed.

Extracting full-field dynamic strain on a wind turbine rotor subjected to arbitrary excitations using 3D point tracking and a modal expansion technique

NASA Astrophysics Data System (ADS)

Baqersad, Javad; Niezrecki, Christopher; Avitabile, Peter

2015-09-01

Health monitoring of rotating structures such as wind turbines and helicopter rotors is generally performed using conventional sensors that provide a limited set of data at discrete locations near or on the hub. These sensors usually provide no data on the blades or inside them where failures might occur. Within this paper, an approach was used to extract the full-field dynamic strain on a wind turbine assembly subject to arbitrary loading conditions. A three-bladed wind turbine having 2.3-m long blades was placed in a semi-built-in boundary condition using a hub, a machining chuck, and a steel block. For three different test cases, the turbine was excited using (1) pluck testing, (2) random impacts on blades with three impact hammers, and (3) random excitation by a mechanical shaker. The response of the structure to the excitations was measured using three-dimensional point tracking. A pair of high-speed cameras was used to measure displacement of optical targets on the structure when the blades were vibrating. The measured displacements at discrete locations were expanded and applied to the finite element model of the structure to extract the full-field dynamic strain. The results of the paper show an excellent correlation between the strain predicted using the proposed approach and the strain measured with strain-gages for each of the three loading conditions. The approach used in this paper to predict the strain showed higher accuracy than the digital image correlation technique. The new expansion approach is able to extract dynamic strain all over the entire structure, even inside the structure beyond the line of sight of the measurement system. Because the method is based on a non-contacting measurement approach, it can be readily applied to a variety of structures having different boundary and operating conditions, including rotating blades.

Integrating semantic information into multiple kernels for protein-protein interaction extraction from biomedical literatures.

PubMed

Li, Lishuang; Zhang, Panpan; Zheng, Tianfu; Zhang, Hongying; Jiang, Zhenchao; Huang, Degen

2014-01-01

Protein-Protein Interaction (PPI) extraction is an important task in the biomedical information extraction. Presently, many machine learning methods for PPI extraction have achieved promising results. However, the performance is still not satisfactory. One reason is that the semantic resources were basically ignored. In this paper, we propose a multiple-kernel learning-based approach to extract PPIs, combining the feature-based kernel, tree kernel and semantic kernel. Particularly, we extend the shortest path-enclosed tree kernel (SPT) by a dynamic extended strategy to retrieve the richer syntactic information. Our semantic kernel calculates the protein-protein pair similarity and the context similarity based on two semantic resources: WordNet and Medical Subject Heading (MeSH). We evaluate our method with Support Vector Machine (SVM) and achieve an F-score of 69.40% and an AUC of 92.00%, which show that our method outperforms most of the state-of-the-art systems by integrating semantic information.

Topological structure dynamics revealing collective evolution in active nematics

PubMed Central

Shi, Xia-qing; Ma, Yu-qiang

2013-01-01

Topological defects frequently emerge in active matter like bacterial colonies, cytoskeleton extracts on substrates, self-propelled granular or colloidal layers and so on, but their dynamical properties and the relations to large-scale organization and fluctuations in these active systems are seldom touched. Here we reveal, through a simple model for active nematics using self-driven hard elliptic rods, that the excitation, annihilation and transportation of topological defects differ markedly from those in non-active media. These dynamical processes exhibit strong irreversibility in active nematics in the absence of detailed balance. Moreover, topological defects are the key factors in organizing large-scale dynamic structures and collective flows, resulting in multi-spatial temporal effects. These findings allow us to control the self-organization of active matter through topological structures. PMID:24346733

Leveraging Ensemble Dynamical Properties to Prioritize Exoplanet Follow-Up Observations

NASA Astrophysics Data System (ADS)

Ballard, Sarah

2017-01-01

The number of transiting exoplanets now exceeds several thousand, enabling ensemble studies of the dynamical properties of exoplanetary systems. We require a mixture model of dynamical conditions (whether frozen in from formation or sculpted by planet-planet interactions) to recover Kepler's yield of transiting planets. Around M dwarfs, which will be predominate sites of exoplanet follow-up atmospheric study in the next decade, even a modest orbital eccentricity can sterilize a planet. I will describe efforts to link cheap observables, such as number of transiting planets and presence of transit timing variations, to eccentricity and mutual inclination in exoplanet systems. The addition of a second transiting planet, for example, halves the expected orbital eccentricity. For the vast majority of TESS targets, the light curve alone will furnish the sum total of data about the exoplanet. Extracting information about orbital properties from these light curves will help prioritize precious follow-up resources.

Automated reverse engineering of nonlinear dynamical systems

PubMed Central

Bongard, Josh; Lipson, Hod

2007-01-01

Complex nonlinear dynamics arise in many fields of science and engineering, but uncovering the underlying differential equations directly from observations poses a challenging task. The ability to symbolically model complex networked systems is key to understanding them, an open problem in many disciplines. Here we introduce for the first time a method that can automatically generate symbolic equations for a nonlinear coupled dynamical system directly from time series data. This method is applicable to any system that can be described using sets of ordinary nonlinear differential equations, and assumes that the (possibly noisy) time series of all variables are observable. Previous automated symbolic modeling approaches of coupled physical systems produced linear models or required a nonlinear model to be provided manually. The advance presented here is made possible by allowing the method to model each (possibly coupled) variable separately, intelligently perturbing and destabilizing the system to extract its less observable characteristics, and automatically simplifying the equations during modeling. We demonstrate this method on four simulated and two real systems spanning mechanics, ecology, and systems biology. Unlike numerical models, symbolic models have explanatory value, suggesting that automated “reverse engineering” approaches for model-free symbolic nonlinear system identification may play an increasing role in our ability to understand progressively more complex systems in the future. PMID:17553966

Automated reverse engineering of nonlinear dynamical systems.

PubMed

Bongard, Josh; Lipson, Hod

2007-06-12

Complex nonlinear dynamics arise in many fields of science and engineering, but uncovering the underlying differential equations directly from observations poses a challenging task. The ability to symbolically model complex networked systems is key to understanding them, an open problem in many disciplines. Here we introduce for the first time a method that can automatically generate symbolic equations for a nonlinear coupled dynamical system directly from time series data. This method is applicable to any system that can be described using sets of ordinary nonlinear differential equations, and assumes that the (possibly noisy) time series of all variables are observable. Previous automated symbolic modeling approaches of coupled physical systems produced linear models or required a nonlinear model to be provided manually. The advance presented here is made possible by allowing the method to model each (possibly coupled) variable separately, intelligently perturbing and destabilizing the system to extract its less observable characteristics, and automatically simplifying the equations during modeling. We demonstrate this method on four simulated and two real systems spanning mechanics, ecology, and systems biology. Unlike numerical models, symbolic models have explanatory value, suggesting that automated "reverse engineering" approaches for model-free symbolic nonlinear system identification may play an increasing role in our ability to understand progressively more complex systems in the future.

Dynamic displacement measurement of large-scale structures based on the Lucas-Kanade template tracking algorithm

NASA Astrophysics Data System (ADS)

Guo, Jie; Zhu, Chang`an

2016-01-01

The development of optics and computer technologies enables the application of the vision-based technique that uses digital cameras to the displacement measurement of large-scale structures. Compared with traditional contact measurements, vision-based technique allows for remote measurement, has a non-intrusive characteristic, and does not necessitate mass introduction. In this study, a high-speed camera system is developed to complete the displacement measurement in real time. The system consists of a high-speed camera and a notebook computer. The high-speed camera can capture images at a speed of hundreds of frames per second. To process the captured images in computer, the Lucas-Kanade template tracking algorithm in the field of computer vision is introduced. Additionally, a modified inverse compositional algorithm is proposed to reduce the computing time of the original algorithm and improve the efficiency further. The modified algorithm can rapidly accomplish one displacement extraction within 1 ms without having to install any pre-designed target panel onto the structures in advance. The accuracy and the efficiency of the system in the remote measurement of dynamic displacement are demonstrated in the experiments on motion platform and sound barrier on suspension viaduct. Experimental results show that the proposed algorithm can extract accurate displacement signal and accomplish the vibration measurement of large-scale structures.

Dynamic RSA: Examining parasympathetic regulatory dynamics via vector-autoregressive modeling of time-varying RSA and heart period.

PubMed

Fisher, Aaron J; Reeves, Jonathan W; Chi, Cyrus

2016-07-01

Expanding on recently published methods, the current study presents an approach to estimating the dynamic, regulatory effect of the parasympathetic nervous system on heart period on a moment-to-moment basis. We estimated second-to-second variation in respiratory sinus arrhythmia (RSA) in order to estimate the contemporaneous and time-lagged relationships among RSA, interbeat interval (IBI), and respiration rate via vector autoregression. Moreover, we modeled these relationships at lags of 1 s to 10 s, in order to evaluate the optimal latency for estimating dynamic RSA effects. The IBI (t) on RSA (t-n) regression parameter was extracted from individual models as an operationalization of the regulatory effect of RSA on IBI-referred to as dynamic RSA (dRSA). Dynamic RSA positively correlated with standard averages of heart rate and negatively correlated with standard averages of RSA. We propose that dRSA reflects the active downregulation of heart period by the parasympathetic nervous system and thus represents a novel metric that provides incremental validity in the measurement of autonomic cardiac control-specifically, a method by which parasympathetic regulatory effects can be measured in process. © 2016 Society for Psychophysiological Research.

Probing nanocrystalline grain dynamics in nanodevices

PubMed Central

Yeh, Sheng-Shiuan; Chang, Wen-Yao; Lin, Juhn-Jong

2017-01-01

Dynamical structural defects exist naturally in a wide variety of solids. They fluctuate temporally and hence can deteriorate the performance of many electronic devices. Thus far, the entities of these dynamic objects have been identified to be individual atoms. On the other hand, it is a long-standing question whether a nanocrystalline grain constituted of a large number of atoms can switch, as a whole, reversibly like a dynamical atomic defect (that is, a two-level system). This is an emergent issue considering the current development of nanodevices with ultralow electrical noise, qubits with long quantum coherence time, and nanoelectromechanical system sensors with ultrahigh resolution. We demonstrate experimental observations of dynamic nanocrystalline grains that repeatedly switch between two or more metastable coordinate states. We study temporal resistance fluctuations in thin ruthenium dioxide (RuO2) metal nanowires and extract microscopic parameters, including relaxation time scales, mobile grain sizes, and the bonding strengths of nanograin boundaries. These material parameters are not obtainable by other experimental approaches. When combined with previous in situ high-resolution transmission electron microscopy, our electrical method can be used to infer rich information about the structural dynamics of a wide variety of nanodevices and new two-dimensional materials. PMID:28691094

Modal identification of spindle-tool unit in high-speed machining

NASA Astrophysics Data System (ADS)

Gagnol, Vincent; Le, Thien-Phu; Ray, Pascal

2011-10-01

The accurate knowledge of high-speed motorised spindle dynamic behaviour during machining is important in order to ensure the reliability of machine tools in service and the quality of machined parts. More specifically, the prediction of stable cutting regions, which is a critical requirement for high-speed milling operations, requires the accurate estimation of tool/holder/spindle set dynamic modal parameters. These estimations are generally obtained through Frequency Response Function (FRF) measurements of the non-rotating spindle. However, significant changes in modal parameters are expected to occur during operation, due to high-speed spindle rotation. The spindle's modal variations are highlighted through an integrated finite element model of the dynamic high-speed spindle-bearing system, taking into account rotor dynamics effects. The dependency of dynamic behaviour on speed range is then investigated and determined with accuracy. The objective of the proposed paper is to validate these numerical results through an experiment-based approach. Hence, an experimental setup is elaborated to measure rotating tool vibration during the machining operation in order to determine the spindle's modal frequency variation with respect to spindle speed in an industrial environment. The identification of natural frequencies of the spindle under rotating conditions is challenging, due to the low number of sensors and the presence of many harmonics in the measured signals. In order to overcome these issues and to extract the characteristics of the system, the spindle modes are determined through a 3-step procedure. First, spindle modes are highlighted using the Frequency Domain Decomposition (FDD) technique, with a new formulation at the considered rotating speed. These extracted modes are then analysed through the value of their respective damping ratios in order to separate the harmonics component from structural spindle natural frequencies. Finally, the stochastic properties of the modes are also investigated by considering the probability density of the retained modes. Results show a good correlation between numerical and experiment-based identified frequencies. The identified spindle-tool modal properties during machining allow the numerical model to be considered as representative of the real dynamic properties of the system.

An augmented magnetic navigation system for Transcatheter Aortic Valve Implantation.

PubMed

Luo, Zhe; Cai, Junfeng; Nie, Yuanyuan; Wang, Guotai; Gu, Lixu

2013-01-01

This research proposes an augmented magnetic navigation system for Transcatheter Aortic Valve Implantation (TAVI) employing a magnetic tracking system (MTS) combined with a dynamic aortic model and intra-operative ultrasound (US) images. The dynamic 3D aortic model is constructed based on the preoperative 4D computed tomography (CT), which is animated according to the real time electrocardiograph (ECG) input of patient. And a preoperative planning is performed to determine the target position of the aortic valve prosthesis. The temporal alignment is performed to synchronize the ECG signals, intra-operative US image and tracking information. Afterwards, with the assistance of synchronized ECG signals, the contour of aortic root automatic extracted from short axis US image is registered to the dynamic aortic model by a feature based registration intra-operatively. Then the augmented MTS guides the interventionist to confidently position and deploy the aortic valve prosthesis to target. The system was validated by animal studies on three porcine subjects, the deployment and tilting errors of which are 3.17 ± 0.91 mm and 7.40 ± 2.89° respectively.

A.I.-based real-time support for high performance aircraft operations

NASA Technical Reports Server (NTRS)

Vidal, J. J.

1985-01-01

Artificial intelligence (AI) based software and hardware concepts are applied to the handling system malfunctions during flight tests. A representation of malfunction procedure logic using Boolean normal forms are presented. The representation facilitates the automation of malfunction procedures and provides easy testing for the embedded rules. It also forms a potential basis for a parallel implementation in logic hardware. The extraction of logic control rules, from dynamic simulation and their adaptive revision after partial failure are examined. It uses a simplified 2-dimensional aircraft model with a controller that adaptively extracts control rules for directional thrust that satisfies a navigational goal without exceeding pre-established position and velocity limits. Failure recovery (rule adjusting) is examined after partial actuator failure. While this experiment was performed with primitive aircraft and mission models, it illustrates an important paradigm and provided complexity extrapolations for the proposed extraction of expertise from simulation, as discussed. The use of relaxation and inexact reasoning in expert systems was also investigated.

Realization of a Quantum Integer-Spin Chain with Controllable Interactions

DTIC Science & Technology

2015-06-17

site participate in the dynamics. We observe the time evolution of the system and verify its coherence by entangling a pair of effective three-level...states generated by the XY Hamiltonian, we can verify entangle - ment between a pair of three-level systems with fidelities of up to 86%. Adding a time...3(b) shows an example of the measured parity curve used to extract the amplitude A and verify entanglement between the qutrit pair . Such measurements

Optimal Design of MPPT Controllers for Grid Connected Photovoltaic Array System

NASA Astrophysics Data System (ADS)

Ebrahim, M. A.; AbdelHadi, H. A.; Mahmoud, H. M.; Saied, E. M.; Salama, M. M.

2016-10-01

Integrating photovoltaic (PV) plants into electric power system exhibits challenges to power system dynamic performance. These challenges stem primarily from the natural characteristics of PV plants, which differ in some respects from the conventional plants. The most significant challenge is how to extract and regulate the maximum power from the sun. This paper presents the optimal design for the most commonly used Maximum Power Point Tracking (MPPT) techniques based on Proportional Integral tuned by Particle Swarm Optimization (PI-PSO). These suggested techniques are, (1) the incremental conductance, (2) perturb and observe, (3) fractional short circuit current and (4) fractional open circuit voltage techniques. This research work provides a comprehensive comparative study with the energy availability ratio from photovoltaic panels. The simulation results proved that the proposed controllers have an impressive tracking response. The system dynamic performance improved greatly using the proposed controllers.

Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation

PubMed Central

2017-01-01

The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. However, the original definition of dynamical compensation amounts to lack of structural identifiability. This is relevant if model parameters need to be estimated, as is often the case in biological modelling. Care should we taken when using an unidentifiable model to extract biological insight: the estimated values of structurally unidentifiable parameters are meaningless, and model predictions about unmeasured state variables can be wrong. Taking this into account, we explore alternative definitions of dynamical compensation that do not necessarily imply structural unidentifiability. Accordingly, we show different ways in which a model can be made identifiable while exhibiting dynamical compensation. Our analyses enable the use of the new concept of dynamical compensation in the context of parameter identification, and reconcile it with the desirable property of structural identifiability. PMID:29186132

A rapid method for the extraction and analysis of carotenoids and other hydrophobic substances suitable for systems biology studies with photosynthetic bacteria.

PubMed

Bóna-Lovász, Judit; Bóna, Aron; Ederer, Michael; Sawodny, Oliver; Ghosh, Robin

2013-10-11

A simple, rapid, and inexpensive extraction method for carotenoids and other non-polar compounds present in phototrophic bacteria has been developed. The method, which has been extensively tested on the phototrophic purple non-sulphur bacterium Rhodospirillum rubrum, is suitable for extracting large numbers of samples, which is common in systems biology studies, and yields material suitable for subsequent analysis using HPLC and mass spectroscopy. The procedure is particularly suitable for carotenoids and other terpenoids, including quinones, bacteriochlorophyll a and bacteriopheophytin a, and is also useful for the analysis of polar phospholipids. The extraction procedure requires only a single step extraction with a hexane/methanol/water mixture, followed by HPLC using a Spherisorb C18 column, with a mobile phase consisting of acetone-water and a non-linear gradient of 50%-100% acetone. The method was employed for examining the carotenoid composition observed during microaerophilic growth of R. rubrum strains, and was able to determine 18 carotenoids, 4 isoprenoid-quinones, bacteriochlorophyll a and bacteriopheophytin a as well as four different phosphatidylglycerol species of different acyl chain compositions. The analytical procedure was used to examine the dynamics of carotenoid biosynthesis in the major and minor pathways operating simultaneously in a carotenoid biosynthesis mutant of R. rubrum.

Validation for Vegetation Green-up Date Extracted from GIMMS NDVI and NDVI3g Using Variety of Methods

NASA Astrophysics Data System (ADS)

Chang, Q.; Jiao, W.

2017-12-01

Phenology is a sensitive and critical feature of vegetation change that has regarded as a good indicator in climate change studies. So far, variety of remote sensing data sources and phenology extraction methods from satellite datasets have been developed to study the spatial-temporal dynamics of vegetation phenology. However, the differences between vegetation phenology results caused by the varies satellite datasets and phenology extraction methods are not clear, and the reliability for different phenology results extracted from remote sensing datasets is not verified and compared using the ground observation data. Based on three most popular remote sensing phenology extraction methods, this research calculated the Start of the growing season (SOS) for each pixels in the Northern Hemisphere for two kinds of long time series satellite datasets: GIMMS NDVIg (SOSg) and GIMMS NDVI3g (SOS3g). The three methods used in this research are: maximum increase method, dynamic threshold method and midpoint method. Then, this study used SOS calculated from NEE datasets (SOS_NEE) monitored by 48 eddy flux tower sites in global flux website to validate the reliability of six phenology results calculated from remote sensing datasets. Results showed that both SOSg and SOS3g extracted by maximum increase method are not correlated with ground observed phenology metrics. SOSg and SOS3g extracted by the dynamic threshold method and midpoint method are both correlated with SOS_NEE significantly. Compared with SOSg extracted by the dynamic threshold method, SOSg extracted by the midpoint method have a stronger correlation with SOS_NEE. And, the same to SOS3g. Additionally, SOSg showed stronger correlation with SOS_NEE than SOS3g extracted by the same method. SOS extracted by the midpoint method from GIMMS NDVIg datasets seemed to be the most reliable results when validated with SOS_NEE. These results can be used as reference for data and method selection in future's phenology study.

4D motion modeling of the coronary arteries from CT images for robotic assisted minimally invasive surgery

NASA Astrophysics Data System (ADS)

Zhang, Dong Ping; Edwards, Eddie; Mei, Lin; Rueckert, Daniel

2009-02-01

In this paper, we present a novel approach for coronary artery motion modeling from cardiac Computed Tomography( CT) images. The aim of this work is to develop a 4D motion model of the coronaries for image guidance in robotic-assisted totally endoscopic coronary artery bypass (TECAB) surgery. To utilize the pre-operative cardiac images to guide the minimally invasive surgery, it is essential to have a 4D cardiac motion model to be registered with the stereo endoscopic images acquired intraoperatively using the da Vinci robotic system. In this paper, we are investigating the extraction of the coronary arteries and the modelling of their motion from a dynamic sequence of cardiac CT. We use a multi-scale vesselness filter to enhance vessels in the cardiac CT images. The centerlines of the arteries are extracted using a ridge traversal algorithm. Using this method the coronaries can be extracted in near real-time as only local information is used in vessel tracking. To compute the deformation of the coronaries due to cardiac motion, the motion is extracted from a dynamic sequence of cardiac CT. Each timeframe in this sequence is registered to the end-diastole timeframe of the sequence using a non-rigid registration algorithm based on free-form deformations. Once the images have been registered a dynamic motion model of the coronaries can be obtained by applying the computed free-form deformations to the extracted coronary arteries. To validate the accuracy of the motion model we compare the actual position of the coronaries in each time frame with the predicted position of the coronaries as estimated from the non-rigid registration. We expect that this motion model of coronaries can facilitate the planning of TECAB surgery, and through the registration with real-time endoscopic video images it can reduce the conversion rate from TECAB to conventional procedures.

Isovector dipole resonance and shear viscosity in low energy heavy-ion collisions

NASA Astrophysics Data System (ADS)

Guo, C. Q.; Ma, Y. G.; He, W. B.; Cao, X. G.; Fang, D. Q.; Deng, X. G.; Zhou, C. L.

2017-05-01

The ratio of shear viscosity over entropy density in low energy heavy-ion collision has been calculated by using the Green-Kubo method in the framework of an extended quantum molecular dynamics model. After the system almost reaches a local equilibration for a head-on 40Ca+100Mo collision, thermodynamic and transport properties are extracted. Meanwhile, the isovector giant dipole resonance (IVGDR) of the collision system also is studied. By the Gaussian fits to the IVGDR photon spectra, the peak energies of the IVGDR are extracted at different incident energies. The result shows that the IVGDR peak energy has a positive correlation with the ratio of shear viscosity over entropy density. This is a quantum effect and indicates a difference between nuclear matter and classical fluid.

Reconstruction of active regular motion in amoeba extract: dynamic cooperation between sol and gel states.

PubMed

Nishigami, Yukinori; Ichikawa, Masatoshi; Kazama, Toshiya; Kobayashi, Ryo; Shimmen, Teruo; Yoshikawa, Kenichi; Sonobe, Seiji

2013-01-01

Amoeboid locomotion is one of the typical modes of biological cell migration. Cytoplasmic sol-gel conversion of an actomyosin system is thought to play an important role in locomotion. However, the mechanisms underlying sol-gel conversion, including trigger, signal, and regulating factors, remain unclear. We developed a novel model system in which an actomyosin fraction moves like an amoeba in a cytoplasmic extract. Rheological study of this model system revealed that the actomyosin fraction exhibits shear banding: the sol-gel state of actomyosin can be regulated by shear rate or mechanical force. Furthermore, study of the living cell indicated that the shear-banding property also causes sol-gel conversion with the same order of magnitude as that of shear rate. Our results suggest that the inherent sol-gel transition property plays an essential role in the self-regulation of autonomous translational motion in amoeba.

Reconstruction of Active Regular Motion in Amoeba Extract: Dynamic Cooperation between Sol and Gel States

PubMed Central

Kazama, Toshiya; Kobayashi, Ryo; Shimmen, Teruo; Yoshikawa, Kenichi; Sonobe, Seiji

2013-01-01

Amoeboid locomotion is one of the typical modes of biological cell migration. Cytoplasmic sol–gel conversion of an actomyosin system is thought to play an important role in locomotion. However, the mechanisms underlying sol–gel conversion, including trigger, signal, and regulating factors, remain unclear. We developed a novel model system in which an actomyosin fraction moves like an amoeba in a cytoplasmic extract. Rheological study of this model system revealed that the actomyosin fraction exhibits shear banding: the sol–gel state of actomyosin can be regulated by shear rate or mechanical force. Furthermore, study of the living cell indicated that the shear-banding property also causes sol–gel conversion with the same order of magnitude as that of shear rate. Our results suggest that the inherent sol–gel transition property plays an essential role in the self-regulation of autonomous translational motion in amoeba. PMID:23940560

Trend Motif: A Graph Mining Approach for Analysis of Dynamic Complex Networks

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

Jin, R; McCallen, S; Almaas, E

2007-05-28

Complex networks have been used successfully in scientific disciplines ranging from sociology to microbiology to describe systems of interacting units. Until recently, studies of complex networks have mainly focused on their network topology. However, in many real world applications, the edges and vertices have associated attributes that are frequently represented as vertex or edge weights. Furthermore, these weights are often not static, instead changing with time and forming a time series. Hence, to fully understand the dynamics of the complex network, we have to consider both network topology and related time series data. In this work, we propose a motifmore » mining approach to identify trend motifs for such purposes. Simply stated, a trend motif describes a recurring subgraph where each of its vertices or edges displays similar dynamics over a userdefined period. Given this, each trend motif occurrence can help reveal significant events in a complex system; frequent trend motifs may aid in uncovering dynamic rules of change for the system, and the distribution of trend motifs may characterize the global dynamics of the system. Here, we have developed efficient mining algorithms to extract trend motifs. Our experimental validation using three disparate empirical datasets, ranging from the stock market, world trade, to a protein interaction network, has demonstrated the efficiency and effectiveness of our approach.« less

Phase-Space Detection of Cyber Events

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

Hernandez Jimenez, Jarilyn M; Ferber, Aaron E; Prowell, Stacy J

Energy Delivery Systems (EDS) are a network of processes that produce, transfer and distribute energy. EDS are increasingly dependent on networked computing assets, as are many Industrial Control Systems. Consequently, cyber-attacks pose a real and pertinent threat, as evidenced by Stuxnet, Shamoon and Dragonfly. Hence, there is a critical need for novel methods to detect, prevent, and mitigate effects of such attacks. To detect cyber-attacks in EDS, we developed a framework for gathering and analyzing timing data that involves establishing a baseline execution profile and then capturing the effect of perturbations in the state from injecting various malware. The datamore » analysis was based on nonlinear dynamics and graph theory to improve detection of anomalous events in cyber applications. The goal was the extraction of changing dynamics or anomalous activity in the underlying computer system. Takens' theorem in nonlinear dynamics allows reconstruction of topologically invariant, time-delay-embedding states from the computer data in a sufficiently high-dimensional space. The resultant dynamical states were nodes, and the state-to-state transitions were links in a mathematical graph. Alternatively, sequential tabulation of executing instructions provides the nodes with corresponding instruction-to-instruction links. Graph theorems guarantee graph-invariant measures to quantify the dynamical changes in the running applications. Results showed a successful detection of cyber events.« less

Comparison of supercritical fluid extraction and ultrasound-assisted extraction of fatty acids from quince (Cydonia oblonga Miller) seed using response surface methodology and central composite design.

PubMed

Daneshvand, Behnaz; Ara, Katayoun Mahdavi; Raofie, Farhad

2012-08-24

Fatty acids of Cydonia oblonga Miller cultivated in Iran were obtained by supercritical (carbon dioxide) extraction and ultrasound-assisted extraction methods. The oils were analyzed by capillary gas chromatography using mass spectrometric detections. The compounds were identified according to their retention indices and mass spectra (EI, 70eV). The experimental parameters of SFE such as pressure, temperature, modifier volume, static and dynamic extraction time were optimized using a Central Composite Design (CCD) after a 2(5) factorial design. Pressure and dynamic extraction time had significant effect on the extraction yield, while the other factors (temperature, static extraction time and modifier volume) were not identified as significant factors under the selected conditions. The results of chemometrics analysis showed the highest yield for SFE (24.32%), which was obtained at a pressure of 353bar, temperature of 35°C, modifier (methanol) volume of 150μL, and static and dynamic extraction times of 10 and 60min, respectively. Ultrasound-assisted extraction (UAE) of Fatty acids from C. oblonga Miller was optimized, using a rotatable central composite design. The optimum conditions were as follows: solvent (n-hexane) volume, 22mL; extraction time, 30min; and extraction temperature, 55°C. This resulted in a maximum oil recovery of 19.5%. The extracts with higher yield from both methods were subjected to transesterification and GC-MS analysis. The results show that the oil obtained by SFE with the optimal operating conditions allowed a fatty acid composition similar to the oil obtained by UAE in optimum condition and no significant differences were found. The major components of oil extract were Linoleic, Palmitic, Oleic, Stearic and Eicosanoic acids. Copyright © 2012 Elsevier B.V. All rights reserved.

Flight test planning and parameter extraction for rotorcraft system identification

NASA Technical Reports Server (NTRS)

Wang, J. C.; Demiroz, M. Y.; Talbot, P. D.

1986-01-01

The present study is concerned with the mathematical modelling of aircraft dynamics on the basis of an investigation conducted with the aid of the Rotor System Research Aircraft (RSRA). The particular characteristics of RSRA make it possible to investigate aircraft properties which cannot be readily studied elsewhere, for example in the wind tunnel. The considered experiment had mainly the objective to develop an improved understanding of the physics of rotor flapping dynamics and rotor loads in maneuvers. The employed approach is based on a utilization of parameter identification methodology (PID) with application to helicopters. A better understanding of the contribution of the main rotor to the overall aircraft forces and moments is also to be obtained. Attention is given to the mathematical model of a rotorcraft system, an integrated identification method, flight data processing, and the identification of RSRA mathematical models.

A Foreign Object Damage Event Detector Data Fusion System for Turbofan Engines

NASA Technical Reports Server (NTRS)

Turso, James A.; Litt, Jonathan S.

2004-01-01

A Data Fusion System designed to provide a reliable assessment of the occurrence of Foreign Object Damage (FOD) in a turbofan engine is presented. The FOD-event feature level fusion scheme combines knowledge of shifts in engine gas path performance obtained using a Kalman filter, with bearing accelerometer signal features extracted via wavelet analysis, to positively identify a FOD event. A fuzzy inference system provides basic probability assignments (bpa) based on features extracted from the gas path analysis and bearing accelerometers to a fusion algorithm based on the Dempster-Shafer-Yager Theory of Evidence. Details are provided on the wavelet transforms used to extract the foreign object strike features from the noisy data and on the Kalman filter-based gas path analysis. The system is demonstrated using a turbofan engine combined-effects model (CEM), providing both gas path and rotor dynamic structural response, and is suitable for rapid-prototyping of control and diagnostic systems. The fusion of the disparate data can provide significantly more reliable detection of a FOD event than the use of either method alone. The use of fuzzy inference techniques combined with Dempster-Shafer-Yager Theory of Evidence provides a theoretical justification for drawing conclusions based on imprecise or incomplete data.

Vehicle detection in aerial surveillance using dynamic Bayesian networks.

PubMed

Cheng, Hsu-Yung; Weng, Chih-Chia; Chen, Yi-Ying

2012-04-01

We present an automatic vehicle detection system for aerial surveillance in this paper. In this system, we escape from the stereotype and existing frameworks of vehicle detection in aerial surveillance, which are either region based or sliding window based. We design a pixelwise classification method for vehicle detection. The novelty lies in the fact that, in spite of performing pixelwise classification, relations among neighboring pixels in a region are preserved in the feature extraction process. We consider features including vehicle colors and local features. For vehicle color extraction, we utilize a color transform to separate vehicle colors and nonvehicle colors effectively. For edge detection, we apply moment preserving to adjust the thresholds of the Canny edge detector automatically, which increases the adaptability and the accuracy for detection in various aerial images. Afterward, a dynamic Bayesian network (DBN) is constructed for the classification purpose. We convert regional local features into quantitative observations that can be referenced when applying pixelwise classification via DBN. Experiments were conducted on a wide variety of aerial videos. The results demonstrate flexibility and good generalization abilities of the proposed method on a challenging data set with aerial surveillance images taken at different heights and under different camera angles.

An experimental investigation of the structural dynamics of a torsionally soft rotor in vacuum

NASA Technical Reports Server (NTRS)

Srinivasan, A. V.; Cutts, D. G.; Shu, H. T.

1986-01-01

An extensive data base of structural dynamic characteristics has been generated from an experimental program conducted on a torsionally soft two-bladed model helicopter rotor system. Measurements of vibratory strains for five modes of vibration were made at twenty-one locations on the two blades at speeds varying from 0 to 1000 RPM and for several combinations of precone, droop and flexure stiffness. Tests were conducted in vacuum under carefully controlled conditions using a unique excitation device with a system of piezoelectric crystals bonded to the blade surface near the root. Frequencies, strain mode shapes and dampings are extracted from the time histories and can be used to validate structural dynamics codes. The dynamics of the system are such that there is a clear tendency for the first torsion and second flap modes to couple within the speed range considered. Strain mode shapes vary significantly with speed and configuration. This feature is important in the calcualtion of aeroelastic instabilities. The tension axis tests confirmed that the modulus-weighted centroid for the nonhomogeneous airfoil is slightly off the mass centroid and validated previous static tests done to determine location of the tension axis.

Born in weak fields: below-threshold photoelectron dynamics

NASA Astrophysics Data System (ADS)

Williams, J. B.; Saalmann, U.; Trinter, F.; Schöffler, M. S.; Weller, M.; Burzynski, P.; Goihl, C.; Henrichs, K.; Janke, C.; Griffin, B.; Kastirke, G.; Neff, J.; Pitzer, M.; Waitz, M.; Yang, Y.; Schiwietz, G.; Zeller, S.; Jahnke, T.; Dörner, R.

2017-02-01

We investigate the dynamics of ultra-low kinetic energy photoelectrons. Many experimental techniques employed for the detection of photoelectrons require the presence of (more or less) weak electric extraction fields in order to perform the measurement. Our studies show that ultra-low energy photoelectrons exhibit a characteristic shift in their apparent measured momentum when the target system is exposed to such static electric fields. Already fields as weak as 1 V cm-1 have an observable influence on the detected electron momentum. This apparent shift is demonstrated by an experiment on zero energy photoelectrons emitted from He and explained through theoretical model calculations.

International Space Station Model Correlation Analysis

NASA Technical Reports Server (NTRS)

Laible, Michael R.; Fitzpatrick, Kristin; Hodge, Jennifer; Grygier, Michael

2018-01-01

This paper summarizes the on-orbit structural dynamic data and the related modal analysis, model validation and correlation performed for the International Space Station (ISS) configuration ISS Stage ULF7, 2015 Dedicated Thruster Firing (DTF). The objective of this analysis is to validate and correlate the analytical models used to calculate the ISS internal dynamic loads and compare the 2015 DTF with previous tests. During the ISS configurations under consideration, on-orbit dynamic measurements were collected using the three main ISS instrumentation systems; Internal Wireless Instrumentation System (IWIS), External Wireless Instrumentation System (EWIS) and the Structural Dynamic Measurement System (SDMS). The measurements were recorded during several nominal on-orbit DTF tests on August 18, 2015. Experimental modal analyses were performed on the measured data to extract modal parameters including frequency, damping, and mode shape information. Correlation and comparisons between test and analytical frequencies and mode shapes were performed to assess the accuracy of the analytical models for the configurations under consideration. These mode shapes were also compared to earlier tests. Based on the frequency comparisons, the accuracy of the mathematical models is assessed and model refinement recommendations are given. In particular, results of the first fundamental mode will be discussed, nonlinear results will be shown, and accelerometer placement will be assessed.

Dynamic replanning of 3D automated reconstruction using situation graph trees and illumination adjustment

NASA Astrophysics Data System (ADS)

Kohler, Sophie; Far, Aïcha Beya; Hirsch, Ernest

2007-01-01

This paper presents an original approach for the optimal 3D reconstruction of manufactured workpieces based on a priori planification of the task, enhanced on-line through dynamic adjustment of the lighting conditions, and built around a cognitive intelligent sensory system using so-called Situation Graph Trees. The system takes explicitely structural knowledge related to image acquisition conditions, type of illumination sources, contents of the scene (e. g., CAD models and tolerance information), etc. into account. The principle of the approach relies on two steps. First, a socalled initialization phase, leading to the a priori task plan, collects this structural knowledge. This knowledge is conveniently encoded, as a sub-part, in the Situation Graph Tree building the backbone of the planning system specifying exhaustively the behavior of the application. Second, the image is iteratively evaluated under the control of this Situation Graph Tree. The information describing the quality of the piece to analyze is thus extracted and further exploited for, e. g., inspection tasks. Lastly, the approach enables dynamic adjustment of the Situation Graph Tree, enabling the system to adjust itself to the actual application run-time conditions, thus providing the system with a self-learning capability.

Batch process fault detection and identification based on discriminant global preserving kernel slow feature analysis.

PubMed

Zhang, Hanyuan; Tian, Xuemin; Deng, Xiaogang; Cao, Yuping

2018-05-16

As an attractive nonlinear dynamic data analysis tool, global preserving kernel slow feature analysis (GKSFA) has achieved great success in extracting the high nonlinearity and inherently time-varying dynamics of batch process. However, GKSFA is an unsupervised feature extraction method and lacks the ability to utilize batch process class label information, which may not offer the most effective means for dealing with batch process monitoring. To overcome this problem, we propose a novel batch process monitoring method based on the modified GKSFA, referred to as discriminant global preserving kernel slow feature analysis (DGKSFA), by closely integrating discriminant analysis and GKSFA. The proposed DGKSFA method can extract discriminant feature of batch process as well as preserve global and local geometrical structure information of observed data. For the purpose of fault detection, a monitoring statistic is constructed based on the distance between the optimal kernel feature vectors of test data and normal data. To tackle the challenging issue of nonlinear fault variable identification, a new nonlinear contribution plot method is also developed to help identifying the fault variable after a fault is detected, which is derived from the idea of variable pseudo-sample trajectory projection in DGKSFA nonlinear biplot. Simulation results conducted on a numerical nonlinear dynamic system and the benchmark fed-batch penicillin fermentation process demonstrate that the proposed process monitoring and fault diagnosis approach can effectively detect fault and distinguish fault variables from normal variables. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Aqueous biphasic systems formed by deep eutectic solvent and new-type salts for the high-performance extraction of pigments.

PubMed

Zhang, Hongmei; Wang, Yuzhi; Zhou, Yigang; Chen, Jing; Wei, Xiaoxiao; Xu, Panli

2018-05-01

Deep eutectic solvent (DES) composed of polypropylene glycol 400 (PPG 400) and tetrabutylammonium bromide (TBAB) was combined with a series of new-type salts such as quaternary ammonium salts, amino acid and polyols to form Aqueous Biphasic Systems (ABSs). Phase-forming ability of the salts was investigated firstly. The results showed that polyols had a relatively weak power to produce phases within studied scopes. And the shorter of carbon chain length of salts, the easier to obtain phase-splitting. Then partitioning of three pigments in PPG 400/betaine-based ABSs was addressed to investigate the effect of pigments' hydrophobicity on extraction efficiency. It was found that an increase in hydrophobicity contributed to the migration of pigments in the DES-rich phase. On the other hand, with a decline in phase-forming ability of salts, the extraction efficiency of the whole systems started to go down gradually. Based on the results, selective separation experiment was conducted successfully in the PPG 400/betaine-based systems, including more than 93.00% Sudan Ⅲ in the top phase and about 80.00% sunset yellow FCF/amaranth in the bottom phase. Additionally, ABSs constructed by DES/betaine for partitioning amaranth were further utilized to explore the performances of influence factors and back extraction. It can be concluded that after the optimization above 98.00% amaranth was transferred into the top phase. And 67.98% amaranth can be transferred into the bottom phase in back-extraction experiment. At last, dynamic light scattering (DLS) and transmission electron microscope (TEM) were applied to probe into extraction mechanism. The results demonstrated that hydrophobicity played an important role in the separation process of pigments. Through combining with new-type DES, this work was devoted to introducing plentiful salts as novel compositions of ABSs and providing an eco-friendly extraction way for partitioning pigments, which boosted development of ABSs in the monitoring food safety field. Copyright © 2018 Elsevier B.V. All rights reserved.

Non-invasive assessment of skeletal muscle activity

NASA Astrophysics Data System (ADS)

Merletti, Roberto; Orizio, Claudio; di Prampero, Pietro E.; Tesch, Per

2005-10-01

After the first 3 years (2002-2005), the MAP project has made available: - systems fo electrodes, signal conditioning and digital processing for multichannel simultaneously-detected EMG and MMG as well as for simultaneous electrical stimulation and EMG detection with artifact cancellation. - innovative non-invasive techniques for the extraction of individual motor unit action potentials (MUAPS) and individual motor and MMG contributions from the surface EMG interference signal and the MMG signal. - processing techniques for extractions of indicators of progressive fatigue from the electrically-elicited (M-wave) EMG signal. - techniques for the analysis of dynamic multichannel EMG during cyclic or explosive exercise (in collaboration with project EXER/MAP-MED-027).

A pilot scale ultrasonic system to enhance extraction processes with dense gases

NASA Astrophysics Data System (ADS)

Riera, E.; Blasco, M.; Tornero, A.; Casas, E.; Roselló, C.; Simal, S.; Acosta, V. M.; Gallego-Juárez, J. A.

2012-05-01

The use of dense gases (supercritical fluids) as extracting agents has been attracting wide interest for years. In particular, supercritical carbon dioxide is considered nowadays as a green and very useful solvent. Nevertheless, the extraction process has a slow dynamics. Power ultrasound represents an efficient way for accelerating and enhancing the kinetics of the process by producing strong agitation and turbulence, compressions and decompressions, and heating in the media. For this purpose, a device prototype for using ultrasound in supercritical media was developed, tested and validated in extraction processes of oil from grounded almonds (55% oil content, wet basis and 3-4 mm particle size) in a 5 L extraction unit. An amount of 1500 g of grounded almonds was placed in a cylindrical basket during the trials inside the dense gas extractor (DGE) where solvent was introduced at different flow rates, pressures and temperatures. In all cases the ultrasonic energy confirmed the enhancement and acceleration of the almond oil extraction kinetics using supercritical CO2. Presently the power ultrasound effect in such a process is being deeply analyzed in a 5 L extraction unit before scaling-up a new ultrasonic system. This technology, still under development, has been designed for a bigger dense gas pilot-plant consisting of two extractors (20 L capacity), two separation units and has the possibility of operating at a pressure up to 50 MPa. The goal of this work is to study the effect of high-power ultrasound coupled to dense gas extraction inside the basket with the product, and to present a prototype for the use of power ultrasound in extraction processes with dense gases inside a new 20 L extractor unit.

Sexual affordances, perceptual-motor invariance extraction and intentional nonlinear dynamics: sexually deviant and non-deviant patterns in male subjects.

PubMed

Renaud, Patrice; Goyette, Mathieu; Chartier, Sylvain; Zhornitski, Simon; Trottier, Dominique; Rouleau, Joanne-L; Proulx, Jean; Fedoroff, Paul; Bradford, John-P; Dassylva, Benoit; Bouchard, Stephane

2010-10-01

Sexual arousal and gaze behavior dynamics are used to characterize deviant sexual interests in male subjects. Pedophile patients and non-deviant subjects are immersed with virtual characters depicting relevant sexual features. Gaze behavior dynamics as indexed from correlation dimensions (D2) appears to be fractal in nature and significantly different from colored noise (surrogate data tests and recurrence plot analyses were performed). This perceptual-motor fractal dynamics parallels sexual arousal and differs from pedophiles to non-deviant subjects when critical sexual information is processed. Results are interpreted in terms of sexual affordance, perceptual invariance extraction and intentional nonlinear dynamics.

Image contrast mechanisms in dynamic friction force microscopy: Antimony particles on graphite

NASA Astrophysics Data System (ADS)

Mertens, Felix; Göddenhenrich, Thomas; Dietzel, Dirk; Schirmeisen, Andre

2017-01-01

Dynamic Friction Force Microscopy (DFFM) is a technique based on Atomic Force Microscopy (AFM) where resonance oscillations of the cantilever are excited by lateral actuation of the sample. During this process, the AFM tip in contact with the sample undergoes a complex movement which consists of alternating periods of sticking and sliding. Therefore, DFFM can give access to dynamic transition effects in friction that are not accessible by alternative techniques. Using antimony nanoparticles on graphite as a model system, we analyzed how combined influences of friction and topography can effect different experimental configurations of DFFM. Based on the experimental results, for example, contrast inversion between fractional resonance and band excitation imaging strategies to extract reliable tribological information from DFFM images are devised.

Dynamic fluctuations in single-molecule biophysics experiments. Comment on "Extracting physics of life at the molecular level: A review of single-molecule data analyses" by W. Colomb and S.K. Sarkar

NASA Astrophysics Data System (ADS)

Krapf, Diego

2015-06-01

Single-molecule biophysics includes the study of isolated molecules and that of individual molecules within living cells. In both cases, dynamic fluctuations at the nanoscale play a critical role. Colomb and Sarkar emphasize how different noise sources affect the analysis of single molecule data [1]. Fluctuations in biomolecular systems arise from two very different mechanisms. On one hand thermal fluctuations are a predominant feature in the behavior of individual molecules. On the other hand, non-Gaussian fluctuations can arise from inter- and intramolecular interactions [2], spatial heterogeneities [3], non-Poisson external perturbations [4] and complex non-linear dynamics in general [5,6].

Noninvasive hemoglobin measurement using dynamic spectrum

NASA Astrophysics Data System (ADS)

Yi, Xiaoqing; Li, Gang; Lin, Ling

2017-08-01

Spectroscopy methods for noninvasive hemoglobin (Hgb) measurement are interfered by individual difference and particular weak signal. In order to address these problems, we have put forward a series of improvement methods based on dynamic spectrum (DS), including instrument design, spectrum extraction algorithm, and modeling approach. The instrument adopts light sources composed of eight laser diodes with the wavelength range from 600 nm to 1100 nm and records photoplethysmography signals at eight wavelengths synchronously. In order to simplify the optical design, we modulate the light sources with orthogonal square waves and design the corresponding demodulation algorithm, instead of adopting a beam-splitting system. A newly designed algorithm named difference accumulation has been proved to be effective in improving the accuracy of dynamic spectrum extraction. 220 subjects are involved in the clinical experiment. An extreme learning machine calibration model between the DS data and the Hgb levels is established. Correlation coefficient and root-mean-square error of prediction sets are 0.8645 and 8.48 g/l, respectively. The results indicate that the Hgb level can be derived by this approach noninvasively with acceptable precision and accuracy. It is expected to achieve a clinic application in the future.

Quantitative Analysis of Bioactive Compounds from Aromatic Plants by Means of Dynamic Headspace Extraction and Multiple Headspace Extraction-Gas Chromatography-Mass Spectrometry.

PubMed

Omar, Jone; Olivares, Maitane; Alonso, Ibone; Vallejo, Asier; Aizpurua-Olaizola, Oier; Etxebarria, Nestor

2016-04-01

Seven monoterpenes in 4 aromatic plants (sage, cardamom, lavender, and rosemary) were quantified in liquid extracts and directly in solid samples by means of dynamic headspace-gas chromatography-mass spectrometry (DHS-GC-MS) and multiple headspace extraction-gas chromatography-mass spectrometry (MHSE), respectively. The monoterpenes were 1st extracted by means of supercritical fluid extraction (SFE) and analyzed by an optimized DHS-GC-MS. The optimization of the dynamic extraction step and the desorption/cryo-focusing step were tackled independently by experimental design assays. The best working conditions were set at 30 °C for the incubation temperature, 5 min of incubation time, and 40 mL of purge volume for the dynamic extraction step of these bioactive molecules. The conditions of the desorption/cryo-trapping step from the Tenax TA trap were set at follows: the temperature was increased from 30 to 300 °C at 150 °C/min, although the cryo-trapping was maintained at -70 °C. In order to estimate the efficiency of the SFE process, the analysis of monoterpenes in the 4 aromatic plants was directly carried out by means of MHSE because it did not require any sample preparation. Good linearity (r2) > 0.99) and reproducibility (relative standard deviation % <12) was obtained for solid and liquid quantification approaches, in the ranges of 0.5 to 200 ng and 10 to 500 ng/mL, respectively. The developed methods were applied to analyze the concentration of 7 monoterpenes in aromatic plants obtaining concentrations in the range of 2 to 6000 ng/g and 0.25 to 110 μg/mg, respectively. © 2016 Institute of Food Technologists®

Using Medical Text Extraction, Reasoning and Mapping System (MTERMS) to Process Medication Information in Outpatient Clinical Notes

PubMed Central

Zhou, Li; Plasek, Joseph M; Mahoney, Lisa M; Karipineni, Neelima; Chang, Frank; Yan, Xuemin; Chang, Fenny; Dimaggio, Dana; Goldman, Debora S.; Rocha, Roberto A.

2011-01-01

Clinical information is often coded using different terminologies, and therefore is not interoperable. Our goal is to develop a general natural language processing (NLP) system, called Medical Text Extraction, Reasoning and Mapping System (MTERMS), which encodes clinical text using different terminologies and simultaneously establishes dynamic mappings between them. MTERMS applies a modular, pipeline approach flowing from a preprocessor, semantic tagger, terminology mapper, context analyzer, and parser to structure inputted clinical notes. Evaluators manually reviewed 30 free-text and 10 structured outpatient clinical notes compared to MTERMS output. MTERMS achieved an overall F-measure of 90.6 and 94.0 for free-text and structured notes respectively for medication and temporal information. The local medication terminology had 83.0% coverage compared to RxNorm’s 98.0% coverage for free-text notes. 61.6% of mappings between the terminologies are exact match. Capture of duration was significantly improved (91.7% vs. 52.5%) from systems in the third i2b2 challenge. PMID:22195230

Entropy for the Complexity of Physiological Signal Dynamics.

PubMed

Zhang, Xiaohua Douglas

2017-01-01

Recently, the rapid development of large data storage technologies, mobile network technology, and portable medical devices makes it possible to measure, record, store, and track analysis of biological dynamics. Portable noninvasive medical devices are crucial to capture individual characteristics of biological dynamics. The wearable noninvasive medical devices and the analysis/management of related digital medical data will revolutionize the management and treatment of diseases, subsequently resulting in the establishment of a new healthcare system. One of the key features that can be extracted from the data obtained by wearable noninvasive medical device is the complexity of physiological signals, which can be represented by entropy of biological dynamics contained in the physiological signals measured by these continuous monitoring medical devices. Thus, in this chapter I present the major concepts of entropy that are commonly used to measure the complexity of biological dynamics. The concepts include Shannon entropy, Kolmogorov entropy, Renyi entropy, approximate entropy, sample entropy, and multiscale entropy. I also demonstrate an example of using entropy for the complexity of glucose dynamics.

Spacecraft angular velocity estimation algorithm for star tracker based on optical flow techniques

NASA Astrophysics Data System (ADS)

Tang, Yujie; Li, Jian; Wang, Gangyi

2018-02-01

An integrated navigation system often uses the traditional gyro and star tracker for high precision navigation with the shortcomings of large volume, heavy weight and high-cost. With the development of autonomous navigation for deep space and small spacecraft, star tracker has been gradually used for attitude calculation and angular velocity measurement directly. At the same time, with the dynamic imaging requirements of remote sensing satellites and other imaging satellites, how to measure the angular velocity in the dynamic situation to improve the accuracy of the star tracker is the hotspot of future research. We propose the approach to measure angular rate with a nongyro and improve the dynamic performance of the star tracker. First, the star extraction algorithm based on morphology is used to extract the star region, and the stars in the two images are matched according to the method of angular distance voting. The calculation of the displacement of the star image is measured by the improved optical flow method. Finally, the triaxial angular velocity of the star tracker is calculated by the star vector using the least squares method. The method has the advantages of fast matching speed, strong antinoise ability, and good dynamic performance. The triaxial angular velocity of star tracker can be obtained accurately with these methods. So, the star tracker can achieve better tracking performance and dynamic attitude positioning accuracy to lay a good foundation for the wide application of various satellites and complex space missions.

Quasi-elastic neutron scattering studies of the slow dynamics of supercooled and glassy aspirin

NASA Astrophysics Data System (ADS)

Zhang, Yang; Tyagi, Madhusudan; Mamontov, Eugene; Chen, Sow-Hsin

2012-02-01

Aspirin, also known as acetylsalicylic acid (ASA), is not only a wonderful drug, but also a good glass former. Therefore, it serves as an important molecular system to study the near-arrest and arrested phenomena. In this paper, a high-resolution quasi-elastic neutron scattering (QENS) technique is used to investigate the slow dynamics of supercooled liquid and glassy aspirin from 410 down to 350 K. The measured QENS spectra can be analyzed with a stretched exponential model. We find that (i) the stretched exponent β(Q) is independent of the wavevector transfer Q in the measured Q range and (ii) the structural relaxation time τ(Q) follows a power-law dependence on Q. Consequently, the Q-independent structural relaxation time τ0 can be extracted for each temperature to characterize the slow dynamics of aspirin. The temperature dependence of τ0 can be fitted with the mode-coupling power law, the Vogel-Fulcher-Tammann equation and a universal equation for fragile glass forming liquids recently proposed by Tokuyama in the measured temperature range. The calculated dynamic response function χT(Q, t) using the experimentally determined self-intermediate scattering function of the hydrogen atoms of aspirin shows direct evidence of the enhanced dynamic fluctuations as the aspirin is increasingly supercooled, in agreement with the fixed-time mean squared displacement langx2rang and the non-Gaussian parameter α2 extracted from the elastic scattering.

Quasi-Elastic Neutron Scattering Studies of the Slow Dynamics of Supercooled and Glassy Aspirin

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

Zhang, Yang; Tyagi, M.; Mamontov, Eugene

Aspirin, also known as acetylsalicylic acid (ASA), is not only a wonderful drug, but also a good glass former. Therefore, it serves as an important molecular system to study the near-arrest and arrested phenomena. In this paper, a high-resolution quasi-elastic neutron scattering (QENS) technique is used to investigate the slow dynamics of supercooled liquid and glassy aspirin from 410 K down to 350 K. The measured QENS spectra can be analyzed with a stretched exponential model. We find that (i) the stretched exponent (Q) is independent of the wave vector transfer Q in the measured Q-range, and (ii) the structuralmore » relaxation time (Q) follows a power law dependence on Q. Consequently, the Q-independent structural relaxation time 0 can be extracted for each temperature to characterize the slow dynamics of aspirin. The temperature dependence of 0 can be fitted with the mode coupling power law, the Vogel-Fulcher-Tammann equation and a universal equation for fragile glass forming liquids recently proposed by M. Tokuyama in the measured temperature range. The calculated dynamic response function T(Q,t) using the experimentally determined self-intermediate scattering function of the hydrogen atoms of aspirin shows a direct evidence of the enhanced dynamic fluctuations as the aspirin is increasingly supercooled, in agreement with the fixed-time mean squared displacement x2 and non-Gaussian parameter 2 extracted from the elastic scattering.« less

Geophysical fluid dynamics: whence, whither and why?

PubMed Central

2016-01-01

This article discusses the role of geophysical fluid dynamics (GFD) in understanding the natural environment, and in particular the dynamics of atmospheres and oceans on Earth and elsewhere. GFD, as usually understood, is a branch of the geosciences that deals with fluid dynamics and that, by tradition, seeks to extract the bare essence of a phenomenon, omitting detail where possible. The geosciences in general deal with complex interacting systems and in some ways resemble condensed matter physics or aspects of biology, where we seek explanations of phenomena at a higher level than simply directly calculating the interactions of all the constituent parts. That is, we try to develop theories or make simple models of the behaviour of the system as a whole. However, these days in many geophysical systems of interest, we can also obtain information for how the system behaves by almost direct numerical simulation from the governing equations. The numerical model itself then explicitly predicts the emergent phenomena—the Gulf Stream, for example—something that is still usually impossible in biology or condensed matter physics. Such simulations, as manifested, for example, in complicated general circulation models, have in some ways been extremely successful and one may reasonably now ask whether understanding a complex geophysical system is necessary for predicting it. In what follows we discuss such issues and the roles that GFD has played in the past and will play in the future. PMID:27616918

Dynamic full-scalability conversion in scalable video coding

NASA Astrophysics Data System (ADS)

Lee, Dong Su; Bae, Tae Meon; Thang, Truong Cong; Ro, Yong Man

2007-02-01

For outstanding coding efficiency with scalability functions, SVC (Scalable Video Coding) is being standardized. SVC can support spatial, temporal and SNR scalability and these scalabilities are useful to provide a smooth video streaming service even in a time varying network such as a mobile environment. But current SVC is insufficient to support dynamic video conversion with scalability, thereby the adaptation of bitrate to meet a fluctuating network condition is limited. In this paper, we propose dynamic full-scalability conversion methods for QoS adaptive video streaming in SVC. To accomplish full scalability dynamic conversion, we develop corresponding bitstream extraction, encoding and decoding schemes. At the encoder, we insert the IDR NAL periodically to solve the problems of spatial scalability conversion. At the extractor, we analyze the SVC bitstream to get the information which enable dynamic extraction. Real time extraction is achieved by using this information. Finally, we develop the decoder so that it can manage the changing scalability. Experimental results showed that dynamic full-scalability conversion was verified and it was necessary for time varying network condition.

An online handwriting recognition system for Turkish

NASA Astrophysics Data System (ADS)

Vural, Esra; Erdogan, Hakan; Oflazer, Kemal; Yanikoglu, Berrin A.

2004-12-01

Despite recent developments in Tablet PC technology, there has not been any applications for recognizing handwritings in Turkish. In this paper, we present an online handwritten text recognition system for Turkish, developed using the Tablet PC interface. However, even though the system is developed for Turkish, the addressed issues are common to online handwriting recognition systems in general. Several dynamic features are extracted from the handwriting data for each recorded point and Hidden Markov Models (HMM) are used to train letter and word models. We experimented with using various features and HMM model topologies, and report on the effects of these experiments. We started with first and second derivatives of the x and y coordinates and relative change in the pen pressure as initial features. We found that using two more additional features, that is, number of neighboring points and relative heights of each point with respect to the base-line improve the recognition rate. In addition, extracting features within strokes and using a skipping state topology improve the system performance as well. The improved system performance is 94% in recognizing handwritten words from a 1000-word lexicon.

An online handwriting recognition system for Turkish

NASA Astrophysics Data System (ADS)

Vural, Esra; Erdogan, Hakan; Oflazer, Kemal; Yanikoglu, Berrin A.

2005-01-01

Despite recent developments in Tablet PC technology, there has not been any applications for recognizing handwritings in Turkish. In this paper, we present an online handwritten text recognition system for Turkish, developed using the Tablet PC interface. However, even though the system is developed for Turkish, the addressed issues are common to online handwriting recognition systems in general. Several dynamic features are extracted from the handwriting data for each recorded point and Hidden Markov Models (HMM) are used to train letter and word models. We experimented with using various features and HMM model topologies, and report on the effects of these experiments. We started with first and second derivatives of the x and y coordinates and relative change in the pen pressure as initial features. We found that using two more additional features, that is, number of neighboring points and relative heights of each point with respect to the base-line improve the recognition rate. In addition, extracting features within strokes and using a skipping state topology improve the system performance as well. The improved system performance is 94% in recognizing handwritten words from a 1000-word lexicon.

Probing the holographic principle using dynamical gauge effects from open spin-orbit coupling

NASA Astrophysics Data System (ADS)

Zhao, Jianshi; Price, Craig; Liu, Qi; Gemelke, Nathan

2016-05-01

Dynamical gauge fields result from locally defined symmetries and an effective over-labeling of quantum states. Coupling atoms weakly to a reservoir of laser modes can create an effective dynamical gauge field purely due to the disregard of information in the optical states. Here we report measurements revealing effects of open spin-orbit coupling in a system where an effective model can be formed from a non-abelian SU(2) × U(1) field theory following the Yang-Mills construct. Forming a close analogy to dynamical gauge effects in quantum chromodynamics, we extract a measure of atomic motion which reveals the analog of a closing mass gap for the relevant gauge boson, shedding insight on long standing open problems in gauge-fixing scale anomalies. Using arguments following the holographic principle, we measure scaling relations which can be understood by quantifying information present in the local potential. New prospects using these techniques for developing fractionalization of multi-particle and macroscopic systems using dissipative and non-abelian gauge fields will also be discussed. We acknowledge support from NSF Award No. 1068570, and the Charles E. Kaufman Foundation.

Human fatigue expression recognition through image-based dynamic multi-information and bimodal deep learning

NASA Astrophysics Data System (ADS)

Zhao, Lei; Wang, Zengcai; Wang, Xiaojin; Qi, Yazhou; Liu, Qing; Zhang, Guoxin

2016-09-01

Human fatigue is an important cause of traffic accidents. To improve the safety of transportation, we propose, in this paper, a framework for fatigue expression recognition using image-based facial dynamic multi-information and a bimodal deep neural network. First, the landmark of face region and the texture of eye region, which complement each other in fatigue expression recognition, are extracted from facial image sequences captured by a single camera. Then, two stacked autoencoder neural networks are trained for landmark and texture, respectively. Finally, the two trained neural networks are combined by learning a joint layer on top of them to construct a bimodal deep neural network. The model can be used to extract a unified representation that fuses landmark and texture modalities together and classify fatigue expressions accurately. The proposed system is tested on a human fatigue dataset obtained from an actual driving environment. The experimental results demonstrate that the proposed method performs stably and robustly, and that the average accuracy achieves 96.2%.

Force and Stress along Simulated Dissociation Pathways of Cucurbituril-Guest Systems.

PubMed

Velez-Vega, Camilo; Gilson, Michael K

2012-03-13

The field of host-guest chemistry provides computationally tractable yet informative model systems for biomolecular recognition. We applied molecular dynamics simulations to study the forces and mechanical stresses associated with forced dissociation of aqueous cucurbituril-guest complexes with high binding affinities. First, the unbinding transitions were modeled with constant velocity pulling (steered dynamics) and a soft spring constant, to model atomic force microscopy (AFM) experiments. The computed length-force profiles yield rupture forces in good agreement with available measurements. We also used steered dynamics with high spring constants to generate paths characterized by a tight control over the specified pulling distance; these paths were then equilibrated via umbrella sampling simulations and used to compute time-averaged mechanical stresses along the dissociation pathways. The stress calculations proved to be informative regarding the key interactions determining the length-force profiles and rupture forces. In particular, the unbinding transition of one complex is found to be a stepwise process, which is initially dominated by electrostatic interactions between the guest's ammoniums and the host's carbonyl groups, and subsequently limited by the extraction of the guest's bulky bicyclooctane moiety; the latter step requires some bond stretching at the cucurbituril's extraction portal. Conversely, the dissociation of a second complex with a more slender guest is mainly driven by successive electrostatic interactions between the different guest's ammoniums and the host's carbonyl groups. The calculations also provide information on the origins of thermodynamic irreversibilities in these forced dissociation processes.

Informatics in radiology: automated Web-based graphical dashboard for radiology operational business intelligence.

PubMed

Nagy, Paul G; Warnock, Max J; Daly, Mark; Toland, Christopher; Meenan, Christopher D; Mezrich, Reuben S

2009-11-01

Radiology departments today are faced with many challenges to improve operational efficiency, performance, and quality. Many organizations rely on antiquated, paper-based methods to review their historical performance and understand their operations. With increased workloads, geographically dispersed image acquisition and reading sites, and rapidly changing technologies, this approach is increasingly untenable. A Web-based dashboard was constructed to automate the extraction, processing, and display of indicators and thereby provide useful and current data for twice-monthly departmental operational meetings. The feasibility of extracting specific metrics from clinical information systems was evaluated as part of a longer-term effort to build a radiology business intelligence architecture. Operational data were extracted from clinical information systems and stored in a centralized data warehouse. Higher-level analytics were performed on the centralized data, a process that generated indicators in a dynamic Web-based graphical environment that proved valuable in discussion and root cause analysis. Results aggregated over a 24-month period since implementation suggest that this operational business intelligence reporting system has provided significant data for driving more effective management decisions to improve productivity, performance, and quality of service in the department.

Inferring Regulatory Networks from Experimental Morphological Phenotypes: A Computational Method Reverse-Engineers Planarian Regeneration

PubMed Central

Lobo, Daniel; Levin, Michael

2015-01-01

Transformative applications in biomedicine require the discovery of complex regulatory networks that explain the development and regeneration of anatomical structures, and reveal what external signals will trigger desired changes of large-scale pattern. Despite recent advances in bioinformatics, extracting mechanistic pathway models from experimental morphological data is a key open challenge that has resisted automation. The fundamental difficulty of manually predicting emergent behavior of even simple networks has limited the models invented by human scientists to pathway diagrams that show necessary subunit interactions but do not reveal the dynamics that are sufficient for complex, self-regulating pattern to emerge. To finally bridge the gap between high-resolution genetic data and the ability to understand and control patterning, it is critical to develop computational tools to efficiently extract regulatory pathways from the resultant experimental shape phenotypes. For example, planarian regeneration has been studied for over a century, but despite increasing insight into the pathways that control its stem cells, no constructive, mechanistic model has yet been found by human scientists that explains more than one or two key features of its remarkable ability to regenerate its correct anatomical pattern after drastic perturbations. We present a method to infer the molecular products, topology, and spatial and temporal non-linear dynamics of regulatory networks recapitulating in silico the rich dataset of morphological phenotypes resulting from genetic, surgical, and pharmacological experiments. We demonstrated our approach by inferring complete regulatory networks explaining the outcomes of the main functional regeneration experiments in the planarian literature; By analyzing all the datasets together, our system inferred the first systems-biology comprehensive dynamical model explaining patterning in planarian regeneration. This method provides an automated, highly generalizable framework for identifying the underlying control mechanisms responsible for the dynamic regulation of growth and form. PMID:26042810

A non-contacting approach for full field dynamic strain monitoring of rotating structures using the photogrammetry, finite element, and modal expansion techniques

NASA Astrophysics Data System (ADS)

Baqersad, Javad

Health monitoring of rotating structures such as wind turbines and helicopter rotors is generally performed using conventional sensors that provide a limited set of data at discrete locations near or on the hub. These sensors usually provide no data on the blades or interior locations where failures may occur. Within this work, an unique expansion algorithm was extended and combined with finite element (FE) modeling and an optical measurement technique to identify the dynamic strain in rotating structures. The merit of the approach is shown by using the approach to predict the dynamic strain on a small non-rotating and rotating wind turbine. A three-bladed wind turbine having 2.3-meter long blades was placed in a semi-built-in boundary condition using a hub, a machining chuck, and a steel block. A finite element model of the three wind turbine blades assembled to the hub was created and used to extract resonant frequencies and mode shapes. The FE model was validated and updated using experimental modal tests. For the non-rotating optical test, the turbine was excited using a sinusoidal excitation, a pluck test, arbitrary impacts on three blades, and random force excitations with a mechanical shaker. The response of the structure to the excitations was measured using three-dimensional point tracking. A pair of high-speed cameras was used to measure the displacement of optical targets on the structure when the blades were vibrating. The measured displacements at discrete locations were expanded and applied to the finite element model of the structure to extract the full-field dynamic strain. The results of the work show an excellent correlation between the strain predicted using the proposed approach and the strain measured with strain-gages for all of the three loading conditions. Similar to the non-rotating case, optical measurements were also preformed on a rotating wind turbine. The point tracking technique measured both rigid body displacement and flexible deformation of the blades at target locations. The measured displacements were expanded and applied to the finite element model of the turbine to extract full-field dynamic strain on the structure. In order to validate the results for the rotating turbine, the predicted strain was compared to strain measured at four locations on the spinning blades using a wireless strain-gage system. The approach used in this work to predict the strain showed higher accuracy than measurements obtainable by using the digital image correlation technique. The new expansion approach is able to extract dynamic strain all over the entire structure, even inside the structure beyond the line of sight of the measurement system. Because the method is based on a non-contacting measurement approach, it can be readily applied to a variety of structures having different boundary and operating conditions, including rotating blades.

[Mass Transfer Kinetics Model of Ultrasonic Extraction of Pomegranate Peel Polyphenols].

PubMed

Wang, Zhan-yi; Zhang, Li-hua; Wang, Yu-hai; Zhang, Yuan-hu; Ma, Li; Zheng, Dan-dan

2015-05-01

The dynamic mathematical model of ultrasonic extraction of polyphenols from pomegranate peel was constructed with the Fick's second law as the theoretical basis. The spherical model was selected, with mass concentrations of pomegranate peel polyphenols as the index, 50% ethanol as the extraction solvent and ultrasonic extraction as the extraction method. In different test conditions including the liquid ratio, extraction temperature and extraction time, a series of kinetic parameters were solved, such as the extraction process (k), relative raffinate rate, surface diffusion coefficient(D(S)), half life (t½) and the apparent activation energy (E(a)). With the extraction temperature increasing, k and D(S) were gradually increased with t½ decreasing,which indicated that the elevated temperature was favorable to the extraction of pomegranate peel polyphenols. The exponential equation of relative raffinate rate showed that the established numerical dynamics model fitted the extraction of pomegranate peel polyphenols, and the relationship between the reaction conditions and pomegranate peel polyphenols concentration was well reflected by the model. Based on the experimental results, a feasible and reliable kinetic model for ultrasonic extraction of polyphenols from pomegranate peel is established, which can be used for the optimization control of engineering magnifying production.

Thermo Dynamics and Economics Evaluations: Substitution of the Extraction Steam with the Wasted Heat of Flue Gas

NASA Astrophysics Data System (ADS)

Hao, Lifen; Qiu, Lixia; Li, Jinping; Li, Dongxiong

2018-01-01

A new heat supplying system is proposed that utilizes the exhausted gas of the boiler to substitute the extraction steam from the turbine as the driving force for the adsorption heat pump regarding the recovery of the condensation heat of power plant. However, our system is not subject to the low efficiency of wasted heat utilization due to the low temperature of flue gas, which hence possesses higher performance in COP factors in the utilization of heat than that of the conventional techniques of using flues gas, so the amount of extracted gas from turbine can be reduced and the power generate rate be enhanced. Subsequently, detailed evaluation of the performance of this system in the point of views of thermodynamics and economics are presented in this work. For the instance of a 330 MW heat supply unit, 5 sample cities are chosen to demonstrate and confirm our economic analysis. It is revealed that when the heating coefficient of the heat pump is 1.8, the investment payback periods for these 5 cities are within the range of 2.4 to 4.8 years, which are far below the service year of the heat pump, demonstrating remarkable economic benefits for our system.

Optimising resolution for a preparative separation of Chinese herbal medicine using a surrogate model sample system.

PubMed

Ye, Haoyu; Ignatova, Svetlana; Peng, Aihua; Chen, Lijuan; Sutherland, Ian

2009-06-26

This paper builds on previous modelling research with short single layer columns to develop rapid methods for optimising high-performance counter-current chromatography at constant stationary phase retention. Benzyl alcohol and p-cresol are used as model compounds to rapidly optimise first flow and then rotational speed operating conditions at a preparative scale with long columns for a given phase system using a Dynamic Extractions Midi-DE centrifuge. The transfer to a high value extract such as the crude ethanol extract of Chinese herbal medicine Millettia pachycarpa Benth. is then demonstrated and validated using the same phase system. The results show that constant stationary phase modelling of flow and speed with long multilayer columns works well as a cheap, quick and effective method of optimising operating conditions for the chosen phase system-hexane-ethyl acetate-methanol-water (1:0.8:1:0.6, v/v). Optimum conditions for resolution were a flow of 20 ml/min and speed of 1200 rpm, but for throughput were 80 ml/min at the same speed. The results show that 80 ml/min gave the best throughputs for tephrosin (518 mg/h), pyranoisoflavone (47.2 mg/h) and dehydrodeguelin (10.4 mg/h), whereas for deguelin (100.5 mg/h), the best flow rate was 40 ml/min.

Model development for prediction of soil water dynamics in plant production.

PubMed

Hu, Zhengfeng; Jin, Huixia; Zhang, Kefeng

2015-09-01

Optimizing water use in agriculture and medicinal plants is crucially important worldwide. Soil sensor-controlled irrigation systems are increasingly becoming available. However it is questionable whether irrigation scheduling based on soil measurements in the top soil could make best use of water for deep-rooted crops. In this study a mechanistic model was employed to investigate water extraction by a deep-rooted cabbage crop from the soil profile throughout crop growth. The model accounts all key processes governing water dynamics in the soil-plant-atmosphere system. Results show that the subsoil provides a significant proportion of the seasonal transpiration, about a third of water transpired over the whole growing season. This suggests that soil water in the entire root zone should be taken into consideration in irrigation scheduling, and for sensor-controlled irrigation systems sensors in the subsoil are essential for detecting soil water status for deep-rooted crops.

Research on FBG-Based CFRP Structural Damage Identification Using BP Neural Network

NASA Astrophysics Data System (ADS)

Geng, Xiangyi; Lu, Shizeng; Jiang, Mingshun; Sui, Qingmei; Lv, Shanshan; Xiao, Hang; Jia, Yuxi; Jia, Lei

2018-06-01

A damage identification system of carbon fiber reinforced plastics (CFRP) structures is investigated using fiber Bragg grating (FBG) sensors and back propagation (BP) neural network. FBG sensors are applied to construct the sensing network to detect the structural dynamic response signals generated by active actuation. The damage identification model is built based on the BP neural network. The dynamic signal characteristics extracted by the Fourier transform are the inputs, and the damage states are the outputs of the model. Besides, damages are simulated by placing lumped masses with different weights instead of inducing real damages, which is confirmed to be feasible by finite element analysis (FEA). At last, the damage identification system is verified on a CFRP plate with 300 mm × 300 mm experimental area, with the accurate identification of varied damage states. The system provides a practical way for CFRP structural damage identification.

Revealing missing charges with generalised quantum fluctuation relations.

PubMed

Mur-Petit, J; Relaño, A; Molina, R A; Jaksch, D

2018-05-22

The non-equilibrium dynamics of quantum many-body systems is one of the most fascinating problems in physics. Open questions range from how they relax to equilibrium to how to extract useful work from them. A critical point lies in assessing whether a system has conserved quantities (or 'charges'), as these can drastically influence its dynamics. Here we propose a general protocol to reveal the existence of charges based on a set of exact relations between out-of-equilibrium fluctuations and equilibrium properties of a quantum system. We apply these generalised quantum fluctuation relations to a driven quantum simulator, demonstrating their relevance to obtain unbiased temperature estimates from non-equilibrium measurements. Our findings will help guide research on the interplay of quantum and thermal fluctuations in quantum simulation, in studying the transition from integrability to chaos and in the design of new quantum devices.

Dynamic area telethermometry and its clinical applications

NASA Astrophysics Data System (ADS)

Anbar, Michael

1995-03-01

Dynamic area telethermometry (DAT) is a recent development in thermology, the science of biological heat generation and dissipation. DAT is based on monitoring changes in infrared emission, deriving from them information on the kinetics and mechanisms of biological thermoregulation. Remotely monitoring infrared emission is the most reliable technique to study bioenergetics, because it minimally perturbs the investigated system. Area monitoring of heat dissipating surfaces is needed because temporal changes in the spatial distribution of temperature conveys information on mechanisms of thermoregulation. DAT can be applied to biological systems ranging from single cells (microtelecalorimetry) to large areas of human skin (clinical thermology). DAT requires the accumulation of many (hundreds to thousands) thermal images followed by analysis of the thermokinetics of each pixel or group of pixels. In clinical thermology this analysis uses FFT to extract systemic, regional and local thermoregulatory frequencies (TRFs). DAT also extracts information on local thermoregulation from the temporal behavior of homogeneity of skin temperature (HST). Analysis of the relative contributions (FFT amplitudes) of the different frequencies allows distinction between vascular, neurological, and immunological thermoregulatory dysfunctions. This analysis, which can reveal the mechanism of the dysfunction, can be very useful in the diagnosis and staging of various disorders, ranging from diabetes mellitus and liver cirrhosis to breast cancer and malignant melanoma. From the engineering standpoint DAT requires highly stable imaging systems and effective display of the spatial distribution of TRFs to allow identification of thermoregulatory pathways and their dysfunction.

Single ion dynamics in molten sodium bromide

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

Alcaraz, O.; Trullas, J.; Demmel, F.

We present a study on the single ion dynamics in the molten alkali halide NaBr. Quasielastic neutron scattering was employed to extract the self-diffusion coefficient of the sodium ions at three temperatures. Molecular dynamics simulations using rigid and polarizable ion models have been performed in parallel to extract the sodium and bromide single dynamics and ionic conductivities. Two methods have been employed to derive the ion diffusion, calculating the mean squared displacements and the velocity autocorrelation functions, as well as analysing the increase of the line widths of the self-dynamic structure factors. The sodium diffusion coefficients show a remarkable goodmore » agreement between experiment and simulation utilising the polarisable potential.« less

Scan Line Based Road Marking Extraction from Mobile LiDAR Point Clouds.

PubMed

Yan, Li; Liu, Hua; Tan, Junxiang; Li, Zan; Xie, Hong; Chen, Changjun

2016-06-17

Mobile Mapping Technology (MMT) is one of the most important 3D spatial data acquisition technologies. The state-of-the-art mobile mapping systems, equipped with laser scanners and named Mobile LiDAR Scanning (MLS) systems, have been widely used in a variety of areas, especially in road mapping and road inventory. With the commercialization of Advanced Driving Assistance Systems (ADASs) and self-driving technology, there will be a great demand for lane-level detailed 3D maps, and MLS is the most promising technology to generate such lane-level detailed 3D maps. Road markings and road edges are necessary information in creating such lane-level detailed 3D maps. This paper proposes a scan line based method to extract road markings from mobile LiDAR point clouds in three steps: (1) preprocessing; (2) road points extraction; (3) road markings extraction and refinement. In preprocessing step, the isolated LiDAR points in the air are removed from the LiDAR point clouds and the point clouds are organized into scan lines. In the road points extraction step, seed road points are first extracted by Height Difference (HD) between trajectory data and road surface, then full road points are extracted from the point clouds by moving least squares line fitting. In the road markings extraction and refinement step, the intensity values of road points in a scan line are first smoothed by a dynamic window median filter to suppress intensity noises, then road markings are extracted by Edge Detection and Edge Constraint (EDEC) method, and the Fake Road Marking Points (FRMPs) are eliminated from the detected road markings by segment and dimensionality feature-based refinement. The performance of the proposed method is evaluated by three data samples and the experiment results indicate that road points are well extracted from MLS data and road markings are well extracted from road points by the applied method. A quantitative study shows that the proposed method achieves an average completeness, correctness, and F-measure of 0.96, 0.93, and 0.94, respectively. The time complexity analysis shows that the scan line based road markings extraction method proposed in this paper provides a promising alternative for offline road markings extraction from MLS data.

Scan Line Based Road Marking Extraction from Mobile LiDAR Point Clouds†

PubMed Central

Yan, Li; Liu, Hua; Tan, Junxiang; Li, Zan; Xie, Hong; Chen, Changjun

2016-01-01

Mobile Mapping Technology (MMT) is one of the most important 3D spatial data acquisition technologies. The state-of-the-art mobile mapping systems, equipped with laser scanners and named Mobile LiDAR Scanning (MLS) systems, have been widely used in a variety of areas, especially in road mapping and road inventory. With the commercialization of Advanced Driving Assistance Systems (ADASs) and self-driving technology, there will be a great demand for lane-level detailed 3D maps, and MLS is the most promising technology to generate such lane-level detailed 3D maps. Road markings and road edges are necessary information in creating such lane-level detailed 3D maps. This paper proposes a scan line based method to extract road markings from mobile LiDAR point clouds in three steps: (1) preprocessing; (2) road points extraction; (3) road markings extraction and refinement. In preprocessing step, the isolated LiDAR points in the air are removed from the LiDAR point clouds and the point clouds are organized into scan lines. In the road points extraction step, seed road points are first extracted by Height Difference (HD) between trajectory data and road surface, then full road points are extracted from the point clouds by moving least squares line fitting. In the road markings extraction and refinement step, the intensity values of road points in a scan line are first smoothed by a dynamic window median filter to suppress intensity noises, then road markings are extracted by Edge Detection and Edge Constraint (EDEC) method, and the Fake Road Marking Points (FRMPs) are eliminated from the detected road markings by segment and dimensionality feature-based refinement. The performance of the proposed method is evaluated by three data samples and the experiment results indicate that road points are well extracted from MLS data and road markings are well extracted from road points by the applied method. A quantitative study shows that the proposed method achieves an average completeness, correctness, and F-measure of 0.96, 0.93, and 0.94, respectively. The time complexity analysis shows that the scan line based road markings extraction method proposed in this paper provides a promising alternative for offline road markings extraction from MLS data. PMID:27322279

A microfluidic cigarette smoke collecting platform for simultaneous sample extraction and multiplex analysis.

PubMed

Hu, Shan-Wen; Xu, Bi-Yi; Qiao, Shu; Zhao, Ge; Xu, Jing-Juan; Chen, Hong-Yuan; Xie, Fu-Wei

2016-04-01

In this work, we report a novel microfluidic gas collecting platform aiming at simultaneous sample extraction and multiplex mass spectrometry (MS) analysis. An alveolar-mimicking elastic polydimethylsiloxane (PDMS) structures was designed to move dynamically driven by external pressure. The movement was well tuned both by its amplitude and rhythm following the natural process of human respiration. By integrating the alveolar units into arrays and assembling them to gas channels, a cyclic contraction/expansion system for gas inhale and exhale was successfully constructed. Upon equipping this system with a droplet array on the alveolar array surface, we were able to get information of inhaled smoke in a new strategy. Here, with cigarette smoke as an example, analysis of accumulation for target molecules during passive smoking is taken. Relationships between the breathing times, distances away from smokers and inhaled content of nicotine are clarified. Further, by applying different types of extraction solvent droplets on different locations of the droplet array, simultaneous extraction of nicotine, formaldehyde and caproic acid in sidestream smoke (SS) are realized. Since the extract droplets are spatially separated, they can be directly analyzed by MS which is fast and can rid us of all complex sample separation and purification steps. Combining all these merits, this small, cheap and portable platform might find wide application in inhaled air pollutant analysis both in and outdoors. Copyright © 2015 Elsevier B.V. All rights reserved.

Transforming Healthcare Delivery: Integrating Dynamic Simulation Modelling and Big Data in Health Economics and Outcomes Research.

PubMed

Marshall, Deborah A; Burgos-Liz, Lina; Pasupathy, Kalyan S; Padula, William V; IJzerman, Maarten J; Wong, Peter K; Higashi, Mitchell K; Engbers, Jordan; Wiebe, Samuel; Crown, William; Osgood, Nathaniel D

2016-02-01

In the era of the Information Age and personalized medicine, healthcare delivery systems need to be efficient and patient-centred. The health system must be responsive to individual patient choices and preferences about their care, while considering the system consequences. While dynamic simulation modelling (DSM) and big data share characteristics, they present distinct and complementary value in healthcare. Big data and DSM are synergistic-big data offer support to enhance the application of dynamic models, but DSM also can greatly enhance the value conferred by big data. Big data can inform patient-centred care with its high velocity, volume, and variety (the three Vs) over traditional data analytics; however, big data are not sufficient to extract meaningful insights to inform approaches to improve healthcare delivery. DSM can serve as a natural bridge between the wealth of evidence offered by big data and informed decision making as a means of faster, deeper, more consistent learning from that evidence. We discuss the synergies between big data and DSM, practical considerations and challenges, and how integrating big data and DSM can be useful to decision makers to address complex, systemic health economics and outcomes questions and to transform healthcare delivery.

Dynamic deformation inspection of a human arm by using a line-scan imaging system

NASA Astrophysics Data System (ADS)

Hu, Eryi

2009-11-01

A line-scan imaging system is used in the dynamic deformation measurement of a human arm when the muscle is contracting and relaxing. The measurement principle is based on the projection grating profilometry, and the measuring system is consisted of a line-scan CCD camera, a projector, optical lens and a personal computer. The detected human arm is put upon a reference plane, and a sinusoidal grating is projected onto the object surface and reference plane at an incidence angle, respectively. The deformed fringe pattern in the same line of the dynamic detected arm is captured by the line-scan CCD camera with free trigger model, and the deformed fringe pattern is recorded in the personal computer for processing. A fast Fourier transform combining with a filtering and spectrum shifting method is used to extract the phase information caused by the profile of the detected object. Thus, the object surface profile can be obtained following the geometric relationship between the fringe deformation and the object surface height. Furthermore, the deformation procedure can be obtained line by line. Some experimental results are presented to prove the feasibility of the inspection system.

Neutron star dynamics under time-dependent external torques

NASA Astrophysics Data System (ADS)

Gügercinoǧlu, Erbil; Alpar, M. Ali

2017-11-01

The two-component model describes neutron star dynamics incorporating the response of the superfluid interior. Conventional solutions and applications involve constant external torques, as appropriate for radio pulsars on dynamical time-scales. We present the general solution of two-component dynamics under arbitrary time-dependent external torques, with internal torques that are linear in the rotation rates, or with the extremely non-linear internal torques due to vortex creep. The two-component model incorporating the response of linear or non-linear internal torques can now be applied not only to radio pulsars but also to magnetars and to neutron stars in binary systems, with strong observed variability and noise in the spin-down or spin-up rates. Our results allow the extraction of the time-dependent external torques from the observed spin-down (or spin-up) time series, \\dot{Ω }(t). Applications are discussed.

Dark-field-based observation of single-nanoparticle dynamics on a supported lipid bilayer for in situ analysis of interacting molecules and nanoparticles.

PubMed

Lee, Young Kwang; Kim, Sungi; Nam, Jwa-Min

2015-01-12

Observation of single plasmonic nanoparticles in reconstituted biological systems allows us to obtain snapshots of dynamic processes between molecules and nanoparticles with unprecedented spatiotemporal resolution and single-molecule/single-particle-level data acquisition. This Concept is intended to introduce nanoparticle-tethered supported lipid bilayer platforms that allow for the dynamic confinement of nanoparticles on a two-dimensional fluidic surface. The dark-field-based long-term, stable, real-time observation of freely diffusing plasmonic nanoparticles on a lipid bilayer enables one to extract a broad range of information about interparticle and molecular interactions throughout the entire reaction period. Herein, we highlight important developments in this context to provide ideas on how molecular interactions can be interpreted by monitoring dynamic behaviors and optical signals of laterally mobile nanoparticles. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Influences of groundwater extraction on flow dynamics and arsenic levels in the western Hetao Basin, Inner Mongolia, China

NASA Astrophysics Data System (ADS)

Zhang, Zhuo; Guo, Huaming; Zhao, Weiguang; Liu, Shuai; Cao, Yongsheng; Jia, Yongfeng

2018-04-01

Data on spatiotemporal variations in groundwater levels are crucial for understanding arsenic (As) behavior and dynamics in groundwater systems. Little is known about the influences of groundwater extraction on the transport and mobilization of As in the Hetao Basin, Inner Mongolia (China), so groundwater levels were recorded in five monitoring wells from 2011 to 2016 and in 57 irrigation wells and two multilevel wells in 2016. Results showed that groundwater level in the groundwater irrigation area had two troughs each year, induced by extensive groundwater extraction, while groundwater levels in the river-diverted (Yellow River) water irrigation area had two peaks each year, resulting from surface-water irrigation. From 2011 to 2016, groundwater levels in the groundwater irrigation area presented a decreasing trend due to the overextraction. Groundwater samples were taken for geochemical analysis each year in July from 2011 to 2016. Increasing trends were observed in groundwater total dissolved solids (TDS) and As. Owing to the reverse groundwater flow direction, the Shahai Lake acts as a new groundwater recharge source. Lake water had flushed the near-surface sediments, which contain abundant soluble components, and increased groundwater salinity. In addition, groundwater extraction induced strong downward hydraulic gradients, which led to leakage recharge from shallow high-TDS groundwater to the deep semiconfined aquifer. The most plausible explanation for similar variations among As, Fe(II) and total organic carbon (TOC) concentrations is the expected dissimilatory reduction of Fe(III) oxyhydroxides.

Lipid Nanocarriers for Oral Delivery of Serenoa repens CO2 Extract: A Study of Microemulsion and Self-Microemulsifying Drug Delivery Systems.

PubMed

Guccione, Clizia; Bergonzi, Maria Camilla; Awada, Khaled M; Piazzini, Vieri; Bilia, Anna Rita

2018-07-01

The aim of this study was the development and characterization of lipid nanocarriers using food grade components for oral delivery of Serenoa repens CO 2 extract, namely microemulsions (MEs) and self-microemulsifying drug delivery systems (SMEDDSs) to improve the oral absorption. A commercial blend (CB) containing 320 of S. repens CO 2 extract plus the aqueous soluble extracts of nettle root and pineapple stem was formulated in two MEs and two SMEDDSs. The optimized ME loaded with the CB (CBM2) had a very low content of water (only 17.3%). The drug delivery systems were characterized by dynamic light scattering, transmission electron microscopy, and high-performance liquid chromatography (HPLC) with a diode-array detector analyses in order to evaluate the size, the homogeneity, the morphology, and the encapsulation efficiency. β -carotene was selected as marker for the quantitative HPLC analysis. Additionally, physical and chemical stabilities were acceptable during 3 wk at 4 °C. Stability of these nanocarriers in simulated stomach and intestinal conditions was proved. Finally, the improvement of oral absorption of S. repens was studied in vitro using parallel artificial membrane permeability assay. An enhancement of oral permeation was found in both CBM2 and CBS2 nanoformulations comparing with the CB and S. repens CO 2 extract. The best performance was obtained by the CBM2 nanoformulation (~ 17%) predicting a 30 - 70% passive oral human absorption in vivo . Georg Thieme Verlag KG Stuttgart · New York.

Highly excited and exotic meson spectrum from dynamical lattice QCD.

PubMed

Dudek, Jozef J; Edwards, Robert G; Peardon, Michael J; Richards, David G; Thomas, Christopher E

2009-12-31

Using a new quark-field construction algorithm and a large variational basis of operators, we extract a highly excited isovector meson spectrum on dynamical anisotropic lattices. We show how carefully constructed operators can be used to reliably identify the continuum spin of extracted states, overcoming the reduced cubic symmetry of the lattice. Using this method we extract, with confidence, excited states, states with exotic quantum numbers (0+-, 1-+, and 2+-), and states of high spin, including, for the first time in lattice QCD, spin-four states.

Effects of Neutron-Star Dynamic Tides on Gravitational Waveforms within the Effective-One-Body Approach

NASA Astrophysics Data System (ADS)

Hinderer, Tanja; Taracchini, Andrea; Foucart, Francois; Buonanno, Alessandra; Steinhoff, Jan; Duez, Matthew; Kidder, Lawrence E.; Pfeiffer, Harald P.; Scheel, Mark A.; Szilagyi, Bela; Hotokezaka, Kenta; Kyutoku, Koutarou; Shibata, Masaru; Carpenter, Cory W.

2016-05-01

Extracting the unique information on ultradense nuclear matter from the gravitational waves emitted by merging neutron-star binaries requires robust theoretical models of the signal. We develop a novel effective-one-body waveform model that includes, for the first time, dynamic (instead of only adiabatic) tides of the neutron star as well as the merger signal for neutron-star-black-hole binaries. We demonstrate the importance of the dynamic tides by comparing our model against new numerical-relativity simulations of nonspinning neutron-star-black-hole binaries spanning more than 24 gravitational-wave cycles, and to other existing numerical simulations for double neutron-star systems. Furthermore, we derive an effective description that makes explicit the dependence of matter effects on two key parameters: tidal deformability and fundamental oscillation frequency.

Effects of Neutron-Star Dynamic Tides on Gravitational Waveforms within the Effective-One-Body Approach.

PubMed

Hinderer, Tanja; Taracchini, Andrea; Foucart, Francois; Buonanno, Alessandra; Steinhoff, Jan; Duez, Matthew; Kidder, Lawrence E; Pfeiffer, Harald P; Scheel, Mark A; Szilagyi, Bela; Hotokezaka, Kenta; Kyutoku, Koutarou; Shibata, Masaru; Carpenter, Cory W

2016-05-06

Extracting the unique information on ultradense nuclear matter from the gravitational waves emitted by merging neutron-star binaries requires robust theoretical models of the signal. We develop a novel effective-one-body waveform model that includes, for the first time, dynamic (instead of only adiabatic) tides of the neutron star as well as the merger signal for neutron-star-black-hole binaries. We demonstrate the importance of the dynamic tides by comparing our model against new numerical-relativity simulations of nonspinning neutron-star-black-hole binaries spanning more than 24 gravitational-wave cycles, and to other existing numerical simulations for double neutron-star systems. Furthermore, we derive an effective description that makes explicit the dependence of matter effects on two key parameters: tidal deformability and fundamental oscillation frequency.

Extraction of tryptophan with ionic liquids studied with molecular dynamics simulations.

PubMed

Seduraman, Abirami; Wu, Ping; Klähn, Marco

2012-01-12

Extraction of amino acids from aqueous solutions with ionic liquids (ILs) in biphasic systems is analyzed with molecular dynamics (MD) simulations. Extraction of tryptophan (TRP) with the imidazolium-based ILs [C(4)mim][PF(6)], [C(8)mim][PF(6)], and [C(8)mim][BF(4)] are considered as model cases. Solvation free energies of TRP are calculated with MD simulations and thermodynamic integration in combination with an empirical force field, whose parametrization is based on the liquid-phase charge distribution of the ILs. Calculated solvation free energies reproduce successfully all observed experimental trends according to the previously reported partition of TRP between water and IL phases. Water is present in ILs as a cosolvent, due to direct contact with the aqueous phase during extraction, and is found to play a major role in the extraction of TRP. Water improves solvation of cationic TRP by 7.8 and 5.1 kcal/mol in [C(4)mim][PF(6)] and [C(8)mim][PF(6)], respectively, which is in the case of [C(4)mim][PF(6)] sufficient to extract TRP. Extraction in [C(8)mim][PF(6)] is not feasible, since the hydrophobic octyl groups of the cations limit the water concentration in the IL. The solvation of cationic TRP is 2.4 kcal/mol less favorable in [C(8)mim][PF(6)] than in [C(4)mim][PF(6)]. Water improves the solvation of TRP in ILs mostly through dipole-dipole interactions with the polar backbone of TRP. Extraction is most efficient with [C(8)mim][BF(4)], where hydrophilic BF(4)(-) anions substantially increase the water concentration in the IL. Additionally, stronger direct electrostatic interactions of TRP with BF(4)(-) anions improve its solvation in the IL further. The solvation of cationic TRP in [C(8)mim][BF(4)] is 3.4 kcal/mol more favorable than in [C(8)mim][PF(6)]. Overall, the extractive power of the ILs correlates with the water saturation concentration of the IL phase, which in turn is determined by the hydrophilicity of the constituting ions. The results of this work identify relations between the extraction performance of ILs and the basic chemical properties of the ions, which provide guidelines that could contribute to the design of improved novel ILs for amino acid extraction.

Self-Organized Criticality and Scaling in Lifetime of Traffic Jams

NASA Astrophysics Data System (ADS)

Nagatani, Takashi

1995-01-01

The deterministic cellular automaton 184 (the one-dimensional asymmetric simple-exclusion model with parallel dynamics) is extended to take into account injection or extraction of particles. The model presents the traffic flow on a highway with inflow or outflow of cars.Introducing injection or extraction of particles into the asymmetric simple-exclusion model drives the system asymptotically into a steady state exhibiting a self-organized criticality. The typical lifetime of traffic jams scales as \\cong Lν with ν=0.65±0.04. It is shown that the cumulative distribution Nm (L) of lifetimes satisfies the finite-size scaling form Nm (L) \\cong L-1 f(m/Lν).

Dynamic microwave assisted extraction coupled with dispersive micro-solid-phase extraction of herbicides in soybeans.

PubMed

Li, Na; Wu, Lijie; Nian, Li; Song, Ying; Lei, Lei; Yang, Xiao; Wang, Kun; Wang, Zhibing; Zhang, Liyuan; Zhang, Hanqi; Yu, Aimin; Zhang, Ziwei

2015-09-01

Non-polar solvent dynamic microwave assisted extraction was firstly applied to the treatment of high-fat soybean samples. In the dispersive micro-solid-phase extraction (D-µ-SPE), the herbicides in the high-fat extract were directly adsorbed on metal-organic frameworks MIL-101(Cr). The effects of several experimental parameters, including extraction solvent, microwave absorption medium, microwave power, volume and flow rate of extraction solvent, amount of MIL-101(Cr), and D-µ-SPE time, were investigated. At the optimal conditions, the limits of detection for the herbicides ranged from 1.56 to 2.00 μg kg(-1). The relative recoveries of the herbicides were in the range of 91.1-106.7%, and relative standard deviations were equal to or lower than 6.7%. The present method was simple, rapid and effective. A large amount of fat was also removed. This method was demonstrated to be suitable for treatment of high-fat samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Reliability of unstable periodic orbit based control strategies in biological systems.

PubMed

Mishra, Nagender; Hasse, Maria; Biswal, B; Singh, Harinder P

2015-04-01

Presence of recurrent and statistically significant unstable periodic orbits (UPOs) in time series obtained from biological systems is now routinely used as evidence for low dimensional chaos. Extracting accurate dynamical information from the detected UPO trajectories is vital for successful control strategies that either aim to stabilize the system near the fixed point or steer the system away from the periodic orbits. A hybrid UPO detection method from return maps that combines topological recurrence criterion, matrix fit algorithm, and stringent criterion for fixed point location gives accurate and statistically significant UPOs even in the presence of significant noise. Geometry of the return map, frequency of UPOs visiting the same trajectory, length of the data set, strength of the noise, and degree of nonstationarity affect the efficacy of the proposed method. Results suggest that establishing determinism from unambiguous UPO detection is often possible in short data sets with significant noise, but derived dynamical properties are rarely accurate and adequate for controlling the dynamics around these UPOs. A repeat chaos control experiment on epileptic hippocampal slices through more stringent control strategy and adaptive UPO tracking is reinterpreted in this context through simulation of similar control experiments on an analogous but stochastic computer model of epileptic brain slices. Reproduction of equivalent results suggests that far more stringent criteria are needed for linking apparent success of control in such experiments with possible determinism in the underlying dynamics.

Reliability of unstable periodic orbit based control strategies in biological systems

NASA Astrophysics Data System (ADS)

Mishra, Nagender; Hasse, Maria; Biswal, B.; Singh, Harinder P.

2015-04-01

Presence of recurrent and statistically significant unstable periodic orbits (UPOs) in time series obtained from biological systems is now routinely used as evidence for low dimensional chaos. Extracting accurate dynamical information from the detected UPO trajectories is vital for successful control strategies that either aim to stabilize the system near the fixed point or steer the system away from the periodic orbits. A hybrid UPO detection method from return maps that combines topological recurrence criterion, matrix fit algorithm, and stringent criterion for fixed point location gives accurate and statistically significant UPOs even in the presence of significant noise. Geometry of the return map, frequency of UPOs visiting the same trajectory, length of the data set, strength of the noise, and degree of nonstationarity affect the efficacy of the proposed method. Results suggest that establishing determinism from unambiguous UPO detection is often possible in short data sets with significant noise, but derived dynamical properties are rarely accurate and adequate for controlling the dynamics around these UPOs. A repeat chaos control experiment on epileptic hippocampal slices through more stringent control strategy and adaptive UPO tracking is reinterpreted in this context through simulation of similar control experiments on an analogous but stochastic computer model of epileptic brain slices. Reproduction of equivalent results suggests that far more stringent criteria are needed for linking apparent success of control in such experiments with possible determinism in the underlying dynamics.

Bifurcation and response analysis of a nonlinear flexible rotating disc immersed in bounded compressible fluid

NASA Astrophysics Data System (ADS)

Remigius, W. Dheelibun; Sarkar, Sunetra; Gupta, Sayan

2017-03-01

Use of heavy gases in centrifugal compressors for enhanced oil extraction have made the impellers susceptible to failures through acousto-elastic instabilities. This study focusses on understanding the dynamical behavior of such systems by considering the effects of the bounded fluid housed in a casing on a rotating disc. First, a mathematical model is developed that incorporates the interaction between the rotating impeller - modelled as a flexible disc - and the bounded compressible fluid medium in which it is immersed. The nonlinear effects arising due to large deformations of the disc have been included in the formulation so as to capture the post flutter behavior. A bifurcation analysis is carried out with the disc rotational speed as the bifurcation parameter to investigate the dynamical behavior of the coupled system and estimate the stability boundaries. Parametric studies reveal that the relative strengths of the various dissipation mechanisms in the coupled system play a significant role that affect the bifurcation route and the post flutter behavior in the acousto-elastic system.

Periodic thermodynamics of open quantum systems.

PubMed

Brandner, Kay; Seifert, Udo

2016-06-01

The thermodynamics of quantum systems coupled to periodically modulated heat baths and work reservoirs is developed. By identifying affinities and fluxes, the first and the second law are formulated consistently. In the linear response regime, entropy production becomes a quadratic form in the affinities. Specializing to Lindblad dynamics, we identify the corresponding kinetic coefficients in terms of correlation functions of the unperturbed dynamics. Reciprocity relations follow from symmetries with respect to time reversal. The kinetic coefficients can be split into a classical and a quantum contribution subject to an additional constraint, which follows from a natural detailed balance condition. This constraint implies universal bounds on efficiency and power of quantum heat engines. In particular, we show that Carnot efficiency cannot be reached whenever quantum coherence effects are present, i.e., when the Hamiltonian used for work extraction does not commute with the bare system Hamiltonian. For illustration, we specialize our universal results to a driven two-level system in contact with a heat bath of sinusoidally modulated temperature.

Periodic thermodynamics of open quantum systems

NASA Astrophysics Data System (ADS)

Brandner, Kay; Seifert, Udo

2016-06-01

The thermodynamics of quantum systems coupled to periodically modulated heat baths and work reservoirs is developed. By identifying affinities and fluxes, the first and the second law are formulated consistently. In the linear response regime, entropy production becomes a quadratic form in the affinities. Specializing to Lindblad dynamics, we identify the corresponding kinetic coefficients in terms of correlation functions of the unperturbed dynamics. Reciprocity relations follow from symmetries with respect to time reversal. The kinetic coefficients can be split into a classical and a quantum contribution subject to an additional constraint, which follows from a natural detailed balance condition. This constraint implies universal bounds on efficiency and power of quantum heat engines. In particular, we show that Carnot efficiency cannot be reached whenever quantum coherence effects are present, i.e., when the Hamiltonian used for work extraction does not commute with the bare system Hamiltonian. For illustration, we specialize our universal results to a driven two-level system in contact with a heat bath of sinusoidally modulated temperature.

Real-time observation of fluctuations in a driven-dissipative quantum many-body system undergoing a phase transition

NASA Astrophysics Data System (ADS)

Donner, Tobias

2015-03-01

A Bose-Einstein condensate whose motional degrees of freedom are coupled to a high-finesse optical cavity via a transverse pump beam constitutes a dissipative quantum many-body system with long range interactions. These interactions can induce a structural phase transition from a flat to a density-modulated state. The transverse pump field simultaneously represents a probe of the atomic density via cavity- enhanced Bragg scattering. By spectrally analyzing the light field leaking out of the cavity, we measure non-destructively the dynamic structure factor of the fluctuating atomic density while the system undergoes the phase transition. An observed asymmetry in the dynamic structure factor is attributed to the coupling to dissipative baths. Critical exponents for both sides of the phase transition can be extracted from the data. We further discuss our progress in adding strong short-range interactions to this system, in order to explore Bose-Hubbard physics with cavity-mediated long-range interactions and self-organization in lower dimensions.

In Vitro Anti/Pro-oxidant Activities of R. ferruginea Extract and Its Effect on Glioma Cell Viability: Correlation with Phenolic Compound Content and Effects on Membrane Dynamics.

PubMed

Dos Santos, Desirée Magalhães; Rocha, Camila Valesca Jardim; da Silveira, Elita Ferreira; Marinho, Marcelo Augusto Germani; Rodrigues, Marisa Raquel; Silva, Nichole Osti; da Silva Ferreira, Ailton; de Moura, Neusa Fernandes; Darelli, Gabriel Jorge Sagrera; Braganhol, Elizandra; Horn, Ana Paula; de Lima, Vânia Rodrigues

2018-04-01

Rapanea ferruginea antioxidant and antitumoral properties were not explored before in literature. This study aimed to investigate these biological activities for the R. ferruginea leaf extract and correlate them with its phenolic content and influence in biological membrane dynamics. Thus, in this study, anti/pro-oxidative properties of R. ferruginea leaf extract by in vitro DPPH and TBARS assays, with respect to the free radical reducing potential and to its activity regarding membrane free radical-induced peroxidation, respectively. Furthermore, preliminary tests related to the extract effect on in vitro glioma cell viability were also performed. In parallel, the phenolic content was detected by HPLC-DAD and included syringic and trans-cinnamic acids, quercetrin, catechin, quercetin, and gallic acid. In an attempt to correlate the biological activity of R. ferruginea extract and its effect on membrane dynamics, the molecular interaction between the extract and a liposomal model with natural-sourced phospholipids was investigated. Location and changes in vibrational, rotational, and translational lipid motions, as well as in the phase state of liposomes, induced by R. ferruginea extract, were monitored by Fourier-transform infrared spectroscopy, nuclear magnetic resonance, differential scanning calorimetry, and UV-visible spectroscopy. In its free form, the extract showed promising in vitro antioxidant properties. Free-form extract (at 1000µ g/mL) exposure reduced glioma cell in vitro viability in 40%, as evidenced by MTT tests. Pro-oxidant behavior was observed when the extract was loaded into liposomes. A 70.8% cell viability reduction was achieved with 500 µg/mL of liposome-loaded extract. The compounds of R. ferruginea extract ordered liposome interface and disorder edits a polar region. Phenolic content, as well as membrane interaction and modulation may have an important role in the oxidative and antitumoral activities of the R. ferruginea leaf extract.

PDMS Network Structure-Property Relationships: Influence of Molecular Architecture on Mechanical and Wetting Properties

NASA Astrophysics Data System (ADS)

Melillo, Matthew Joseph

Poly(dimethylsiloxane) (PDMS) is one of the most common elastomers, with applications ranging from sealants and marine-antifouling coatings to medical devices and absorbents for water treatment. Fundamental understanding of how liquids spread on the surface of and absorb into and leach out of PDMS networks is of critical importance for the design and use in another application - microfluidic devices. The growing use of PDMS in microfluidic devices raises the concern that some researchers may use this material without fully understanding all of its advantages, drawbacks, and intricacies. The primary goal of this Ph.D. dissertation is to elucidate PDMS network molecular structure to macroscopic property relationships and to demonstrate how molecular architecture can alter dynamic mechanical and wetting characteristics. We prepare PDMS materials by using vinyl/ tetrakis(dimethylsiloxy)silane (TDSS) and silanol/ tetraethylorthosilicate (TEOS) combinations of PDMS end-groups and crosslinkers as two model systems. Under constant curing conditions, we systematically study the effects of polymer molecular weight, loading of crosslinker, and end-group chemical functionality on the extent of gelation and the dynamic mechanical and water wetting properties of end-linked PDMS networks. The extent of the gelation reaction is determined using the Soxhlet extraction to quantify the amount of material that did and did not participate in the crosslinking reactions, termed the gel and sol fractions, respectively. We use the Miller-Macosko model in conjunction with the gel fraction and precise chemical composition (i.e., stoichiometric ratio and molecular weight) to determine the fractions of elastic and pendant material, the molecular weight between chemical crosslinks, and the average effective functionality of the crosslinker molecule. Based on dynamic mechanical testing, we find that the maximum storage moduli are achieved at optimal stoichiometric conditions in the vinyl/TDSS and commercial PDMS-based Sylgard 184 composite, but only keep improving with additional crosslinker in the silanol/TEOS systems due to in situ TEOS aggregation. We relate molecular network topology to mechanical properties using outputs from the Miller-Macosko model in the vinyl/TDSS system. The elastic fraction and storage modulus correlate well, as do the pendant fraction and the loss tangent, demonstrating the importance of each fraction in bulk mechanical properties. By studying the dynamic behavior of water droplets wetting PDMS substrates, we observe non-linear wetting behaviors that are markedly different from linear behaviors seen on glassy polymer substrates. The non-linear behavior is only observed prior to extraction, while after extraction, both systems demonstrate behavior similar to glassy polymers. This reveals the dramatic role small amounts of uncrosslinked materials present in the sol fraction play in the surface wetting dynamics of PDMS materials. We further demonstrate the role of uncrosslinked material by adding silicone oils into otherwise fully crosslinked PDMS networks and study their wetting properties. Through careful formulation and preparation of PDMS materials, compared to simply mixing two formulations present in Sylgard 184, one can apply polymer network models to glean useful information about network topology. The benefits of doing so outweigh the costs. We stress the importance of performing Soxhlet extraction to remove unreacted components from PDMS materials, even when using optimal stoichiometry. These mobile molecules that remain after crosslinking can alter significantly wetting behavior and readily leach into liquid environments. However, it is equally important to stress that Soxhlet extraction will not remove all unreacted material. Some will always remain in PDMS, which is often the practice in preparing microfluidic devices. While Sylgard 184 is very well suited for some applications, the results presented in this dissertation demonstrate to researchers that the material does have its limitations and that other options are available. These findings will aid in the design and implementation of reliable microfluidic devices and other PDMS-based materials that encounter liquid interfaces.

Analysis of the dynamic behavior of structures using the high-rate GNSS-PPP method combined with a wavelet-neural model: Numerical simulation and experimental tests

NASA Astrophysics Data System (ADS)

Kaloop, Mosbeh R.; Yigit, Cemal O.; Hu, Jong W.

2018-03-01

Recently, the high rate global navigation satellite system-precise point positioning (GNSS-PPP) technique has been used to detect the dynamic behavior of structures. This study aimed to increase the accuracy of the extraction oscillation properties of structural movements based on the high-rate (10 Hz) GNSS-PPP monitoring technique. A developmental model based on the combination of wavelet package transformation (WPT) de-noising and neural network prediction (NN) was proposed to improve the dynamic behavior of structures for GNSS-PPP method. A complicated numerical simulation involving highly noisy data and 13 experimental cases with different loads were utilized to confirm the efficiency of the proposed model design and the monitoring technique in detecting the dynamic behavior of structures. The results revealed that, when combined with the proposed model, GNSS-PPP method can be used to accurately detect the dynamic behavior of engineering structures as an alternative to relative GNSS method.

Principal component analysis of indocyanine green fluorescence dynamics for diagnosis of vascular diseases

NASA Astrophysics Data System (ADS)

Seo, Jihye; An, Yuri; Lee, Jungsul; Choi, Chulhee

2015-03-01

Indocyanine green (ICG), a near-infrared fluorophore, has been used in visualization of vascular structure and non-invasive diagnosis of vascular disease. Although many imaging techniques have been developed, there are still limitations in diagnosis of vascular diseases. We have recently developed a minimally invasive diagnostics system based on ICG fluorescence imaging for sensitive detection of vascular insufficiency. In this study, we used principal component analysis (PCA) to examine ICG spatiotemporal profile and to obtain pathophysiological information from ICG dynamics. Here we demonstrated that principal components of ICG dynamics in both feet showed significant differences between normal control and diabetic patients with vascula complications. We extracted the PCA time courses of the first three components and found distinct pattern in diabetic patient. We propose that PCA of ICG dynamics reveal better classification performance compared to fluorescence intensity analysis. We anticipate that specific feature of spatiotemporal ICG dynamics can be useful in diagnosis of various vascular diseases.

Experimental Determination of the Dynamic Hydraulic Transfer Function for the J-2X Oxidizer Turbopump. Part One; Methodology

NASA Technical Reports Server (NTRS)

Zoladz, Tom; Patel, Sandeep; Lee, Erik; Karon, Dave

2011-01-01

An advanced methodology for extracting the hydraulic dynamic pump transfer matrix (Yp) for a cavitating liquid rocket engine turbopump inducer+impeller has been developed. The transfer function is required for integrated vehicle pogo stability analysis as well as optimization of local inducer pumping stability. Laboratory pulsed subscale waterflow test of the J-2X oxygen turbo pump is introduced and our new extraction method applied to the data collected. From accurate measures of pump inlet and discharge perturbational mass flows and pressures, and one-dimensional flow models that represents complete waterflow loop physics, we are able to derive Yp and hence extract the characteristic pump parameters: compliance, pump gain, impedance, mass flow gain. Detailed modeling is necessary to accurately translate instrument plane measurements to the pump inlet and discharge and extract Yp. We present the MSFC Dynamic Lump Parameter Fluid Model Framework and describe critical dynamic component details. We report on fit minimization techniques, cost (fitness) function derivation, and resulting model fits to our experimental data are presented. Comparisons are made to alternate techniques for spatially translating measurement stations to actual pump inlet and discharge.

Thermal energy storage to minimize cost and improve efficiency of a polygeneration district energy system in a real-time electricity market

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

Powell, Kody M.; Kim, Jong Suk; Cole, Wesley J.

2016-10-01

District energy systems can produce low-cost utilities for large energy networks, but can also be a resource for the electric grid by their ability to ramp production or to store thermal energy by responding to real-time market signals. In this work, dynamic optimization exploits the flexibility of thermal energy storage by determining optimal times to store and extract excess energy. This concept is applied to a polygeneration distributed energy system with combined heat and power, district heating, district cooling, and chilled water thermal energy storage. The system is a university campus responsible for meeting the energy needs of tens ofmore » thousands of people. The objective for the dynamic optimization problem is to minimize cost over a 24-h period while meeting multiple loads in real time. The paper presents a novel algorithm to solve this dynamic optimization problem with energy storage by decomposing the problem into multiple static mixed-integer nonlinear programming (MINLP) problems. Another innovative feature of this work is the study of a large, complex energy network which includes the interrelations of a wide variety of energy technologies. Results indicate that a cost savings of 16.5% is realized when the system can participate in the wholesale electricity market.« less

Polymeric ionic liquid modified graphene oxide-grafted silica for solid-phase extraction to analyze the excretion-dynamics of flavonoids in urine by Box-Behnken statistical design.

PubMed

Hou, Xiudan; Liu, Shujuan; Zhou, Panpan; Li, Jin; Liu, Xia; Wang, Licheng; Guo, Yong

2016-07-22

A solid-phase extraction method for the efficient analysis of the excretion-dynamics of flavonoids in urine was established and described. In this work, in situ surface radical chain-transfer polymerization and in situ anion exchange were utilized to tune the extraction performance of poly(1-vinyl-3-hexylimidazolium bromide)-graphene oxide-grafted silica (poly(VHIm(+)Br(-))@GO@Sil). Graphene oxide (GO) was first coated onto the silica using a layer-by-layer fabrication method, and then the anion of poly(VHIm(+)Br(-))@GO@Sil was changed into hexafluorophosphate (PF6(-)) by in situ anion exchange. The interaction energies between two PILs and four flavonoids were calculated with the Gaussian09 suite of programs. A Box-Behnken design was used for the optimization of four greatly influential parameters after single-factor experiments to obtain more accurate and precise results. Coupled to high performance liquid chromatography, the poly(VHIm(+)PF6(-))@GO@Sil method showed acceptable extraction recoveries for the four flavonoids, with limits of detection in the range of 0.1-0.5μgL(-1), and wide linear ranges with correlation coefficients (R) ranging from 0.9935 to 0.9987. Under the optimum conditions, the proposed method was applied to analyze the urines collected from a healthy volunteer. The excretion amount-time profiles revealed that 4-15h was the main excretion time for the detected flavonoids. The results indicated that the newly developed method offered the advantages of being feasible, green and cost-effective, and could be successfully applied to the extraction and enrichment of flavonoids in human body systems allowing the study of the metabolic kinetics. Copyright © 2016. Published by Elsevier B.V.

Extracting Dynamic Evidence Networks

DTIC Science & Technology

2004-12-01

on the performance of the three models as a function of training set size, and on experiments showing the viability of using active learning techniques...potential relation instances, which include 28K actual relations. 2.3.2 Active Learning We also ran a set of experiments designed to explore the...viability of using active learning techniques to maximize the usefulness of the training data annotated for use by the system. The idea is to

Dynamic Bayesian wavelet transform: New methodology for extraction of repetitive transients

NASA Astrophysics Data System (ADS)

Wang, Dong; Tsui, Kwok-Leung

2017-05-01

Thanks to some recent research works, dynamic Bayesian wavelet transform as new methodology for extraction of repetitive transients is proposed in this short communication to reveal fault signatures hidden in rotating machine. The main idea of the dynamic Bayesian wavelet transform is to iteratively estimate posterior parameters of wavelet transform via artificial observations and dynamic Bayesian inference. First, a prior wavelet parameter distribution can be established by one of many fast detection algorithms, such as the fast kurtogram, the improved kurtogram, the enhanced kurtogram, the sparsogram, the infogram, continuous wavelet transform, discrete wavelet transform, wavelet packets, multiwavelets, empirical wavelet transform, empirical mode decomposition, local mean decomposition, etc.. Second, artificial observations can be constructed based on one of many metrics, such as kurtosis, the sparsity measurement, entropy, approximate entropy, the smoothness index, a synthesized criterion, etc., which are able to quantify repetitive transients. Finally, given artificial observations, the prior wavelet parameter distribution can be posteriorly updated over iterations by using dynamic Bayesian inference. More importantly, the proposed new methodology can be extended to establish the optimal parameters required by many other signal processing methods for extraction of repetitive transients.

Non-criticality of interaction network over system's crises: A percolation analysis.

PubMed

Shirazi, Amir Hossein; Saberi, Abbas Ali; Hosseiny, Ali; Amirzadeh, Ehsan; Toranj Simin, Pourya

2017-11-20

Extraction of interaction networks from multi-variate time-series is one of the topics of broad interest in complex systems. Although this method has a wide range of applications, most of the previous analyses have focused on the pairwise relations. Here we establish the potential of such a method to elicit aggregated behavior of the system by making a connection with the concepts from percolation theory. We study the dynamical interaction networks of a financial market extracted from the correlation network of indices, and build a weighted network. In correspondence with the percolation model, we find that away from financial crises the interaction network behaves like a critical random network of Erdős-Rényi, while close to a financial crisis, our model deviates from the critical random network and behaves differently at different size scales. We perform further analysis to clarify that our observation is not a simple consequence of the growth in correlations over the crises.

Traffic flow behavior at un-signalized intersection with crossings pedestrians

NASA Astrophysics Data System (ADS)

Khallouk, A.; Echab, H.; Ez-Zahraouy, H.; Lakouari, N.

2018-02-01

Mixed traffic flux composed of crossing pedestrians and vehicles extensively exists in cities. To study the characteristics of the interference traffic flux, we develop a pedestrian-vehicle cellular automata model to present the interaction behaviors on a simple cross road. By realizing the fundamental parameters (i.e. injecting rates α1, α2, the extracting rate β and the pedestrian arrival rate αP), simulations are carried out. The vehicular traffic flux is calculated in terms of rates. The effect of the crosswalk can be regarded as a dynamic impurity. The system phase diagrams in the (α1 ,αP) plane are built. It is found that the phase diagrams consist essentially of four phases namely Free Flow, Congested, Maximal Current and Gridlock. The value of the Maximal current phase depends on the extracting rate β, while the Gridlock phase is achieved only when the pedestrians generating rate is higher than a critical value. Furthermore, the effect of vehicles changing lane (Pch1 ,Pch2) and the location of the crosswalk XP on the dynamic characteristics of vehicles flow are investigated. It is found that traffic situation in the system is slightly enhanced if the location of the crosswalks XP is far from the intersection. However, when Pch1, Pch2 increase, the traffic becomes congested and the Gridlock phase enlarges.

Rhythmic Extended Kalman Filter for Gait Rehabilitation Motion Estimation and Segmentation.

PubMed

Joukov, Vladimir; Bonnet, Vincent; Karg, Michelle; Venture, Gentiane; Kulic, Dana

2018-02-01

This paper proposes a method to enable the use of non-intrusive, small, wearable, and wireless sensors to estimate the pose of the lower body during gait and other periodic motions and to extract objective performance measures useful for physiotherapy. The Rhythmic Extended Kalman Filter (Rhythmic-EKF) algorithm is developed to estimate the pose, learn an individualized model of periodic movement over time, and use the learned model to improve pose estimation. The proposed approach learns a canonical dynamical system model of the movement during online observation, which is used to accurately model the acceleration during pose estimation. The canonical dynamical system models the motion as a periodic signal. The estimated phase and frequency of the motion also allow the proposed approach to segment the motion into repetitions and extract useful features, such as gait symmetry, step length, and mean joint movement and variance. The algorithm is shown to outperform the extended Kalman filter in simulation, on healthy participant data, and stroke patient data. For the healthy participant marching dataset, the Rhythmic-EKF improves joint acceleration and velocity estimates over regular EKF by 40% and 37%, respectively, estimates joint angles with 2.4° root mean squared error, and segments the motion into repetitions with 96% accuracy.

Automatic Human Movement Assessment With Switching Linear Dynamic System: Motion Segmentation and Motor Performance.

PubMed

de Souza Baptista, Roberto; Bo, Antonio P L; Hayashibe, Mitsuhiro

2017-06-01

Performance assessment of human movement is critical in diagnosis and motor-control rehabilitation. Recent developments in portable sensor technology enable clinicians to measure spatiotemporal aspects to aid in the neurological assessment. However, the extraction of quantitative information from such measurements is usually done manually through visual inspection. This paper presents a novel framework for automatic human movement assessment that executes segmentation and motor performance parameter extraction in time-series of measurements from a sequence of human movements. We use the elements of a Switching Linear Dynamic System model as building blocks to translate formal definitions and procedures from human movement analysis. Our approach provides a method for users with no expertise in signal processing to create models for movements using labeled dataset and later use it for automatic assessment. We validated our framework on preliminary tests involving six healthy adult subjects that executed common movements in functional tests and rehabilitation exercise sessions, such as sit-to-stand and lateral elevation of the arms and five elderly subjects, two of which with limited mobility, that executed the sit-to-stand movement. The proposed method worked on random motion sequences for the dual purpose of movement segmentation (accuracy of 72%-100%) and motor performance assessment (mean error of 0%-12%).

Extracting motor synergies from random movements for low-dimensional task-space control of musculoskeletal robots.

PubMed

Fu, Kin Chung Denny; Dalla Libera, Fabio; Ishiguro, Hiroshi

2015-10-08

In the field of human motor control, the motor synergy hypothesis explains how humans simplify body control dimensionality by coordinating groups of muscles, called motor synergies, instead of controlling muscles independently. In most applications of motor synergies to low-dimensional control in robotics, motor synergies are extracted from given optimal control signals. In this paper, we address the problems of how to extract motor synergies without optimal data given, and how to apply motor synergies to achieve low-dimensional task-space tracking control of a human-like robotic arm actuated by redundant muscles, without prior knowledge of the robot. We propose to extract motor synergies from a subset of randomly generated reaching-like movement data. The essence is to first approximate the corresponding optimal control signals, using estimations of the robot's forward dynamics, and to extract the motor synergies subsequently. In order to avoid modeling difficulties, a learning-based control approach is adopted such that control is accomplished via estimations of the robot's inverse dynamics. We present a kernel-based regression formulation to estimate the forward and the inverse dynamics, and a sliding controller in order to cope with estimation error. Numerical evaluations show that the proposed method enables extraction of motor synergies for low-dimensional task-space control.

Model studies on the release of aroma compounds from structured and nonstructured oil systems using proton-transfer reaction mass spectrometry.

PubMed

Landy, Pascale; Pollien, Philippe; Rytz, Andreas; Leser, Martin E; Sagalowicz, Laurent; Blank, Imre; Spadone, Jean-Claude

2007-03-07

Relative retention, volatility, and temporal release of volatile compounds taken from aldehyde, ester, and alcohol chemical classes were studied at 70 degrees C in model systems using equilibrium static headspace analysis and real time dynamic headspace analysis. These systems were medium-chain triglycerides (MCT), sunflower oil, and two structured systems, i.e., water-in-oil emulsion and L2 phase (water-in-oil microemulsion). Hydrophilic domains of the emulsion type media retained specifically the hydrophilic compounds and alcohols. Four kinetic parameters characterizing the concentration- and time-dependent releases were extracted from the aroma release curves. Most of the kinetic parameter values were higher in structured systems than in oils particularly when using MCT. The oil nature was found to better control the dynamic release profiles than the system structures. The release parameters were well-related (i) to the volatile hydrophobicity as a function of the oil used and (ii) to the retention data in the specific case of the L2 phase due to a specific release behavior of alcohols.

Impact of Microorganisms on the Dynamics of Unsaturated Flow Within Fractures

NASA Astrophysics Data System (ADS)

Stoner, D. L.; Stedtfeld, R. D.; Tyler, T. L.; White, F. J.; McJunkin, T. R.

2002-12-01

Understanding the impact of microorganisms on fluid flow in groundwater and subsurface environments is of significance because of the importance of natural water resources, contaminant transport, and in situ bioprocesses such as mineral dissolution and recovery, enhanced oil recovery, and remediation. In this study, the impact of microorganisms and nutrient amendments on the behavior of water within a fracture system was evaluated using an experimental system comprised of limestone blocks and a groundwater isolate, {\\ it Sphingomonas} sp. Four blocks (25 cm x 6.6 cm x 5 cm) were configured to make a vertical fracture (50.2 x 5 x 0.07 cm) that was intersected by a horizontal fracture (13.4 x 5 x 0.1 cm). To monitor the behavior of water within the fracture, 5 optical sensors each consisting of a light emitting diode and photocell were installed external to the vertical fracture. Two were installed above the fracture intersection, two below and one at the intersection. The presence of fluid in the fracture was detected as a decrease in light transmission as the fluid passed by each detector. Drop interval (the period of time between succeeding drops at the same detector) and drop width (the period of time it took for a water drop or stream to pass by each detector) data were collected for each of the five detectors. Liquids were introduced via a single needle at the top of the fracture at a rate of 0.5 ml/min. Deionized water, which had been chemically equilibrated with the limestone rock, was the control medium to which 1) cells; 2) cells with 0.01% yeast extract; 3) cells with 0.1% yeast extract; and 4) cells with 0.1% yeast extract and 30 mM urea were added. For the equilibrated water, drop intervals and drop widths above the fracture intersection were ~1 s and <0.1 s, respectively. Drop intervals and drop widths at and below the intersection were ~100 s and ~10 s, respectively. Above the fracture intersection, the addition of cells or cells with 0.01% yeast extract had little effect on drop intervals and drop widths. At and below the intersection, however, drop intervals increased to ~500 s and drop widths to ~10 s. Later with the addition of 0.1% yeast extract or 0.1% yeast extract with urea, drop interval and drop width immediately increased at locations above the fracture intersection and within 24 hours, continuous streaming was observed. For the lower sensors, drop interval and drop width initially decreased, followed by continuous streaming the day after the 0.1% yeast extract and urea was added to the system. In conclusion, the dynamics of drop behavior in fracture systems is a complex process that is impacted by the presence of bacteria and nutrient amendments as well as the fracture configuration.

Identifying compromised systems through correlation of suspicious traffic from malware behavioral analysis

NASA Astrophysics Data System (ADS)

Camilo, Ana E. F.; Grégio, André; Santos, Rafael D. C.

2016-05-01

Malware detection may be accomplished through the analysis of their infection behavior. To do so, dynamic analysis systems run malware samples and extract their operating system activities and network traffic. This traffic may represent malware accessing external systems, either to steal sensitive data from victims or to fetch other malicious artifacts (configuration files, additional modules, commands). In this work, we propose the use of visualization as a tool to identify compromised systems based on correlating malware communications in the form of graphs and finding isomorphisms between them. We produced graphs from over 6 thousand distinct network traffic files captured during malware execution and analyzed the existing relationships among malware samples and IP addresses.

Visualization of suspicious lesions in breast MRI based on intelligent neural systems

NASA Astrophysics Data System (ADS)

Twellmann, Thorsten; Lange, Oliver; Nattkemper, Tim Wilhelm; Meyer-Bäse, Anke

2006-05-01

Intelligent medical systems based on supervised and unsupervised artificial neural networks are applied to the automatic visualization and classification of suspicious lesions in breast MRI. These systems represent an important component of future sophisticated computer-aided diagnosis systems and enable the extraction of spatial and temporal features of dynamic MRI data stemming from patients with confirmed lesion diagnosis. By taking into account the heterogenity of the cancerous tissue, these techniques reveal the malignant, benign and normal kinetic signals and and provide a regional subclassification of pathological breast tissue. Intelligent medical systems are expected to have substantial implications in healthcare politics by contributing to the diagnosis of indeterminate breast lesions by non-invasive imaging.

Molecular Dynamics Simulation of Mahkota Dewa (Phaleria Macrocarpa) Extract in Subcritical Water Extraction Process

NASA Astrophysics Data System (ADS)

Hashim, N. A.; Mudalip, S. K. Abdul; Harun, N.; Che Man, R.; Sulaiman, S. Z.; Arshad, Z. I. M.; Shaarani, S. M.

2018-05-01

Mahkota Dewa (Phaleria Macrocarpa), a good source of saponin, flavanoid, polyphenol, alkaloid, and mangiferin has an extensive range of medicinal effects. The intermolecular interactions between solute and solvents such as hydrogen bonding considered as an important factor that affect the extraction of bioactive compounds. In this work, molecular dynamics simulation was performed to elucidate the hydrogen bonding exists between Mahkota Dewa extracts and water during subcritical extraction process. A bioactive compound in the Mahkota Dewa extract, namely mangiferin was selected as a model compound. The simulation was performed at 373 K and 4.0 MPa using COMPASS force field and Ewald summation method available in Material Studio 7.0 simulation package. The radial distribution functions (RDF) between mangiferin and water signify the presence of hydrogen bonding in the extraction process. The simulation of the binary mixture of mangiferin:water shows that strong hydrogen bonding was formed. It is suggested that, the intermolecular interaction between OH2O••HMR4(OH1) has been identified to be responsible for the mangiferin extraction process.

Update: Advancement of Contact Dynamics Modeling for Human Spaceflight Simulation Applications

NASA Technical Reports Server (NTRS)

Brain, Thomas A.; Kovel, Erik B.; MacLean, John R.; Quiocho, Leslie J.

2017-01-01

Pong is a new software tool developed at the NASA Johnson Space Center that advances interference-based geometric contact dynamics based on 3D graphics models. The Pong software consists of three parts: a set of scripts to extract geometric data from 3D graphics models, a contact dynamics engine that provides collision detection and force calculations based on the extracted geometric data, and a set of scripts for visualizing the dynamics response with the 3D graphics models. The contact dynamics engine can be linked with an external multibody dynamics engine to provide an integrated multibody contact dynamics simulation. This paper provides a detailed overview of Pong including the overall approach and modeling capabilities, which encompasses force generation from contact primitives and friction to computational performance. Two specific Pong-based examples of International Space Station applications are discussed, and the related verification and validation using this new tool are also addressed.

Global minimum profile error (GMPE) - a least-squares-based approach for extracting macroscopic rate coefficients for complex gas-phase chemical reactions.

PubMed

Duong, Minh V; Nguyen, Hieu T; Mai, Tam V-T; Huynh, Lam K

2018-01-03

Master equation/Rice-Ramsperger-Kassel-Marcus (ME/RRKM) has shown to be a powerful framework for modeling kinetic and dynamic behaviors of a complex gas-phase chemical system on a complicated multiple-species and multiple-channel potential energy surface (PES) for a wide range of temperatures and pressures. Derived from the ME time-resolved species profiles, the macroscopic or phenomenological rate coefficients are essential for many reaction engineering applications including those in combustion and atmospheric chemistry. Therefore, in this study, a least-squares-based approach named Global Minimum Profile Error (GMPE) was proposed and implemented in the MultiSpecies-MultiChannel (MSMC) code (Int. J. Chem. Kinet., 2015, 47, 564) to extract macroscopic rate coefficients for such a complicated system. The capability and limitations of the new approach were discussed in several well-defined test cases.

Capturing Revolute Motion and Revolute Joint Parameters with Optical Tracking

NASA Astrophysics Data System (ADS)

Antonya, C.

2017-12-01

Optical tracking of users and various technical systems are becoming more and more popular. It consists of analysing sequence of recorded images using video capturing devices and image processing algorithms. The returned data contains mainly point-clouds, coordinates of markers or coordinates of point of interest. These data can be used for retrieving information related to the geometry of the objects, but also to extract parameters for the analytical model of the system useful in a variety of computer aided engineering simulations. The parameter identification of joints deals with extraction of physical parameters (mainly geometric parameters) for the purpose of constructing accurate kinematic and dynamic models. The input data are the time-series of the marker’s position. The least square method was used for fitting the data into different geometrical shapes (ellipse, circle, plane) and for obtaining the position and orientation of revolute joins.

Synchronous Motions Across the Instrumental Climate Record

NASA Astrophysics Data System (ADS)

Carl, Peter

The Earth's climate system bears a rich variety of feedback mechanisms that may give rise to complex, evolving modal structures under internal and external control. Various types of synchronization may be identified in the system's motion when looking at representative time series of the instrumental period through the glasses of an advanced technique of sparse data approximation, the Matching Pursuit (MP) approach. To disentangle the emerging network of oscillatory modes to the degree that climate dynamics turns out to be separable, a large dictionary of "Gaussian logons," i.e. frequency modulated (FM) Gabor atoms, is applied. Though the extracted modes make up linear decompositions, this flexible analyzing signal matches highly nonlinear waveforms. Univariate analyses over the period 1870-1997 are presented of a set of customary time series in annual resolution, comprising global and regional climate, central European synoptic systems, German precipitation, and runoff of the Elbe river near Dresden. All the evidence from this first-generation MP-FM study, obtained in subsequent multivariate syntheses, points to dynamically excited regimes of an organized yet complex climate system under permanent change—perhaps a (pre)chaotic one at centennial timescales, suggesting a "chaos control" perspective on global climate dynamics and change. Findings and conclusions include, among others, internal structure of reconstructed insolation, the episodic nature of global warming as reflected in multidecadal temperature modes, their swarm of "interdomain" companions across the whole system that unveils an unknown regime character of interannual climate dynamics, and the apparent onset early in the 1990s of the present thermal stagnation.

Parametric Identification of Nonlinear Dynamical Systems

NASA Technical Reports Server (NTRS)

Feeny, Brian

2002-01-01

In this project, we looked at the application of harmonic balancing as a tool for identifying parameters (HBID) in a nonlinear dynamical systems with chaotic responses. The main idea is to balance the harmonics of periodic orbits extracted from measurements of each coordinate during a chaotic response. The periodic orbits are taken to be approximate solutions to the differential equations that model the system, the form of the differential equations being known, but with unknown parameters to be identified. Below we summarize the main points addressed in this work. The details of the work are attached as drafts of papers, and a thesis, in the appendix. Our study involved the following three parts: (1) Application of the harmonic balance to a simulation case in which the differential equation model has known form for its nonlinear terms, in contrast to a differential equation model which has either power series or interpolating functions to represent the nonlinear terms. We chose a pendulum, which has sinusoidal nonlinearities; (2) Application of the harmonic balance to an experimental system with known nonlinear forms. We chose a double pendulum, for which chaotic response were easily generated. Thus we confronted a two-degree-of-freedom system, which brought forth challenging issues; (3) A study of alternative reconstruction methods. The reconstruction of the phase space is necessary for the extraction of periodic orbits from the chaotic responses, which is needed in this work. Also, characterization of a nonlinear system is done in the reconstructed phase space. Such characterizations are needed to compare models with experiments. Finally, some nonlinear prediction methods can be applied in the reconstructed phase space. We developed two reconstruction methods that may be considered if the common method (method of delays) is not applicable.

Extracting, Tracking, and Visualizing Magnetic Flux Vortices in 3D Complex-Valued Superconductor Simulation Data.

PubMed

Guo, Hanqi; Phillips, Carolyn L; Peterka, Tom; Karpeyev, Dmitry; Glatz, Andreas

2016-01-01

We propose a method for the vortex extraction and tracking of superconducting magnetic flux vortices for both structured and unstructured mesh data. In the Ginzburg-Landau theory, magnetic flux vortices are well-defined features in a complex-valued order parameter field, and their dynamics determine electromagnetic properties in type-II superconductors. Our method represents each vortex line (a 1D curve embedded in 3D space) as a connected graph extracted from the discretized field in both space and time. For a time-varying discrete dataset, our vortex extraction and tracking method is as accurate as the data discretization. We then apply 3D visualization and 2D event diagrams to the extraction and tracking results to help scientists understand vortex dynamics and macroscale superconductor behavior in greater detail than previously possible.

Geometrically motivated coordinate system for exploring spacetime dynamics in numerical-relativity simulations using a quasi-Kinnersley tetrad

NASA Astrophysics Data System (ADS)

Zhang, Fan; Brink, Jeandrew; Szilágyi, Béla; Lovelace, Geoffrey

2012-10-01

We investigate the suitability and properties of a quasi-Kinnersley tetrad and a geometrically motivated coordinate system as tools for quantifying both strong-field and wave-zone effects in numerical relativity (NR) simulations. We fix two of the coordinate degrees of freedom of the metric, namely, the radial and latitudinal coordinates, using the Coulomb potential associated with the quasi-Kinnersley transverse frame. These coordinates are invariants of the spacetime and can be used to unambiguously fix the outstanding spin-boost freedom associated with the quasi-Kinnersley frame (and thus can be used to choose a preferred quasi-Kinnersley tetrad). In the limit of small perturbations about a Kerr spacetime, these geometrically motivated coordinates and quasi-Kinnersley tetrad reduce to Boyer-Lindquist coordinates and the Kinnersley tetrad, irrespective of the simulation gauge choice. We explore the properties of this construction both analytically and numerically, and we gain insights regarding the propagation of radiation described by a super-Poynting vector, further motivating the use of this construction in NR simulations. We also quantify in detail the peeling properties of the chosen tetrad and gauge. We argue that these choices are particularly well-suited for a rapidly converging wave-extraction algorithm as the extraction location approaches infinity, and we explore numerically the extent to which this property remains applicable on the interior of a computational domain. Using a number of additional tests, we verify numerically that the prescription behaves as required in the appropriate limits regardless of simulation gauge; these tests could also serve to benchmark other wave extraction methods. We explore the behavior of the geometrically motivated coordinate system in dynamical binary-black-hole NR mergers; while we obtain no unexpected results, we do find that these coordinates turn out to be useful for visualizing NR simulations (for example, for vividly illustrating effects such as the initial burst of spurious junk radiation passing through the computational domain). Finally, we carefully scrutinize the head-on collision of two black holes and, for example, the way in which the extracted waveform changes as it moves through the computational domain.

Comparison of quantitatively analyzed dynamic area-detector CT using various mathematic methods with FDG PET/CT in management of solitary pulmonary nodules.

PubMed

Ohno, Yoshiharu; Nishio, Mizuho; Koyama, Hisanobu; Fujisawa, Yasuko; Yoshikawa, Takeshi; Matsumoto, Sumiaki; Sugimura, Kazuro

2013-06-01

The objective of our study was to prospectively compare the capability of dynamic area-detector CT analyzed with different mathematic methods and PET/CT in the management of pulmonary nodules. Fifty-two consecutive patients with 96 pulmonary nodules underwent dynamic area-detector CT, PET/CT, and microbacterial or pathologic examinations. All nodules were classified into the following groups: malignant nodules (n = 57), benign nodules with low biologic activity (n = 15), and benign nodules with high biologic activity (n = 24). On dynamic area-detector CT, the total, pulmonary arterial, and systemic arterial perfusions were calculated using the dual-input maximum slope method; perfusion was calculated using the single-input maximum slope method; and extraction fraction and blood volume (BV) were calculated using the Patlak plot method. All indexes were statistically compared among the three nodule groups. Then, receiver operating characteristic analyses were used to compare the diagnostic capabilities of the maximum standardized uptake value (SUVmax) and each perfusion parameter having a significant difference between malignant and benign nodules. Finally, the diagnostic performances of the indexes were compared by means of the McNemar test. No adverse effects were observed in this study. All indexes except extraction fraction and BV, both of which were calculated using the Patlak plot method, showed significant differences among the three groups (p < 0.05). Areas under the curve of total perfusion calculated using the dual-input method, pulmonary arterial perfusion calculated using the dual-input method, and perfusion calculated using the single-input method were significantly larger than that of SUVmax (p < 0.05). The accuracy of total perfusion (83.3%) was significantly greater than the accuracy of the other indexes: pulmonary arterial perfusion (72.9%, p < 0.05), systemic arterial perfusion calculated using the dual-input method (69.8%, p < 0.05), perfusion (66.7%, p < 0.05), and SUVmax (60.4%, p < 0.05). Dynamic area-detector CT analyzed using the dual-input maximum slope method has better potential for the diagnosis of pulmonary nodules than dynamic area-detector CT analyzed using other methods and than PET/CT.

Comparison of social and physical free energies on a toy model.

PubMed

Kasac, Josip; Stefancic, Hrvoje; Stepanic, Josip

2004-01-01

Social free energy has been recently introduced as a measure of social action obtainable in a given social system, without changes in its structure. The authors of this paper argue that social free energy surpasses the gap between the verbally formulated value sets of social systems and the quantitatively based predictions. This point is further developed by analyzing the relation between the social and the physical free energy. Generically, this is done for a particular type of social dynamics. The extracted type of social dynamics is one of many realistic types of the differing proportion of social and economic elements. Numerically, this has been done for a toy model of interacting agents. The values of the social and physical free energies are, within the numerical accuracy, equivalent in the class of nontrivial, quasistationary model states.

Gyrodampers for large space structures

NASA Technical Reports Server (NTRS)

Aubrun, J. N.; Margulies, G.

1979-01-01

The problem of controlling the vibrations of a large space structures by the use of actively augmented damping devices distributed throughout the structure is addressed. The gyrodamper which consists of a set of single gimbal control moment gyros which are actively controlled to extract the structural vibratory energy through the local rotational deformations of the structure, is described and analyzed. Various linear and nonlinear dynamic simulations of gyrodamped beams are shown, including results on self-induced vibrations due to sensor noise and rotor imbalance. The complete nonlinear dynamic equations are included. The problem of designing and sizing a system of gyrodampers for a given structure, or extrapolating results for one gyrodamped structure to another is solved in terms of scaling laws. Novel scaling laws for gyro systems are derived, based upon fundamental physical principles, and various examples are given.

Sweep excitation with order tracking: A new tactic for beam crack analysis

NASA Astrophysics Data System (ADS)

Wei, Dongdong; Wang, KeSheng; Zhang, Mian; Zuo, Ming J.

2018-04-01

Crack detection in beams and beam-like structures is an important issue in industry and has attracted numerous investigations. A local crack leads to global system dynamics changes and produce non-linear vibration responses. Many researchers have studied these non-linearities for beam crack diagnosis. However, most reported methods are based on impact excitation and constant frequency excitation. Few studies have focused on crack detection through external sweep excitation which unleashes abundant dynamic characteristics of the system. Together with a signal resampling technique inspired by Computed Order Tracking, this paper utilize vibration responses under sweep excitations to diagnose crack status of beams. A data driven method for crack depth evaluation is proposed and window based harmonics extracting approaches are studied. The effectiveness of sweep excitation and the proposed method is experimentally validated.

Determination of Heritage SSME Pogo Suppressor Resistance and Inertance from Waterflow Pulse Testing

NASA Technical Reports Server (NTRS)

McDougal, Chris; Eberhart, Chad; Lee, Erik

2016-01-01

Waterflow tests of a heritage Space Shuttle Main Engine pogo suppressor were performed to experimentally quantify the resistance and inertance provided by the suppressor. Measurements of dynamic pressure and flow rate in response to pulsing flow were made throughout the test loop. A unique system identification methodology combined all sensor measurements with a one-dimensional perturbational flow model of the complete water flow loop to spatially translate physical measurements to the device under test. Multiple techniques were then employed to extract the effective resistance and inertance for the pogo suppressor. Parameters such as steady flow rate, perturbational flow rate magnitude, and pulse frequency were investigated to assess their influence on the behavior of the pogo suppressor dynamic response. These results support validation of the RS-25 pogo suppressor performance for use on the Space Launch System Core Stage.

Methods for Modeling Brassinosteroid-Mediated Signaling in Plant Development.

PubMed

Frigola, David; Caño-Delgado, Ana I; Ibañes, Marta

2017-01-01

Mathematical modeling of biological processes is a useful tool to draw conclusions that are contained in the data, but not directly reachable, as well as to make predictions and select the most efficient follow-up experiments. Here we outline a method to model systems of a few proteins that interact transcriptionally and/or posttranscriptionally, by representing the system as Ordinary Differential Equations and to study the model dynamics and stationary states. We exemplify this method by focusing on the regulation by the brassinosteroid (BR) signaling component BRASSINOSTEROID INSENSITIVE1 ETHYL METHYL SULFONATE SUPPRESSOR1 (BES1) of BRAVO, a quiescence-regulating transcription factor expressed in the quiescent cells of Arabidopsis thaliana roots. The method to extract the stationary states and the dynamics is provided as a Mathematica code and requires basic knowledge of the Mathematica software to be executed.

Event-Based Computation of Motion Flow on a Neuromorphic Analog Neural Platform

PubMed Central

Giulioni, Massimiliano; Lagorce, Xavier; Galluppi, Francesco; Benosman, Ryad B.

2016-01-01

Estimating the speed and direction of moving objects is a crucial component of agents behaving in a dynamic world. Biological organisms perform this task by means of the neural connections originating from their retinal ganglion cells. In artificial systems the optic flow is usually extracted by comparing activity of two or more frames captured with a vision sensor. Designing artificial motion flow detectors which are as fast, robust, and efficient as the ones found in biological systems is however a challenging task. Inspired by the architecture proposed by Barlow and Levick in 1965 to explain the spiking activity of the direction-selective ganglion cells in the rabbit's retina, we introduce an architecture for robust optical flow extraction with an analog neuromorphic multi-chip system. The task is performed by a feed-forward network of analog integrate-and-fire neurons whose inputs are provided by contrast-sensitive photoreceptors. Computation is supported by the precise time of spike emission, and the extraction of the optical flow is based on time lag in the activation of nearby retinal neurons. Mimicking ganglion cells our neuromorphic detectors encode the amplitude and the direction of the apparent visual motion in their output spiking pattern. Hereby we describe the architectural aspects, discuss its latency, scalability, and robustness properties and demonstrate that a network of mismatched delicate analog elements can reliably extract the optical flow from a simple visual scene. This work shows how precise time of spike emission used as a computational basis, biological inspiration, and neuromorphic systems can be used together for solving specific tasks. PMID:26909015

Event-Based Computation of Motion Flow on a Neuromorphic Analog Neural Platform.

PubMed

Giulioni, Massimiliano; Lagorce, Xavier; Galluppi, Francesco; Benosman, Ryad B

2016-01-01

Estimating the speed and direction of moving objects is a crucial component of agents behaving in a dynamic world. Biological organisms perform this task by means of the neural connections originating from their retinal ganglion cells. In artificial systems the optic flow is usually extracted by comparing activity of two or more frames captured with a vision sensor. Designing artificial motion flow detectors which are as fast, robust, and efficient as the ones found in biological systems is however a challenging task. Inspired by the architecture proposed by Barlow and Levick in 1965 to explain the spiking activity of the direction-selective ganglion cells in the rabbit's retina, we introduce an architecture for robust optical flow extraction with an analog neuromorphic multi-chip system. The task is performed by a feed-forward network of analog integrate-and-fire neurons whose inputs are provided by contrast-sensitive photoreceptors. Computation is supported by the precise time of spike emission, and the extraction of the optical flow is based on time lag in the activation of nearby retinal neurons. Mimicking ganglion cells our neuromorphic detectors encode the amplitude and the direction of the apparent visual motion in their output spiking pattern. Hereby we describe the architectural aspects, discuss its latency, scalability, and robustness properties and demonstrate that a network of mismatched delicate analog elements can reliably extract the optical flow from a simple visual scene. This work shows how precise time of spike emission used as a computational basis, biological inspiration, and neuromorphic systems can be used together for solving specific tasks.

Handling of subpixel structures in the application of satellite derived irradiance data for solar energy system analysis - a review

NASA Astrophysics Data System (ADS)

Beyer, Hans Georg

2016-04-01

With the increasing availability of satellite derived irradiance information, this type of data set is more and more in use for the design and operation of solar energy systems, most notably PV- and CSP-systems. By this, the need for data measured on-site is reduced. However, due to basic limitations of the satellite-derived data, several requirements put by the intended application cannot be coped with this data type directly. Traw satellite information has to be enhanced in both space and time resolution by additional information to be fully applicable for all aspects of the modelling od solar energy systems. To cope with this problem, several individual and collaborative projects had been performed in the recent years or are ongoing. Approaches are on one hand based on pasting synthesized high-resolution data into the low-resolution original sets. Pre-requite is an appropriate model, validated against real world data. For the case of irradiance data, these models can be extracted either directly from ground measured data sets or from data referring to the cloud situation as gained from the images of sky cameras or from monte -carlo initialized physical models. The current models refer to the spatial structure of the cloud fields. Dynamics are imposed by moving the cloud structures according to a large scale cloud motion vector, either extracted from the dynamics interfered from consecutive satellite images or taken from a meso-scale meteorological model. Dynamic irradiance information is then derived from the cloud field structure and the cloud motion vector. This contribution, which is linked to subtask A - Solar Resource Applications for High Penetration of Solar Technologies - of IEA SHC task 46, will present the different approaches and discuss examples in view of validation, need for auxiliary information and respective general applicability.

A Bayesian framework for extracting human gait using strong prior knowledge.

PubMed

Zhou, Ziheng; Prügel-Bennett, Adam; Damper, Robert I

2006-11-01

Extracting full-body motion of walking people from monocular video sequences in complex, real-world environments is an important and difficult problem, going beyond simple tracking, whose satisfactory solution demands an appropriate balance between use of prior knowledge and learning from data. We propose a consistent Bayesian framework for introducing strong prior knowledge into a system for extracting human gait. In this work, the strong prior is built from a simple articulated model having both time-invariant (static) and time-variant (dynamic) parameters. The model is easily modified to cater to situations such as walkers wearing clothing that obscures the limbs. The statistics of the parameters are learned from high-quality (indoor laboratory) data and the Bayesian framework then allows us to "bootstrap" to accurate gait extraction on the noisy images typical of cluttered, outdoor scenes. To achieve automatic fitting, we use a hidden Markov model to detect the phases of images in a walking cycle. We demonstrate our approach on silhouettes extracted from fronto-parallel ("sideways on") sequences of walkers under both high-quality indoor and noisy outdoor conditions. As well as high-quality data with synthetic noise and occlusions added, we also test walkers with rucksacks, skirts, and trench coats. Results are quantified in terms of chamfer distance and average pixel error between automatically extracted body points and corresponding hand-labeled points. No one part of the system is novel in itself, but the overall framework makes it feasible to extract gait from very much poorer quality image sequences than hitherto. This is confirmed by comparing person identification by gait using our method and a well-established baseline recognition algorithm.

System Identification and Verification of Rotorcraft UAVs

NASA Astrophysics Data System (ADS)

Carlton, Zachary M.

The task of a controls engineer is to design and implement control logic. To complete this task, it helps tremendously to have an accurate model of the system to be controlled. Obtaining a very accurate system model is not a trivial one, as much time and money is usually associated with the development of such a model. A typical physics based approach can require hundreds of hours of flight time. In an iterative process the model is tuned in such a way that it accurately models the physical system's response. This process becomes even more complicated for unstable and highly non-linear systems such as the dynamics of rotorcraft. An alternate approach to solving this problem is to extract an accurate model by analyzing the frequency response of the system. This process involves recording the system's responses for a frequency range of input excitations. From this data, an accurate system model can then be deduced. Furthermore, it has been shown that with use of the software package CIFER® (Comprehensive Identification from FrEquency Responses), this process can both greatly reduce the cost of modeling a dynamic system and produce very accurate results. The topic of this thesis is to apply CIFER® to a quadcopter to extract a system model for the flight condition of hover. The quadcopter itself is comprised of off-the-shelf components with a Pixhack flight controller board running open source Ardupilot controller logic. In this thesis, both the closed and open loop systems are identified. The model is next compared to dissimilar flight data and verified in the time domain. Additionally, the ESC (Electronic Speed Controller) motor/rotor subsystem, which is comprised of all the vehicle's actuators, is also identified. This process required the development of a test bench environment, which included a GUI (Graphical User Interface), data pre and post processing, as well as the augmentation of the flight controller source code. This augmentation of code allowed for proper data logging rates of all needed parameters.

Systems science and systems thinking for public health: a systematic review of the field

PubMed Central

Carey, Gemma; Malbon, Eleanor; Carey, Nicole; Joyce, Andrew; Crammond, Brad; Carey, Alan

2015-01-01

Objectives This paper reports on findings from a systematic review designed to investigate the state of systems science research in public health. The objectives were to: (1) explore how systems methodologies are being applied within public health and (2) identify fruitful areas of activity. Design A systematic review was conducted from existing literature that draws on or uses systems science (in its various forms) and relates to key public health areas of action and concern, including tobacco, alcohol, obesity and the social determinants of health. Data analysis 117 articles were included in the review. An inductive qualitative content analysis was used for data extraction. The following were systematically extracted from the articles: approach, methodology, transparency, strengths and weaknesses. These were then organised according to theme (ie, commonalities between studies within each category), in order to provide an overview of the state of the field as a whole. The assessment of data quality was intrinsic to the goals of the review itself, and therefore, was carried out as part of the analysis. Results 4 categories of research were identified from the review, ranging from editorial and commentary pieces to complex system dynamic modelling. Our analysis of each of these categories of research highlighted areas of potential for systems science to strengthen public health efforts, while also revealing a number of limitations in the dynamic systems modelling being carried out in public health. Conclusions There is a great deal of interest in how the application of systems concepts and approach might aid public health. Our analysis suggests that soft systems modelling techniques are likely to be the most useful addition to public health, and align well with current debate around knowledge transfer and policy. However, the full range of systems methodologies is yet to be engaged with by public health researchers. PMID:26719314

Systems science and systems thinking for public health: a systematic review of the field.

PubMed

Carey, Gemma; Malbon, Eleanor; Carey, Nicole; Joyce, Andrew; Crammond, Brad; Carey, Alan

2015-12-30

This paper reports on findings from a systematic review designed to investigate the state of systems science research in public health. The objectives were to: (1) explore how systems methodologies are being applied within public health and (2) identify fruitful areas of activity. A systematic review was conducted from existing literature that draws on or uses systems science (in its various forms) and relates to key public health areas of action and concern, including tobacco, alcohol, obesity and the social determinants of health. 117 articles were included in the review. An inductive qualitative content analysis was used for data extraction. The following were systematically extracted from the articles: approach, methodology, transparency, strengths and weaknesses. These were then organised according to theme (ie, commonalities between studies within each category), in order to provide an overview of the state of the field as a whole. The assessment of data quality was intrinsic to the goals of the review itself, and therefore, was carried out as part of the analysis. 4 categories of research were identified from the review, ranging from editorial and commentary pieces to complex system dynamic modelling. Our analysis of each of these categories of research highlighted areas of potential for systems science to strengthen public health efforts, while also revealing a number of limitations in the dynamic systems modelling being carried out in public health. There is a great deal of interest in how the application of systems concepts and approach might aid public health. Our analysis suggests that soft systems modelling techniques are likely to be the most useful addition to public health, and align well with current debate around knowledge transfer and policy. However, the full range of systems methodologies is yet to be engaged with by public health researchers. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Experimental Observations of Multiscale Dynamics of Viscous Fluid Behavior: Implications in Volcanic Systems

NASA Astrophysics Data System (ADS)

Arciniega-Ceballos, A.; Spina, L.; Scheu, B.; Dingwell, D. B.

2015-12-01

We have investigated the dynamics of Newtonian fluids with viscosities (10-1000 Pa s; corresponding to mafic to intermediate silicate melts) during slow decompression, in a Plexiglas shock tube. As an analogue fluid we used silicon oil saturated with Argon gas for 72 hours. Slow decompression, dropping from 10 MPa to ambient pressure, acts as the excitation mechanism, initiating several processes with their own distinct timescales. The evolution of this multi-timescale phenomenon generates complex non-stationary microseismic signals, which have been recorded with 7 high-dynamic piezoelectric sensors located along the conduit. Correlation analysis of these time series with the associated high-speed imaging enables characterization of distinct phases of the dynamics of these viscous fluids and the extraction of the time and the frequency characteristics of the individual processes. We have identified fluid-solid elastic interaction, degassing, fluid mass expansion and flow, bubble nucleation, growth, coalescence and collapse, foam building and vertical wagging. All these processes (in fine and coarse scales) are sequentially coupled in time, occur within specific pressure intervals, and exhibit a localized distribution in space. Their coexistence and interactions constitute the stress field and driving forces that determine the dynamics of the system. Our observations point to the great potential of this experimental approach in the understanding of volcanic processes and volcanic seismicity.

Dynamics of acoustic-convective drying of sunflower cake

NASA Astrophysics Data System (ADS)

Zhilin, A. A.

2017-10-01

The dynamics of drying sunflower cake by a new acoustic-convective method has been studied. Unlike the conventional (thermal-convective) method, the proposed method allows moisture to be extracted from porous materials without applying heat to the sample to be dried. Kinetic curves of drying by the thermal-convective and acoustic-convective methods were obtained and analyzed. The advantages of the acoustic-convective extraction of moisture over the thermal-convective method are discussed. The relaxation times of drying were determined for both drying methods. An intermittent drying mode which improves the efficiency of acoustic-convective extraction of moisture is considered.

Extraction of Extended Small-Scale Objects in Digital Images

NASA Astrophysics Data System (ADS)

Volkov, V. Y.

2015-05-01

Detection and localization problem of extended small-scale objects with different shapes appears in radio observation systems which use SAR, infra-red, lidar and television camera. Intensive non-stationary background is the main difficulty for processing. Other challenge is low quality of images, blobs, blurred boundaries; in addition SAR images suffer from a serious intrinsic speckle noise. Statistics of background is not normal, it has evident skewness and heavy tails in probability density, so it is hard to identify it. The problem of extraction small-scale objects is solved here on the basis of directional filtering, adaptive thresholding and morthological analysis. New kind of masks is used which are open-ended at one side so it is possible to extract ends of line segments with unknown length. An advanced method of dynamical adaptive threshold setting is investigated which is based on isolated fragments extraction after thresholding. Hierarchy of isolated fragments on binary image is proposed for the analysis of segmentation results. It includes small-scale objects with different shape, size and orientation. The method uses extraction of isolated fragments in binary image and counting points in these fragments. Number of points in extracted fragments is normalized to the total number of points for given threshold and is used as effectiveness of extraction for these fragments. New method for adaptive threshold setting and control maximises effectiveness of extraction. It has optimality properties for objects extraction in normal noise field and shows effective results for real SAR images.

Cosmology from group field theory formalism for quantum gravity.

PubMed

Gielen, Steffen; Oriti, Daniele; Sindoni, Lorenzo

2013-07-19

We identify a class of condensate states in the group field theory (GFT) formulation of quantum gravity that can be interpreted as macroscopic homogeneous spatial geometries. We then extract the dynamics of such condensate states directly from the fundamental quantum GFT dynamics, following the procedure used in ordinary quantum fluids. The effective dynamics is a nonlinear and nonlocal extension of quantum cosmology. We also show that any GFT model with a kinetic term of Laplacian type gives rise, in a semiclassical (WKB) approximation and in the isotropic case, to a modified Friedmann equation. This is the first concrete, general procedure for extracting an effective cosmological dynamics directly from a fundamental theory of quantum geometry.

Chemically differentiating ascorbate-mediated dissolution of quantum dots in cell culture media

NASA Astrophysics Data System (ADS)

Su, Cheng-Kuan; Sun, Yuh-Chang

2013-02-01

To investigate the dynamic dissolution of quantum dots (QDs) in cell culture media, in this study we constructed an online automatic analytical system comprising a sequential in-tube solid phase extraction (SPE) device and an inductively coupled plasma (ICP) mass spectrometer. By means of selectively extracting QDs and cadmium ions (Cd2+) onto the interior surface of the polytetrafluoroethylene (PTFE) tube, this novel SPE device could be used to determine the degree of QD dissolution through a simple adjustment of sample acidity. To the best of our knowledge, this study is the first to exploit PTFE tubing as a selective SPE adsorbent for the online chemical differentiation of QDs and Cd2+ ions with the goal of monitoring the phenomenon of QD dissolution in complicated biological matrices. We confirmed the analytical reliability of this system through comparison of the measured Cd-to-QD ratios to the expected values. When analyzing QDs and Cd2+ ions at picomolar levels, a temporal resolution of 8 min was required to load sufficient amounts of the analytes to meet the sensitivity requirements of the ICP mass spectrometer. To demonstrate the practicability of this developed method, we measured the dynamic variations in the Cd-to-QD705 ratio in the presence of ascorbate as a physiological stimulant to generate reactive oxygen species in cell culture media and trigger the dissolution of QDs; our results suggest that the ascorbate-induced QD dissolution was dependent on the time, treatment concentration, and nature of the biomolecule.To investigate the dynamic dissolution of quantum dots (QDs) in cell culture media, in this study we constructed an online automatic analytical system comprising a sequential in-tube solid phase extraction (SPE) device and an inductively coupled plasma (ICP) mass spectrometer. By means of selectively extracting QDs and cadmium ions (Cd2+) onto the interior surface of the polytetrafluoroethylene (PTFE) tube, this novel SPE device could be used to determine the degree of QD dissolution through a simple adjustment of sample acidity. To the best of our knowledge, this study is the first to exploit PTFE tubing as a selective SPE adsorbent for the online chemical differentiation of QDs and Cd2+ ions with the goal of monitoring the phenomenon of QD dissolution in complicated biological matrices. We confirmed the analytical reliability of this system through comparison of the measured Cd-to-QD ratios to the expected values. When analyzing QDs and Cd2+ ions at picomolar levels, a temporal resolution of 8 min was required to load sufficient amounts of the analytes to meet the sensitivity requirements of the ICP mass spectrometer. To demonstrate the practicability of this developed method, we measured the dynamic variations in the Cd-to-QD705 ratio in the presence of ascorbate as a physiological stimulant to generate reactive oxygen species in cell culture media and trigger the dissolution of QDs; our results suggest that the ascorbate-induced QD dissolution was dependent on the time, treatment concentration, and nature of the biomolecule. Electronic supplementary information (ESI) available: The operation sequence, optimized parameters, instrumental operation conditions, and schematic representations for the proposed sequential in-tube PTFE SPE-ICP-MS hyphenated system are provided. See DOI: 10.1039/c2nr33365a

Damage-mitigating control of aerospace systems for high performance and extended life

NASA Technical Reports Server (NTRS)

Ray, Asok; Wu, Min-Kuang; Carpino, Marc; Lorenzo, Carl F.; Merrill, Walter C.

1992-01-01

The concept of damage-mitigating control is to minimize fatigue (as well as creep and corrosion) damage of critical components of mechanical structures while simultaneously maximizing the system dynamic performance. Given a dynamic model of the plant and the specifications for performance and stability robustness, the task is to synthesize a control law that would meet the system requirements and, at the same time, satisfy the constraints that are imposed by the material and structural properties of the critical components. The authors present the concept of damage-mitigating control systems design with the following objectives: (1) to achieve high performance with a prolonged life span; and (2) to systematically update the controller as the new technology of advanced materials evolves. The major challenge is to extract the information from the material properties and then utilize this information in a mathematical form so that it can be directly applied to robust control synthesis for mechanical systems. The basic concept of damage-mitigating control is illustrated using a relatively simplified model of a space shuttle main engine.

An independent software system for the analysis of dynamic MR images.

PubMed

Torheim, G; Lombardi, M; Rinck, P A

1997-01-01

A computer system for the manual, semi-automatic, and automatic analysis of dynamic MR images was to be developed on UNIX and personal computer platforms. The system was to offer an integrated and standardized way of performing both image processing and analysis that was independent of the MR unit used. The system consists of modules that are easily adaptable to special needs. Data from MR units or other diagnostic imaging equipment in techniques such as CT, ultrasonography, or nuclear medicine can be processed through the ACR-NEMA/DICOM standard file formats. A full set of functions is available, among them cine-loop visual analysis, and generation of time-intensity curves. Parameters such as cross-correlation coefficients, area under the curve, peak/maximum intensity, wash-in and wash-out slopes, time to peak, and relative signal intensity/contrast enhancement can be calculated. Other parameters can be extracted by fitting functions like the gamma-variate function. Region-of-interest data and parametric values can easily be exported. The system has been successfully tested in animal and patient examinations.

Musical structure analysis using similarity matrix and dynamic programming

NASA Astrophysics Data System (ADS)

Shiu, Yu; Jeong, Hong; Kuo, C.-C. Jay

2005-10-01

Automatic music segmentation and structure analysis from audio waveforms based on a three-level hierarchy is examined in this research, where the three-level hierarchy includes notes, measures and parts. The pitch class profile (PCP) feature is first extracted at the note level. Then, a similarity matrix is constructed at the measure level, where a dynamic time warping (DTW) technique is used to enhance the similarity computation by taking the temporal distortion of similar audio segments into account. By processing the similarity matrix, we can obtain a coarse-grain music segmentation result. Finally, dynamic programming is applied to the coarse-grain segments so that a song can be decomposed into several major parts such as intro, verse, chorus, bridge and outro. The performance of the proposed music structure analysis system is demonstrated for pop and rock music.

Gain in computational efficiency by vectorization in the dynamic simulation of multi-body systems

NASA Technical Reports Server (NTRS)

Amirouche, F. M. L.; Shareef, N. H.

1991-01-01

An improved technique for the identification and extraction of the exact quantities associated with the degrees of freedom at the element as well as the flexible body level is presented. It is implemented in the dynamic equations of motions based on the recursive formulation of Kane et al. (1987) and presented in a matrix form, integrating the concepts of strain energy, the finite-element approach, modal analysis, and reduction of equations. This technique eliminates the CPU intensive matrix multiplication operations in the code's hot spots for the dynamic simulation of the interconnected rigid and flexible bodies. A study of a simple robot with flexible links is presented by comparing the execution times on a scalar machine and a vector-processor with and without vector options. Performance figures demonstrating the substantial gains achieved by the technique are plotted.

Insights into the Cell Shape Dynamics of Migrating Dictyostelium discoideum

NASA Astrophysics Data System (ADS)

Driscoll, Meghan; Homan, Tess; McCann, Colin; Parent, Carole; Fourkas, John; Losert, Wolfgang

2010-03-01

Dynamic cell shape is a highly visible manifestation of the interaction between the internal biochemical state of a cell and its external environment. We analyzed the dynamic cell shape of migrating cells using the model system Dictyostelium discoideum. Applying a snake algorithm to experimental movies, we extracted cell boundaries in each frame and followed local boundary motion over long time intervals. Using a local motion measure that corresponds to protrusive/retractive activity, we found that protrusions are intermittent and zig-zag, whereas retractions are more sustained and straight. Correlations of this local motion measure reveal that protrusions appear more localized than retractions. Using a local shape measure, curvature, we also found that small peaks in boundary curvature tend to originate at the front of cells and propagate backwards. We will review the possible cytoskeletal origin of these mechanical waves.

Collaborative human-machine analysis to disambiguate entities in unstructured text and structured datasets

NASA Astrophysics Data System (ADS)

Davenport, Jack H.

2016-05-01

Intelligence analysts demand rapid information fusion capabilities to develop and maintain accurate situational awareness and understanding of dynamic enemy threats in asymmetric military operations. The ability to extract relationships between people, groups, and locations from a variety of text datasets is critical to proactive decision making. The derived network of entities must be automatically created and presented to analysts to assist in decision making. DECISIVE ANALYTICS Corporation (DAC) provides capabilities to automatically extract entities, relationships between entities, semantic concepts about entities, and network models of entities from text and multi-source datasets. DAC's Natural Language Processing (NLP) Entity Analytics model entities as complex systems of attributes and interrelationships which are extracted from unstructured text via NLP algorithms. The extracted entities are automatically disambiguated via machine learning algorithms, and resolution recommendations are presented to the analyst for validation; the analyst's expertise is leveraged in this hybrid human/computer collaborative model. Military capability is enhanced by these NLP Entity Analytics because analysts can now create/update an entity profile with intelligence automatically extracted from unstructured text, thereby fusing entity knowledge from structured and unstructured data sources. Operational and sustainment costs are reduced since analysts do not have to manually tag and resolve entities.

Stochastic global identification of a bio-inspired self-sensing composite UAV wing via wind tunnel experiments

NASA Astrophysics Data System (ADS)

Kopsaftopoulos, Fotios; Nardari, Raphael; Li, Yu-Hung; Wang, Pengchuan; Chang, Fu-Kuo

2016-04-01

In this work, the system design, integration, and wind tunnel experimental evaluation are presented for a bioinspired self-sensing intelligent composite unmanned aerial vehicle (UAV) wing. A total of 148 micro-sensors, including piezoelectric, strain, and temperature sensors, in the form of stretchable sensor networks are embedded in the layup of a composite wing in order to enable its self-sensing capabilities. Novel stochastic system identification techniques based on time series models and statistical parameter estimation are employed in order to accurately interpret the sensing data and extract real-time information on the coupled air flow-structural dynamics. Special emphasis is given to the wind tunnel experimental assessment under various flight conditions defined by multiple airspeeds and angles of attack. A novel modeling approach based on the recently introduced Vector-dependent Functionally Pooled (VFP) model structure is employed for the stochastic identification of the "global" coupled airflow-structural dynamics of the wing and their correlation with dynamic utter and stall. The obtained results demonstrate the successful system-level integration and effectiveness of the stochastic identification approach, thus opening new perspectives for the state sensing and awareness capabilities of the next generation of "fly-by-fee" UAVs.

Sol-gel titania-coated needles for solid phase dynamic extraction-GC/MS analysis of desomorphine and desocodeine.

PubMed

Su, Chi-Ju; Srimurugan, Sankarewaran; Chen, Chinpiao; Shu, Hun-Chi

2011-01-01

Novel sol-gel titania film coated needles for solid-phase dynamic extraction (SPDE)-GC/MS analysis of desomorphine and desocodeine are described. The high thermal stability of titania film permits efficient extraction and analysis of poorly volatile opiate drugs. The influences of sol-gel reaction time, coating layer, extraction and desorption time and temperature on the SPDE needle performance were investigated. The deuterium labeled internal standard was introduced either during the extraction of analyte or directly injected to GC after the extraction process. The latter method was shown to be more sensitive for the analysis of water and urine samples containing opiate drugs. The proposed conditions provided a wide linear range (from 5-5000 ppb), and satisfactory linearity, with R(2) values from 0.9958 to 0.9999, and prominent sensitivity, LOQs (1.0-5.0 ng/g). The sol-gel titania film coated needle with SPDE-GC/MS will be a promising technique for desomorphine and desocodeine analysis in urine.

Dynamic Policy Evaluation for Containing Network Attacks (DEFCN)

DTIC Science & Technology

2005-03-01

API reads policy information from the target users ".ssh" directory and applies those policies to determine whether remote login is allowed to a...types of events that can be controlled by the threshold detectors and reported by the GAA-API include the number of failed login attempts within a given...other uses of the system. Emerald architecture [2] includes a data- collection module integrated with Apache Web server. The module extracts the request

Numerical modelling of distributed vibration sensor based on phase-sensitive OTDR

NASA Astrophysics Data System (ADS)

Masoudi, A.; Newson, T. P.

2017-04-01

A Distributed Vibration Sensor Based on Phase-Sensitive OTDR is numerically modeled. The advantage of modeling the building blocks of the sensor individually and combining the blocks to analyse the behavior of the sensing system is discussed. It is shown that the numerical model can accurately imitate the response of the experimental setup to dynamic perturbations a signal processing procedure similar to that used to extract the phase information from sensing setup.

Space debris tracking based on fuzzy running Gaussian average adaptive particle filter track-before-detect algorithm

NASA Astrophysics Data System (ADS)

Torteeka, Peerapong; Gao, Peng-Qi; Shen, Ming; Guo, Xiao-Zhang; Yang, Da-Tao; Yu, Huan-Huan; Zhou, Wei-Ping; Zhao, You

2017-02-01

Although tracking with a passive optical telescope is a powerful technique for space debris observation, it is limited by its sensitivity to dynamic background noise. Traditionally, in the field of astronomy, static background subtraction based on a median image technique has been used to extract moving space objects prior to the tracking operation, as this is computationally efficient. The main disadvantage of this technique is that it is not robust to variable illumination conditions. In this article, we propose an approach for tracking small and dim space debris in the context of a dynamic background via one of the optical telescopes that is part of the space surveillance network project, named the Asia-Pacific ground-based Optical Space Observation System or APOSOS. The approach combines a fuzzy running Gaussian average for robust moving-object extraction with dim-target tracking using a particle-filter-based track-before-detect method. The performance of the proposed algorithm is experimentally evaluated, and the results show that the scheme achieves a satisfactory level of accuracy for space debris tracking.

Quantifying heterogeneity of lesion uptake in dynamic contrast enhanced MRI for breast cancer diagnosis

NASA Astrophysics Data System (ADS)

Karahaliou, A.; Vassiou, K.; Skiadopoulos, S.; Kanavou, T.; Yiakoumelos, A.; Costaridou, L.

2009-07-01

The current study investigates whether texture features extracted from lesion kinetics feature maps can be used for breast cancer diagnosis. Fifty five women with 57 breast lesions (27 benign, 30 malignant) were subjected to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) on 1.5T system. A linear-slope model was fitted pixel-wise to a representative lesion slice time series and fitted parameters were used to create three kinetic maps (wash out, time to peak enhancement and peak enhancement). 28 grey level co-occurrence matrices features were extracted from each lesion kinetic map. The ability of texture features per map in discriminating malignant from benign lesions was investigated using a Probabilistic Neural Network classifier. Additional classification was performed by combining classification outputs of most discriminating feature subsets from the three maps, via majority voting. The combined scheme outperformed classification based on individual maps achieving area under Receiver Operating Characteristics curve 0.960±0.029. Results suggest that heterogeneity of breast lesion kinetics, as quantified by texture analysis, may contribute to computer assisted tissue characterization in DCE-MRI.

Fault detection method for railway wheel flat using an adaptive multiscale morphological filter

NASA Astrophysics Data System (ADS)

Li, Yifan; Zuo, Ming J.; Lin, Jianhui; Liu, Jianxin

2017-02-01

This study explores the capacity of the morphology analysis for railway wheel flat fault detection. A dynamic model of vehicle systems with 56 degrees of freedom was set up along with a wheel flat model to calculate the dynamic responses of axle box. The vehicle axle box vibration signal is complicated because it not only contains the information of wheel defect, but also includes track condition information. Thus, how to extract the influential features of wheels from strong background noise effectively is a typical key issue for railway wheel fault detection. In this paper, an algorithm for adaptive multiscale morphological filtering (AMMF) was proposed, and its effect was evaluated by a simulated signal. And then this algorithm was employed to study the axle box vibration caused by wheel flats, as well as the influence of track irregularity and vehicle running speed on diagnosis results. Finally, the effectiveness of the proposed method was verified by bench testing. Research results demonstrate that the AMMF extracts the influential characteristic of axle box vibration signals effectively and can diagnose wheel flat faults in real time.

Extraction of Blebs in Human Embryonic Stem Cell Videos.

PubMed

Guan, Benjamin X; Bhanu, Bir; Talbot, Prue; Weng, Nikki Jo-Hao

2016-01-01

Blebbing is an important biological indicator in determining the health of human embryonic stem cells (hESC). Especially, areas of a bleb sequence in a video are often used to distinguish two cell blebbing behaviors in hESC: dynamic and apoptotic blebbings. This paper analyzes various segmentation methods for bleb extraction in hESC videos and introduces a bio-inspired score function to improve the performance in bleb extraction. Full bleb formation consists of bleb expansion and retraction. Blebs change their size and image properties dynamically in both processes and between frames. Therefore, adaptive parameters are needed for each segmentation method. A score function derived from the change of bleb area and orientation between consecutive frames is proposed which provides adaptive parameters for bleb extraction in videos. In comparison to manual analysis, the proposed method provides an automated fast and accurate approach for bleb sequence extraction.

Multiaperture ion beam extraction from gas-dynamic electron cyclotron resonance source of multicharged ions

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

Sidorov, A.; Dorf, M.; Zorin, V.

2008-02-15

Electron cyclotron resonance ion source with quasi-gas-dynamic regime of plasma confinement (ReGIS), constructed at the Institute of Applied Physics, Russia, provides opportunities for extracting intense and high-brightness multicharged ion beams. Despite the short plasma lifetime in a magnetic trap of a ReGIS, the degree of multiple ionization may be significantly enhanced by the increase in power and frequency of the applied microwave radiation. The present work is focused on studying the intense beam quality of this source by the pepper-pot method. A single beamlet emittance measured by the pepper-pot method was found to be {approx}70 {pi} mm mrad, and themore » total extracted beam current obtained at 14 kV extraction voltage was {approx}25 mA. The results of the numerical simulations of ion beam extraction are found to be in good agreement with experimental data.« less

Advances in the Control System for a High Precision Dissolved Organic Carbon Analyzer

NASA Astrophysics Data System (ADS)

Liao, M.; Stubbins, A.; Haidekker, M.

2017-12-01

Dissolved organic carbon (DOC) is a master variable in aquatic ecosystems. DOC in the ocean is one of the largest carbon stores on earth. Studies of the dynamics of DOC in the ocean and other low DOC systems (e.g. groundwater) are hindered by the lack of high precision (sub-micromolar) analytical techniques. Results are presented from efforts to construct and optimize a flow-through, wet chemical DOC analyzer. This study focused on the design, integration and optimization of high precision components and control systems required for such a system (mass flow controller, syringe pumps, gas extraction, reactor chamber with controlled UV and temperature). Results of the approaches developed are presented.

A meta-model for computer executable dynamic clinical safety checklists.

PubMed

Nan, Shan; Van Gorp, Pieter; Lu, Xudong; Kaymak, Uzay; Korsten, Hendrikus; Vdovjak, Richard; Duan, Huilong

2017-12-12

Safety checklist is a type of cognitive tool enforcing short term memory of medical workers with the purpose of reducing medical errors caused by overlook and ignorance. To facilitate the daily use of safety checklists, computerized systems embedded in the clinical workflow and adapted to patient-context are increasingly developed. However, the current hard-coded approach of implementing checklists in these systems increase the cognitive efforts of clinical experts and coding efforts for informaticists. This is due to the lack of a formal representation format that is both understandable by clinical experts and executable by computer programs. We developed a dynamic checklist meta-model with a three-step approach. Dynamic checklist modeling requirements were extracted by performing a domain analysis. Then, existing modeling approaches and tools were investigated with the purpose of reusing these languages. Finally, the meta-model was developed by eliciting domain concepts and their hierarchies. The feasibility of using the meta-model was validated by two case studies. The meta-model was mapped to specific modeling languages according to the requirements of hospitals. Using the proposed meta-model, a comprehensive coronary artery bypass graft peri-operative checklist set and a percutaneous coronary intervention peri-operative checklist set have been developed in a Dutch hospital and a Chinese hospital, respectively. The result shows that it is feasible to use the meta-model to facilitate the modeling and execution of dynamic checklists. We proposed a novel meta-model for the dynamic checklist with the purpose of facilitating creating dynamic checklists. The meta-model is a framework of reusing existing modeling languages and tools to model dynamic checklists. The feasibility of using the meta-model is validated by implementing a use case in the system.

Phase Transitions in Geomorphology

NASA Astrophysics Data System (ADS)

Ortiz, C. P.; Jerolmack, D. J.

2015-12-01

Landscapes are patterns in a dynamic steady-state, due to competing processes that smooth or sharpen features over large distances and times. Geomorphic transport laws have been developed to model the mass-flux due to different processes, but are unreasonably effective at recovering the scaling relations of landscape features. Using a continuum approximation to compare experimental landscapes and the observed landscapes of the earth, one finds they share similar morphodynamics despite a breakdown of classical dynamical similarity between the two. We propose the origin of this effectiveness is a different kind of dynamic similarity in the statistics of initiation and cessation of motion of groups of grains, which is common to disordered systems of grains under external driving. We will show how the existing data of sediment transport points to common signatures with dynamical phase transitions between "mobile" and "immobile" phases in other disordered systems, particularly granular materials, colloids, and foams. Viewing landscape evolution from the lens of non-equilibrium statistical physics of disordered systems leads to predictions that the transition of bulk measurements such as particle flux is continuous from one phase to another, that the collective nature of the particle dynamics leads to very slow aging of bulk properties, and that the dynamics are history-dependent. Recent results from sediment transport experiments support these predictions, suggesting that existing geomorphic transport laws may need to be replaced by a new generation of stochastic models with ingredients based on the physics of disordered phase transitions. We discuss possible strategies for extracting the necessary information to develop these models from measurements of geomorphic transport noise by connecting particle-scale collective dynamics and space-time fluctuations over landscape features.

A Surrogate for Debye-Waller Factors from Dynamic Stokes Shifts

PubMed Central

Zhong, Qin; Johnson, Jerainne; Aamer, Khaled A.; Tyagi, Madhusudan

2011-01-01

We show that the short-time behavior of time-resolved fluorescence Stokes shifts (TRSS) are similar to that of the intermediate scattering function obtained from neutron scattering at q near the peak in the static structure factor for glycerol. This allows us to extract a Debye-Waller (DW) factor analog from TRSS data at times as short as 1 ps in a relatively simple way. Using the time-domain relaxation data obtained by this method we show that DW factors evaluated at times ≥ 40 ps can be directly influenced by α relaxation and thus should be used with caution when evaluating relationships between fast and slow dynamics in glassforming systems. PMID:21701673

Visualizing and quantifying the in vivo structure and dynamics of the Arabidopsis cortical cytoskeleton using CLSM and VAEM.

PubMed

Rosero, Amparo; Zárský, Viktor; Cvrčková, Fatima

2014-01-01

The cortical microtubules, and to some extent also the actin meshwork, play a central role in the shaping of plant cells. Transgenic plants expressing fluorescent protein markers specifically tagging the two main cytoskeletal systems are available, allowing noninvasive in vivo studies. Advanced microscopy techniques, in particular confocal laser scanning microscopy (CLSM) and variable angle epifluorescence microscopy (VAEM), can be nowadays used for imaging the cortical cytoskeleton of living cells with unprecedented spatial and temporal resolution. With the aid of suitable computing techniques, quantitative information can be extracted from microscopic images and video sequences, providing insight into both architecture and dynamics of the cortical cytoskeleton.

NOUS: Construction and Querying of Dynamic Knowledge Graphs

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

Choudhury, Sutanay; Agarwal, Khushbu; Purohit, Sumit

The ability to construct domain specific knowledge graphs (KG) and perform question-answering or hypothesis generation is a trans- formative capability. Despite their value, automated construction of knowledge graphs remains an expensive technical challenge that is beyond the reach for most enterprises and academic institutions. We propose an end-to-end framework for developing custom knowl- edge graph driven analytics for arbitrary application domains. The uniqueness of our system lies A) in its combination of curated KGs along with knowledge extracted from unstructured text, B) support for advanced trending and explanatory questions on a dynamic KG, and C) the ability to answer queriesmore » where the answer is embedded across multiple data sources.« less

Andreev Bound States Formation and Quasiparticle Trapping in Quench Dynamics Revealed by Time-Dependent Counting Statistics.

PubMed

Souto, R Seoane; Martín-Rodero, A; Yeyati, A Levy

2016-12-23

We analyze the quantum quench dynamics in the formation of a phase-biased superconducting nanojunction. We find that in the absence of an external relaxation mechanism and for very general conditions the system gets trapped in a metastable state, corresponding to a nonequilibrium population of the Andreev bound states. The use of the time-dependent full counting statistics analysis allows us to extract information on the asymptotic population of even and odd many-body states, demonstrating that a universal behavior, dependent only on the Andreev state energy, is reached in the quantum point contact limit. These results shed light on recent experimental observations on quasiparticle trapping in superconducting atomic contacts.

Mass and stiffness estimation using mobile devices for structural health monitoring

NASA Astrophysics Data System (ADS)

Le, Viet; Yu, Tzuyang

2015-04-01

In the structural health monitoring (SHM) of civil infrastructure, dynamic methods using mass, damping, and stiffness for characterizing structural health have been a traditional and widely used approach. Changes in these system parameters over time indicate the progress of structural degradation or deterioration. In these methods, capability of predicting system parameters is essential to their success. In this paper, research work on the development of a dynamic SHM method based on perturbation analysis is reported. The concept is to use externally applied mass to perturb an unknown system and measure the natural frequency of the system. Derived theoretical expressions for mass and stiffness prediction are experimentally verified by a building model. Dynamic responses of the building model perturbed by various masses in free vibration were experimentally measured by a mobile device (cell phone) to extract the natural frequency of the building model. Single-degreeof- freedom (SDOF) modeling approach was adopted for the sake of using a cell phone. From the experimental result, it is shown that the percentage error of predicted mass increases when the mass ratio increases, while the percentage error of predicted stiffness decreases when the mass ratio increases. This work also demonstrated the potential use of mobile devices in the health monitoring of civil infrastructure.

A Neural-Dynamic Architecture for Concurrent Estimation of Object Pose and Identity

PubMed Central

Lomp, Oliver; Faubel, Christian; Schöner, Gregor

2017-01-01

Handling objects or interacting with a human user about objects on a shared tabletop requires that objects be identified after learning from a small number of views and that object pose be estimated. We present a neurally inspired architecture that learns object instances by storing features extracted from a single view of each object. Input features are color and edge histograms from a localized area that is updated during processing. The system finds the best-matching view for the object in a novel input image while concurrently estimating the object’s pose, aligning the learned view with current input. The system is based on neural dynamics, computationally operating in real time, and can handle dynamic scenes directly off live video input. In a scenario with 30 everyday objects, the system achieves recognition rates of 87.2% from a single training view for each object, while also estimating pose quite precisely. We further demonstrate that the system can track moving objects, and that it can segment the visual array, selecting and recognizing one object while suppressing input from another known object in the immediate vicinity. Evaluation on the COIL-100 dataset, in which objects are depicted from different viewing angles, revealed recognition rates of 91.1% on the first 30 objects, each learned from four training views. PMID:28503145

Experimental Results From the Thermal Energy Storage-1 (TES-1) Flight Experiment

NASA Technical Reports Server (NTRS)

Jacqmin, David

1995-01-01

The Thermal Energy Storage (TES) experiments are designed to provide data to help researchers understand the long-duration microgravity behavior of thermal energy storage fluoride salts that undergo repeated melting and freezing. Such data, which have never been obtained before, have direct application to space-based solar dynamic power systems. These power systems will store solar energy in a thermal energy salt, such as lithium fluoride (LiF) or a eutectic of lithium fluoride/calcium difluoride (LiF-CaF2) (which melts at a lower temperature). The energy will be stored as the latent heat of fusion when the salt is melted by absorbing solar thermal energy. The stored energy will then be extracted during the shade portion of the orbit, enabling the solar dynamic power system to provide constant electrical power over the entire orbit. Analytical computer codes have been developed to predict the performance of a spacebased solar dynamic power system. However, the analytical predictions must be verified experimentally before the analytical results can be used for future space power design applications. Four TES flight experiments will be used to obtain the needed experimental data. This article focuses on the flight results from the first experiment, TES-1, in comparison to the predicted results from the Thermal Energy Storage Simulation (TESSIM) analytical computer code.

[Study on condition for extraction of arctiin from fruits of Arctium lappa using supercritical fluid extraction].

PubMed

Dong, Wen-hong; Liu, Ben

2006-08-01

To study the feasibility of supercritical fluid extraction (SFE) for arctiin from the fruits of Arctium lappa. The extracts were analyzed by HPLC, optimum extraction conditions were studied by orthogonal tests. The optimal extraction conditions were: pressure 40 MPa, temperature 70 degrees C, using methanol as modifier carrier at the rate of 0.55 mL x min(-1), static extraction time 5 min, dynamic extraction 30 min, flow rate of CO2 2 L x min(-1). SFE has the superiority of adjustable polarity, and has the ability of extracting arctiin.

Quantitative, simultaneous, and collinear eye-tracked, high dynamic range optical coherence tomography at 850 and 1060 nm

NASA Astrophysics Data System (ADS)

Mooser, Matthias; Burri, Christian; Stoller, Markus; Luggen, David; Peyer, Michael; Arnold, Patrik; Meier, Christoph; Považay, Boris

2017-07-01

Ocular optical coherence tomography at the wavelengths ranges of 850 and 1060 nm have been integrated with a confocal scanning laser ophthalmoscope eye-tracker as a clinical commercial-class system. Collinear optics enables an exact overlap of the different channels to produce precisely overlapping depth-scans for evaluating the similarities and differences between the wavelengths to extract additional physiologic information. A reliable segmentation algorithm utilizing Graphcuts has been implemented and applied to automatically extract retinal and choroidal shape in cross-sections and volumes. The device has been tested in normals and pathologies including a cross-sectional and longitudinal study of myopia progress and control with a duplicate instrument in Asian children.

Relation of retinal blood flow and retinal oxygen extraction during stimulation with diffuse luminance flicker

PubMed Central

Palkovits, Stefan; Lasta, Michael; Told, Reinhard; Schmidl, Doreen; Werkmeister, René; Cherecheanu, Alina Popa; Garhöfer, Gerhard; Schmetterer, Leopold

2015-01-01

Cerebral and retinal blood flow are dependent on local neuronal activity. Several studies quantified the increase in cerebral blood flow and oxygen consumption during activity. In the present study we investigated the relation between changes in retinal blood flow and oxygen extraction during stimulation with diffuse luminance flicker and the influence of breathing gas mixtures with different fractions of O2 (FiO2; 100% 15% and 12%). Twenty-four healthy subjects were included. Retinal blood flow was studied by combining measurement of vessel diameters using the Dynamic Vessel Analyser with measurements of blood velocity using laser Doppler velocimetry. Oxygen saturation was measured using spectroscopic reflectometry and oxygen extraction was calculated. Flicker stimulation increased retinal blood flow (57.7 ± 17.8%) and oxygen extraction (34.6 ± 24.1%; p < 0.001 each). During 100% oxygen breathing the response of retinal blood flow and oxygen extraction was increased (p < 0.01 each). By contrast, breathing gas mixtures with 12% and 15% FiO2 did not alter flicker–induced retinal haemodynamic changes. The present study indicates that at a comparable increase in blood flow the increase in oxygen extraction in the retina is larger than in the brain. During systemic hyperoxia the blood flow and oxygen extraction responses to neural stimulation are augmented. The underlying mechanism is unknown. PMID:26672758

Upgrade of the beam extraction system of the GTS-LHC electron cyclotron resonance ion source at CERN.

PubMed

Toivanen, V; Bellodi, G; Dimov, V; Küchler, D; Lombardi, A M; Maintrot, M

2016-02-01

Linac3 is the first accelerator in the heavy ion injector chain of the Large Hadron Collider (LHC), providing multiply charged heavy ion beams for the CERN experimental program. The ion beams are produced with GTS-LHC, a 14.5 GHz electron cyclotron resonance ion source, operated in afterglow mode. Improvement of the GTS-LHC beam formation and beam transport along Linac3 is part of the upgrade program of the injector chain in preparation for the future high luminosity LHC. A mismatch between the ion beam properties in the ion source extraction region and the acceptance of the following Low Energy Beam Transport (LEBT) section has been identified as one of the factors limiting the Linac3 performance. The installation of a new focusing element, an einzel lens, into the GTS-LHC extraction region is foreseen as a part of the Linac3 upgrade, as well as a redesign of the first section of the LEBT. Details of the upgrade and results of a beam dynamics study of the extraction region and LEBT modifications will be presented.

Quantifying root water extraction after drought recovery using sub-mm in situ empirical data

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

Dhiman, Indu; Bilheux, Hassina Z.; DeCarlo, Keito F.

Root-specific responses to stress are not well-known, and have been largely based on indirect measurements of bulk soil water extraction, which limits mechanistic modeling of root function. Here, we used neutron radiography to examine in situ root-soil water dynamics of a previously droughted black cottonwood ( Populus trichocarpa) seedling, contrasting water uptake by younger, thinner or older, thicker parts of the fine root system. The smaller diameter roots had greater water uptake capacity per unit surface area than the larger diameter roots, but they had less total surface area leading to less total water extraction; rates ranged from 0.0027 –more » 0.0116 g cm -2 hr -1. The finest most-active roots were not visible in the radiographs, indicating the need to include destructive sampling. Analysis based on bulk soil hydraulic properties indicated substantial redistribution of water via saturated/unsaturated flow, capillary wicking, and root hydraulic redistribution across the layers - suggesting water uptake dynamics following an infiltration event may be more complex than approximated by common soil hydraulic or root surface area modeling approaches. Lastly, our results highlight the need for continued exploration of root-trait specific water uptake rates in situ, and impacts of roots on soil hydraulic properties – both critical components for mechanistic modeling of root function.« less

Quantifying root water extraction after drought recovery using sub-mm in situ empirical data

DOE PAGES

Dhiman, Indu; Bilheux, Hassina Z.; DeCarlo, Keito F.; ...

2017-09-09

Root-specific responses to stress are not well-known, and have been largely based on indirect measurements of bulk soil water extraction, which limits mechanistic modeling of root function. Here, we used neutron radiography to examine in situ root-soil water dynamics of a previously droughted black cottonwood ( Populus trichocarpa) seedling, contrasting water uptake by younger, thinner or older, thicker parts of the fine root system. The smaller diameter roots had greater water uptake capacity per unit surface area than the larger diameter roots, but they had less total surface area leading to less total water extraction; rates ranged from 0.0027 –more » 0.0116 g cm -2 hr -1. The finest most-active roots were not visible in the radiographs, indicating the need to include destructive sampling. Analysis based on bulk soil hydraulic properties indicated substantial redistribution of water via saturated/unsaturated flow, capillary wicking, and root hydraulic redistribution across the layers - suggesting water uptake dynamics following an infiltration event may be more complex than approximated by common soil hydraulic or root surface area modeling approaches. Lastly, our results highlight the need for continued exploration of root-trait specific water uptake rates in situ, and impacts of roots on soil hydraulic properties – both critical components for mechanistic modeling of root function.« less

Exciton-exciton annihilation in a disordered molecular system by direct and multistep Förster transfer

NASA Astrophysics Data System (ADS)

Fennel, Franziska; Lochbrunner, Stefan

2015-10-01

Exciton annihilation dynamics in a disordered organic model system is investigated by ultrafast absorption spectroscopy. We show that the temporal evolution of the exciton density can be quantitatively understood by applying Förster energy transfer theory to describe the diffusion of the excitons as well as the annihilation step itself. To this end, previous formulations of Förster theory are extended to account for the inhomogeneous distribution of the S0-S1 transition energies resulting in an effective exciton diffusion constant. Two annihilation pathways are considered, the direct transfer of an exciton between two excited molecules and diffusive motion by multiple transfer steps towards a second exciton preceding the annihilation event. One pathway can be emphasized with respect to the other by tuning the exciton diffusion constant via the chromophore concentration. The investigated system allows one to extract all relevant parameters for the description and provides in this way a proof that the annihilation dynamics can be entirely understood and modeled by Förster energy transfer.

Experimental Rectification of Entropy Production by Maxwell's Demon in a Quantum System

NASA Astrophysics Data System (ADS)

Camati, Patrice A.; Peterson, John P. S.; Batalhão, Tiago B.; Micadei, Kaonan; Souza, Alexandre M.; Sarthour, Roberto S.; Oliveira, Ivan S.; Serra, Roberto M.

2016-12-01

Maxwell's demon explores the role of information in physical processes. Employing information about microscopic degrees of freedom, this "intelligent observer" is capable of compensating entropy production (or extracting work), apparently challenging the second law of thermodynamics. In a modern standpoint, it is regarded as a feedback control mechanism and the limits of thermodynamics are recast incorporating information-to-energy conversion. We derive a trade-off relation between information-theoretic quantities empowering the design of an efficient Maxwell's demon in a quantum system. The demon is experimentally implemented as a spin-1 /2 quantum memory that acquires information, and employs it to control the dynamics of another spin-1 /2 system, through a natural interaction. Noise and imperfections in this protocol are investigated by the assessment of its effectiveness. This realization provides experimental evidence that the irreversibility in a nonequilibrium dynamics can be mitigated by assessing microscopic information and applying a feed-forward strategy at the quantum scale.

Experimental Rectification of Entropy Production by Maxwell's Demon in a Quantum System.

PubMed

Camati, Patrice A; Peterson, John P S; Batalhão, Tiago B; Micadei, Kaonan; Souza, Alexandre M; Sarthour, Roberto S; Oliveira, Ivan S; Serra, Roberto M

2016-12-09

Maxwell's demon explores the role of information in physical processes. Employing information about microscopic degrees of freedom, this "intelligent observer" is capable of compensating entropy production (or extracting work), apparently challenging the second law of thermodynamics. In a modern standpoint, it is regarded as a feedback control mechanism and the limits of thermodynamics are recast incorporating information-to-energy conversion. We derive a trade-off relation between information-theoretic quantities empowering the design of an efficient Maxwell's demon in a quantum system. The demon is experimentally implemented as a spin-1/2 quantum memory that acquires information, and employs it to control the dynamics of another spin-1/2 system, through a natural interaction. Noise and imperfections in this protocol are investigated by the assessment of its effectiveness. This realization provides experimental evidence that the irreversibility in a nonequilibrium dynamics can be mitigated by assessing microscopic information and applying a feed-forward strategy at the quantum scale.

A robust and efficient method for the extraction of plant extracellular surface lipids as applied to the analysis of silks and seedling leaves of maize

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

Loneman, Derek M.; Peddicord, Layton; Al-Rashid, Amani

Aerial plant organs possess a diverse array of extracellular surface lipids, including both non-polar and amphipathic constituents that collectively provide a primary line of defense against environmental stressors. Extracellular surface lipids on the stigmatic silks of maize are composed primarily of saturated and unsaturated linear hydrocarbons, as well as fatty acids, and aldehydes. To efficiently extract lipids of differing polarities from maize silks, five solvent systems (hexanes; hexanes:diethyl ether (95:5); hexanes:diethyl ether (90:10); chloroform:hexanes (1:1) and chloroform) were tested by immersing fresh silks in solvent for different extraction times. Surface lipid recovery and the relative composition of individual constituents weremore » impacted to varying degrees depending on solvent choice and duration of extraction. Analyses were performed using both silks and leaves to demonstrate the utility of the solvent- and time-optimized protocol in comparison to extraction with the commonly used chloroform solvent. Overall, the preferred solvent system was identified as hexanes:diethyl ether (90:10), based on its effectiveness in extracting surface hydrocarbons and fatty acids as well as its reduced propensity to extract presumed internal fatty acids. Metabolite profiling of wildtype and glossy1 seedlings, which are impaired in surface lipid biosynthesis, demonstrated the ability of the preferred solvent to extract extracellular surface lipids rich in amphipathic compounds (aldehydes and alcohols). In addition to the expected deficiencies in dotriacontanal and dotriacontan-1-ol for gl1 seedlings, an unexpected increase in fatty acid recovery was observed in gl1 seedlings extracted in chloroform, suggesting that chloro-form extracts lipids from internal tissues of gl1 seedlings. This highlights the importance of extraction method when evaluating mutants that have altered cuticular lipid compositions. Lastly, metabolite profiling of silks from maize inbreds B73 and Mo17, exposed to different environments and harvested at different ages, revealed differences in hydrocarbon and fatty acid composition, demonstrating the dynamic nature of surface lipid accumulation on silks.« less

A robust and efficient method for the extraction of plant extracellular surface lipids as applied to the analysis of silks and seedling leaves of maize

DOE PAGES

Loneman, Derek M.; Peddicord, Layton; Al-Rashid, Amani; ...

2017-07-11

Aerial plant organs possess a diverse array of extracellular surface lipids, including both non-polar and amphipathic constituents that collectively provide a primary line of defense against environmental stressors. Extracellular surface lipids on the stigmatic silks of maize are composed primarily of saturated and unsaturated linear hydrocarbons, as well as fatty acids, and aldehydes. To efficiently extract lipids of differing polarities from maize silks, five solvent systems (hexanes; hexanes:diethyl ether (95:5); hexanes:diethyl ether (90:10); chloroform:hexanes (1:1) and chloroform) were tested by immersing fresh silks in solvent for different extraction times. Surface lipid recovery and the relative composition of individual constituents weremore » impacted to varying degrees depending on solvent choice and duration of extraction. Analyses were performed using both silks and leaves to demonstrate the utility of the solvent- and time-optimized protocol in comparison to extraction with the commonly used chloroform solvent. Overall, the preferred solvent system was identified as hexanes:diethyl ether (90:10), based on its effectiveness in extracting surface hydrocarbons and fatty acids as well as its reduced propensity to extract presumed internal fatty acids. Metabolite profiling of wildtype and glossy1 seedlings, which are impaired in surface lipid biosynthesis, demonstrated the ability of the preferred solvent to extract extracellular surface lipids rich in amphipathic compounds (aldehydes and alcohols). In addition to the expected deficiencies in dotriacontanal and dotriacontan-1-ol for gl1 seedlings, an unexpected increase in fatty acid recovery was observed in gl1 seedlings extracted in chloroform, suggesting that chloro-form extracts lipids from internal tissues of gl1 seedlings. This highlights the importance of extraction method when evaluating mutants that have altered cuticular lipid compositions. Lastly, metabolite profiling of silks from maize inbreds B73 and Mo17, exposed to different environments and harvested at different ages, revealed differences in hydrocarbon and fatty acid composition, demonstrating the dynamic nature of surface lipid accumulation on silks.« less

Reliability of unstable periodic orbit based control strategies in biological systems

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

Mishra, Nagender; Singh, Harinder P.; Hasse, Maria

2015-04-15

Presence of recurrent and statistically significant unstable periodic orbits (UPOs) in time series obtained from biological systems is now routinely used as evidence for low dimensional chaos. Extracting accurate dynamical information from the detected UPO trajectories is vital for successful control strategies that either aim to stabilize the system near the fixed point or steer the system away from the periodic orbits. A hybrid UPO detection method from return maps that combines topological recurrence criterion, matrix fit algorithm, and stringent criterion for fixed point location gives accurate and statistically significant UPOs even in the presence of significant noise. Geometry ofmore » the return map, frequency of UPOs visiting the same trajectory, length of the data set, strength of the noise, and degree of nonstationarity affect the efficacy of the proposed method. Results suggest that establishing determinism from unambiguous UPO detection is often possible in short data sets with significant noise, but derived dynamical properties are rarely accurate and adequate for controlling the dynamics around these UPOs. A repeat chaos control experiment on epileptic hippocampal slices through more stringent control strategy and adaptive UPO tracking is reinterpreted in this context through simulation of similar control experiments on an analogous but stochastic computer model of epileptic brain slices. Reproduction of equivalent results suggests that far more stringent criteria are needed for linking apparent success of control in such experiments with possible determinism in the underlying dynamics.« less

Direct thermal desorption in the analysis of cheese volatiles by gas chromatography and gas chromatography-mass spectrometry: comparison with simultaneous distillation-extraction and dynamic headspace.

PubMed

Valero, E; Sanz, J; Martínez-Castro, I

2001-06-01

Direct thermal desorption (DTD) has been used as a technique for extracting volatile components of cheese as a preliminary step to their gas chromatographic (GC) analysis. In this study, it is applied to different cheese varieties: Camembert, blue, Chaumes, and La Serena. Volatiles are also extracted using other techniques such as simultaneous distillation-extraction and dynamic headspace. Separation and identification of the cheese components are carried out by GC-mass spectrometry. Approximately 100 compounds are detected in the examined cheeses. The described results show that DTD is fast, simple, and easy to automate; requires only a small amount of sample (approximately 50 mg); and affords quantitative information about the main groups of compounds present in cheeses.

Summary of CPAS EDU Testing Analysis Results

NASA Technical Reports Server (NTRS)

Romero, Leah M.; Bledsoe, Kristin J.; Davidson, John.; Engert, Meagan E.; Fraire, Usbaldo, Jr.; Galaviz, Fernando S.; Galvin, Patrick J.; Ray, Eric S.; Varela, Jose

2015-01-01

The Orion program's Capsule Parachute Assembly System (CPAS) project is currently conducting its third generation of testing, the Engineering Development Unit (EDU) series. This series utilizes two test articles, a dart-shaped Parachute Compartment Drop Test Vehicle (PCDTV) and capsule-shaped Parachute Test Vehicle (PTV), both of which include a full size, flight-like parachute system and require a pallet delivery system for aircraft extraction. To date, 15 tests have been completed, including six with PCDTVs and nine with PTVs. Two of the PTV tests included the Forward Bay Cover (FBC) provided by Lockheed Martin. Advancements in modeling techniques applicable to parachute fly-out, vehicle rate of descent, torque, and load train, also occurred during the EDU testing series. An upgrade from a composite to an independent parachute simulation allowed parachute modeling at a higher level of fidelity than during previous generations. The complexity of separating the test vehicles from their pallet delivery systems necessitated the use the Automatic Dynamic Analysis of Mechanical Systems (ADAMS) simulator for modeling mated vehicle aircraft extraction and separation. This paper gives an overview of each EDU test and summarizes the development of CPAS analysis tools and techniques during EDU testing.

Building entity models through observation and learning

NASA Astrophysics Data System (ADS)

Garcia, Richard; Kania, Robert; Fields, MaryAnne; Barnes, Laura

2011-05-01

To support the missions and tasks of mixed robotic/human teams, future robotic systems will need to adapt to the dynamic behavior of both teammates and opponents. One of the basic elements of this adaptation is the ability to exploit both long and short-term temporal data. This adaptation allows robotic systems to predict/anticipate, as well as influence, future behavior for both opponents and teammates and will afford the system the ability to adjust its own behavior in order to optimize its ability to achieve the mission goals. This work is a preliminary step in the effort to develop online entity behavior models through a combination of learning techniques and observations. As knowledge is extracted from the system through sensor and temporal feedback, agents within the multi-agent system attempt to develop and exploit a basic movement model of an opponent. For the purpose of this work, extraction and exploitation is performed through the use of a discretized two-dimensional game. The game consists of a predetermined number of sentries attempting to keep an unknown intruder agent from penetrating their territory. The sentries utilize temporal data coupled with past opponent observations to hypothesize the probable locations of the opponent and thus optimize their guarding locations.

Advanced image collection, information extraction, and change detection in support of NN-20 broad area search and analysis

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

Petrie, G.M.; Perry, E.M.; Kirkham, R.R.

1997-09-01

This report describes the work performed at the Pacific Northwest National Laboratory (PNNL) for the U.S. Department of Energy`s Office of Nonproliferation and National Security, Office of Research and Development (NN-20). The work supports the NN-20 Broad Area Search and Analysis, a program initiated by NN-20 to improve the detection and classification of undeclared weapons facilities. Ongoing PNNL research activities are described in three main components: image collection, information processing, and change analysis. The Multispectral Airborne Imaging System, which was developed to collect georeferenced imagery in the visible through infrared regions of the spectrum, and flown on a light aircraftmore » platform, will supply current land use conditions. The image information extraction software (dynamic clustering and end-member extraction) uses imagery, like the multispectral data collected by the PNNL multispectral system, to efficiently generate landcover information. The advanced change detection uses a priori (benchmark) information, current landcover conditions, and user-supplied rules to rank suspect areas by probable risk of undeclared facilities or proliferation activities. These components, both separately and combined, provide important tools for improving the detection of undeclared facilities.« less

Using STELLA System Dynamic Model to Analyze Greenhouse Gases' Emission From Solid Waste Management in Taiwan

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

Horng, Jao-Jia; Lee, R.F.; Liao, K.Y.

2004-03-31

Using a system dynamic model (SDM), such as STELLA, to analyze the waste management policy is a new trial for Taiwan's research communities. We have developed an easy and relatively accurate model for analyzing the greenhouse gases emission for the wastes from animal farming and municipalities. With the local research data of the past decade, we extract the most prominent factors and assemble the SDM. The results and scenarios were compared with the national inventory. By comparing to the past data, we found these models reasonably represent the situation in Taiwan. However, SDM can program many scenarios and produce amore » lot of prediction data. With the development of many program control tools on STELLA, we believe the models could be further used by researchers or policy-makers to find the needed research topics, to set the future scenarios and to determine the management tools.« less

State-Dependent Decoding Algorithms Improve the Performance of a Bidirectional BMI in Anesthetized Rats.

PubMed

De Feo, Vito; Boi, Fabio; Safaai, Houman; Onken, Arno; Panzeri, Stefano; Vato, Alessandro

2017-01-01

Brain-machine interfaces (BMIs) promise to improve the quality of life of patients suffering from sensory and motor disabilities by creating a direct communication channel between the brain and the external world. Yet, their performance is currently limited by the relatively small amount of information that can be decoded from neural activity recorded form the brain. We have recently proposed that such decoding performance may be improved when using state-dependent decoding algorithms that predict and discount the large component of the trial-to-trial variability of neural activity which is due to the dependence of neural responses on the network's current internal state. Here we tested this idea by using a bidirectional BMI to investigate the gain in performance arising from using a state-dependent decoding algorithm. This BMI, implemented in anesthetized rats, controlled the movement of a dynamical system using neural activity decoded from motor cortex and fed back to the brain the dynamical system's position by electrically microstimulating somatosensory cortex. We found that using state-dependent algorithms that tracked the dynamics of ongoing activity led to an increase in the amount of information extracted form neural activity by 22%, with a consequently increase in all of the indices measuring the BMI's performance in controlling the dynamical system. This suggests that state-dependent decoding algorithms may be used to enhance BMIs at moderate computational cost.

Using Dynamic Multi-Task Non-Negative Matrix Factorization to Detect the Evolution of User Preferences in Collaborative Filtering

PubMed Central

Ju, Bin; Qian, Yuntao; Ye, Minchao; Ni, Rong; Zhu, Chenxi

2015-01-01

Predicting what items will be selected by a target user in the future is an important function for recommendation systems. Matrix factorization techniques have been shown to achieve good performance on temporal rating-type data, but little is known about temporal item selection data. In this paper, we developed a unified model that combines Multi-task Non-negative Matrix Factorization and Linear Dynamical Systems to capture the evolution of user preferences. Specifically, user and item features are projected into latent factor space by factoring co-occurrence matrices into a common basis item-factor matrix and multiple factor-user matrices. Moreover, we represented both within and between relationships of multiple factor-user matrices using a state transition matrix to capture the changes in user preferences over time. The experiments show that our proposed algorithm outperforms the other algorithms on two real datasets, which were extracted from Netflix movies and Last.fm music. Furthermore, our model provides a novel dynamic topic model for tracking the evolution of the behavior of a user over time. PMID:26270539

Using Dynamic Multi-Task Non-Negative Matrix Factorization to Detect the Evolution of User Preferences in Collaborative Filtering.

PubMed

Ju, Bin; Qian, Yuntao; Ye, Minchao; Ni, Rong; Zhu, Chenxi

2015-01-01

Predicting what items will be selected by a target user in the future is an important function for recommendation systems. Matrix factorization techniques have been shown to achieve good performance on temporal rating-type data, but little is known about temporal item selection data. In this paper, we developed a unified model that combines Multi-task Non-negative Matrix Factorization and Linear Dynamical Systems to capture the evolution of user preferences. Specifically, user and item features are projected into latent factor space by factoring co-occurrence matrices into a common basis item-factor matrix and multiple factor-user matrices. Moreover, we represented both within and between relationships of multiple factor-user matrices using a state transition matrix to capture the changes in user preferences over time. The experiments show that our proposed algorithm outperforms the other algorithms on two real datasets, which were extracted from Netflix movies and Last.fm music. Furthermore, our model provides a novel dynamic topic model for tracking the evolution of the behavior of a user over time.

A comparative analysis of alternative approaches for quantifying nonlinear dynamics in cardiovascular system.

PubMed

Chen, Yun; Yang, Hui

2013-01-01

Heart rate variability (HRV) analysis has emerged as an important research topic to evaluate autonomic cardiac function. However, traditional time and frequency-domain analysis characterizes and quantify only linear and stationary phenomena. In the present investigation, we made a comparative analysis of three alternative approaches (i.e., wavelet multifractal analysis, Lyapunov exponents and multiscale entropy analysis) for quantifying nonlinear dynamics in heart rate time series. Note that these extracted nonlinear features provide information about nonlinear scaling behaviors and the complexity of cardiac systems. To evaluate the performance, we used 24-hour HRV recordings from 54 healthy subjects and 29 heart failure patients, available in PhysioNet. Three nonlinear methods are evaluated not only individually but also in combination using three classification algorithms, i.e., linear discriminate analysis, quadratic discriminate analysis and k-nearest neighbors. Experimental results show that three nonlinear methods capture nonlinear dynamics from different perspectives and the combined feature set achieves the best performance, i.e., sensitivity 97.7% and specificity 91.5%. Collectively, nonlinear HRV features are shown to have the promise to identify the disorders in autonomic cardiovascular function.

Nuclear Fission: from more phenomenology and adjusted parameters to more fundamental theory and increased predictive power

NASA Astrophysics Data System (ADS)

Bulgac, Aurel; Jin, Shi; Magierski, Piotr; Roche, Kenneth; Schunck, Nicolas; Stetcu, Ionel

2017-11-01

Two major recent developments in theory and computational resources created the favorable conditions for achieving a microscopic description of fission dynamics in classically allowed regions of the collective potential energy surface, almost eighty years after its discovery in 1939 by Hahn and Strassmann [1]. The first major development was in theory, the extension of the Time-Dependent Density Functional Theory (TDDFT) [2-5] to superfluid fermion systems [6]. The second development was in computing, the emergence of powerful enough supercomputers capable of solving the complex systems of equations describing the time evolution in three dimensions without any restrictions of hundreds of strongly interacting nucleons. Thus the conditions have been created to renounce phenomenological models and incomplete microscopic treatments with uncontrollable approximations and/or assumptions in the description of the complex dynamics of fission. Even though the available nuclear energy density functionals (NEDFs) are phenomenological still, their accuracy is improving steadily and the prospects of being able to perform calculations of the nuclear fission dynamics and to predict many properties of the fission fragments, otherwise not possible to extract from experiments.

The dynamics of information-driven coordination phenomena: A transfer entropy analysis

PubMed Central

Borge-Holthoefer, Javier; Perra, Nicola; Gonçalves, Bruno; González-Bailón, Sandra; Arenas, Alex; Moreno, Yamir; Vespignani, Alessandro

2016-01-01

Data from social media provide unprecedented opportunities to investigate the processes that govern the dynamics of collective social phenomena. We consider an information theoretical approach to define and measure the temporal and structural signatures typical of collective social events as they arise and gain prominence. We use the symbolic transfer entropy analysis of microblogging time series to extract directed networks of influence among geolocalized subunits in social systems. This methodology captures the emergence of system-level dynamics close to the onset of socially relevant collective phenomena. The framework is validated against a detailed empirical analysis of five case studies. In particular, we identify a change in the characteristic time scale of the information transfer that flags the onset of information-driven collective phenomena. Furthermore, our approach identifies an order-disorder transition in the directed network of influence between social subunits. In the absence of clear exogenous driving, social collective phenomena can be represented as endogenously driven structural transitions of the information transfer network. This study provides results that can help define models and predictive algorithms for the analysis of societal events based on open source data. PMID:27051875

The dynamics of information-driven coordination phenomena: A transfer entropy analysis.

PubMed

Borge-Holthoefer, Javier; Perra, Nicola; Gonçalves, Bruno; González-Bailón, Sandra; Arenas, Alex; Moreno, Yamir; Vespignani, Alessandro

2016-04-01

Data from social media provide unprecedented opportunities to investigate the processes that govern the dynamics of collective social phenomena. We consider an information theoretical approach to define and measure the temporal and structural signatures typical of collective social events as they arise and gain prominence. We use the symbolic transfer entropy analysis of microblogging time series to extract directed networks of influence among geolocalized subunits in social systems. This methodology captures the emergence of system-level dynamics close to the onset of socially relevant collective phenomena. The framework is validated against a detailed empirical analysis of five case studies. In particular, we identify a change in the characteristic time scale of the information transfer that flags the onset of information-driven collective phenomena. Furthermore, our approach identifies an order-disorder transition in the directed network of influence between social subunits. In the absence of clear exogenous driving, social collective phenomena can be represented as endogenously driven structural transitions of the information transfer network. This study provides results that can help define models and predictive algorithms for the analysis of societal events based on open source data.

Supercritical carbon dioxide extraction of seed oil from winter melon (Benincasa hispida) and its antioxidant activity and fatty acid composition.

PubMed

Bimakr, Mandana; Rahman, Russly Abdul; Taip, Farah Saleena; Adzahan, Noranizan Mohd; Sarker, Md Zaidul Islam; Ganjloo, Ali

2013-01-15

In the present study, supercritical carbon dioxide (SC-CO(2)) extraction of seed oil from winter melon (Benincasa hispida) was investigated. The effects of process variables namely pressure (150-300 bar), temperature (40-50 °C) and dynamic extraction time (60-120 min) on crude extraction yield (CEY) were studied through response surface methodology (RSM). The SC-CO(2) extraction process was modified using ethanol (99.9%) as co-solvent. Perturbation plot revealed the significant effect of all process variables on the CEY. A central composite design (CCD) was used to optimize the process conditions to achieve maximum CEY. The optimum conditions were 244 bar pressure, 46 °C temperature and 97 min dynamic extraction time. Under these optimal conditions, the CEY was predicted to be 176.30 mg-extract/g-dried sample. The validation experiment results agreed with the predicted value. The antioxidant activity and fatty acid composition of crude oil obtained under optimized conditions were determined and compared with published results using Soxhlet extraction (SE) and ultrasound assisted extraction (UAE). It was found that the antioxidant activity of the extract obtained by SC-CO(2) extraction was strongly higher than those obtained by SE and UAE. Identification of fatty acid composition using gas chromatography (GC) showed that all the extracts were rich in unsaturated fatty acids with the most being linoleic acid. In contrast, the amount of saturated fatty acids extracted by SE was higher than that extracted under optimized SC-CO(2) extraction conditions.

Extracting full-field dynamic strain response of a rotating wind turbine using photogrammetry

NASA Astrophysics Data System (ADS)

Baqersad, Javad; Poozesh, Peyman; Niezrecki, Christopher; Avitabile, Peter

2015-04-01

Health monitoring of wind turbines is typically performed using conventional sensors (e.g. strain-gages and accelerometers) that are usually mounted to the nacelle or gearbox. Although many wind turbines stop operating due to blade failures, there are typically few to no sensor mounted on the blades. Placing sensors on the rotating parts of the structure is a challenge due to the wiring and data transmission constraints. Within the current work, an approach to monitor full-field dynamic response of rotating structures (e.g. wind turbine blades or helicopter rotors) is developed and experimentally verified. A wind turbine rotor was used as the test structure and was mounted to a block and horizontally placed on the ground. A pair of bearings connected to the rotor shaft allowed the turbine to freely spin along the shaft. Several optical targets were mounted to the blades and a pair of high-speed cameras was used to monitor the dynamics of the spinning turbine. Displacements of the targets during rotation were measured using three-dimensional point tracking. The point tracking technique measured both rigid body displacement and flexible deformation of the blades at target locations. While the structure is rotating, only flap displacements of optical targets (displacements out of the rotation plane) were used in strain prediction process. The measured displacements were expanded and applied to the finite element model of the turbine to extract full-field dynamic strain on the structure. The proposed approach enabled the prediction of dynamic response on the outer surface as well as within the inner points of the structure where no other sensor could be easily mounted. In order to validate the proposed approach, the predicted strain was compared to strain measured at four locations on the spinning blades using a wireless strain-gage system.

Future Oil Spills and Possibilities for Intervention: A Model for the Coupled Human-Environmental Resource Extraction System

NASA Astrophysics Data System (ADS)

Shughrue, C. M.; Werner, B.; Nugnug, P. T.

2010-12-01

The catastrophic Deepwater Horizon oil spill highlights the risks for widespread environmental damage resulting from petroleum resource extraction. Possibilities for amelioration of these risks depend critically on understanding the dynamics and nonlinear interactions between various components of the coupled human-environmental resource extraction system. We use a complexity analysis to identify the levels of description and time scales at which these interactions are strongest, and then use the analysis as the basis for an agent-based numerical model with which decadal trends can be analyzed. Oil industry economic and technological activity and associated oil spills are components of a complex system that is coupled to natural environment, legislation, regulation, media, and resistance systems over annual to decadal time scales. In the model, oil spills are produced stochastically with a range of magnitudes depending on a reliability-engineering-based assessment of failure for the technology employed, human factors including compliance with operating procedures, and risks associated with the drilling environment. Oil industry agents determine drilling location and technological investment using a cost-benefit analysis relating projected revenue from added production to technology cost and government regulation. Media outlet agents reporting on the oil industry and environmental damage from oil spills assess the impacts of aggressively covering a story on circulation increases, advertiser concerns and potential loss of information sources. Environmental advocacy group agents increase public awareness of environmental damage (through media and public contact), solicit memberships and donations, and apply direct pressure on legislators for policy change. Heterogeneous general public agents adjust their desire for change in the level of regulation, contact their representatives or participate in resistance via protest by considering media sources, personal experiences with oil spills and individual predispositions toward the industry. Legislator agents pass legislation and influence regulator agents based on interaction with oil industry, media and general public agents. Regulator agents generate and enforce regulations by responding to pressure from legislator and oil industry agents. Oil spill impacts on the natural environment are related to number and magnitude of spills, drilling locations, and spill response methodology, determined collaboratively by government and oil company agents. Agents at the corporate and government levels use heterogeneous prediction models combined with a constant absolute risk aversion utility for wealth. This model simulates a nonlinear adaptive system with mechanisms to self-regulate oil industry activity, environmental damage and public response. A comparison of model output with historical oil industry development and environmental damage; the sensitivity of oil spill damage to economic, political and social factors; the potential for the emergence of new and possibly unstable behaviors; and opportunities for intervening in system dynamics to alter expected outcomes will be discussed. Supported by NSF: Geomorphology and Land Use Dynamics Program

Repetitive Regeneration of Media #1 in a Dynamic Column Extraction using Brine #1

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

Gary Garland

This data is from a regeneration study from a dynamic column extraction experiment where we ran a solution of REE's through a column of media #1 then stripped the REE's off the media using 2M HNO3 solution. We then re-equilibrated the media and repeated the process of running a REE solution through the column and stripping the REE's off the media and comparing the two runs.

Novel method of extracting motion from natural movies.

PubMed

Suzuki, Wataru; Ichinohe, Noritaka; Tani, Toshiki; Hayami, Taku; Miyakawa, Naohisa; Watanabe, Satoshi; Takeichi, Hiroshige

2017-11-01

The visual system in primates can be segregated into motion and shape pathways. Interaction occurs at multiple stages along these pathways. Processing of shape-from-motion and biological motion is considered to be a higher-order integration process involving motion and shape information. However, relatively limited types of stimuli have been used in previous studies on these integration processes. We propose a new algorithm to extract object motion information from natural movies and to move random dots in accordance with the information. The object motion information is extracted by estimating the dynamics of local normal vectors of the image intensity projected onto the x-y plane of the movie. An electrophysiological experiment on two adult common marmoset monkeys (Callithrix jacchus) showed that the natural and random dot movies generated with this new algorithm yielded comparable neural responses in the middle temporal visual area. In principle, this algorithm provided random dot motion stimuli containing shape information for arbitrary natural movies. This new method is expected to expand the neurophysiological and psychophysical experimental protocols to elucidate the integration processing of motion and shape information in biological systems. The novel algorithm proposed here was effective in extracting object motion information from natural movies and provided new motion stimuli to investigate higher-order motion information processing. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Towards ultrafast dynamics with split-pulse X-ray photon correlation spectroscopy at free electron laser sources

DOE PAGES

Roseker, W.; Hruszkewycz, S. O.; Lehmkuhler, F.; ...

2018-04-27

One of the important challenges in condensed matter science is to understand ultrafast, atomic-scale fluctuations that dictate dynamic processes in equilibrium and non-equilibrium materials. Here, we report an important step towards reaching that goal by using a state-of-the-art perfect crystal based split-and-delay system, capable of splitting individual X-ray pulses and introducing femtosecond to nanosecond time delays. We show the results of an ultrafast hard X-ray photon correlation spectroscopy experiment at LCLS where split X-ray pulses were used to measure the dynamics of gold nanoparticles suspended in hexane. We show how reliable speckle contrast values can be extracted even from verymore » low intensity free electron laser (FEL) speckle patterns by applying maximum likelihood fitting, thus demonstrating the potential of a split-and-delay approach for dynamics measurements at FEL sources. This will enable the characterization of equilibrium and, importantly also reversible non-equilibrium processes in atomically disordered materials.« less

Application of system identification to analytic rotor modeling from simulated and wind tunnel dynamic test data, part 2

NASA Technical Reports Server (NTRS)

Hohenemser, K. H.; Banerjee, D.

1977-01-01

An introduction to aircraft state and parameter identification methods is presented. A simplified form of the maximum likelihood method is selected to extract analytical aeroelastic rotor models from simulated and dynamic wind tunnel test results for accelerated cyclic pitch stirring excitation. The dynamic inflow characteristics for forward flight conditions from the blade flapping responses without direct inflow measurements were examined. The rotor blades are essentially rigid for inplane bending and for torsion within the frequency range of study, but flexible in out-of-plane bending. Reverse flow effects are considered for high rotor advance ratios. Two inflow models are studied; the first is based on an equivalent blade Lock number, the second is based on a time delayed momentum inflow. In addition to the inflow parameters, basic rotor parameters like the blade natural frequency and the actual blade Lock number are identified together with measurement bias values. The effect of the theoretical dynamic inflow on the rotor eigenvalues is evaluated.

Towards ultrafast dynamics with split-pulse X-ray photon correlation spectroscopy at free electron laser sources

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

Roseker, W.; Hruszkewycz, S. O.; Lehmkuhler, F.

One of the important challenges in condensed matter science is to understand ultrafast, atomic-scale fluctuations that dictate dynamic processes in equilibrium and non-equilibrium materials. Here, we report an important step towards reaching that goal by using a state-of-the-art perfect crystal based split-and-delay system, capable of splitting individual X-ray pulses and introducing femtosecond to nanosecond time delays. We show the results of an ultrafast hard X-ray photon correlation spectroscopy experiment at LCLS where split X-ray pulses were used to measure the dynamics of gold nanoparticles suspended in hexane. We show how reliable speckle contrast values can be extracted even from verymore » low intensity free electron laser (FEL) speckle patterns by applying maximum likelihood fitting, thus demonstrating the potential of a split-and-delay approach for dynamics measurements at FEL sources. This will enable the characterization of equilibrium and, importantly also reversible non-equilibrium processes in atomically disordered materials.« less

Detecting intrinsic dynamics of traffic flow with recurrence analysis and empirical mode decomposition

NASA Astrophysics Data System (ADS)

Xiong, Hui; Shang, Pengjian; Bian, Songhan

2017-05-01

In this paper, we apply the empirical mode decomposition (EMD) method to the recurrence plot (RP) and recurrence quantification analysis (RQA), to evaluate the frequency- and time-evolving dynamics of the traffic flow. Based on the cumulative intrinsic mode functions extracted by the EMD, the frequency-evolving RP regarding different oscillation of modes suggests that apparent dynamics of the data considered are mainly dominated by its components of medium- and low-frequencies while severely affected by fast oscillated noises contained in the signal. Noises are then eliminated to analyze the intrinsic dynamics and consequently, the denoised time-evolving RQA diversely characterizes the properties of the signal and marks crucial points more accurately where white bands in the RP occur, whereas a strongly qualitative agreement exists between all the non-denoised RQA measures. Generally, the EMD combining with the recurrence analysis sheds more reliable, abundant and inherent lights into the traffic flow, which is meaningful to the empirical analysis of complex systems.

Imaging transcription factors dynamics with advanced fluorescence microscopy methods.

PubMed

Verneri, Paula; Romero, Juan José; De Rossi, María Cecilia; Alvarez, Yanina; Oses, Camila; Guberman, Alejandra; Levi, Valeria

2018-05-10

Pluripotent stem cells (PSCs) are capable of self-renewing and producing all cell types derived from the three germ layers in response to developmental cues, constituting an important promise for regenerative medicine. Pluripotency depends on specific transcription factors (TFs) that induce genes required to preserve the undifferentiated state and repress other genes related to differentiation. The transcription machinery and regulatory components such as TFs are recruited dynamically on their target genes making it essential exploring their dynamics in living cells to understand the transcriptional output. Non-invasive and very sensitive fluorescence microscopy methods are making it possible visualizing the dynamics of TFs in living specimens, complementing the information extracted from studies in fixed specimens and bulk assays. In this work, we briefly describe the basis of these microscopy methods and review how they contributed to our knowledge of the function of TFs relevant to embryo development and cell differentiation in a variety of systems ranging from single cells to whole organisms. Copyright © 2017. Published by Elsevier B.V.

Detecting many-body-localization lengths with cold atoms

NASA Astrophysics Data System (ADS)

Guo, Xuefei; Li, Xiaopeng

2018-03-01

Considering ultracold atoms in optical lattices, we propose experimental protocols to study many-body-localization (MBL) length and criticality in quench dynamics. Through numerical simulations with exact diagonalization, we show that in the MBL phase the perturbed density profile following a local quench remains exponentially localized in postquench dynamics. The size of this density profile after long-time-dynamics defines a localization length, which tends to diverge at the MBL-to-ergodic transition as we increase the system size. The determined localization transition point agrees with previous exact diagonalization calculations using other diagnostics. Our numerical results provide evidence for violation of the Harris-Chayes bound for the MBL criticality. The critical exponent ν can be extracted from our proposed dynamical procedure, which can then be used directly in experiments to determine whether the Harris-Chayes-bound holds for the MBL transition. These proposed protocols to detect localization criticality are justified by benchmarking to the well-established results for the noninteracting three-dimensional Anderson localization.

Hierarchical classification of dynamically varying radar pulse repetition interval modulation patterns.

PubMed

Kauppi, Jukka-Pekka; Martikainen, Kalle; Ruotsalainen, Ulla

2010-12-01

The central purpose of passive signal intercept receivers is to perform automatic categorization of unknown radar signals. Currently, there is an urgent need to develop intelligent classification algorithms for these devices due to emerging complexity of radar waveforms. Especially multifunction radars (MFRs) capable of performing several simultaneous tasks by utilizing complex, dynamically varying scheduled waveforms are a major challenge for automatic pattern classification systems. To assist recognition of complex radar emissions in modern intercept receivers, we have developed a novel method to recognize dynamically varying pulse repetition interval (PRI) modulation patterns emitted by MFRs. We use robust feature extraction and classifier design techniques to assist recognition in unpredictable real-world signal environments. We classify received pulse trains hierarchically which allows unambiguous detection of the subpatterns using a sliding window. Accuracy, robustness and reliability of the technique are demonstrated with extensive simulations using both static and dynamically varying PRI modulation patterns. Copyright © 2010 Elsevier Ltd. All rights reserved.

Petrological Geodynamics of Mantle Melting II. AlphaMELTS + Multiphase Flow: Dynamic Fractional Melting

NASA Astrophysics Data System (ADS)

Tirone, Massimiliano

2018-03-01

In this second installment of a series that aims to investigate the dynamic interaction between the composition and abundance of the solid mantle and its melt products, the classic interpretation of fractional melting is extended to account for the dynamic nature of the process. A multiphase numerical flow model is coupled with the program AlphaMELTS, which provides at the moment possibly the most accurate petrological description of melting based on thermodynamic principles. The conceptual idea of this study is based on a description of the melting process taking place along a 1-D vertical ideal column where chemical equilibrium is assumed to apply in two local sub-systems separately on some spatial and temporal scale. The solid mantle belongs to a local sub-system (ss1) that does not interact chemically with the melt reservoir which forms a second sub-system (ss2). The local melt products are transferred in the melt sub-system ss2 where the melt phase eventually can also crystallize into a different solid assemblage and will evolve dynamically. The main difference with the usual interpretation of fractional melting is that melt is not arbitrarily and instantaneously extracted from the mantle, but instead remains a dynamic component of the model, hence the process is named dynamic fractional melting (DFM). Some of the conditions that may affect the DFM model are investigated in this study, in particular the effect of temperature, mantle velocity at the boundary of the mantle column. A comparison is made with the dynamic equilibrium melting (DEM) model discussed in the first installment. The implications of assuming passive flow or active flow are also considered to some extent. Complete data files of most of the DFM simulations, four animations and two new DEM simulations (passive/active flow) are available following the instructions in the supplementary material.

Comparison of different approaches to quantitative adenovirus detection in stool specimens of hematopoietic stem cell transplant recipients.

PubMed

Kosulin, K; Dworzak, S; Lawitschka, A; Matthes-Leodolter, S; Lion, T

2016-12-01

Adenoviruses almost invariably proliferate in the gastrointestinal tract prior to dissemination, and critical threshold concentrations in stool correlate with the risk of viremia. Monitoring of adenovirus loads in stool may therefore be important for timely initiation of treatment in order to prevent invasive infection. Comparison of a manual DNA extraction kit in combination with a validated in-house PCR assay with automated extraction on the NucliSENS-EasyMAG device coupled with the Adenovirus R-gene kit (bioMérieux) for quantitative adenovirus analysis in stool samples. Stool specimens spiked with adenovirus concentrations in a range from 10E2-10E11 copies/g and 32 adenovirus-positive clinical stool specimens from pediatric stem cell transplant recipients were tested along with appropriate negative controls. Quantitative analysis of viral load in adenovirus-positive stool specimens revealed a median difference of 0.5 logs (range 0.1-2.2) between the detection systems tested and a difference of 0.3 logs (range 0.0-1.7) when the comparison was restricted to the PCR assays only. Spiking experiments showed a detection limit of 10 2 -10 3 adenovirus copies/g stool revealing a somewhat higher sensitivity offered by the automated extraction. The dynamic range of accurate quantitative analysis by both systems investigated was between 10 3 and 10 8 virus copies/g. The differences in quantitative analysis of adenovirus copy numbers between the systems tested were primarily attributable to the DNA extraction method used, while the qPCR assays revealed a high level of concordance. Both systems showed adequate performance for detection and monitoring of adenoviral load in stool specimens. Copyright © 2016 Elsevier B.V. All rights reserved.

A heuristic method for identifying chaos from frequency content.

PubMed

Wiebe, R; Virgin, L N

2012-03-01

The sign of the largest Lyapunov exponent is the fundamental indicator of chaos in a dynamical system. However, although the extraction of Lyapunov exponents can be accomplished with (necessarily noisy) the experimental data, this is still a relatively data-intensive and sensitive endeavor. This paper presents an alternative pragmatic approach to identifying chaos using response frequency characteristics and extending the concept of the spectrogram. The method is shown to work well on both experimental and simulated time series.

A Design Support Framework through Dynamic Deployment of Hypothesis and Verification in the Design Process

NASA Astrophysics Data System (ADS)

Nomaguch, Yutaka; Fujita, Kikuo

This paper proposes a design support framework, named DRIFT (Design Rationale Integration Framework of Three layers), which dynamically captures and manages hypothesis and verification in the design process. A core of DRIFT is a three-layered design process model of action, model operation and argumentation. This model integrates various design support tools and captures design operations performed on them. Action level captures the sequence of design operations. Model operation level captures the transition of design states, which records a design snapshot over design tools. Argumentation level captures the process of setting problems and alternatives. The linkage of three levels enables to automatically and efficiently capture and manage iterative hypothesis and verification processes through design operations over design tools. In DRIFT, such a linkage is extracted through the templates of design operations, which are extracted from the patterns embeded in design tools such as Design-For-X (DFX) approaches, and design tools are integrated through ontology-based representation of design concepts. An argumentation model, gIBIS (graphical Issue-Based Information System), is used for representing dependencies among problems and alternatives. A mechanism of TMS (Truth Maintenance System) is used for managing multiple hypothetical design stages. This paper also demonstrates a prototype implementation of DRIFT and its application to a simple design problem. Further, it is concluded with discussion of some future issues.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Analysis of musical expression in audio signals

NASA Astrophysics Data System (ADS)

Dixon, Simon

2003-01-01

In western art music, composers communicate their work to performers via a standard notation which specificies the musical pitches and relative timings of notes. This notation may also include some higher level information such as variations in the dynamics, tempo and timing. Famous performers are characterised by their expressive interpretation, the ability to convey structural and emotive information within the given framework. The majority of work on audio content analysis focusses on retrieving score-level information; this paper reports on the extraction of parameters describing the performance, a task which requires a much higher degree of accuracy. Two systems are presented: BeatRoot, an off-line beat tracking system which finds the times of musical beats and tracks changes in tempo throughout a performance, and the Performance Worm, a system which provides a real-time visualisation of the two most important expressive dimensions, tempo and dynamics. Both of these systems are being used to process data for a large-scale study of musical expression in classical and romantic piano performance, which uses artificial intelligence (machine learning) techniques to discover fundamental patterns or principles governing expressive performance.

Feedforward Categorization on AER Motion Events Using Cortex-Like Features in a Spiking Neural Network.

PubMed

Zhao, Bo; Ding, Ruoxi; Chen, Shoushun; Linares-Barranco, Bernabe; Tang, Huajin

2015-09-01

This paper introduces an event-driven feedforward categorization system, which takes data from a temporal contrast address event representation (AER) sensor. The proposed system extracts bio-inspired cortex-like features and discriminates different patterns using an AER based tempotron classifier (a network of leaky integrate-and-fire spiking neurons). One of the system's most appealing characteristics is its event-driven processing, with both input and features taking the form of address events (spikes). The system was evaluated on an AER posture dataset and compared with two recently developed bio-inspired models. Experimental results have shown that it consumes much less simulation time while still maintaining comparable performance. In addition, experiments on the Mixed National Institute of Standards and Technology (MNIST) image dataset have demonstrated that the proposed system can work not only on raw AER data but also on images (with a preprocessing step to convert images into AER events) and that it can maintain competitive accuracy even when noise is added. The system was further evaluated on the MNIST dynamic vision sensor dataset (in which data is recorded using an AER dynamic vision sensor), with testing accuracy of 88.14%.

A data mining framework for time series estimation.

PubMed

Hu, Xiao; Xu, Peng; Wu, Shaozhi; Asgari, Shadnaz; Bergsneider, Marvin

2010-04-01

Time series estimation techniques are usually employed in biomedical research to derive variables less accessible from a set of related and more accessible variables. These techniques are traditionally built from systems modeling approaches including simulation, blind decovolution, and state estimation. In this work, we define target time series (TTS) and its related time series (RTS) as the output and input of a time series estimation process, respectively. We then propose a novel data mining framework for time series estimation when TTS and RTS represent different sets of observed variables from the same dynamic system. This is made possible by mining a database of instances of TTS, its simultaneously recorded RTS, and the input/output dynamic models between them. The key mining strategy is to formulate a mapping function for each TTS-RTS pair in the database that translates a feature vector extracted from RTS to the dissimilarity between true TTS and its estimate from the dynamic model associated with the same TTS-RTS pair. At run time, a feature vector is extracted from an inquiry RTS and supplied to the mapping function associated with each TTS-RTS pair to calculate a dissimilarity measure. An optimal TTS-RTS pair is then selected by analyzing these dissimilarity measures. The associated input/output model of the selected TTS-RTS pair is then used to simulate the TTS given the inquiry RTS as an input. An exemplary implementation was built to address a biomedical problem of noninvasive intracranial pressure assessment. The performance of the proposed method was superior to that of a simple training-free approach of finding the optimal TTS-RTS pair by a conventional similarity-based search on RTS features. 2009 Elsevier Inc. All rights reserved.

Singularity-free backstepping controller for model helicopters.

PubMed

Zou, Yao; Huo, Wei

2016-11-01

This paper develops a backstepping controller for model helicopters to achieve trajectory tracking without singularity, which occurs in the attitude representation when the roll or pitch reaches ±π2. Based on a simplified model with unmodeled dynamics, backstepping technique is introduced to exploit the controller and hyperbolic tangent functions are utilized to compensate the unmodeled dynamics. Firstly, a position loop controller is designed for the position tracking, where an auxiliary dynamic system with suitable parameters is introduced to warrant the singularity-free requirement for the extracted command attitude. Then, a novel attitude loop controller is proposed to obviate singularity. It is demonstrated that, based on the established criteria for selecting controller parameters and desired trajectories, the proposed controller realizes the singularity-free trajectory tracking of the model helicopter. Simulations confirm the theoretical results. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Transition from lognormal to χ2-superstatistics for financial time series

NASA Astrophysics Data System (ADS)

Xu, Dan; Beck, Christian

2016-07-01

Share price returns on different time scales can be well modelled by a superstatistical dynamics. Here we provide an investigation which type of superstatistics is most suitable to properly describe share price dynamics on various time scales. It is shown that while χ2-superstatistics works well on a time scale of days, on a much smaller time scale of minutes the price changes are better described by lognormal superstatistics. The system dynamics thus exhibits a transition from lognormal to χ2 superstatistics as a function of time scale. We discuss a more general model interpolating between both statistics which fits the observed data very well. We also present results on correlation functions of the extracted superstatistical volatility parameter, which exhibits exponential decay for returns on large time scales, whereas for returns on small time scales there are long-range correlations and power-law decay.

Dimensionless embedding for nonlinear time series analysis

NASA Astrophysics Data System (ADS)

Hirata, Yoshito; Aihara, Kazuyuki

2017-09-01

Recently, infinite-dimensional delay coordinates (InDDeCs) have been proposed for predicting high-dimensional dynamics instead of conventional delay coordinates. Although InDDeCs can realize faster computation and more accurate short-term prediction, it is still not well-known whether InDDeCs can be used in other applications of nonlinear time series analysis in which reconstruction is needed for the underlying dynamics from a scalar time series generated from a dynamical system. Here, we give theoretical support for justifying the use of InDDeCs and provide numerical examples to show that InDDeCs can be used for various applications for obtaining the recurrence plots, correlation dimensions, and maximal Lyapunov exponents, as well as testing directional couplings and extracting slow-driving forces. We demonstrate performance of the InDDeCs using the weather data. Thus, InDDeCs can eventually realize "dimensionless embedding" while we enjoy faster and more reliable computations.

High order magnetic optics for high dynamic range proton radiography at a kinetic energy of 800 MeV

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

Sjue, S. K. L., E-mail: sjue@lanl.gov; Mariam, F. G.; Merrill, F. E.

2016-01-15

Flash radiography with 800 MeV kinetic energy protons at Los Alamos National Laboratory is an important experimental tool for investigations of dynamic material behavior driven by high explosives or pulsed power. The extraction of quantitative information about density fields in a dynamic experiment from proton generated images requires a high fidelity model of the proton imaging process. It is shown that accurate calculations of the transmission through the magnetic lens system require terms beyond second order for protons far from the tune energy. The approach used integrates the correlated multiple Coulomb scattering distribution simultaneously over the collimator and the imagemore » plane. Comparison with a series of static calibration images demonstrates the model’s accurate reproduction of both the transmission and blur over a wide range of tune energies in an inverse identity lens that consists of four quadrupole electromagnets.« less

High order magnetic optics for high dynamic range proton radiography at a kinetic energy 800 MeV

DOE PAGES

Sjue, Sky K. L.; Morris, Christopher L.; Merrill, Frank Edward; ...

2016-01-14

Flash radiography with 800 MeV kinetic energy protons at Los Alamos National Laboratory is an important experimental tool for investigations of dynamic material behavior driven by high explosives or pulsed power. The extraction of quantitative information about density fields in a dynamic experiment from proton generated images requires a high fidelity model of the protonimaging process. It is shown that accurate calculations of the transmission through the magnetic lens system require terms beyond second order for protons far from the tune energy. The approach used integrates the correlated multiple Coulomb scattering distribution simultaneously over the collimator and the image plane.more » Furthermore, comparison with a series of static calibrationimages demonstrates the model’s accurate reproduction of both the transmission and blur over a wide range of tune energies in an inverse identity lens that consists of four quadrupole electromagnets.« less

The North American Energy System: Overview of the 3rd Chapter of SOCCR-2

NASA Astrophysics Data System (ADS)

Marcotullio, P. J.

2016-12-01

North America, including Canada, Mexico and the United States, has a large and complex energy system, which includes the extraction and conversion of primary energy sources and their storage, transmission, distribution and ultimate end use in the building, transportation and industrial sectors. The chapter overviews this system focusing on our understanding of the energy trends and system feedback dynamics, key drivers of change, and subsequent carbon emissions and the basis for carbon management. We also put the carbon emissions from the North American system in global context. Highlights include the changes to the system (sources, fuel mix, drivers, infrastructure, etc.,) over the past decade, and a review of scenarios that provide glimpses into future emissions levels and meeting the requirements for decarbonization in the medium and longer term.

Slowest kinetic modes revealed by metabasin renormalization

NASA Astrophysics Data System (ADS)

Okushima, Teruaki; Niiyama, Tomoaki; Ikeda, Kensuke S.; Shimizu, Yasushi

2018-02-01

Understanding the slowest relaxations of complex systems, such as relaxation of glass-forming materials, diffusion in nanoclusters, and folding of biomolecules, is important for physics, chemistry, and biology. For a kinetic system, the relaxation modes are determined by diagonalizing its transition rate matrix. However, for realistic systems of interest, numerical diagonalization, as well as extracting physical understanding from the diagonalization results, is difficult due to the high dimensionality. Here, we develop an alternative and generally applicable method of extracting the long-time scale relaxation dynamics by combining the metabasin analysis of Okushima et al. [Phys. Rev. E 80, 036112 (2009), 10.1103/PhysRevE.80.036112] and a Jacobi method. We test the method on an illustrative model of a four-funnel model, for which we obtain a renormalized kinematic equation of much lower dimension sufficient for determining slow relaxation modes precisely. The method is successfully applied to the vacancy transport problem in ionic nanoparticles [Niiyama et al., Chem. Phys. Lett. 654, 52 (2016), 10.1016/j.cplett.2016.04.088], allowing a clear physical interpretation that the final relaxation consists of two successive, characteristic processes.

Gesture-Controlled Interfaces for Self-Service Machines

NASA Technical Reports Server (NTRS)

Cohen, Charles J.; Beach, Glenn

2006-01-01

Gesture-controlled interfaces are software- driven systems that facilitate device control by translating visual hand and body signals into commands. Such interfaces could be especially attractive for controlling self-service machines (SSMs) for example, public information kiosks, ticket dispensers, gasoline pumps, and automated teller machines (see figure). A gesture-controlled interface would include a vision subsystem comprising one or more charge-coupled-device video cameras (at least two would be needed to acquire three-dimensional images of gestures). The output of the vision system would be processed by a pure software gesture-recognition subsystem. Then a translator subsystem would convert a sequence of recognized gestures into commands for the SSM to be controlled; these could include, for example, a command to display requested information, change control settings, or actuate a ticket- or cash-dispensing mechanism. Depending on the design and operational requirements of the SSM to be controlled, the gesture-controlled interface could be designed to respond to specific static gestures, dynamic gestures, or both. Static and dynamic gestures can include stationary or moving hand signals, arm poses or motions, and/or whole-body postures or motions. Static gestures would be recognized on the basis of their shapes; dynamic gestures would be recognized on the basis of both their shapes and their motions. Because dynamic gestures include temporal as well as spatial content, this gesture- controlled interface can extract more information from dynamic than it can from static gestures.

Decoding of finger trajectory from ECoG using deep learning.

PubMed

Xie, Ziqian; Schwartz, Odelia; Prasad, Abhishek

2018-06-01

Conventional decoding pipeline for brain-machine interfaces (BMIs) consists of chained different stages of feature extraction, time-frequency analysis and statistical learning models. Each of these stages uses a different algorithm trained in a sequential manner, which makes it difficult to make the whole system adaptive. The goal was to create an adaptive online system with a single objective function and a single learning algorithm so that the whole system can be trained in parallel to increase the decoding performance. Here, we used deep neural networks consisting of convolutional neural networks (CNN) and a special kind of recurrent neural network (RNN) called long short term memory (LSTM) to address these needs. We used electrocorticography (ECoG) data collected by Kubanek et al. The task consisted of individual finger flexions upon a visual cue. Our model combined a hierarchical feature extractor CNN and a RNN that was able to process sequential data and recognize temporal dynamics in the neural data. CNN was used as the feature extractor and LSTM was used as the regression algorithm to capture the temporal dynamics of the signal. We predicted the finger trajectory using ECoG signals and compared results for the least angle regression (LARS), CNN-LSTM, random forest, LSTM model (LSTM_HC, for using hard-coded features) and a decoding pipeline consisting of band-pass filtering, energy extraction, feature selection and linear regression. The results showed that the deep learning models performed better than the commonly used linear model. The deep learning models not only gave smoother and more realistic trajectories but also learned the transition between movement and rest state. This study demonstrated a decoding network for BMI that involved a convolutional and recurrent neural network model. It integrated the feature extraction pipeline into the convolution and pooling layer and used LSTM layer to capture the state transitions. The discussed network eliminated the need to separately train the model at each step in the decoding pipeline. The whole system can be jointly optimized using stochastic gradient descent and is capable of online learning.

Decoding of finger trajectory from ECoG using deep learning

NASA Astrophysics Data System (ADS)

Xie, Ziqian; Schwartz, Odelia; Prasad, Abhishek

2018-06-01

Objective. Conventional decoding pipeline for brain-machine interfaces (BMIs) consists of chained different stages of feature extraction, time-frequency analysis and statistical learning models. Each of these stages uses a different algorithm trained in a sequential manner, which makes it difficult to make the whole system adaptive. The goal was to create an adaptive online system with a single objective function and a single learning algorithm so that the whole system can be trained in parallel to increase the decoding performance. Here, we used deep neural networks consisting of convolutional neural networks (CNN) and a special kind of recurrent neural network (RNN) called long short term memory (LSTM) to address these needs. Approach. We used electrocorticography (ECoG) data collected by Kubanek et al. The task consisted of individual finger flexions upon a visual cue. Our model combined a hierarchical feature extractor CNN and a RNN that was able to process sequential data and recognize temporal dynamics in the neural data. CNN was used as the feature extractor and LSTM was used as the regression algorithm to capture the temporal dynamics of the signal. Main results. We predicted the finger trajectory using ECoG signals and compared results for the least angle regression (LARS), CNN-LSTM, random forest, LSTM model (LSTM_HC, for using hard-coded features) and a decoding pipeline consisting of band-pass filtering, energy extraction, feature selection and linear regression. The results showed that the deep learning models performed better than the commonly used linear model. The deep learning models not only gave smoother and more realistic trajectories but also learned the transition between movement and rest state. Significance. This study demonstrated a decoding network for BMI that involved a convolutional and recurrent neural network model. It integrated the feature extraction pipeline into the convolution and pooling layer and used LSTM layer to capture the state transitions. The discussed network eliminated the need to separately train the model at each step in the decoding pipeline. The whole system can be jointly optimized using stochastic gradient descent and is capable of online learning.

Chromatography, solid-phase extraction, and capillary electrochromatography with MIPs.

PubMed

Tóth, Blanka; Horvai, George

2012-01-01

Most analytical applications of molecularly imprinted polymers are based on their selective adsorption properties towards the template or its analogs. In chromatography, solid phase extraction and electrochromatography this adsorption is a dynamic process. The dynamic process combined with the nonlinear adsorption isotherm of the polymers and other factors results in complications which have limited the success of imprinted polymers. This chapter explains these problems and shows many examples of successful applications overcoming or avoiding the problems.

Optimization of dynamic-microwave assisted enzymatic hydrolysis extraction of total ginsenosides from stems and leaves of panax ginseng by response surface methodology.

PubMed

Wang, Xiao-Yan; Ren, Hui

2018-03-21

Ginseng stems and leaves (GSAL) are abundant in ginsenosides compounds. For efficient utilization of GSAL and the enhancement of total ginsenosides (TG) compound yields in GSAL, TG from GSAL were extracted, using dynamic-microwave assisted extraction coupled with enzymatic hydrolysis (DMAE-EH) method. The extraction process has been simulated and its main influencing factors such as ethanol concentration, microwave temperature, microwave time and pump flow rate have been optimized by response surface methodology coupled with a Box-Behnken design(BBD). The experimental results indicated that optimal extraction conditions of TG from GSAL were as follows: ethanol concentration of 75%, microwave temperature of 60°C, microwave time of 20 min and pump flow rate of 38 r/min. After experimental verification, the experimental yields of TG was 60.62 ± 0.85 mg g -1 , which were well agreement with the predicted by the model. In general, the present results demonstrated that DMAE-EH method was successfully used to extract total ginsenosides in GSAL.

The community dynamics of major bioleaching microorganisms during chalcopyrite leaching under the effect of organics.

PubMed

Li, Qihou; Tian, Ye; Fu, Xian; Yin, Huaqun; Zhou, Zhijun; Liang, Yiting; Qiu, Guanzhou; Liu, Jie; Liu, Hongwei; Liang, Yili; Shen, Li; Cong, Jing; Liu, Xueduan

2011-08-01

To determine the effect of organics (yeast extract) on microbial community during chalcopyrite bioleaching at different temperature, real-time polymerase chain reaction (PCR) was employed to analyze community dynamics of major bacteria applied in bioleaching. The results showed that yeast extract exerted great impact on microbial community, and therefore influencing bioleaching rate. To be specific, yeast extract was adverse to this bioleaching process at 30°C due to decreased proportion of important chemolithotrophs such as Acidithiobacillus ferrooxidans and Acidithiobacillus thiooxidans. However, yeast extract could promote bioleaching rate at 40°C on account of the increased number and enhanced work of Ferroplasma thermophilum, a kind of facultative bacteria. Similarly, bioleaching rate was enhanced under the effect of yeast extract at 50°C owing to the work of Acidianus brierleyi. At 60°C, bioleaching rate was close to 100% and temperature was the dominant factor determining bioleaching rate. Interestingly, the existence of yeast extract greatly enhanced the relative competitiveness of Ferroplasma thermophilum in this complex bioleaching microbial community.

Linear modeling of human hand-arm dynamics relevant to right-angle torque tool interaction.

PubMed

Ay, Haluk; Sommerich, Carolyn M; Luscher, Anthony F

2013-10-01

A new protocol was evaluated for identification of stiffness, mass, and damping parameters employing a linear model for human hand-arm dynamics relevant to right-angle torque tool use. Powered torque tools are widely used to tighten fasteners in manufacturing industries. While these tools increase accuracy and efficiency of tightening processes, operators are repetitively exposed to impulsive forces, posing risk of upper extremity musculoskeletal injury. A novel testing apparatus was developed that closely mimics biomechanical exposure in torque tool operation. Forty experienced torque tool operators were tested with the apparatus to determine model parameters and validate the protocol for physical capacity assessment. A second-order hand-arm model with parameters extracted in the time domain met model accuracy criterion of 5% for time-to-peak displacement error in 93% of trials (vs. 75% for frequency domain). Average time-to-peak handle displacement and relative peak handle force errors were 0.69 ms and 0.21%, respectively. Model parameters were significantly affected by gender and working posture. Protocol and numerical calculation procedures provide an alternative method for assessing mechanical parameters relevant to right-angle torque tool use. The protocol more closely resembles tool use, and calculation procedures demonstrate better performance of parameter extraction using time domain system identification methods versus frequency domain. Potential future applications include parameter identification for in situ torque tool operation and equipment development for human hand-arm dynamics simulation under impulsive forces that could be used for assessing torque tools based on factors relevant to operator health (handle dynamics and hand-arm reaction force).

Structural versus dynamical origins of mean-field behavior in a self-organized critical model of neuronal avalanches

NASA Astrophysics Data System (ADS)

Moosavi, S. Amin; Montakhab, Afshin

2015-11-01

Critical dynamics of cortical neurons have been intensively studied over the past decade. Neuronal avalanches provide the main experimental as well as theoretical tools to consider criticality in such systems. Experimental studies show that critical neuronal avalanches show mean-field behavior. There are structural as well as recently proposed [Phys. Rev. E 89, 052139 (2014), 10.1103/PhysRevE.89.052139] dynamical mechanisms that can lead to mean-field behavior. In this work we consider a simple model of neuronal dynamics based on threshold self-organized critical models with synaptic noise. We investigate the role of high-average connectivity, random long-range connections, as well as synaptic noise in achieving mean-field behavior. We employ finite-size scaling in order to extract critical exponents with good accuracy. We conclude that relevant structural mechanisms responsible for mean-field behavior cannot be justified in realistic models of the cortex. However, strong dynamical noise, which can have realistic justifications, always leads to mean-field behavior regardless of the underlying structure. Our work provides a different (dynamical) origin than the conventionally accepted (structural) mechanisms for mean-field behavior in neuronal avalanches.

A Mathematical Model to study the Dynamics of Epithelial Cellular Networks

PubMed Central

Abate, Alessandro; Vincent, Stéphane; Dobbe, Roel; Silletti, Alberto; Master, Neal; Axelrod, Jeffrey D.; Tomlin, Claire J.

2013-01-01

Epithelia are sheets of connected cells that are essential across the animal kingdom. Experimental observations suggest that the dynamical behavior of many single-layered epithelial tissues has strong analogies with that of specific mechanical systems, namely large networks consisting of point masses connected through spring-damper elements and undergoing the influence of active and dissipating forces. Based on this analogy, this work develops a modeling framework to enable the study of the mechanical properties and of the dynamic behavior of large epithelial cellular networks. The model is built first by creating a network topology that is extracted from the actual cellular geometry as obtained from experiments, then by associating a mechanical structure and dynamics to the network via spring-damper elements. This scalable approach enables running simulations of large network dynamics: the derived modeling framework in particular is predisposed to be tailored to study general dynamics (for example, morphogenesis) of various classes of single-layered epithelial cellular networks. In this contribution we test the model on a case study of the dorsal epithelium of the Drosophila melanogaster embryo during early dorsal closure (and, less conspicuously, germband retraction). PMID:23221083

Multisensor-based real-time quality monitoring by means of feature extraction, selection and modeling for Al alloy in arc welding

NASA Astrophysics Data System (ADS)

Zhang, Zhifen; Chen, Huabin; Xu, Yanling; Zhong, Jiyong; Lv, Na; Chen, Shanben

2015-08-01

Multisensory data fusion-based online welding quality monitoring has gained increasing attention in intelligent welding process. This paper mainly focuses on the automatic detection of typical welding defect for Al alloy in gas tungsten arc welding (GTAW) by means of analzing arc spectrum, sound and voltage signal. Based on the developed algorithms in time and frequency domain, 41 feature parameters were successively extracted from these signals to characterize the welding process and seam quality. Then, the proposed feature selection approach, i.e., hybrid fisher-based filter and wrapper was successfully utilized to evaluate the sensitivity of each feature and reduce the feature dimensions. Finally, the optimal feature subset with 19 features was selected to obtain the highest accuracy, i.e., 94.72% using established classification model. This study provides a guideline for feature extraction, selection and dynamic modeling based on heterogeneous multisensory data to achieve a reliable online defect detection system in arc welding.

Modelling Nonlinear Dynamic Textures using Hybrid DWT-DCT and Kernel PCA with GPU

NASA Astrophysics Data System (ADS)

Ghadekar, Premanand Pralhad; Chopade, Nilkanth Bhikaji

2016-12-01

Most of the real-world dynamic textures are nonlinear, non-stationary, and irregular. Nonlinear motion also has some repetition of motion, but it exhibits high variation, stochasticity, and randomness. Hybrid DWT-DCT and Kernel Principal Component Analysis (KPCA) with YCbCr/YIQ colour coding using the Dynamic Texture Unit (DTU) approach is proposed to model a nonlinear dynamic texture, which provides better results than state-of-art methods in terms of PSNR, compression ratio, model coefficients, and model size. Dynamic texture is decomposed into DTUs as they help to extract temporal self-similarity. Hybrid DWT-DCT is used to extract spatial redundancy. YCbCr/YIQ colour encoding is performed to capture chromatic correlation. KPCA is applied to capture nonlinear motion. Further, the proposed algorithm is implemented on Graphics Processing Unit (GPU), which comprise of hundreds of small processors to decrease time complexity and to achieve parallelism.

Initiation of DNA replication requires actin dynamics and formin activity.

PubMed

Parisis, Nikolaos; Krasinska, Liliana; Harker, Bethany; Urbach, Serge; Rossignol, Michel; Camasses, Alain; Dewar, James; Morin, Nathalie; Fisher, Daniel

2017-11-02

Nuclear actin regulates transcriptional programmes in a manner dependent on its levels and polymerisation state. This dynamics is determined by the balance of nucleocytoplasmic shuttling, formin- and redox-dependent filament polymerisation. Here, using Xenopus egg extracts and human somatic cells, we show that actin dynamics and formins are essential for DNA replication. In proliferating cells, formin inhibition abolishes nuclear transport and initiation of DNA replication, as well as general transcription. In replicating nuclei from transcriptionally silent Xenopus egg extracts, we identified numerous actin regulators, and disruption of actin dynamics abrogates nuclear transport, preventing NLS (nuclear localisation signal)-cargo release from RanGTP-importin complexes. Nuclear formin activity is further required to promote loading of cyclin-dependent kinase (CDK) and proliferating cell nuclear antigen (PCNA) onto chromatin, as well as initiation and elongation of DNA replication. Therefore, actin dynamics and formins control DNA replication by multiple direct and indirect mechanisms. © 2017 The Authors.

Self-sustained vibrations in volcanic areas extracted by Independent Component Analysis: a review and new results

NASA Astrophysics Data System (ADS)

de Lauro, E.; de Martino, S.; Falanga, M.; Palo, M.

2011-12-01

We investigate the physical processes associated with volcanic tremor and explosions. A volcano is a complex system where a fluid source interacts with the solid edifice so generating seismic waves in a regime of low turbulence. Although the complex behavior escapes a simple universal description, the phases of activity generate stable (self-sustained) oscillations that can be described as a non-linear dynamical system of low dimensionality. So, the system requires to be investigated with non-linear methods able to individuate, decompose, and extract the main characteristics of the phenomenon. Independent Component Analysis (ICA), an entropy-based technique is a good candidate for this purpose. Here, we review the results of ICA applied to seismic signals acquired in some volcanic areas. We emphasize analogies and differences among the self-oscillations individuated in three cases: Stromboli (Italy), Erebus (Antarctica) and Volcán de Colima (Mexico). The waveforms of the extracted independent components are specific for each volcano, whereas the similarity can be ascribed to a very general common source mechanism involving the interaction between gas/magma flow and solid structures (the volcanic edifice). Indeed, chocking phenomena or inhomogeneities in the volcanic cavity can play the same role in generating self-oscillations as the languid and the reed do in musical instruments. The understanding of these background oscillations is relevant not only for explaining the volcanic source process and to make a forecast into the future, but sheds light on the physics of complex systems developing low turbulence.

[Advances in studies on multi-stage countercurrent extraction technology in traditional Chinese medicine].

PubMed

Xie, Zhi-Peng; Liu, Xue-Song; Chen, Yong; Cai, Ming; Qu, Hai-Bin; Cheng, Yi-Yu

2007-05-01

Multi-stage countercurrent extraction technology, integrating solvent extraction, repercolation with dynamic and countercurrent extraction, is a novel extraction technology for the traditional Chinese medicine. This solvent-saving, energy-saving and high-extraction-efficiency technology can at the most drive active compounds to diffuse from the herbal materials into the solvent stage by stage by creating concentration differences between the herbal materials and the solvents. This paper reviewed the basic principle, the influence factors and the research progress and trends of the equipments and the application of the multi-stage countercurrent extraction.

Neural computing for numeric-to-symbolic conversion in control systems

NASA Technical Reports Server (NTRS)

Passino, Kevin M.; Sartori, Michael A.; Antsaklis, Panos J.

1989-01-01

A type of neural network, the multilayer perceptron, is used to classify numeric data and assign appropriate symbols to various classes. This numeric-to-symbolic conversion results in a type of information extraction, which is similar to what is called data reduction in pattern recognition. The use of the neural network as a numeric-to-symbolic converter is introduced, its application in autonomous control is discussed, and several applications are studied. The perceptron is used as a numeric-to-symbolic converter for a discrete-event system controller supervising a continuous variable dynamic system. It is also shown how the perceptron can implement fault trees, which provide useful information (alarms) in a biological system and information for failure diagnosis and control purposes in an aircraft example.

Inverting pump-probe spectroscopy for state tomography of excitonic systems.

PubMed

Hoyer, Stephan; Whaley, K Birgitta

2013-04-28

We propose a two-step protocol for inverting ultrafast spectroscopy experiments on a molecular aggregate to extract the time-evolution of the excited state density matrix. The first step is a deconvolution of the experimental signal to determine a pump-dependent response function. The second step inverts this response function to obtain the quantum state of the system, given a model for how the system evolves following the probe interaction. We demonstrate this inversion analytically and numerically for a dimer model system, and evaluate the feasibility of scaling it to larger molecular aggregates such as photosynthetic protein-pigment complexes. Our scheme provides a direct alternative to the approach of determining all Hamiltonian parameters and then simulating excited state dynamics.

Identification of potential sewer mining locations: a Monte-Carlo based approach.

PubMed

Tsoukalas, I K; Makropoulos, C K; Michas, S N

2017-12-01

Rapid urbanization affecting demand patterns, coupled with potential water shortages due to supply side impacts of climatic changes, has led to the emergence of new technologies for water and wastewater reuse. Sewer mining (SM) is a novel decentralized option that could potentially provide non-potable water for urban uses, including for example the irrigation of urban green spaces, providing a mid-scale solution to effective wastewater reuse. SM is based on extracting wastewater from local sewers and treatment at the point of demand and entails in some cases the return of treatment residuals back to the sewer system. Several challenges are currently in the way of such applications in Europe, including public perception, inadequate regulatory frameworks and engineering issues. In this paper we consider some of these engineering challenges, looking at the sewer network as a system where multiple physical, biological and chemical processes take place. We argue that prior to implementing SM, the dynamics of the sewer system should be investigated in order to identify optimum ways of deploying SM without endangering the reliability of the system. Specifically, both wastewater extraction and sludge return could result in altering the biochemical process of the network, thus unintentionally leading to degradation of the sewer infrastructure. We propose a novel Monte-Carlo based method that takes into account both spatial properties and water demand characteristics of a given area of SM deployment while simultaneously accounting for the variability of sewer network dynamics in order to identify potential locations for SM implementation. The outcomes of this study suggest that the method can provide rational results and useful guidelines for upscale SM technologies at a city level.

Gender-specific automatic valence recognition of affective olfactory stimulation through the analysis of the electrodermal activity.

PubMed

Greco, Alberto; Lanata, Antonio; Valenza, Gaetano; Di Francesco, Fabio; Scilingo, Enzo Pasquale

2016-08-01

This study reports on the development of a gender-specific classification system able to discern between two valence levels of smell, through information gathered from electrodermal activity (EDA) dynamics. Specifically, two odorants were administered to 32 healthy volunteers (16 males) while monitoring EDA. CvxEDA model was used to process the EDA signal and extract features from both tonic and phasic components. The feature set was used as input to a K-NN classifier implementing a leave-one-subject-out procedure. Results show strong differences in the accuracy of valence recognition between men (62.5%) and women (78%). We can conclude that affective olfactory stimulation significantly affect EDA dynamics with a highly specific gender dependency.

Perspective: Differential dynamic microscopy extracts multi-scale activity in complex fluids and biological systems

NASA Astrophysics Data System (ADS)

Cerbino, Roberto; Cicuta, Pietro

2017-09-01

Differential dynamic microscopy (DDM) is a technique that exploits optical microscopy to obtain local, multi-scale quantitative information about dynamic samples, in most cases without user intervention. It is proving extremely useful in understanding dynamics in liquid suspensions, soft materials, cells, and tissues. In DDM, image sequences are analyzed via a combination of image differences and spatial Fourier transforms to obtain information equivalent to that obtained by means of light scattering techniques. Compared to light scattering, DDM offers obvious advantages, principally (a) simplicity of the setup; (b) possibility of removing static contributions along the optical path; (c) power of simultaneous different microscopy contrast mechanisms; and (d) flexibility of choosing an analysis region, analogous to a scattering volume. For many questions, DDM has also advantages compared to segmentation/tracking approaches and to correlation techniques like particle image velocimetry. The very straightforward DDM approach, originally demonstrated with bright field microscopy of aqueous colloids, has lately been used to probe a variety of other complex fluids and biological systems with many different imaging methods, including dark-field, differential interference contrast, wide-field, light-sheet, and confocal microscopy. The number of adopting groups is rapidly increasing and so are the applications. Here, we briefly recall the working principles of DDM, we highlight its advantages and limitations, we outline recent experimental breakthroughs, and we provide a perspective on future challenges and directions. DDM can become a standard primary tool in every laboratory equipped with a microscope, at the very least as a first bias-free automated evaluation of the dynamics in a system.

Coupled intertwiner dynamics: A toy model for coupling matter to spin foam models

NASA Astrophysics Data System (ADS)

Steinhaus, Sebastian

2015-09-01

The universal coupling of matter and gravity is one of the most important features of general relativity. In quantum gravity, in particular spin foams, matter couplings have been defined in the past, yet the mutual dynamics, in particular if matter and gravity are strongly coupled, are hardly explored, which is related to the definition of both matter and gravitational degrees of freedom on the discretization. However, extracting these mutual dynamics is crucial in testing the viability of the spin foam approach and also establishing connections to other discrete approaches such as lattice gauge theories. Therefore, we introduce a simple two-dimensional toy model for Yang-Mills coupled to spin foams, namely an Ising model coupled to so-called intertwiner models defined for SU (2 )k. The two systems are coupled by choosing the Ising coupling constant to depend on spin labels of the background, as these are interpreted as the edge lengths of the discretization. We coarse grain this toy model via tensor network renormalization and uncover an interesting dynamics: the Ising phase transition temperature turns out to be sensitive to the background configurations and conversely, the Ising model can induce phase transitions in the background. Moreover, we observe a strong coupling of both systems if close to both phase transitions.

Impact Testing and Simulation of Composite Airframe Structures

NASA Technical Reports Server (NTRS)

Jackson, Karen E.; Littell, Justin D.; Horta, Lucas G.; Annett, Martin S.; Fasanella, Edwin L.; Seal, Michael D., II

2014-01-01

Dynamic tests were performed at NASA Langley Research Center on composite airframe structural components of increasing complexity to evaluate their energy absorption behavior when subjected to impact loading. A second objective was to assess the capabilities of predicting the dynamic response of composite airframe structures, including damage initiation and progression, using a state-of-the-art nonlinear, explicit transient dynamic finite element code, LS-DYNA. The test specimens were extracted from a previously tested composite prototype fuselage section developed and manufactured by Sikorsky Aircraft Corporation under the US Army's Survivable Affordable Repairable Airframe Program (SARAP). Laminate characterization testing was conducted in tension and compression. In addition, dynamic impact tests were performed on several components, including I-beams, T-sections, and cruciform sections. Finally, tests were conducted on two full-scale components including a subfloor section and a framed fuselage section. These tests included a modal vibration and longitudinal impact test of the subfloor section and a quasi-static, modal vibration, and vertical drop test of the framed fuselage section. Most of the test articles were manufactured of graphite unidirectional tape composite with a thermoplastic resin system. However, the framed fuselage section was constructed primarily of a plain weave graphite fabric material with a thermoset resin system. Test data were collected from instrumentation such as accelerometers and strain gages and from full-field photogrammetry.

Gene regulatory network identification from the yeast cell cycle based on a neuro-fuzzy system.

PubMed

Wang, B H; Lim, J W; Lim, J S

2016-08-30

Many studies exist for reconstructing gene regulatory networks (GRNs). In this paper, we propose a method based on an advanced neuro-fuzzy system, for gene regulatory network reconstruction from microarray time-series data. This approach uses a neural network with a weighted fuzzy function to model the relationships between genes. Fuzzy rules, which determine the regulators of genes, are very simplified through this method. Additionally, a regulator selection procedure is proposed, which extracts the exact dynamic relationship between genes, using the information obtained from the weighted fuzzy function. Time-series related features are extracted from the original data to employ the characteristics of temporal data that are useful for accurate GRN reconstruction. The microarray dataset of the yeast cell cycle was used for our study. We measured the mean squared prediction error for the efficiency of the proposed approach and evaluated the accuracy in terms of precision, sensitivity, and F-score. The proposed method outperformed the other existing approaches.

Rate-equation modelling and ensemble approach to extraction of parameters for viral infection-induced cell apoptosis and necrosis

NASA Astrophysics Data System (ADS)

Domanskyi, Sergii; Schilling, Joshua E.; Gorshkov, Vyacheslav; Libert, Sergiy; Privman, Vladimir

2016-09-01

We develop a theoretical approach that uses physiochemical kinetics modelling to describe cell population dynamics upon progression of viral infection in cell culture, which results in cell apoptosis (programmed cell death) and necrosis (direct cell death). Several model parameters necessary for computer simulation were determined by reviewing and analyzing available published experimental data. By comparing experimental data to computer modelling results, we identify the parameters that are the most sensitive to the measured system properties and allow for the best data fitting. Our model allows extraction of parameters from experimental data and also has predictive power. Using the model we describe interesting time-dependent quantities that were not directly measured in the experiment and identify correlations among the fitted parameter values. Numerical simulation of viral infection progression is done by a rate-equation approach resulting in a system of "stiff" equations, which are solved by using a novel variant of the stochastic ensemble modelling approach. The latter was originally developed for coupled chemical reactions.

Rate-equation modelling and ensemble approach to extraction of parameters for viral infection-induced cell apoptosis and necrosis

NASA Astrophysics Data System (ADS)

Domanskyi, Sergii; Schilling, Joshua; Gorshkov, Vyacheslav; Libert, Sergiy; Privman, Vladimir

We develop a theoretical approach that uses physiochemical kinetics modelling to describe cell population dynamics upon progression of viral infection in cell culture, which results in cell apoptosis (programmed cell death) and necrosis (direct cell death). Several model parameters necessary for computer simulation were determined by reviewing and analyzing available published experimental data. By comparing experimental data to computer modelling results, we identify the parameters that are the most sensitive to the measured system properties and allow for the best data fitting. Our model allows extraction of parameters from experimental data and also has predictive power. Using the model we describe interesting time-dependent quantities that were not directly measured in the experiment and identify correlations among the fitted parameter values. Numerical simulation of viral infection progression is done by a rate-equation approach resulting in a system of ``stiff'' equations, which are solved by using a novel variant of the stochastic ensemble modelling approach. The latter was originally developed for coupled chemical reactions.

High-quality and small-capacity e-learning video featuring lecturer-superimposing PC screen images

NASA Astrophysics Data System (ADS)

Nomura, Yoshihiko; Murakami, Michinobu; Sakamoto, Ryota; Sugiura, Tokuhiro; Matsui, Hirokazu; Kato, Norihiko

2006-10-01

Information processing and communication technology are progressing quickly, and are prevailing throughout various technological fields. Therefore, the development of such technology should respond to the needs for improvement of quality in the e-learning education system. The authors propose a new video-image compression processing system that ingeniously employs the features of the lecturing scene. While dynamic lecturing scene is shot by a digital video camera, screen images are electronically stored by a PC screen image capturing software in relatively long period at a practical class. Then, a lecturer and a lecture stick are extracted from the digital video images by pattern recognition techniques, and the extracted images are superimposed on the appropriate PC screen images by off-line processing. Thus, we have succeeded to create a high-quality and small-capacity (HQ/SC) video-on-demand educational content featuring the advantages: the high quality of image sharpness, the small electronic file capacity, and the realistic lecturer motion.

Determination of the distribution and speciation of selenium in an argillaceous sample using chemical extractions and post-extractions analyses: application to the hydrogeological experimental site of Poitiers.

PubMed

Bassil, Joseph; Naveau, Aude; Bueno, Maïté; Di Tullo, Pamela; Grasset, Laurent; Kazpard, Véronique; Razack, Moumtaz

2016-05-01

To better understand selenium's dynamics in environmental systems, the present study aims to investigate selenium speciation and distribution in black argillaceous sediments, partially fulfilling karstic cavities into the Hydrogeological Experimental Site of Poitiers. These sediments are suspected to be responsible for selenium concentrations exceeding the European Framework Directive's drinking water limit value (10 μg L(-1)) in some specific wells. A combination of a sequential extractions scheme and single parallel extractions was thus applied on a representative argillaceous sample. Impacts of the extractions on mineral dissolution and organic matter mobilization were followed by quantifying major cations and total organic carbon (TOC) in the aqueous extracts. The nature of the released organic matter was characterized using thermochemolysis coupled with gas chromatography-mass spectrometry (GC-MS). About 10 % of selenium from the black argillaceous studied matrix could be defined as 'easily mobilizable' when the majority (around 70 %) revealed associated with the aliphatic and alkaline-soluble organic matter's fraction (about 20 %). In these fractions, selenium speciation was moreover dominated by oxidized species including a mixture of Se(VI) (20-30 %) and Se(IV) (70-80 %) in the 'easily mobilizable' fraction, while only Se(IV) was detected in alkaline-soluble organic matter fraction.

A methodology for the efficient integration of transient constraints in the design of aircraft dynamic systems

NASA Astrophysics Data System (ADS)

Phan, Leon L.

The motivation behind this thesis mainly stems from previous work performed at Hispano-Suiza (Safran Group) in the context of the European research project "Power Optimised Aircraft". Extensive testing on the COPPER Bird RTM, a test rig designed to characterize aircraft electrical networks, demonstrated the relevance of transient regimes in the design and development of dynamic systems. Transient regimes experienced by dynamic systems may have severe impacts on the operation of the aircraft. For example, the switching on of a high electrical load might cause a network voltage drop inducing a loss of power available to critical aircraft systems. These transient behaviors are thus often regulated by dynamic constraints, requiring the dynamic signals to remain within bounds whose values vary with time. The verification of these peculiar types of constraints, which generally requires high-fidelity time-domain simulation, intervenes late in the system development process, thus potentially causing costly design iterations. The research objective of this thesis is to develop a methodology that integrates the verification of dynamic constraints in the early specification of dynamic systems. In order to circumvent the inefficiencies of time-domain simulation, multivariate dynamic surrogate models of the original time-domain simulation models are generated, building on a nonlinear system identification technique using wavelet neural networks (or wavenets), which allow the multiscale nature of transient signals to be captured. However, training multivariate wavenets can become computationally prohibitive as the number of design variables increases. Therefore, an alternate approach is formulated, in which dynamic surrogate models using sigmoid-based neural networks are used to emulate the transient behavior of the envelopes of the time-domain response. Thus, in order to train the neural network, the envelopes are extracted by first separating the scales of the dynamic response, using a multiresolution analysis (MRA) based on the discrete wavelet transform. The MRA separates the dynamic response into a trend and a noise signal (ripple). The envelope of the noise is then computed with a windowing method, and recombined with the trend in order to reconstruct the global envelope of the dynamic response. The run-time efficiency of the resulting dynamic surrogate models enable the implementation of a data farming approach, in which a Monte-Carlo simulation generates time-domain behaviors of transient responses for a vast set of design and operation scenarios spanning the design and operation space. An interactive visualization environment, enabling what-if analyses, will be developed; the user can thereby instantaneously comprehend the transient response of the system (or its envelope) and its sensitivities to design and operation variables, as well as filter the design space to have it exhibit only the design scenarios verifying the dynamic constraints. The proposed methodology, along with its foundational hypotheses, are tested on the design and optimization of a 350VDC network, where a generator and its control system are concurrently designed in order to minimize the electrical losses, while ensuring that the transient undervoltage induced by peak demands in the consumption of a motor does not violate transient power quality constraints.

Photoluminescence studies on the complexation of Eu(III) and Tb(III) with acetohydroxamic acid (AHA) in nitrate medium

NASA Astrophysics Data System (ADS)

Pathak, P. N.; Mohapatra, M.; Godbole, S. V.

2013-11-01

UREX process has been proposed for selective extraction of U(VI) and Tc(VII) from nitric acid medium (∼1 M HNO3) using tri-n-butyl phosphate (TBP) as extractant and retaining Pu, Np and fission products in the aqueous phase. The feasibility of the use of luminescence spectroscopy as a technique to understand the complexation of trivalent f-elements cations viz. Eu(III) and Tb(III) with acetohydroxamic acid (AHA) in nitric acid medium has been examined. The luminescence lifetimes for the 1 × 10-3 M Eu(III) and AHA complex system decreased with increased AHA concentration from 116 ± 0.2 μs (no AHA) to 1.6 ± 0.1 μs (0.1 M AHA) which was attributed to dynamic quenching. The corrected fluorescence intensities were used to calculate the stability constant (log K) for the formation of 1:1 Eu3+-AHA complex as 1.42 ± 0.64 under the conditions of this study. By contrast, the Tb(III)-AHA system at pH 3 (HNO3) did not show any significant variation in the life times of the excited state (364 ± 9 μs) suggesting the absence of dynamic quenching. The spectral changes in Tb(III)-AHA system showed the formation of 1:1 complex (log K: 1.72 ± 0.21). These studies suggest that the extent of AHA complexation with the rare earth elements will be insignificant as compared to tetravalent metal ions Pu(IV) and Np(IV) under UREX process conditions.

Rise and Fall of one of World's largest deltas; the Mekong delta in Vietnam

NASA Astrophysics Data System (ADS)

Minderhoud, P. S. J.; Eslami Arab, S.; Pham, H. V.; Erkens, G.; van der Vegt, M.; Oude Essink, G.; Stouthamer, E.; Hoekstra, P.

2017-12-01

The Mekong delta is the third's largest delta in the world. It is home to almost 20 million people and an important region for the food security in South East Asia. As most deltas, the Mekong delta is the dynamic result of a balance of sediment supply, sea level rise and subsidence, hosting a system of fresh and salt water dynamics. Ongoing urbanization, industrialization and intensification of agricultural practices in the delta, during the past decades, resulted in growing domestic, agricultural and industrial demands, and have led to a dramatic increase of fresh water use. Since the year 2000, the amount of fresh groundwater extracted from the subsurface increased by 500%. This accelerated delta subsidence as the groundwater system compacts, with current sinking rates exceeding global sea level rise up to an order of magnitude. These high sinking rates have greatly altered the sediment budget of the delta and, with over 50% of the Mekong delta surface elevated less than 1 meter above sea level, greatly increase vulnerability to flooding and storm surges and ultimately, permanent inundation. Furthermore, as the increasingly larger extractions rapidly reduce the fresh groundwater reserves, groundwater salinization subsequently increases. On top of that, dry season low-flows by the Mekong river cause record salt water intrusion in the delta's estuarine system, creating major problems for rice irrigation. We present the work of three years research by the Dutch-Vietnamese `Rise and Fall' project on land subsidence and salinization in both groundwater and surface water in the Vietnamese Mekong delta.

How do you assign persistent identifiers to extracts from large, complex, dynamic data sets that underpin scholarly publications?

NASA Astrophysics Data System (ADS)

Wyborn, Lesley; Car, Nicholas; Evans, Benjamin; Klump, Jens

2016-04-01

Persistent identifiers in the form of a Digital Object Identifier (DOI) are becoming more mainstream, assigned at both the collection and dataset level. For static datasets, this is a relatively straight-forward matter. However, many new data collections are dynamic, with new data being appended, models and derivative products being revised with new data, or the data itself revised as processing methods are improved. Further, because data collections are becoming accessible as services, researchers can log in and dynamically create user-defined subsets for specific research projects: they also can easily mix and match data from multiple collections, each of which can have a complex history. Inevitably extracts from such dynamic data sets underpin scholarly publications, and this presents new challenges. The National Computational Infrastructure (NCI) has been experiencing and making progress towards addressing these issues. The NCI is large node of the Research Data Services initiative (RDS) of the Australian Government's research infrastructure, which currently makes available over 10 PBytes of priority research collections, ranging from geosciences, geophysics, environment, and climate, through to astronomy, bioinformatics, and social sciences. Data are replicated to, or are produced at, NCI and then processed there to higher-level data products or directly analysed. Individual datasets range from multi-petabyte computational models and large volume raster arrays, down to gigabyte size, ultra-high resolution datasets. To facilitate access, maximise reuse and enable integration across the disciplines, datasets have been organized on a platform called the National Environmental Research Data Interoperability Platform (NERDIP). Combined, the NERDIP data collections form a rich and diverse asset for researchers: their co-location and standardization optimises the value of existing data, and forms a new resource to underpin data-intensive Science. New publication procedures require that a persistent identifier (DOI) be provided for the dataset that underpins the publication. Being able to produce these for data extracts from the NCI data node using only DOIs is proving difficult: preserving a copy of each data extract is not possible due to data scale. A proposal is for researchers to use workflows that capture the provenance of each data extraction, including metadata (e.g., version of the dataset used, the query and time of extraction). In parallel, NCI is now working with the NERDIP dataset providers to ensure that the provenance of data publication is also captured in provenance systems including references to previous versions and a history of data appended or modified. This proposed solution would require an enhancement to new scholarly publication procedures whereby the reference to underlying dataset to a scholarly publication would be the persistent identifier of the provenance workflow that created the data extract. In turn, the provenance workflow would itself link to a series of persistent identifiers that, at a minimum, provide complete dataset production transparency and, if required, would facilitate reconstruction of the dataset. Such a solution will require strict adherence to design patterns for provenance representation to ensure that the provenance representation of the workflow does indeed contain information required to deliver dataset generation transparency and a pathway to reconstruction.

Topological characterization and early detection of bifurcations and chaos in complex systems using persistent homology.

PubMed

Mittal, Khushboo; Gupta, Shalabh

2017-05-01

Early detection of bifurcations and chaos and understanding their topological characteristics are essential for safe and reliable operation of various electrical, chemical, physical, and industrial processes. However, the presence of non-linearity and high-dimensionality in system behavior makes this analysis a challenging task. The existing methods for dynamical system analysis provide useful tools for anomaly detection (e.g., Bendixson-Dulac and Poincare-Bendixson criteria can detect the presence of limit cycles); however, they do not provide a detailed topological understanding about system evolution during bifurcations and chaos, such as the changes in the number of subcycles and their positions, lifetimes, and sizes. This paper addresses this research gap by using topological data analysis as a tool to study system evolution and develop a mathematical framework for detecting the topological changes in the underlying system using persistent homology. Using the proposed technique, topological features (e.g., number of relevant k-dimensional holes, etc.) are extracted from nonlinear time series data which are useful for deeper analysis of the system behavior and early detection of bifurcations and chaos. When applied to a Logistic map, a Duffing oscillator, and a real life Op-amp based Jerk circuit, these features are shown to accurately characterize the system dynamics and detect the onset of chaos.

Microbial community structures in high rate algae ponds for bioconversion of agricultural wastes from livestock industry for feed production.

PubMed

Mark Ibekwe, A; Murinda, Shelton E; Murry, Marcia A; Schwartz, Gregory; Lundquist, Trygve

2017-02-15

Dynamics of seasonal microbial community compositions in algae cultivation ponds are complex. However, there is very limited knowledge on bacterial communities that may play significant roles with algae in the bioconversion of manure nutrients to animal feed. In this study, water samples were collected during winter, spring, summer, and fall from the dairy lagoon effluent (DLE), high rate algae ponds (HRAP) that were fed with diluted DLE, and municipal waste water treatment plant (WWTP) effluent which was included as a comparison system for the analysis of total bacteria, Cyanobacteria, and microalgae communities using MiSeq Illumina sequencing targeting the 16S V4 rDNA region. The main objective was to examine dynamics in microbial community composition in the HRAP used for the production of algal biomass. DNA was extracted from the different sample types using three commercially available DNA extraction kits; MoBio Power water extraction kit, Zymo fungi/bacterial extraction kit, and MP Biomedicals FastDNA SPIN Kit. Permutational analysis of variance (PERMANOVA) using distance matrices on each variable showed significant differences (P=0.001) in beta-diversity based on sample source. Environmental variables such as hydraulic retention time (HRT; P<0.031), total N (P<0.002), total inorganic N (P<0.002), total P (P<0.002), alkalinity (P<0.002), pH (P<0.022), total suspended solid (TSS; P<0.003), and volatile suspended solids (VSS; P<0.002) significantly affected microbial communities in DLE, HRAP, and WWTP. Of the operational taxonomic units (OTUs) identified to phyla level, the dominant classes of bacteria identified were: Cyanobacteria, Alpha-, Beta-, Gamma-, Epsilon-, and Delta-proteobacteria, Bacteroidetes, Firmicutes, and Planctomycetes. Our data suggest that microbial communities were significantly affected in HRAP by different environmental variables, and care must be taken in extraction procedures when evaluating specific groups of microbial communities for specific functions. Published by Elsevier B.V.

Energy-absorption spectroscopy of unitary Fermi gases in a uniform potential

NASA Astrophysics Data System (ADS)

Zhang, Pengfei; Yu, Zhenhua

2018-04-01

We propose to use the energy absorption spectroscopy to measure the kinetic coefficients of unitary Fermi gases in a uniform potential. We show that, in our scheme, the energy absorption spectrum is proportional to the dynamic structure factor of the system. The profile of the spectrum depends on the shear viscosity η , the thermal conductivity κ , and the superfluid bulk viscosity ξ3. We show that extraction of these coefficients from the spectrum is achievable in present experiments.

Adaptive Control of Four-Leg VSC Based DSTATCOM in Distribution System

NASA Astrophysics Data System (ADS)

Singh, Bhim; Arya, Sabha Raj

2014-01-01

This work discusses an experimental performance of a four-leg Distribution Static Compensator (DSTATCOM) using an adaptive filter based approach. It is used for estimation of reference supply currents through extracting the fundamental active power components of three-phase distorted load currents. This control algorithm is implemented on an assembled DSTATCOM for harmonics elimination, neutral current compensation and load balancing, under nonlinear loads. Experimental results are discussed, and it is noticed that DSTATCOM is effective solution to perform satisfactory performance under load dynamics.

Effects of Transient Power Extraction on an Integrated Hardware-in-the-Loop Aircraft/Propulsion/Power System

DTIC Science & Technology

2008-11-01

Simulations of an engine and its Full Authority Digital Engine Control ( FADEC ), along with a 6 degree-of-freedom (6DoF) airframe dynamics model and...as needed. In its current configuration, the generic turbine engine model’s FADEC is included in the same simulation and runs primarily on 2 a...back to the engine. As mentioned previously, the FADEC and engine are combined into one simulation and are collectively referred to as “the engine

Two-Dimensional Spectroscopy Is Being Used to Address Core Scientific Questions in Biology and Materials Science.

PubMed

Petti, Megan K; Lomont, Justin P; Maj, Michał; Zanni, Martin T

2018-02-15

Two-dimensional spectroscopy is a powerful tool for extracting structural and dynamic information from a wide range of chemical systems. We provide a brief overview of the ways in which two-dimensional visible and infrared spectroscopies are being applied to elucidate fundamental details of important processes in biological and materials science. The topics covered include amyloid proteins, photosynthetic complexes, ion channels, photovoltaics, batteries, as well as a variety of promising new methods in two-dimensional spectroscopy.

Model parameter learning using Kullback-Leibler divergence

NASA Astrophysics Data System (ADS)

Lin, Chungwei; Marks, Tim K.; Pajovic, Milutin; Watanabe, Shinji; Tung, Chih-kuan

2018-02-01

In this paper, we address the following problem: For a given set of spin configurations whose probability distribution is of the Boltzmann type, how do we determine the model coupling parameters? We demonstrate that directly minimizing the Kullback-Leibler divergence is an efficient method. We test this method against the Ising and XY models on the one-dimensional (1D) and two-dimensional (2D) lattices, and provide two estimators to quantify the model quality. We apply this method to two types of problems. First, we apply it to the real-space renormalization group (RG). We find that the obtained RG flow is sufficiently good for determining the phase boundary (within 1% of the exact result) and the critical point, but not accurate enough for critical exponents. The proposed method provides a simple way to numerically estimate amplitudes of the interactions typically truncated in the real-space RG procedure. Second, we apply this method to the dynamical system composed of self-propelled particles, where we extract the parameter of a statistical model (a generalized XY model) from a dynamical system described by the Viscek model. We are able to obtain reasonable coupling values corresponding to different noise strengths of the Viscek model. Our method is thus able to provide quantitative analysis of dynamical systems composed of self-propelled particles.

Symbolic dynamic filtering and language measure for behavior identification of mobile robots.

PubMed

Mallapragada, Goutham; Ray, Asok; Jin, Xin

2012-06-01

This paper presents a procedure for behavior identification of mobile robots, which requires limited or no domain knowledge of the underlying process. While the features of robot behavior are extracted by symbolic dynamic filtering of the observed time series, the behavior patterns are classified based on language measure theory. The behavior identification procedure has been experimentally validated on a networked robotic test bed by comparison with commonly used tools, namely, principal component analysis for feature extraction and Bayesian risk analysis for pattern classification.

Segmentation of Unstructured Datasets

NASA Technical Reports Server (NTRS)

Bhat, Smitha

1996-01-01

Datasets generated by computer simulations and experiments in Computational Fluid Dynamics tend to be extremely large and complex. It is difficult to visualize these datasets using standard techniques like Volume Rendering and Ray Casting. Object Segmentation provides a technique to extract and quantify regions of interest within these massive datasets. This thesis explores basic algorithms to extract coherent amorphous regions from two-dimensional and three-dimensional scalar unstructured grids. The techniques are applied to datasets from Computational Fluid Dynamics and from Finite Element Analysis.

Electromagnetic {\\varvec{N}}^{\\varvec{*}} Transition Form Factors in the ANL-Osaka Dynamical Coupled-Channels Approach

NASA Astrophysics Data System (ADS)

Kamano, Hiroyuki

2018-05-01

We give an overview of our recent efforts to extract electromagnetic transition form factors for N^* and Δ^* baryon resonances through a global analysis of the single-pion electroproductions off the proton within the ANL-Osaka dynamical coupled-channels approach. Preliminary results for the extracted form factors associated with Δ(1232)3/2^+ and the Roper resonance are presented, with emphasis on the complex-valued nature of the transition form factors defined by poles.

Simultaneous refraction measurement and OCT axial biometry of the eye during accommodation (Conference Presentation)

NASA Astrophysics Data System (ADS)

De Freitas, Carolina; Hernandez, Victor M.; Ruggeri, Marco; Durkee, Heather A.; Williams, Siobhan; Gregori, Giovanni; Ho, Arthur; Manns, Fabrice; Parel, Jean-Marie

2016-03-01

The purpose of this project is to design and evaluate a system that will enable objective assessment of the optical accommodative response in real-time while acquiring axial biometric information. The system combines three sub-systems which were integrated and mounted on a joystick x-y-z adjustable modified slit-lamp base to facilitate alignment and data acquisition: (1) a Shack-Hartmann wavefront sensor for dynamic refraction measurement, provided software calculates sphere, cylinder and axis values, (2) an extended-depth Optical Coherence Tomography (OCT) system using an optical switch records high-resolution cross-sectional images across the length of the eye, from which, dynamic axial biometry (corneal thickness, anterior chamber depth, crystalline lens thickness and vitreous depth) can be extracted, and (3) a modified dual-channel accommodation stimulus unit based on the Badal optometer for providing a step change in accommodative stimulus. The prototypal system is capable of taking simultaneous measurements of both the optical and the mechanical response of lens accommodation. These measurements can provide insight into correlating changes in lens shape with changes in lens power and ocular refraction and ultimately provide a more comprehensive understanding of accommodation, presbyopia and an objective assessment of presbyopia correction techniques.

Dynamical arrest, percolation, gelation, and glass formation in model nanoparticle dispersions with thermoreversible adhesive interactions.

PubMed

Eberle, Aaron P R; Castañeda-Priego, Ramón; Kim, Jung M; Wagner, Norman J

2012-01-24

We report an experimental study of the dynamical arrest transition for a model system consisting of octadecyl coated silica suspended in n-tetradecane from dilute to concentrated conditions spanning the state diagram. The dispersion's interparticle potential is tuned by temperature affecting the brush conformation leading to a thermoreversible model system. The critical temperature for dynamical arrest, T*, is determined as a function of dispersion volume fraction by small-amplitude dynamic oscillatory shear rheology. We corroborate this transition temperature by measuring a power-law decay of the autocorrelation function and a loss of ergodicity via fiber-optic quasi-elastic light scattering. The structure at T* is measured using small-angle neutron scattering. The scattering intensity is fit to extract the interparticle pair-potential using the Ornstein-Zernike equation with the Percus-Yevick closure approximation, assuming a square-well interaction potential with a short-range interaction (1% of particle diameter). (1) The strength of attraction is characterized using the Baxter temperature (2) and mapped onto the adhesive hard sphere state diagram. The experiments show a continuous dynamical arrest transition line that follows the predicted dynamical percolation line until ϕ ≈ 0.41 where it subtends the predictions toward the mode coupling theory attractive-driven glass line. An alternative analysis of the phase transition through the reduced second virial coefficient B(2)* shows a change in the functional dependence of B(2)* on particle concentration around ϕ ≈ 0.36. We propose this signifies the location of a gel-to-glass transition. The results presented herein differ from those observed for depletion flocculated dispersion of micrometer-sized particles in polymer solutions, where dynamical arrest is a consequence of multicomponent phase separation, suggesting dynamical arrest is sensitive to the physical mechanism of attraction.

Extracting Damping Ratio from Dynamic Data and Numerical Solutions

NASA Technical Reports Server (NTRS)

Casiano, M. J.

2016-01-01

There are many ways to extract damping parameters from data or models. This Technical Memorandum provides a quick reference for some of the more common approaches used in dynamics analysis. Described are six methods of extracting damping from data: the half-power method, logarithmic decrement (decay rate) method, an autocorrelation/power spectral density fitting method, a frequency response fitting method, a random decrement fitting method, and a newly developed half-quadratic gain method. Additionally, state-space models and finite element method modeling tools, such as COMSOL Multiphysics (COMSOL), provide a theoretical damping via complex frequency. Each method has its advantages which are briefly noted. There are also likely many other advanced techniques in extracting damping within the operational modal analysis discipline, where an input excitation is unknown; however, these approaches discussed here are objective, direct, and can be implemented in a consistent manner.

[Study on dynamic accumulation of index components from Bupleurum chinense in various collecting periods].

PubMed

Wang, Qi-shuai; Li, Xiao-kun; Yang, Yun; Xiao, Gong-sheng; Feng, Wei-sheng

2010-08-01

To study the dynamic change law of volatile oil, saikosaponin a, d and alcohol-extract from Bupleurum chinense at Songxian region in Henan province, and to explore the optimal harvest period of Bupleurum chinense. With the contents of saikosaponin a and d, absorbance of volatile oil and percentage of alcohol-extract as indexes, HPLC-ELSD and ultraviolet spectrophotometry were successively used to analyze them. There are obvious differences among the contents of volatile oil, saikosaponin a, d and alcohol-extract in various collecting periods sample, the absorption of volatile oil in distillation was the highest in October, the content of saikosaponin a was the highest in September, the saikosaponin d in December and the percentage of alcohol-extract in October. The optimal harvest period of Bupleurum chinense at Songxian region in Henan is identified, which can provide scientific basis for crude drug production and processing.

Dynamic topographical pattern classification of multichannel prefrontal NIRS signals: II. Online differentiation of mental arithmetic and rest

NASA Astrophysics Data System (ADS)

Schudlo, Larissa C.; Chau, Tom

2014-02-01

Objective. Near-infrared spectroscopy (NIRS) has recently gained attention as a modality for brain-computer interfaces (BCIs), which may serve as an alternative access pathway for individuals with severe motor impairments. For NIRS-BCIs to be used as a real communication pathway, reliable online operation must be achieved. Yet, only a limited number of studies have been conducted online to date. These few studies were carried out under a synchronous paradigm and did not accommodate an unconstrained resting state, precluding their practical clinical implication. Furthermore, the potentially discriminative power of spatiotemporal characteristics of activation has yet to be considered in an online NIRS system. Approach. In this study, we developed and evaluated an online system-paced NIRS-BCI which was driven by a mental arithmetic activation task and accommodated an unconstrained rest state. With a dual-wavelength, frequency domain near-infrared spectrometer, measurements were acquired over nine sites of the prefrontal cortex, while ten able-bodied participants selected letters from an on-screen scanning keyboard via intentionally controlled brain activity (using mental arithmetic). Participants were provided dynamic NIR topograms as continuous visual feedback of their brain activity as well as binary feedback of the BCI's decision (i.e. if the letter was selected or not). To classify the hemodynamic activity, temporal features extracted from the NIRS signals and spatiotemporal features extracted from the dynamic NIR topograms were used in a majority vote combination of multiple linear classifiers. Main results. An overall online classification accuracy of 77.4 ± 10.5% was achieved across all participants. The binary feedback was found to be very useful during BCI use, while not all participants found value in the continuous feedback provided. Significance. These results demonstrate that mental arithmetic is a potent mental task for driving an online system-paced NIRS-BCI. BCI feedback that reflects the classifier's decision has the potential to improve user performance. The proposed system can provide a framework for future online NIRS-BCI development and testing.

A novel visual saliency analysis model based on dynamic multiple feature combination strategy

NASA Astrophysics Data System (ADS)

Lv, Jing; Ye, Qi; Lv, Wen; Zhang, Libao

2017-06-01

The human visual system can quickly focus on a small number of salient objects. This process was known as visual saliency analysis and these salient objects are called focus of attention (FOA). The visual saliency analysis mechanism can be used to extract the salient regions and analyze saliency of object in an image, which is time-saving and can avoid unnecessary costs of computing resources. In this paper, a novel visual saliency analysis model based on dynamic multiple feature combination strategy is introduced. In the proposed model, we first generate multi-scale feature maps of intensity, color and orientation features using Gaussian pyramids and the center-surround difference. Then, we evaluate the contribution of all feature maps to the saliency map according to the area of salient regions and their average intensity, and attach different weights to different features according to their importance. Finally, we choose the largest salient region generated by the region growing method to perform the evaluation. Experimental results show that the proposed model cannot only achieve higher accuracy in saliency map computation compared with other traditional saliency analysis models, but also extract salient regions with arbitrary shapes, which is of great value for the image analysis and understanding.

On continuous user authentication via typing behavior.

PubMed

Roth, Joseph; Liu, Xiaoming; Metaxas, Dimitris

2014-10-01

We hypothesize that an individual computer user has a unique and consistent habitual pattern of hand movements, independent of the text, while typing on a keyboard. As a result, this paper proposes a novel biometric modality named typing behavior (TB) for continuous user authentication. Given a webcam pointing toward a keyboard, we develop real-time computer vision algorithms to automatically extract hand movement patterns from the video stream. Unlike the typical continuous biometrics, such as keystroke dynamics (KD), TB provides a reliable authentication with a short delay, while avoiding explicit key-logging. We collect a video database where 63 unique subjects type static text and free text for multiple sessions. For one typing video, the hands are segmented in each frame and a unique descriptor is extracted based on the shape and position of hands, as well as their temporal dynamics in the video sequence. We propose a novel approach, named bag of multi-dimensional phrases, to match the cross-feature and cross-temporal pattern between a gallery sequence and probe sequence. The experimental results demonstrate a superior performance of TB when compared with KD, which, together with our ultrareal-time demo system, warrant further investigation of this novel vision application and biometric modality.

Topological properties of flat electroencephalography's state space

NASA Astrophysics Data System (ADS)

Ken, Tan Lit; Ahmad, Tahir bin; Mohd, Mohd Sham bin; Ngien, Su Kong; Suwa, Tohru; Meng, Ong Sie

2016-02-01

Neuroinverse problem are often associated with complex neuronal activity. It involves locating problematic cell which is highly challenging. While epileptic foci localization is possible with the aid of EEG signals, it relies greatly on the ability to extract hidden information or pattern within EEG signals. Flat EEG being an enhancement of EEG is a way of viewing electroencephalograph on the real plane. In the perspective of dynamical systems, Flat EEG is equivalent to epileptic seizure hence, making it a great platform to study epileptic seizure. Throughout the years, various mathematical tools have been applied on Flat EEG to extract hidden information that is hardly noticeable by traditional visual inspection. While these tools have given worthy results, the journey towards understanding seizure process completely is yet to be succeeded. Since the underlying structure of Flat EEG is dynamic and is deemed to contain wealthy information regarding brainstorm, it would certainly be appealing to explore in depth its structures. To better understand the complex seizure process, this paper studies the event of epileptic seizure via Flat EEG in a more general framework by means of topology, particularly, on the state space where the event of Flat EEG lies.

The Rapidity Density Distributions and Longitudinal Expansion Dynamics of Identified Pions from the STAR Beam Energy Scan

NASA Astrophysics Data System (ADS)

Flores, Christopher E.

2016-12-01

The Beam Energy Scan (BES) at the Relativistic Heavy-Ion Collider was proposed to characterize the properties of the medium produced in heavy-ion interactions over a broad range of baryon chemical potential. The aptitude of the STAR detector for mid-rapidity measurements has previously been leveraged to measure identified particle yields and spectra to extract bulk properties for the BES energies for | y | ≤ 0.1. However, to extract information on expansion dynamics and full phase space particle production, it is necessary to study identified particle rapidity density distributions. We present the first rapidity density distributions of identified pions from Au+Au collisions at √{sNN} = 7.7 , 11.5, and 19.6 GeV from the BES program as measured by the STAR detector. We use these distributions to obtain the full phase space yields of the pions to provide additional information of the system's chemistry. Further, we report the width of the rapidity density distributions compared to the width expected from Landau hydrodynamics. Finally, we interpret the results as a function of collision energy and discuss them in the context of previous energy scans done at the AGS and SPS.

Network structure of multivariate time series.

PubMed

Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

2015-10-21

Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail.

Tsallis non-extensive statistical mechanics in the ionospheric detrended total electron content during quiet and storm periods

NASA Astrophysics Data System (ADS)

Ogunsua, B. O.; Laoye, J. A.

2018-05-01

In this paper, the Tsallis non-extensive q-statistics in ionospheric dynamics was investigated using the total electron content (TEC) obtained from two Global Positioning System (GPS) receiver stations. This investigation was carried out considering the geomagnetically quiet and storm periods. The micro density variation of the ionospheric total electron content was extracted from the TEC data by method of detrending. The detrended total electron content, which represent the variation in the internal dynamics of the system was further analyzed using for non-extensive statistical mechanics using the q-Gaussian methods. Our results reveals that for all the analyzed data sets the Tsallis Gaussian probability distribution (q-Gaussian) with value q > 1 were obtained. It was observed that there is no distinct difference in pattern between the values of qquiet and qstorm. However the values of q varies with geophysical conditions and possibly with local dynamics for the two stations. Also observed are the asymmetric pattern of the q-Gaussian and a highly significant level of correlation for the q-index values obtained for the storm periods compared to the quiet periods between the two GPS receiver stations where the TEC was measured. The factors responsible for this variation can be mostly attributed to the varying mechanisms resulting in the self-reorganization of the system dynamics during the storm periods. The result shows the existence of long range correlation for both quiet and storm periods for the two stations.

Identification of an urban fractured-rock aquifer dynamics using an evolutionary self-organizing modelling

NASA Astrophysics Data System (ADS)

Hong, Yoon-Seok; Rosen, Michael R.

2002-03-01

An urban fractured-rock aquifer system, where disposal of storm water is via 'soak holes' drilled directly into the top of fractured-rock basalt, has a highly dynamic nature where theories or knowledge to generate the model are still incomplete and insufficient. Therefore, formulating an accurate mechanistic model, usually based on first principles (physical and chemical laws, mass balance, and diffusion and transport, etc.), requires time- and money-consuming tasks. Instead of a human developing the mechanistic-based model, this paper presents an approach to automatic model evolution in genetic programming (GP) to model dynamic behaviour of groundwater level fluctuations affected by storm water infiltration. This GP evolves mathematical models automatically that have an understandable structure using function tree representation by methods of natural selection ('survival of the fittest') through genetic operators (reproduction, crossover, and mutation). The simulation results have shown that GP is not only capable of predicting the groundwater level fluctuation due to storm water infiltration but also provides insight into the dynamic behaviour of a partially known urban fractured-rock aquifer system by allowing knowledge extraction of the evolved models. Our results show that GP can work as a cost-effective modelling tool, enabling us to create prototype models quickly and inexpensively and assists us in developing accurate models in less time, even if we have limited experience and incomplete knowledge for an urban fractured-rock aquifer system affected by storm water infiltration.

Upgrade of the beam extraction system of the GTS-LHC electron cyclotron resonance ion source at CERN

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

Toivanen, V., E-mail: ville.aleksi.toivanen@cern.ch; Bellodi, G.; Dimov, V.

2016-02-15

Linac3 is the first accelerator in the heavy ion injector chain of the Large Hadron Collider (LHC), providing multiply charged heavy ion beams for the CERN experimental program. The ion beams are produced with GTS-LHC, a 14.5 GHz electron cyclotron resonance ion source, operated in afterglow mode. Improvement of the GTS-LHC beam formation and beam transport along Linac3 is part of the upgrade program of the injector chain in preparation for the future high luminosity LHC. A mismatch between the ion beam properties in the ion source extraction region and the acceptance of the following Low Energy Beam Transport (LEBT)more » section has been identified as one of the factors limiting the Linac3 performance. The installation of a new focusing element, an einzel lens, into the GTS-LHC extraction region is foreseen as a part of the Linac3 upgrade, as well as a redesign of the first section of the LEBT. Details of the upgrade and results of a beam dynamics study of the extraction region and LEBT modifications will be presented.« less

Will a Category Cue Attract You? Motor Output Reveals Dynamic Competition across Person Construal

ERIC Educational Resources Information Center

Freeman, Jonathan B.; Ambady, Nalini; Rule, Nicholas O.; Johnson, Kerri L.

2008-01-01

People use social categories to perceive others, extracting category cues to glean membership. Growing evidence for continuous dynamics in real-time cognition suggests, contrary to prevailing social psychological accounts, that person construal may involve dynamic competition between simultaneously active representations. To test this, the authors…

Biometric verification in dynamic writing

NASA Astrophysics Data System (ADS)

George, Susan E.

2002-03-01

Pen-tablet devices capable of capturing the dynamics of writing record temporal and pressure information as well as the spatial pattern. This paper explores biometric verification based upon the dynamics of writing where writers are distinguished not on the basis of what they write (ie the signature), but how they write. We have collected samples of dynamic writing from 38 Chinese writers. Each writer was asked to provide 10 copies of a paragraph of text and the same number of signature samples. From the data we have extracted stroke-based primitives from the sentence data utilizing pen-up/down information and heuristic rules about the shape of the character. The x, y and pressure values of each primitive were interpolated into an even temporal range based upon a 20 msec sampling rate. We applied the Daubechies 1 wavelet transform to the x signal, y signal and pressure signal using the coefficients as inputs to a multi-layer perceptron trained with back-propagation on the sentence data. We found a sensitivity of 0.977 and specificity of 0.990 recognizing writers based on test primitives extracted from sentence data and measures of 0.916 and 0.961 respectively, from test primitives extracted from signature data.

Bioassay-guided supercritical fluid extraction of cyclooxygenase-2 inhibiting substances in Plantago major L.

PubMed

Stenholm, A; Göransson, U; Bohlin, L

2013-02-01

Selective extraction of plant materials is advantageous for obtaining extracts enriched with desired constituents, thereby reducing the need for subsequent chromatography purification. Such compounds include three cyclooxygenase-2 (COX-2) inhibitory substances in Plantago major L. targeted in this investigation: α-linolenic acid (α-LNA) (18:3 ω-3) and the triterpenic acids ursolic acid and oleanolic acid. To investigate the scope for tuning the selectivity of supercritical fluid extraction (SFE) using bioassay guidance, and Soxhlet extraction with dichloromethane as solvent as a reference technique, to optimise yields of these substances. Extraction parameters were varied to optimise extracts' COX-2/COX-1 inhibitory effect ratios. The crude extracts were purified initially using a solid phase extraction (SPE) clean-up procedure and the target compounds were identified with GC-MS, LC-ESI-MS and LC-ESI-MS² using GC-FID for quantification. α-LNA was preferentially extracted in dynamic mode using unmodified carbon dioxide at 40°C and 172 bar, at a 0.04% (w/w) yield with a COX-2/COX-1 inhibitory effect ratio of 1.5. Ursolic and oleanolic acids were dynamically extracted at 0.25% and 0.06% yields, respectively, with no traces of (α-LNA) and a COX-2/COX-1-inhibitory effect ratio of 1.1 using 10% (v/v) ethanol as polar modifier at 75°C and 483 bar. The Soxhlet extracts had ursolic acid, oleanolic acid and αLNA yields up to 1.36%, 0.34% and 0.15%, respectively, with a COX-2/COX-1 inhibitory effect ratio of 1.2. The target substances can be extracted selectively by bioassay guided optimisation of SFE conditions. Copyright © 2012 John Wiley & Sons, Ltd.

Dynamic control of osmolality and ionic composition of the xylem sap in two mangrove species.

PubMed

López-Portillo, Jorge; Ewers, Frank W; Méndez-Alonzo, Rodrigo; Paredes López, Claudia L; Angeles, Guillermo; Alarcón Jiménez, Ana Luisa; Lara-Domínguez, Ana Laura; Torres Barrera, María Del Carmen

2014-06-01

• Premise of the study: Xylem sap osmolality and salinity is a critical unresolved issue in plant function with impacts on transport efficiency, pressure gradients, and living cell turgor pressure, especially for halophytes such as mangrove trees.• Methods: We collected successive xylem vessel sap samples from stems and shoots of Avicennia germinans and Laguncularia racemosa using vacuum and pressure extraction and measured their osmolality. Following a series of extractions with the pressure chamber, we depressurized the shoot and pressurized again after various equilibration periods (minutes to hours) to test for dynamic control of osmolality. Transpiration and final sap osmolality were measured in shoots perfused with deionized water or different seawater dilutions.• Key results: For both species, the sap osmolality values of consecutive samples collected by vacuum extraction were stable and matched those of the initial samples extracted with the pressure chamber. Further extraction of samples with the pressure chamber decreased sap osmolality, suggesting reverse osmosis occurred. However, sap osmolalities increased when longer equilibration periods after sap extraction were allowed. Analysis of expressed sap with HPLC indicated a 1:1 relation between measured osmolality and the osmolality of the inorganic ions in the sap (mainly Na + , K + , and Cl - ), suggesting no contamination by organic compounds. In stems perfused with deionized water, the sap osmolality increased to mimic the native sap osmolality.• Conclusions: Xylem sap osmolality and ionic contents are dynamically adjusted by mangroves and may help modulate turgor pressure, hydraulic conductivity, and water potential, thus being important for mangrove physiology, survival, and distribution. © 2014 Botanical Society of America, Inc.

Zero-Point Energy Leakage in Quantum Thermal Bath Molecular Dynamics Simulations.

PubMed

Brieuc, Fabien; Bronstein, Yael; Dammak, Hichem; Depondt, Philippe; Finocchi, Fabio; Hayoun, Marc

2016-12-13

The quantum thermal bath (QTB) has been presented as an alternative to path-integral-based methods to introduce nuclear quantum effects in molecular dynamics simulations. The method has proved to be efficient, yielding accurate results for various systems. However, the QTB method is prone to zero-point energy leakage (ZPEL) in highly anharmonic systems. This is a well-known problem in methods based on classical trajectories where part of the energy of the high-frequency modes is transferred to the low-frequency modes leading to a wrong energy distribution. In some cases, the ZPEL can have dramatic consequences on the properties of the system. Thus, we investigate the ZPEL by testing the QTB method on selected systems with increasing complexity in order to study the conditions and the parameters that influence the leakage. We also analyze the consequences of the ZPEL on the structural and vibrational properties of the system. We find that the leakage is particularly dependent on the damping coefficient and that increasing its value can reduce and, in some cases, completely remove the ZPEL. When using sufficiently high values for the damping coefficient, the expected energy distribution among the vibrational modes is ensured. In this case, the QTB method gives very encouraging results. In particular, the structural properties are well-reproduced. The dynamical properties should be regarded with caution although valuable information can still be extracted from the vibrational spectrum, even for large values of the damping term.

Characterization of a smartphone size haptic rendering system based on thin-film AlN actuators on glass substrates

NASA Astrophysics Data System (ADS)

Bernard, F.; Casset, F.; Danel, J. S.; Chappaz, C.; Basrour, S.

2016-08-01

This paper presents for the first time the characterization of a smartphone-size haptic rendering system based on the friction modulation effect. According to previous work and finite element modeling, the homogeneous flexural modes are needed to get the haptic feedback effect. The device studied consists of a thin film AlN transducers deposited on an 110  ×  65 mm2 glass substrate. The transducer’s localization on the glass plate allows a transparent central area of 90  ×  49 mm2. Electrical and mechanical parameters of the system are extracted from measurement. From this extraction, the electrical impedance matching reduced the applied voltage to 17.5 V AC and the power consumption to 1.53 W at the resonance frequency of the vibrating system to reach the haptic rendering specification. Transient characterizations of the actuation highlight a delay under the dynamic tactile detection. The characterization of the AlN transducers used as sensors, including the noise rejection, the delay or the output charge amplitude allows detections with high accuracy of any variation due to external influences. Those specifications are the first step to a low-power-consumption feedback-looped system.

Biomechanics of milk extraction during breast-feeding.

PubMed

Elad, David; Kozlovsky, Pavel; Blum, Omry; Laine, Andrew F; Po, Ming Jack; Botzer, Eyal; Dollberg, Shaul; Zelicovich, Mabel; Ben Sira, Liat

2014-04-08

How do infants extract milk during breast-feeding? We have resolved a century-long scientific controversy, whether it is sucking of the milk by subatmospheric pressure or mouthing of the nipple-areola complex to induce a peristaltic-like extraction mechanism. Breast-feeding is a dynamic process, which requires coupling between periodic motions of the infant's jaws, undulation of the tongue, and the breast milk ejection reflex. The physical mechanisms executed by the infant have been intriguing topics. We used an objective and dynamic analysis of ultrasound (US) movie clips acquired during breast-feeding to explore the tongue dynamic characteristics. Then, we developed a new 3D biophysical model of the breast and lactiferous tubes that enables the mimicking of dynamic characteristics observed in US imaging during breast-feeding, and thereby, exploration of the biomechanical aspects of breast-feeding. We have shown, for the first time to our knowledge, that latch-on to draw the nipple-areola complex into the infant mouth, as well as milk extraction during breast-feeding, require development of time-varying subatmospheric pressures within the infant's oral cavity. Analysis of the US movies clearly demonstrated that tongue motility during breast-feeding was fairly periodic. The anterior tongue, which is wedged between the nipple-areola complex and the lower lips, moves as a rigid body with the cycling motion of the mandible, while the posterior section of the tongue undulates in a pattern similar to a propagating peristaltic wave, which is essential for swallowing.

Biomechanics of milk extraction during breast-feeding

PubMed Central

Elad, David; Kozlovsky, Pavel; Blum, Omry; Laine, Andrew F.; Po, Ming Jack; Botzer, Eyal; Dollberg, Shaul; Zelicovich, Mabel; Ben Sira, Liat

2014-01-01

How do infants extract milk during breast-feeding? We have resolved a century-long scientific controversy, whether it is sucking of the milk by subatmospheric pressure or mouthing of the nipple–areola complex to induce a peristaltic-like extraction mechanism. Breast-feeding is a dynamic process, which requires coupling between periodic motions of the infant’s jaws, undulation of the tongue, and the breast milk ejection reflex. The physical mechanisms executed by the infant have been intriguing topics. We used an objective and dynamic analysis of ultrasound (US) movie clips acquired during breast-feeding to explore the tongue dynamic characteristics. Then, we developed a new 3D biophysical model of the breast and lactiferous tubes that enables the mimicking of dynamic characteristics observed in US imaging during breast-feeding, and thereby, exploration of the biomechanical aspects of breast-feeding. We have shown, for the first time to our knowledge, that latch-on to draw the nipple–areola complex into the infant mouth, as well as milk extraction during breast-feeding, require development of time-varying subatmospheric pressures within the infant’s oral cavity. Analysis of the US movies clearly demonstrated that tongue motility during breast-feeding was fairly periodic. The anterior tongue, which is wedged between the nipple–areola complex and the lower lips, moves as a rigid body with the cycling motion of the mandible, while the posterior section of the tongue undulates in a pattern similar to a propagating peristaltic wave, which is essential for swallowing. PMID:24706845

3D Blade Vibration Measurements on an 80 m Diameter Wind Turbine by Using Non-contact Remote Measurement Systems

NASA Astrophysics Data System (ADS)

Ozbek, Muammer; Rixen, Daniel J.

Non-contact optical measurement systems photogrammetry and laser interferometry are introduced as cost efficient alternatives to the conventional wind turbine/farm monitoring systems that are currently in use. The proposed techniques are proven to provide an accurate measurement of the dynamic behavior of a 2.5 MW—80 m diameter—wind turbine. Several measurements are taken on the test turbine by using 4 CCD cameras and 1 laser vibrometer and the response of the turbine is monitored from a distance of 220 m. The results of the infield tests and the corresponding analyses show that photogrammetry (also can be called as videogrammetry or computer vision technique) enable the 3D deformations of the rotor to be measured at 33 different points simultaneously with an average accuracy of ±25 mm, while the turbine is rotating. Several important turbine modes can also be extracted from the recorded data. Similarly, laser interferometry (used for the parked turbine only) provides very valuable information on the dynamic properties of the turbine structure. Twelve different turbine modes can be identified from the obtained response data.

The explosion at institute: modeling and analyzing the situation awareness factor.

PubMed

Naderpour, Mohsen; Lu, Jie; Zhang, Guangquan

2014-12-01

In 2008 a runaway chemical reaction caused an explosion at a methomyl unit in West Virginia, USA, killing two employees, injuring eight people, evacuating more than 40,000 residents adjacent to the facility, disrupting traffic on a nearby highway and causing significant business loss and interruption. Although the accident was formally investigated, the role of the situation awareness (SA) factor, i.e., a correct understanding of the situation, and appropriate models to maintain SA, remain unexplained. This paper extracts details of abnormal situations within the methomyl unit and models them into a situational network using dynamic Bayesian networks. A fuzzy logic system is used to resemble the operator's thinking when confronted with these abnormal situations. The combined situational network and fuzzy logic system make it possible for the operator to assess such situations dynamically to achieve accurate SA. The findings show that the proposed structure provides a useful graphical model that facilitates the inclusion of prior background knowledge and the updating of this knowledge when new information is available from monitoring systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Self-consistent phonon calculations of lattice dynamical properties in cubic SrTiO3 with first-principles anharmonic force constants

NASA Astrophysics Data System (ADS)

Tadano, Terumasa; Tsuneyuki, Shinji

2015-08-01

We present an ab initio framework to calculate anharmonic phonon frequency and phonon lifetime that is applicable to severely anharmonic systems. We employ self-consistent phonon (SCPH) theory with microscopic anharmonic force constants, which are extracted from density functional calculations using the least absolute shrinkage and selection operator technique. We apply the method to the high-temperature phase of SrTiO3 and obtain well-defined phonon quasiparticles that are free from imaginary frequencies. Here we show that the anharmonic phonon frequency of the antiferrodistortive mode depends significantly on the system size near the critical temperature of the cubic-to-tetragonal phase transition. By applying perturbation theory to the SCPH result, phonon lifetimes are calculated for cubic SrTiO3, which are then employed to predict lattice thermal conductivity using the Boltzmann transport equation within the relaxation-time approximation. The presented methodology is efficient and accurate, paving the way toward a reliable description of thermodynamic, dynamic, and transport properties of systems with severe anharmonicity, including thermoelectric, ferroelectric, and superconducting materials.

Relaxation mode analysis and Markov state relaxation mode analysis for chignolin in aqueous solution near a transition temperature

NASA Astrophysics Data System (ADS)

Mitsutake, Ayori; Takano, Hiroshi

2015-09-01

It is important to extract reaction coordinates or order parameters from protein simulations in order to investigate the local minimum-energy states and the transitions between them. The most popular method to obtain such data is principal component analysis, which extracts modes of large conformational fluctuations around an average structure. We recently applied relaxation mode analysis for protein systems, which approximately estimates the slow relaxation modes and times from a simulation and enables investigations of the dynamic properties underlying the structural fluctuations of proteins. In this study, we apply this relaxation mode analysis to extract reaction coordinates for a system in which there are large conformational changes such as those commonly observed in protein folding/unfolding. We performed a 750-ns simulation of chignolin protein near its folding transition temperature and observed many transitions between the most stable, misfolded, intermediate, and unfolded states. We then applied principal component analysis and relaxation mode analysis to the system. In the relaxation mode analysis, we could automatically extract good reaction coordinates. The free-energy surfaces provide a clearer understanding of the transitions not only between local minimum-energy states but also between the folded and unfolded states, even though the simulation involved large conformational changes. Moreover, we propose a new analysis method called Markov state relaxation mode analysis. We applied the new method to states with slow relaxation, which are defined by the free-energy surface obtained in the relaxation mode analysis. Finally, the relaxation times of the states obtained with a simple Markov state model and the proposed Markov state relaxation mode analysis are compared and discussed.

Cyclic and Linear Monoterpenes in Phospholipid Membranes: Phase Behavior, Bilayer Structure, and Molecular Dynamics.

PubMed

Pham, Quoc Dat; Topgaard, Daniel; Sparr, Emma

2015-10-13

Monoterpenes are abundant in essential oils extracted from plants. These relatively small and hydrophobic molecules have shown important biological functions, including antimicrobial activity and membrane penetration enhancement. The interaction between the monoterpenes and lipid bilayers is considered important to the understanding of the biological functions of monoterpenes. In this study, we investigated the effect of cyclic and linear monoterpenes on the structure and dynamics of lipids in model membranes. We have studied the ternary system 1,2-dimyristoyl-sn-glycero-3-phosphocholine-monoterpene-water as a model with a focus on dehydrated conditions. By combining complementary techniques, including differential scanning calorimetry, solid-state nuclear magnetic resonance, and small- and wide-angle X-ray scattering, bilayer structure, phase transitions, and lipid molecular dynamics were investigated at different water contents. Monoterpenes cause pronounced melting point depression and phase segregation in lipid bilayers, and the extent of these effects depends on the hydration conditions. The addition of a small amount of thymol to the fluid bilayer (volume fraction of 0.03 in the bilayer) leads to an increased order in the acyl chain close to the bilayer interface. The findings are discussed in relation to biological systems and lipid formulations.