Photoneutron cross sections for 59Co : Systematic uncertainties of data from various experiments

NASA Astrophysics Data System (ADS)

Varlamov, V. V.; Davydov, A. I.; Ishkhanov, B. S.

2017-09-01

Data on partial photoneutron reaction cross sections (γ ,1n), (γ ,2n), and (γ ,3n) for 59Co obtained in two experiments carried out at Livermore (USA) were analyzed. The sources of radiation in both experiments were the monoenergetic photon beams from the annihilation in flight of relativistic positrons. The total yield was sorted by the neutron multiplicity, taking into account the difference in the neutron energy spectra for different multiplicity. The two quoted studies differ in the method of determining the neutron. Significant systematic disagreements between the results of the two experiments exist. They are considered to be caused by large systematic uncertainties in partial cross sections, since they do not satisfy physical criteria for reliability of the data. To obtain reliable cross sections of partial and total photoneutron reactions a new method combining experimental data and theoretical evaluation was used. It is based on the experimental neutron yield cross section which is rather independent of neutron multiplicity and the transitional neutron multiplicity functions of the combined photonucleon reaction model (CPNRM). The model transitional multiplicity functions were used for the decomposition of the neutron yield cross section into the contributions of partial reactions. The results of the new evaluation noticeably differ from the partial cross sections obtained in the two experimental studies are under discussion.

Detecting and removing multiplicative spatial bias in high-throughput screening technologies.

PubMed

Caraus, Iurie; Mazoure, Bogdan; Nadon, Robert; Makarenkov, Vladimir

2017-10-15

Considerable attention has been paid recently to improve data quality in high-throughput screening (HTS) and high-content screening (HCS) technologies widely used in drug development and chemical toxicity research. However, several environmentally- and procedurally-induced spatial biases in experimental HTS and HCS screens decrease measurement accuracy, leading to increased numbers of false positives and false negatives in hit selection. Although effective bias correction methods and software have been developed over the past decades, almost all of these tools have been designed to reduce the effect of additive bias only. Here, we address the case of multiplicative spatial bias. We introduce three new statistical methods meant to reduce multiplicative spatial bias in screening technologies. We assess the performance of the methods with synthetic and real data affected by multiplicative spatial bias, including comparisons with current bias correction methods. We also describe a wider data correction protocol that integrates methods for removing both assay and plate-specific spatial biases, which can be either additive or multiplicative. The methods for removing multiplicative spatial bias and the data correction protocol are effective in detecting and cleaning experimental data generated by screening technologies. As our protocol is of a general nature, it can be used by researchers analyzing current or next-generation high-throughput screens. The AssayCorrector program, implemented in R, is available on CRAN. makarenkov.vladimir@uqam.ca. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Effects of Multiple Intelligences Activities on Writing Skill Development in an EFL Context

ERIC Educational Resources Information Center

Gündüz, Zennure Elgün; Ünal, Ismail Dogan

2016-01-01

This study aims at exploring the effects of multiple intelligences activities versus traditional method on English writing development of the sixth grade students in Turkey. A quasi-experimental research method with a pre-test post-test design was applied. The participants were 50 sixth grade students at a state school in Ardahan in Turkey. The…

Online two-stage association method for robust multiple people tracking

NASA Astrophysics Data System (ADS)

Lv, Jingqin; Fang, Jiangxiong; Yang, Jie

2011-07-01

Robust multiple people tracking is very important for many applications. It is a challenging problem due to occlusion and interaction in crowded scenarios. This paper proposes an online two-stage association method for robust multiple people tracking. In the first stage, short tracklets generated by linking people detection responses grow longer by particle filter based tracking, with detection confidence embedded into the observation model. And, an examining scheme runs at each frame for the reliability of tracking. In the second stage, multiple people tracking is achieved by linking tracklets to generate trajectories. An online tracklet association method is proposed to solve the linking problem, which allows applications in time-critical scenarios. This method is evaluated on the popular CAVIAR dataset. The experimental results show that our two-stage method is robust.

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

PubMed

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

1999-10-01

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

Demodulation of moire fringes in digital holographic interferometry using an extended Kalman filter.

PubMed

Ramaiah, Jagadesh; Rastogi, Pramod; Rajshekhar, Gannavarpu

2018-03-10

This paper presents a method for extracting multiple phases from a single moire fringe pattern in digital holographic interferometry. The method relies on component separation using singular value decomposition and an extended Kalman filter for demodulating the moire fringes. The Kalman filter is applied by modeling the interference field locally as a multi-component polynomial phase signal and extracting the associated multiple polynomial coefficients using the state space approach. In addition to phase, the corresponding multiple phase derivatives can be simultaneously extracted using the proposed method. The applicability of the proposed method is demonstrated using simulation and experimental results.

Experimental and CFD evidence of multiple solutions in a naturally ventilated building.

PubMed

Heiselberg, P; Li, Y; Andersen, A; Bjerre, M; Chen, Z

2004-02-01

This paper considers the existence of multiple solutions to natural ventilation of a simple one-zone building, driven by combined thermal and opposing wind forces. The present analysis is an extension of an earlier analytical study of natural ventilation in a fully mixed building, and includes the effect of thermal stratification. Both computational and experimental investigations were carried out in parallel with an analytical investigation. When flow is dominated by thermal buoyancy, it was found experimentally that there is thermal stratification. When the flow is wind-dominated, the room is fully mixed. Results from all three methods have shown that the hysteresis phenomena exist. Under certain conditions, two different stable steady-state solutions are found to exist by all three methods for the same set of parameters. As shown by both the computational fluid dynamics (CFD) and experimental results, one of the solutions can shift to another when there is a sufficient perturbation. These results have probably provided the strongest evidence so far for the conclusion that multiple states exist in natural ventilation of simple buildings. Different initial conditions in the CFD simulations led to different solutions, suggesting that caution must be taken when adopting the commonly used 'zero initialization'.

Generating multiple orbital angular momentum vortex beams using a metasurface in radio frequency domain

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

Yu, Shixing; Li, Long, E-mail: lilong@mail.xidian.edu.cn, E-mail: gmshi@xidian.edu.cn; Shi, Guangming, E-mail: lilong@mail.xidian.edu.cn, E-mail: gmshi@xidian.edu.cn

In this paper, an electromagnetic metasurface is designed, fabricated, and experimentally demonstrated to generate multiple orbital angular momentum (OAM) vortex beams in radio frequency domain. Theoretical formula of compensated phase-shift distribution is deduced and used to design the metasurface to produce multiple vortex radio waves in different directions with different OAM modes. The prototype of a practical configuration of square-patch metasurface is designed, fabricated, and measured to validate the theoretical analysis at 5.8 GHz. The simulated and experimental results verify that multiple OAM vortex waves can be simultaneously generated by using a single electromagnetic metasurface. The proposed method paves an effectivemore » way to generate multiple OAM vortex waves in radio and microwave wireless communication applications.« less

Analysing and correcting the differences between multi-source and multi-scale spatial remote sensing observations.

PubMed

Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation.

Analysing and Correcting the Differences between Multi-Source and Multi-Scale Spatial Remote Sensing Observations

PubMed Central

Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation. PMID:25405760

3D mapping of turbulence: a laboratory experiment

NASA Astrophysics Data System (ADS)

Le Louarn, Miska; Dainty, Christopher; Paterson, Carl; Tallon, Michel

2000-07-01

In this paper, we present the first experimental results of the 3D mapping method. 3D mapping of turbulence is a method to remove the cone effect with multiple laser guide stars and multiple deformable mirrors. A laboratory experiment was realized to verify the theoretical predictions. The setup consisted of two turbulent phase screens (made with liquid crystal devices) and a Shack-Hartmann wavefront sensor. We describe the interaction matrix involved in reconstructing Zernike commands for multiple deformable mirror from the slope measurements made from laser guide stars. It is shown that mirror commands can indeed be reconstructed with the 3D mapping method. Limiting factors of the method, brought to light by this experiment are discussed.

Strain preservation of experimental animals: vitrification of two-cell stage embryos for multiple mouse strains.

PubMed

Eto, Tomoo; Takahashi, Riichi; Kamisako, Tsutomu

2015-04-01

Strain preservation of experimental animals is crucial for experimental reproducibility. Maintaining complete animal strains, however, is costly and there is a risk for genetic mutations as well as complete loss due to disasters or illness. Therefore, the development of effective vitrification techniques for cryopreservation of multiple experimental animal strains is important. We examined whether a vitrification method using cryoprotectant solutions, P10 and PEPeS, is suitable for preservation of multiple inbred and outbred mouse strains. First, we investigated whether our vitrification method using cryoprotectant solutions was suitable for two-cell stage mouse embryos. In vitro development of embryos exposed to the cryoprotectant solutions was similar to that of fresh controls. Further, the survival rate of the vitrified embryos was extremely high (98.1%). Next, we collected and vitrified two-cell stage embryos of 14 mouse strains. The average number of embryos obtained from one female was 7.3-33.3. The survival rate of vitrified embryos ranged from 92.8% to 99.1%, with no significant differences among mouse strains. In vivo development did not differ significantly between fresh controls and vitrified embryos of each strain. For strain preservation using cryopreserved embryos, two offspring for inbred lines and one offspring for outbred lines must be produced from two-cell stage embryos collected from one female. The expected number of surviving fetuses obtained from embryos collected from one female of either the inbred or outbred strains ranged from 2.9 to 19.5. The findings of the present study indicated that this vitrification method is suitable for strain preservation of multiple mouse strains. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Double-multiple streamtube model for studying vertical-axis wind turbines

NASA Astrophysics Data System (ADS)

Paraschivoiu, Ion

1988-08-01

This work describes the present state-of-the-art in double-multiple streamtube method for modeling the Darrieus-type vertical-axis wind turbine (VAWT). Comparisons of the analytical results with the other predictions and available experimental data show a good agreement. This method, which incorporates dynamic-stall and secondary effects, can be used for generating a suitable aerodynamic-load model for structural design analysis of the Darrieus rotor.

Inkjet printing-based volumetric display projecting multiple full-colour 2D patterns

NASA Astrophysics Data System (ADS)

Hirayama, Ryuji; Suzuki, Tomotaka; Shimobaba, Tomoyoshi; Shiraki, Atsushi; Naruse, Makoto; Nakayama, Hirotaka; Kakue, Takashi; Ito, Tomoyoshi

2017-04-01

In this study, a method to construct a full-colour volumetric display is presented using a commercially available inkjet printer. Photoreactive luminescence materials are minutely and automatically printed as the volume elements, and volumetric displays are constructed with high resolution using easy-to-fabricate means that exploit inkjet printing technologies. The results experimentally demonstrate the first prototype of an inkjet printing-based volumetric display composed of multiple layers of transparent films that yield a full-colour three-dimensional (3D) image. Moreover, we propose a design algorithm with 3D structures that provide multiple different 2D full-colour patterns when viewed from different directions and experimentally demonstrate prototypes. It is considered that these types of 3D volumetric structures and their fabrication methods based on widely deployed existing printing technologies can be utilised as novel information display devices and systems, including digital signage, media art, entertainment and security.

Alternating treatments design: one strategy for comparing the effects of two treatments in a single subject.

PubMed Central

Barlow, D H; Hayes, S C

1979-01-01

A little used and often confused design, capable of comparing two treatments within a single subject, has been termed, variously, a multielement baseline design, a multiple schedule design, and a randomization design. The background of these terms is reviewed, and a new, more descriptive term, Alternating Treatments Design, is proposed. Critical differences between this design and a Simultaneous Treatment Design are outlined, and experimental questions answerable by each design are noted. Potential problems with multiple treatment interference in this procedure are divided into sequential confounding, carryover effects, and alternation effects and the importance of these issues vis-a-vis other single-case experimental designs is considered. Methods of minimizing multiple treatment interference as well as methods of studying these effects are outlined. Finally, appropriate uses of Alternating Treatments Designs are described and discussed in the context of recent examples. PMID:489478

Detection of multiple thin surface cracks using vibrothermography with low-power piezoceramic-based ultrasonic actuator—a numerical study with experimental verification

NASA Astrophysics Data System (ADS)

Parvasi, Seyed Mohammad; Xu, Changhang; Kong, Qingzhao; Song, Gangbing

2016-05-01

Ultrasonic vibrations in cracked structures generate heat at the location of defects mainly due to frictional rubbing and viscoelastic losses at the defects. Vibrothermography is an effective nondestructive evaluation method which uses infrared imaging (IR) techniques to locate defects such as cracks and delaminations by detecting the heat generated at the defects. In this paper a coupled thermo-electro-mechanical analysis with the use of implicit finite element method was used to simulate a low power (10 W) piezoceramic-based ultrasonic actuator and the corresponding heat generation in a metallic plate with multiple surface cracks. Numerical results show that the finite element software Abaqus can be used to simultaneously model the electrical properties of the actuator, the ultrasonic waves propagating within the plate, as well as the thermal properties of the plate. Obtained numerical results demonstrate the ability of these low power transducers in detecting multiple cracks in the simulated aluminum plate. The validity of the numerical simulations was verified through experimental studies on a physical aluminum plate with multiple surface cracks while the same low power piezoceramic stack actuator was used to excite the plate and generate heat at the cracks. An excellent qualitative agreement exists between the experimental results and the numerical simulation’s results.

A Method for Simulating Sedimentation of Fish Eggs to Generate Biological Effects Data for Assessing Dredging Impacts

DTIC Science & Technology

2017-03-01

activities, as well as other causes of sedimentation (e.g., agricultural practices, storm events, tidal flows). BACKGROUND AND PROBLEM: Many naturally...effects originating from many sources (e.g., agriculture , storm event, tidal flows) on multiple aquatic species and life stages. Multiple experimental

A support vector machine based control application to the experimental three-tank system.

PubMed

Iplikci, Serdar

2010-07-01

This paper presents a support vector machine (SVM) approach to generalized predictive control (GPC) of multiple-input multiple-output (MIMO) nonlinear systems. The possession of higher generalization potential and at the same time avoidance of getting stuck into the local minima have motivated us to employ SVM algorithms for modeling MIMO systems. Based on the SVM model, detailed and compact formulations for calculating predictions and gradient information, which are used in the computation of the optimal control action, are given in the paper. The proposed MIMO SVM-based GPC method has been verified on an experimental three-tank liquid level control system. Experimental results have shown that the proposed method can handle the control task successfully for different reference trajectories. Moreover, a detailed discussion on data gathering, model selection and effects of the control parameters have been given in this paper. 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Effects of Writing Instruction on Kindergarten Students' Writing Achievement: An Experimental Study

ERIC Educational Resources Information Center

Jones, Cindy D'On

2015-01-01

This full-year experimental study examined how methods of writing instruction contribute to kindergarten students' acquisition of foundational and compositional early writing skills. Multiple regression with cluster analysis was used to compare 3 writing instructional groups: an interactive writing group, a writing workshop group, and a…

Multiple Drafts of Experimental Laboratory Reports.

ERIC Educational Resources Information Center

Sanford, James F.

Students could gain considerable insight into the philosophy and methods of scientific experimentation if instructors adopted procedures based on an understanding of and respect for writing as a process. Laboratory courses in psychology offer such an opportunity. These courses usually involve a heavy workload for both students and faculty, for, in…

Correlative multiple porosimetries for reservoir sandstones with adoption of a new reference-sample-guided computed-tomographic method.

PubMed

Jin, Jae Hwa; Kim, Junho; Lee, Jeong-Yil; Oh, Young Min

2016-07-22

One of the main interests in petroleum geology and reservoir engineering is to quantify the porosity of reservoir beds as accurately as possible. A variety of direct measurements, including methods of mercury intrusion, helium injection and petrographic image analysis, have been developed; however, their application frequently yields equivocal results because these methods are different in theoretical bases, means of measurement, and causes of measurement errors. Here, we present a set of porosities measured in Berea Sandstone samples by the multiple methods, in particular with adoption of a new method using computed tomography and reference samples. The multiple porosimetric data show a marked correlativeness among different methods, suggesting that these methods are compatible with each other. The new method of reference-sample-guided computed tomography is more effective than the previous methods when the accompanied merits such as experimental conveniences are taken into account.

Correlative multiple porosimetries for reservoir sandstones with adoption of a new reference-sample-guided computed-tomographic method

PubMed Central

Jin, Jae Hwa; Kim, Junho; Lee, Jeong-Yil; Oh, Young Min

2016-01-01

One of the main interests in petroleum geology and reservoir engineering is to quantify the porosity of reservoir beds as accurately as possible. A variety of direct measurements, including methods of mercury intrusion, helium injection and petrographic image analysis, have been developed; however, their application frequently yields equivocal results because these methods are different in theoretical bases, means of measurement, and causes of measurement errors. Here, we present a set of porosities measured in Berea Sandstone samples by the multiple methods, in particular with adoption of a new method using computed tomography and reference samples. The multiple porosimetric data show a marked correlativeness among different methods, suggesting that these methods are compatible with each other. The new method of reference-sample-guided computed tomography is more effective than the previous methods when the accompanied merits such as experimental conveniences are taken into account. PMID:27445105

Determination of effective atomic number of biomedical samples using Gamma ray back-scattering

NASA Astrophysics Data System (ADS)

Singh, Inderjeet; Singh, Bhajan; Sandhu, B. S.; Sabharwal, Arvind D.

2018-05-01

The study of effective atomic number of biomedical sample has been carried out by using a non-destructive multiple back-scattering technique. Also radiation characterization method is used to compare the tissue equivalent material as human tissue. Response function of 3″ × 3″ NaI(Tl) scintillation detector is implemented on recorded pulse-height distribution to boost the counts under the photo-peak and help to reduce the uncertainty in the experimental result. Monte Carlo calculation for multiple back-scattered events supports the reported experimental work.

Automated optimal coordination of multiple-DOF neuromuscular actions in feedforward neuroprostheses.

PubMed

Lujan, J Luis; Crago, Patrick E

2009-01-01

This paper describes a new method for designing feedforward controllers for multiple-muscle, multiple-DOF, motor system neural prostheses. The design process is based on experimental measurement of the forward input/output properties of the neuromechanical system and numerical optimization of stimulation patterns to meet muscle coactivation criteria, thus resolving the muscle redundancy (i.e., overcontrol) and the coupled DOF problems inherent in neuromechanical systems. We designed feedforward controllers to control the isometric forces at the tip of the thumb in two directions during stimulation of three thumb muscles as a model system. We tested the method experimentally in ten able-bodied individuals and one patient with spinal cord injury. Good control of isometric force in both DOFs was observed, with rms errors less than 10% of the force range in seven experiments and statistically significant correlations between the actual and target forces in all ten experiments. Systematic bias and slope errors were observed in a few experiments, likely due to the neuromuscular fatigue. Overall, the tests demonstrated the ability of a general design approach to satisfy both control and coactivation criteria in multiple-muscle, multiple-axis neuromechanical systems, which is applicable to a wide range of neuromechanical systems and stimulation electrodes.

Integrated optics to improve resolution on multiple configuration

NASA Astrophysics Data System (ADS)

Liu, Hua; Ding, Quanxin; Guo, Chunjie; Zhou, Liwei

2015-04-01

Inspired to in order to reveal the structure to improve imaging resolution, further technical requirement is proposed in some areas of the function and influence on the development of multiple configuration. To breakthrough diffraction limit, smart structures are recommended as the most efficient and economical method, while by used to improve the system performance, especially on signal to noise ratio and resolution. Integrated optics were considered in the selection, with which typical multiple configuration, by use the method of simulation experiment. Methodology can change traditional design concept and to develop the application space. Our calculations using multiple matrix transfer method, also the correlative algorithm and full calculations, show the expected beam shaping through system and, in particular, the experimental results will support our argument, which will be reported in the presentation.

Utilizing the Zero-One Linear Programming Constraints to Draw Multiple Sets of Matched Samples from a Non-Treatment Population as Control Groups for the Quasi-Experimental Design

ERIC Educational Resources Information Center

Li, Yuan H.; Yang, Yu N.; Tompkins, Leroy J.; Modarresi, Shahpar

2005-01-01

The statistical technique, "Zero-One Linear Programming," that has successfully been used to create multiple tests with similar characteristics (e.g., item difficulties, test information and test specifications) in the area of educational measurement, was deemed to be a suitable method for creating multiple sets of matched samples to be…

A simple cage-autonomous method for the maintenance of the barrier status of germ-free mice during experimentation.

PubMed

Hecht, G; Bar-Nathan, C; Milite, G; Alon, I; Moshe, Y; Greenfeld, L; Dotsenko, N; Suez, J; Levy, M; Thaiss, C A; Dafni, H; Elinav, E; Harmelin, A

2014-10-01

The use of germ-free (GF) isolators for microbiome-related research is exponentially increasing, yet limited by its cost, isolator size and potential for trans-contamination. As such, current isolator technology is highly limiting to researchers engaged in short period experiments involving multiple mouse strains and employing a variety of mono-inoculated microorganisms. In this study, we evaluate the use of positive pressure Isocages as a solution for short period studies (days to 2-3 weeks) of experimentation with GF mice at multiple simultaneous conditions. We demonstrate that this new Isocage technology is cost-effective and room-sparing, and enables maintenance of multiple simultaneous groups of GF mice. Using this technology, transferring GF mice from isolators to Isocage racks for experimentation, where they are kept under fully germ-free conditions, enables parallel inoculation with different bacterial strains and simultaneous experimentation with multiple research conditions. Altogether, the new GF Isocage technology enables the expansion of GF capabilities in a safe and cost-effective manner that can facilitate the growth, elaboration and flexibility of microbiome research. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Multiple feature extraction by using simultaneous wavelet transforms

NASA Astrophysics Data System (ADS)

Mazzaferri, Javier; Ledesma, Silvia; Iemmi, Claudio

2003-07-01

We propose here a method to optically perform multiple feature extraction by using wavelet transforms. The method is based on obtaining the optical correlation by means of a Vander Lugt architecture, where the scene and the filter are displayed on spatial light modulators (SLMs). Multiple phase filters containing the information about the features that we are interested in extracting are designed and then displayed on an SLM working in phase mostly mode. We have designed filters to simultaneously detect edges and corners or different characteristic frequencies contained in the input scene. Simulated and experimental results are shown.

Grayscale inhomogeneity correction method for multiple mosaicked electron microscope images

NASA Astrophysics Data System (ADS)

Zhou, Fangxu; Chen, Xi; Sun, Rong; Han, Hua

2018-04-01

Electron microscope image stitching is highly desired to acquire microscopic resolution images of large target scenes in neuroscience. However, the result of multiple Mosaicked electron microscope images may exist severe gray scale inhomogeneity due to the instability of the electron microscope system and registration errors, which degrade the visual effect of the mosaicked EM images and aggravate the difficulty of follow-up treatment, such as automatic object recognition. Consequently, the grayscale correction method for multiple mosaicked electron microscope images is indispensable in these areas. Different from most previous grayscale correction methods, this paper designs a grayscale correction process for multiple EM images which tackles the difficulty of the multiple images monochrome correction and achieves the consistency of grayscale in the overlap regions. We adjust overall grayscale of the mosaicked images with the location and grayscale information of manual selected seed images, and then fuse local overlap regions between adjacent images using Poisson image editing. Experimental result demonstrates the effectiveness of our proposed method.

Influence of phase inversion on the formation and stability of one-step multiple emulsions.

PubMed

Morais, Jacqueline M; Rocha-Filho, Pedro A; Burgess, Diane J

2009-07-21

A novel method of preparation of water-in-oil-in-micelle-containing water (W/O/W(m)) multiple emulsions using the one-step emulsification method is reported. These multiple emulsions were normal (not temporary) and stable over a 60 day test period. Previously, reported multiple emulsion by the one-step method were abnormal systems that formed at the inversion point of simple emulsion (where there is an incompatibility in the Ostwald and Bancroft theories, and typically these are O/W/O systems). Pseudoternary phase diagrams and bidimensional process-composition (phase inversion) maps were constructed to assist in process and composition optimization. The surfactants used were PEG40 hydrogenated castor oil and sorbitan oleate, and mineral and vegetables oils were investigated. Physicochemical characterization studies showed experimentally, for the first time, the significance of the ultralow surface tension point on multiple emulsion formation by one-step via phase inversion processes. Although the significance of ultralow surface tension has been speculated previously, to the best of our knowledge, this is the first experimental confirmation. The multiple emulsion system reported here was dependent not only upon the emulsification temperature, but also upon the component ratios, therefore both the emulsion phase inversion and the phase inversion temperature were considered to fully explain their formation. Accordingly, it is hypothesized that the formation of these normal multiple emulsions is not a result of a temporary incompatibility (at the inversion point) during simple emulsion preparation, as previously reported. Rather, these normal W/O/W(m) emulsions are a result of the simultaneous occurrence of catastrophic and transitional phase inversion processes. The formation of the primary emulsions (W/O) is in accordance with the Ostwald theory ,and the formation of the multiple emulsions (W/O/W(m)) is in agreement with the Bancroft theory.

Multiple Representations-Based Face Sketch-Photo Synthesis.

PubMed

Peng, Chunlei; Gao, Xinbo; Wang, Nannan; Tao, Dacheng; Li, Xuelong; Li, Jie

2016-11-01

Face sketch-photo synthesis plays an important role in law enforcement and digital entertainment. Most of the existing methods only use pixel intensities as the feature. Since face images can be described using features from multiple aspects, this paper presents a novel multiple representations-based face sketch-photo-synthesis method that adaptively combines multiple representations to represent an image patch. In particular, it combines multiple features from face images processed using multiple filters and deploys Markov networks to exploit the interacting relationships between the neighboring image patches. The proposed framework could be solved using an alternating optimization strategy and it normally converges in only five outer iterations in the experiments. Our experimental results on the Chinese University of Hong Kong (CUHK) face sketch database, celebrity photos, CUHK Face Sketch FERET Database, IIIT-D Viewed Sketch Database, and forensic sketches demonstrate the effectiveness of our method for face sketch-photo synthesis. In addition, cross-database and database-dependent style-synthesis evaluations demonstrate the generalizability of this novel method and suggest promising solutions for face identification in forensic science.

Multifractal characteristics of multiparticle production in heavy-ion collisions at SPS energies

NASA Astrophysics Data System (ADS)

Khan, Shaista; Ahmad, Shakeel

Entropy, dimensions and other multifractal characteristics of multiplicity distributions of relativistic charged hadrons produced in ion-ion collisions at SPS energies are investigated. The analysis of the experimental data is carried out in terms of phase space bin-size dependence of multiplicity distributions following the Takagi’s approach. Yet another method is also followed to study the multifractality which, is not related to the bin-width and (or) the detector resolution, rather involves multiplicity distribution of charged particles in full phase space in terms of information entropy and its generalization, Rényi’s order-q information entropy. The findings reveal the presence of multifractal structure — a remarkable property of the fluctuations. Nearly constant values of multifractal specific heat “c” estimated by the two different methods of analysis followed indicate that the parameter “c” may be used as a universal characteristic of the particle production in high energy collisions. The results obtained from the analysis of the experimental data agree well with the predictions of Monte Carlo model AMPT.

Modeling of Receptor Tyrosine Kinase Signaling: Computational and Experimental Protocols.

PubMed

Fey, Dirk; Aksamitiene, Edita; Kiyatkin, Anatoly; Kholodenko, Boris N

2017-01-01

The advent of systems biology has convincingly demonstrated that the integration of experiments and dynamic modelling is a powerful approach to understand the cellular network biology. Here we present experimental and computational protocols that are necessary for applying this integrative approach to the quantitative studies of receptor tyrosine kinase (RTK) signaling networks. Signaling by RTKs controls multiple cellular processes, including the regulation of cell survival, motility, proliferation, differentiation, glucose metabolism, and apoptosis. We describe methods of model building and training on experimentally obtained quantitative datasets, as well as experimental methods of obtaining quantitative dose-response and temporal dependencies of protein phosphorylation and activities. The presented methods make possible (1) both the fine-grained modeling of complex signaling dynamics and identification of salient, course-grained network structures (such as feedback loops) that bring about intricate dynamics, and (2) experimental validation of dynamic models.

Multiplicative noise removal via a learned dictionary.

PubMed

Huang, Yu-Mei; Moisan, Lionel; Ng, Michael K; Zeng, Tieyong

2012-11-01

Multiplicative noise removal is a challenging image processing problem, and most existing methods are based on the maximum a posteriori formulation and the logarithmic transformation of multiplicative denoising problems into additive denoising problems. Sparse representations of images have shown to be efficient approaches for image recovery. Following this idea, in this paper, we propose to learn a dictionary from the logarithmic transformed image, and then to use it in a variational model built for noise removal. Extensive experimental results suggest that in terms of visual quality, peak signal-to-noise ratio, and mean absolute deviation error, the proposed algorithm outperforms state-of-the-art methods.

Multiple targets detection method in detection of UWB through-wall radar

NASA Astrophysics Data System (ADS)

Yang, Xiuwei; Yang, Chuanfa; Zhao, Xingwen; Tian, Xianzhong

2017-11-01

In this paper, the problems and difficulties encountered in the detection of multiple moving targets by UWB radar are analyzed. The experimental environment and the penetrating radar system are established. An adaptive threshold method based on local area is proposed to effectively filter out clutter interference The objective of the moving target is analyzed, and the false target is further filtered out by extracting the target feature. Based on the correlation between the targets, the target matching algorithm is proposed to improve the detection accuracy. Finally, the effectiveness of the above method is verified by practical experiment.

Low-cost extrapolation method for maximal LTE radio base station exposure estimation: test and validation.

PubMed

Verloock, Leen; Joseph, Wout; Gati, Azeddine; Varsier, Nadège; Flach, Björn; Wiart, Joe; Martens, Luc

2013-06-01

An experimental validation of a low-cost method for extrapolation and estimation of the maximal electromagnetic-field exposure from long-term evolution (LTE) radio base station installations are presented. No knowledge on downlink band occupation or service characteristics is required for the low-cost method. The method is applicable in situ. It only requires a basic spectrum analyser with appropriate field probes without the need of expensive dedicated LTE decoders. The method is validated both in laboratory and in situ, for a single-input single-output antenna LTE system and a 2×2 multiple-input multiple-output system, with low deviations in comparison with signals measured using dedicated LTE decoders.

Experimental Investigation on the Detection of Multiple Surface Cracks Using Vibrothermography with a Low-Power Piezoceramic Actuator.

PubMed

Xu, Changhang; Xie, Jing; Zhang, Wuyang; Kong, Qingzhao; Chen, Guoming; Song, Gangbing

2017-11-23

Vibrothermography often employs a high-power actuator to generate heat on a specimen to reveal damage, however, the high-power actuator brings inconvenience to the application and possibly introduces additional damage to the inspected objects. This study uses a low-power piezoceramic transducer as the actuator of vibrothermography and explores its ability to detect multiple surface cracks in a metal part. Experiments were conducted on a thin aluminum beam with three cracks in different orientations. Detailed analyses of both thermograms and temperature data are presented to validate the proposed vibrothermography method. To further investigate the performance of the proposed vibrothermography method, we experimentally studied the effects of several critical factors, including the amplitude of excitation signal, specimen constraints, relative position between the transducer and cracks (the transducer is mounted on the same or the opposite side with the cracks). The results demonstrate that all cracks can be detected conveniently and simultaneously by using the proposed low-power vibrothermography. We also found that the magnitude of excitation signal and the specimen constraints have a great influence on detection results. Combined with effective data processing methods, such as Fourier transformation employed in this study, the proposed method provides a promising potential to detect multiple cracks on a metal surface in a safe and effective manner.

Teaching Composition Skills with Weekly Multiple Choice Tests in Lieu of Theme Writing. Final Report.

ERIC Educational Resources Information Center

Scannell, Dale P.; Haugh, Oscar M.

The purpose of the study was to compare the effectiveness with which composition skills could be taught by the traditional theme-assignment approach and by an experimental method using weekly multiple-choice composition tests in lieu of theme writing. The weekly tests were based on original but typical first-draft compositions and covered problems…

Experimental design and quantitative analysis of microbial community multiomics.

PubMed

Mallick, Himel; Ma, Siyuan; Franzosa, Eric A; Vatanen, Tommi; Morgan, Xochitl C; Huttenhower, Curtis

2017-11-30

Studies of the microbiome have become increasingly sophisticated, and multiple sequence-based, molecular methods as well as culture-based methods exist for population-scale microbiome profiles. To link the resulting host and microbial data types to human health, several experimental design considerations, data analysis challenges, and statistical epidemiological approaches must be addressed. Here, we survey current best practices for experimental design in microbiome molecular epidemiology, including technologies for generating, analyzing, and integrating microbiome multiomics data. We highlight studies that have identified molecular bioactives that influence human health, and we suggest steps for scaling translational microbiome research to high-throughput target discovery across large populations.

Measurement and analysis of workload effects on fault latency in real-time systems

NASA Technical Reports Server (NTRS)

Woodbury, Michael H.; Shin, Kang G.

1990-01-01

The authors demonstrate the need to address fault latency in highly reliable real-time control computer systems. It is noted that the effectiveness of all known recovery mechanisms is greatly reduced in the presence of multiple latent faults. The presence of multiple latent faults increases the possibility of multiple errors, which could result in coverage failure. The authors present experimental evidence indicating that the duration of fault latency is dependent on workload. A synthetic workload generator is used to vary the workload, and a hardware fault injector is applied to inject transient faults of varying durations. This method makes it possible to derive the distribution of fault latency duration. Experimental results obtained from the fault-tolerant multiprocessor at the NASA Airlab are presented and discussed.

Experimental characterization of quantum correlated triple beams generated by cascaded four-wave mixing processes

NASA Astrophysics Data System (ADS)

Qin, Zhongzhong; Cao, Leiming; Jing, Jietai

2015-05-01

Quantum correlations and entanglement shared among multiple modes are fundamental ingredients of most continuous-variable quantum technologies. Recently, a method used to generate multiple quantum correlated beams using cascaded four-wave mixing (FWM) processes was theoretically proposed and experimentally realized by our group [Z. Qin et al., Phys. Rev. Lett. 113, 023602 (2014)]. Our study of triple-beam quantum correlation paves the way to showing the tripartite entanglement in our system. Our system also promises to find applications in quantum information and precision measurement such as the controlled quantum communications, the generation of multiple quantum correlated images, and the realization of a multiport nonlinear interferometer. For its applications, the degree of quantum correlation is a crucial figure of merit. In this letter, we experimentally study how various parameters, such as the cell temperatures, one-photon, and two-photon detunings, influence the degree of quantum correlation between the triple beams generated from the cascaded two-FWM configuration.

Experimental characterization of quantum correlated triple beams generated by cascaded four-wave mixing processes

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

Qin, Zhongzhong; Cao, Leiming; Jing, Jietai, E-mail: jtjing@phy.ecnu.edu.cn

2015-05-25

Quantum correlations and entanglement shared among multiple modes are fundamental ingredients of most continuous-variable quantum technologies. Recently, a method used to generate multiple quantum correlated beams using cascaded four-wave mixing (FWM) processes was theoretically proposed and experimentally realized by our group [Z. Qin et al., Phys. Rev. Lett. 113, 023602 (2014)]. Our study of triple-beam quantum correlation paves the way to showing the tripartite entanglement in our system. Our system also promises to find applications in quantum information and precision measurement such as the controlled quantum communications, the generation of multiple quantum correlated images, and the realization of a multiportmore » nonlinear interferometer. For its applications, the degree of quantum correlation is a crucial figure of merit. In this letter, we experimentally study how various parameters, such as the cell temperatures, one-photon, and two-photon detunings, influence the degree of quantum correlation between the triple beams generated from the cascaded two-FWM configuration.« less

Effect of the cooling suit method applied to individuals with multiple sclerosis on fatigue and activities of daily living.

PubMed

Özkan Tuncay, Fatma; Mollaoğlu, Mukadder

2017-12-01

To determine the effects of cooling suit on fatigue and activities of daily living of individuals with multiple sclerosis. Fatigue is one of the most common symptoms in people with multiple sclerosis and adversely affects their activities of daily living. Studies evaluating fatigue associated with multiple sclerosis have reported that most of the fatigue cases are related to the increase in body temperature and that cooling therapy is effective in coping with fatigue. This study used a two sample, control group design. The study sample comprised 75 individuals who met the inclusion criteria. Data were collected with study forms. After the study data were collected, cooling suit treatment was administered to the experimental group. During home visits paid at the fourth and eighth weeks after the intervention, the aforementioned scales were re-administered to the participants in the experimental and control groups. The analyses performed demonstrated that the severity levels of fatigue experienced by the participants in the experimental group wearing cooling suit decreased. The experimental group also exhibited a significant improvement in the participants' levels of independence in activities of daily living. The cooling suit worn by individuals with multiple sclerosis was determined to significantly improve the participants' levels of fatigue and independence in activities of daily living. The cooling suit therapy was found to be an effective intervention for the debilitating fatigue suffered by many multiple sclerosis patients, thus significantly improving their level of independence in activities of daily living. © 2017 John Wiley & Sons Ltd.

Fault diagnosis of sensor networked structures with multiple faults using a virtual beam based approach

NASA Astrophysics Data System (ADS)

Wang, H.; Jing, X. J.

2017-07-01

This paper presents a virtual beam based approach suitable for conducting diagnosis of multiple faults in complex structures with limited prior knowledge of the faults involved. The "virtual beam", a recently-proposed concept for fault detection in complex structures, is applied, which consists of a chain of sensors representing a vibration energy transmission path embedded in the complex structure. Statistical tests and adaptive threshold are particularly adopted for fault detection due to limited prior knowledge of normal operational conditions and fault conditions. To isolate the multiple faults within a specific structure or substructure of a more complex one, a 'biased running' strategy is developed and embedded within the bacterial-based optimization method to construct effective virtual beams and thus to improve the accuracy of localization. The proposed method is easy and efficient to implement for multiple fault localization with limited prior knowledge of normal conditions and faults. With extensive experimental results, it is validated that the proposed method can localize both single fault and multiple faults more effectively than the classical trust index subtract on negative add on positive (TI-SNAP) method.

A Hierarchical Modeling Approach to Data Analysis and Study Design in a Multi-Site Experimental fMRI Study

ERIC Educational Resources Information Center

Zhou, Bo; Konstorum, Anna; Duong, Thao; Tieu, Kinh H.; Wells, William M.; Brown, Gregory G.; Stern, Hal S.; Shahbaba, Babak

2013-01-01

We propose a hierarchical Bayesian model for analyzing multi-site experimental fMRI studies. Our method takes the hierarchical structure of the data (subjects are nested within sites, and there are multiple observations per subject) into account and allows for modeling between-site variation. Using posterior predictive model checking and model…

The reliability of photoneutron cross sections for 90,91,92,94Zr

NASA Astrophysics Data System (ADS)

Varlamov, V. V.; Davydov, A. I.; Ishkhanov, B. S.; Orlin, V. N.

2018-05-01

Data on partial photoneutron reaction cross sections (γ,1n) and (γ,2n) for 90,91,92,94Zr obtained at Livermore (USA) and for 90Zr obtained at Saclay (France) were analyzed. Experimental data were obtained using quasimonoenergetic photon beams from the annihilation in flight of relativistic positrons. The method of photoneutron multiplicity sorting based on the neutron energy measuring was used to separate partial reactions. The research carried out is based on the objective of using the physical criteria of data reliability. The large systematic uncertainties were found in partial cross sections, since they do not satisfy those criteria. To obtain the reliable cross sections of the partial (γ,1n) and (γ,2n) and total (γ,1n) + (γ,2n) reactions on 90,91,92,94Zr and (γ,3n) reaction on 94Zr, the experimental-theoretical method was used. It is based on the experimental data for neutron yield cross section rather independent from the neutron multiplicity and theoretical equations of the combined photonucleon reaction model (CPNRM). Newly evaluated data are compared with experimental ones. The reasons of noticeable disagreements between those are discussed.

Multimodal Spatial Calibration for Accurately Registering EEG Sensor Positions

PubMed Central

Chen, Shengyong; Xiao, Gang; Li, Xiaoli

2014-01-01

This paper proposes a fast and accurate calibration method to calibrate multiple multimodal sensors using a novel photogrammetry system for fast localization of EEG sensors. The EEG sensors are placed on human head and multimodal sensors are installed around the head to simultaneously obtain all EEG sensor positions. A multiple views' calibration process is implemented to obtain the transformations of multiple views. We first develop an efficient local repair algorithm to improve the depth map, and then a special calibration body is designed. Based on them, accurate and robust calibration results can be achieved. We evaluate the proposed method by corners of a chessboard calibration plate. Experimental results demonstrate that the proposed method can achieve good performance, which can be further applied to EEG source localization applications on human brain. PMID:24803954

Regularized Embedded Multiple Kernel Dimensionality Reduction for Mine Signal Processing.

PubMed

Li, Shuang; Liu, Bing; Zhang, Chen

2016-01-01

Traditional multiple kernel dimensionality reduction models are generally based on graph embedding and manifold assumption. But such assumption might be invalid for some high-dimensional or sparse data due to the curse of dimensionality, which has a negative influence on the performance of multiple kernel learning. In addition, some models might be ill-posed if the rank of matrices in their objective functions was not high enough. To address these issues, we extend the traditional graph embedding framework and propose a novel regularized embedded multiple kernel dimensionality reduction method. Different from the conventional convex relaxation technique, the proposed algorithm directly takes advantage of a binary search and an alternative optimization scheme to obtain optimal solutions efficiently. The experimental results demonstrate the effectiveness of the proposed method for supervised, unsupervised, and semisupervised scenarios.

Determining heterogeneous slip activity on multiple slip systems from single crystal orientation pole figures

DOE PAGES

Pagan, Darren C.; Miller, Matthew P.

2016-09-01

A new experimental method to determine heterogeneity of shear strains associated with crystallographic slip in the bulk of ductile, crystalline materials is outlined. The method quantifies the time resolved evolution of misorientation within plastically deforming crystals using single crystal orientation pole figures (SCPFs) measured in-situ with X-ray diffraction. A multiplicative decomposition of the crystal kinematics is used to interpret the distributions of lattice plane orientation observed on the SCPFs in terms of heterogeneous slip activity (shear strains) on multiple slip systems. Here, to show the method’s utility, the evolution of heterogeneous slip is quantified in a silicon single crystal plasticallymore » deformed at high temperature at multiple load steps, with slip activity in sub-volumes of the crystal analyzed simultaneously.« less

Nonlinear structural joint model updating based on instantaneous characteristics of dynamic responses

NASA Astrophysics Data System (ADS)

Wang, Zuo-Cai; Xin, Yu; Ren, Wei-Xin

2016-08-01

This paper proposes a new nonlinear joint model updating method for shear type structures based on the instantaneous characteristics of the decomposed structural dynamic responses. To obtain an accurate representation of a nonlinear system's dynamics, the nonlinear joint model is described as the nonlinear spring element with bilinear stiffness. The instantaneous frequencies and amplitudes of the decomposed mono-component are first extracted by the analytical mode decomposition (AMD) method. Then, an objective function based on the residuals of the instantaneous frequencies and amplitudes between the experimental structure and the nonlinear model is created for the nonlinear joint model updating. The optimal values of the nonlinear joint model parameters are obtained by minimizing the objective function using the simulated annealing global optimization method. To validate the effectiveness of the proposed method, a single-story shear type structure subjected to earthquake and harmonic excitations is simulated as a numerical example. Then, a beam structure with multiple local nonlinear elements subjected to earthquake excitation is also simulated. The nonlinear beam structure is updated based on the global and local model using the proposed method. The results show that the proposed local nonlinear model updating method is more effective for structures with multiple local nonlinear elements. Finally, the proposed method is verified by the shake table test of a real high voltage switch structure. The accuracy of the proposed method is quantified both in numerical and experimental applications using the defined error indices. Both the numerical and experimental results have shown that the proposed method can effectively update the nonlinear joint model.

Classifying four-category visual objects using multiple ERP components in single-trial ERP.

PubMed

Qin, Yu; Zhan, Yu; Wang, Changming; Zhang, Jiacai; Yao, Li; Guo, Xiaojuan; Wu, Xia; Hu, Bin

2016-08-01

Object categorization using single-trial electroencephalography (EEG) data measured while participants view images has been studied intensively. In previous studies, multiple event-related potential (ERP) components (e.g., P1, N1, P2, and P3) were used to improve the performance of object categorization of visual stimuli. In this study, we introduce a novel method that uses multiple-kernel support vector machine to fuse multiple ERP component features. We investigate whether fusing the potential complementary information of different ERP components (e.g., P1, N1, P2a, and P2b) can improve the performance of four-category visual object classification in single-trial EEGs. We also compare the classification accuracy of different ERP component fusion methods. Our experimental results indicate that the classification accuracy increases through multiple ERP fusion. Additional comparative analyses indicate that the multiple-kernel fusion method can achieve a mean classification accuracy higher than 72 %, which is substantially better than that achieved with any single ERP component feature (55.07 % for the best single ERP component, N1). We compare the classification results with those of other fusion methods and determine that the accuracy of the multiple-kernel fusion method is 5.47, 4.06, and 16.90 % higher than those of feature concatenation, feature extraction, and decision fusion, respectively. Our study shows that our multiple-kernel fusion method outperforms other fusion methods and thus provides a means to improve the classification performance of single-trial ERPs in brain-computer interface research.

Generalisation of the identity method for determination of high-order moments of multiplicity distributions with a software implementation

NASA Astrophysics Data System (ADS)

Maćkowiak-Pawłowska, Maja; Przybyła, Piotr

2018-05-01

The incomplete particle identification limits the experimentally-available phase space region for identified particle analysis. This problem affects ongoing fluctuation and correlation studies including the search for the critical point of strongly interacting matter performed on SPS and RHIC accelerators. In this paper we provide a procedure to obtain nth order moments of the multiplicity distribution using the identity method, generalising previously published solutions for n=2 and n=3. Moreover, we present an open source software implementation of this computation, called Idhim, that allows one to obtain the true moments of identified particle multiplicity distributions from the measured ones provided the response function of the detector is known.

Multidimensional Methods for the Formulation of Biopharmaceuticals and Vaccines

PubMed Central

Maddux, Nathaniel R.; Joshi, Sangeeta B.; Volkin, David B.; Ralston, John P.; Middaugh, C. Russell

2013-01-01

Determining and preserving the higher order structural integrity and conformational stability of proteins, plasmid DNA and macromolecular complexes such as viruses, virus-like particles and adjuvanted antigens is often a significant barrier to the successful stabilization and formulation of biopharmaceutical drugs and vaccines. These properties typically must be investigated with multiple lower resolution experimental methods, since each technique monitors only a narrow aspect of the overall conformational state of a macromolecular system. This review describes the use of empirical phase diagrams (EPDs) to combine large amounts of data from multiple high-throughput instruments and construct a map of a target macromolecule's physical state as a function of temperature, solvent conditions, and other stress variables. We present a tutorial on the mathematical methodology, an overview of some of the experimental methods typically used, and examples of some of the previous major formulation applications. We also explore novel applications of EPDs including potential new mathematical approaches as well as possible new biopharmaceutical applications such as analytical comparability, chemical stability, and protein dynamics. PMID:21647886

Analysis and prediction of Multiple-Site Damage (MSD) fatigue crack growth

NASA Technical Reports Server (NTRS)

Dawicke, D. S.; Newman, J. C., Jr.

1992-01-01

A technique was developed to calculate the stress intensity factor for multiple interacting cracks. The analysis was verified through comparison with accepted methods of calculating stress intensity factors. The technique was incorporated into a fatigue crack growth prediction model and used to predict the fatigue crack growth life for multiple-site damage (MSD). The analysis was verified through comparison with experiments conducted on uniaxially loaded flat panels with multiple cracks. Configuration with nearly equal and unequal crack distribution were examined. The fatigue crack growth predictions agreed within 20 percent of the experimental lives for all crack configurations considered.

Power-efficient method for IM-DD optical transmission of multiple OFDM signals.

PubMed

Effenberger, Frank; Liu, Xiang

2015-05-18

We propose a power-efficient method for transmitting multiple frequency-division multiplexed (FDM) orthogonal frequency-division multiplexing (OFDM) signals in intensity-modulation direct-detection (IM-DD) optical systems. This method is based on quadratic soft clipping in combination with odd-only channel mapping. We show, both analytically and experimentally, that the proposed approach is capable of improving the power efficiency by about 3 dB as compared to conventional FDM OFDM signals under practical bias conditions, making it a viable solution in applications such as optical fiber-wireless integrated systems where both IM-DD optical transmission and OFDM signaling are important.

Video based object representation and classification using multiple covariance matrices.

PubMed

Zhang, Yurong; Liu, Quan

2017-01-01

Video based object recognition and classification has been widely studied in computer vision and image processing area. One main issue of this task is to develop an effective representation for video. This problem can generally be formulated as image set representation. In this paper, we present a new method called Multiple Covariance Discriminative Learning (MCDL) for image set representation and classification problem. The core idea of MCDL is to represent an image set using multiple covariance matrices with each covariance matrix representing one cluster of images. Firstly, we use the Nonnegative Matrix Factorization (NMF) method to do image clustering within each image set, and then adopt Covariance Discriminative Learning on each cluster (subset) of images. At last, we adopt KLDA and nearest neighborhood classification method for image set classification. Promising experimental results on several datasets show the effectiveness of our MCDL method.

Ultrasound image edge detection based on a novel multiplicative gradient and Canny operator.

PubMed

Zheng, Yinfei; Zhou, Yali; Zhou, Hao; Gong, Xiaohong

2015-07-01

To achieve the fast and accurate segmentation of ultrasound image, a novel edge detection method for speckle noised ultrasound images was proposed, which was based on the traditional Canny and a novel multiplicative gradient operator. The proposed technique combines a new multiplicative gradient operator of non-Newtonian type with the traditional Canny operator to generate the initial edge map, which is subsequently optimized by the following edge tracing step. To verify the proposed method, we compared it with several other edge detection methods that had good robustness to noise, with experiments on the simulated and in vivo medical ultrasound image. Experimental results showed that the proposed algorithm has higher speed for real-time processing, and the edge detection accuracy could be 75% or more. Thus, the proposed method is very suitable for fast and accurate edge detection of medical ultrasound images. © The Author(s) 2014.

Development and applications of optical interferometric micrometrology in the Angstrom and subangstrom range

NASA Technical Reports Server (NTRS)

Lauer, James L.; Abel, Phillip B.

1988-01-01

The characteristics of the scanning tunneling microscope and atomic force microscope (AFM) are briefly reviewed, and optical methods, mainly interferometry, of sufficient resolution to measure AFM deflections are discussed. The methods include optical resonators, laser interferometry, multiple-beam interferometry, and evanescent wave detection. Experimental results using AFM are reviewed.

There is no silver bullet--a guide to low-level data transforms and normalisation methods for microarray data.

PubMed

Kreil, David P; Russell, Roslin R

2005-03-01

To overcome random experimental variation, even for simple screens, data from multiple microarrays have to be combined. There are, however, systematic differences between arrays, and any bias remaining after experimental measures to ensure consistency needs to be controlled for. It is often difficult to make the right choice of data transformation and normalisation methods to achieve this end. In this tutorial paper we review the problem and a selection of solutions, explaining the basic principles behind normalisation procedures and providing guidance for their application.

Monte Carlo simulation of the radiant field produced by a multiple-lamp quartz heating system

NASA Technical Reports Server (NTRS)

Turner, Travis L.

1991-01-01

A method is developed for predicting the radiant heat flux distribution produced by a reflected bank of tungsten-filament tubular-quartz radiant heaters. The method is correlated with experimental results from two cases, one consisting of a single lamp and a flat reflector and the other consisting of a single lamp and a parabolic reflector. The simulation methodology, computer implementation, and experimental procedures are discussed. Analytical refinements necessary for comparison with experiment are discussed and applied to a multilamp, common reflector heating system.

Applying the Multiple Signal Classification Method to Silent Object Detection Using Ambient Noise

NASA Astrophysics Data System (ADS)

Mori, Kazuyoshi; Yokoyama, Tomoki; Hasegawa, Akio; Matsuda, Minoru

2004-05-01

The revolutionary concept of using ocean ambient noise positively to detect objects, called acoustic daylight imaging, has attracted much attention. The authors attempted the detection of a silent target object using ambient noise and a wide-band beam former consisting of an array of receivers. In experimental results obtained in air, using the wide-band beam former, we successfully applied the delay-sum array (DSA) method to detect a silent target object in an acoustic noise field generated by a large number of transducers. This paper reports some experimental results obtained by applying the multiple signal classification (MUSIC) method to a wide-band beam former to detect silent targets. The ocean ambient noise was simulated by transducers decentralized to many points in air. Both MUSIC and DSA detected a spherical target object in the noise field. The relative power levels near the target obtained with MUSIC were compared with those obtained by DSA. Then the effectiveness of the MUSIC method was evaluated according to the rate of increase in the maximum and minimum relative power levels.

Experimental Design for Multi-drug Combination Studies Using Signaling Networks

PubMed Central

Huang, Hengzhen; Fang, Hong-Bin; Tan, Ming T.

2017-01-01

Summary Combinations of multiple drugs are an important approach to maximize the chance for therapeutic success by inhibiting multiple pathways/targets. Analytic methods for studying drug combinations have received increasing attention because major advances in biomedical research have made available large number of potential agents for testing. The preclinical experiment on multi-drug combinations plays a key role in (especially cancer) drug development because of the complex nature of the disease, the need to reduce development time and costs. Despite recent progresses in statistical methods for assessing drug interaction, there is an acute lack of methods for designing experiments on multi-drug combinations. The number of combinations grows exponentially with the number of drugs and dose-levels and it quickly precludes laboratory testing. Utilizing experimental dose-response data of single drugs and a few combinations along with pathway/network information to obtain an estimate of the functional structure of the dose-response relationship in silico, we propose an optimal design that allows exploration of the dose-effect surface with the smallest possible sample size in this paper. The simulation studies show our proposed methods perform well. PMID:28960231

Vertical decomposition with Genetic Algorithm for Multiple Sequence Alignment

PubMed Central

2011-01-01

Background Many Bioinformatics studies begin with a multiple sequence alignment as the foundation for their research. This is because multiple sequence alignment can be a useful technique for studying molecular evolution and analyzing sequence structure relationships. Results In this paper, we have proposed a Vertical Decomposition with Genetic Algorithm (VDGA) for Multiple Sequence Alignment (MSA). In VDGA, we divide the sequences vertically into two or more subsequences, and then solve them individually using a guide tree approach. Finally, we combine all the subsequences to generate a new multiple sequence alignment. This technique is applied on the solutions of the initial generation and of each child generation within VDGA. We have used two mechanisms to generate an initial population in this research: the first mechanism is to generate guide trees with randomly selected sequences and the second is shuffling the sequences inside such trees. Two different genetic operators have been implemented with VDGA. To test the performance of our algorithm, we have compared it with existing well-known methods, namely PRRP, CLUSTALX, DIALIGN, HMMT, SB_PIMA, ML_PIMA, MULTALIGN, and PILEUP8, and also other methods, based on Genetic Algorithms (GA), such as SAGA, MSA-GA and RBT-GA, by solving a number of benchmark datasets from BAliBase 2.0. Conclusions The experimental results showed that the VDGA with three vertical divisions was the most successful variant for most of the test cases in comparison to other divisions considered with VDGA. The experimental results also confirmed that VDGA outperformed the other methods considered in this research. PMID:21867510

Electromagnetic Vortex-Based Radar Imaging Using a Single Receiving Antenna: Theory and Experimental Results

PubMed Central

Yuan, Tiezhu; Wang, Hongqiang; Cheng, Yongqiang; Qin, Yuliang

2017-01-01

Radar imaging based on electromagnetic vortex can achieve azimuth resolution without relative motion. The present paper investigates this imaging technique with the use of a single receiving antenna through theoretical analysis and experimental results. Compared with the use of multiple receiving antennas, the echoes from a single receiver cannot be used directly for image reconstruction using Fourier method. The reason is revealed by using the point spread function. An additional phase is compensated for each mode before imaging process based on the array parameters and the elevation of the targets. A proof-of-concept imaging system based on a circular phased array is created, and imaging experiments of corner-reflector targets are performed in an anechoic chamber. The azimuthal image is reconstructed by the use of Fourier transform and spectral estimation methods. The azimuth resolution of the two methods is analyzed and compared through experimental data. The experimental results verify the principle of azimuth resolution and the proposed phase compensation method. PMID:28335487

Detection of Multiple Stationary Humans Using UWB MIMO Radar.

PubMed

Liang, Fulai; Qi, Fugui; An, Qiang; Lv, Hao; Chen, Fuming; Li, Zhao; Wang, Jianqi

2016-11-16

Remarkable progress has been achieved in the detection of single stationary human. However, restricted by the mutual interference of multiple humans (e.g., strong sidelobes of the torsos and the shadow effect), detection and localization of the multiple stationary humans remains a huge challenge. In this paper, ultra-wideband (UWB) multiple-input and multiple-output (MIMO) radar is exploited to improve the detection performance of multiple stationary humans for its multiple sight angles and high-resolution two-dimensional imaging capacity. A signal model of the vital sign considering both bi-static angles and attitude angle of the human body is firstly developed, and then a novel detection method is proposed to detect and localize multiple stationary humans. In this method, preprocessing is firstly implemented to improve the signal-to-noise ratio (SNR) of the vital signs, and then a vital-sign-enhanced imaging algorithm is presented to suppress the environmental clutters and mutual affection of multiple humans. Finally, an automatic detection algorithm including constant false alarm rate (CFAR), morphological filtering and clustering is implemented to improve the detection performance of weak human targets affected by heavy clutters and shadow effect. The simulation and experimental results show that the proposed method can get a high-quality image of multiple humans and we can use it to discriminate and localize multiple adjacent human targets behind brick walls.

Detection of Multiple Stationary Humans Using UWB MIMO Radar

PubMed Central

Liang, Fulai; Qi, Fugui; An, Qiang; Lv, Hao; Chen, Fuming; Li, Zhao; Wang, Jianqi

2016-01-01

Remarkable progress has been achieved in the detection of single stationary human. However, restricted by the mutual interference of multiple humans (e.g., strong sidelobes of the torsos and the shadow effect), detection and localization of the multiple stationary humans remains a huge challenge. In this paper, ultra-wideband (UWB) multiple-input and multiple-output (MIMO) radar is exploited to improve the detection performance of multiple stationary humans for its multiple sight angles and high-resolution two-dimensional imaging capacity. A signal model of the vital sign considering both bi-static angles and attitude angle of the human body is firstly developed, and then a novel detection method is proposed to detect and localize multiple stationary humans. In this method, preprocessing is firstly implemented to improve the signal-to-noise ratio (SNR) of the vital signs, and then a vital-sign-enhanced imaging algorithm is presented to suppress the environmental clutters and mutual affection of multiple humans. Finally, an automatic detection algorithm including constant false alarm rate (CFAR), morphological filtering and clustering is implemented to improve the detection performance of weak human targets affected by heavy clutters and shadow effect. The simulation and experimental results show that the proposed method can get a high-quality image of multiple humans and we can use it to discriminate and localize multiple adjacent human targets behind brick walls. PMID:27854356

High-quality slab-based intermixing method for fusion rendering of multiple medical objects.

PubMed

Kim, Dong-Joon; Kim, Bohyoung; Lee, Jeongjin; Shin, Juneseuk; Kim, Kyoung Won; Shin, Yeong-Gil

2016-01-01

The visualization of multiple 3D objects has been increasingly required for recent applications in medical fields. Due to the heterogeneity in data representation or data configuration, it is difficult to efficiently render multiple medical objects in high quality. In this paper, we present a novel intermixing scheme for fusion rendering of multiple medical objects while preserving the real-time performance. First, we present an in-slab visibility interpolation method for the representation of subdivided slabs. Second, we introduce virtual zSlab, which extends an infinitely thin boundary (such as polygonal objects) into a slab with a finite thickness. Finally, based on virtual zSlab and in-slab visibility interpolation, we propose a slab-based visibility intermixing method with the newly proposed rendering pipeline. Experimental results demonstrate that the proposed method delivers more effective multiple-object renderings in terms of rendering quality, compared to conventional approaches. And proposed intermixing scheme provides high-quality intermixing results for the visualization of intersecting and overlapping surfaces by resolving aliasing and z-fighting problems. Moreover, two case studies are presented that apply the proposed method to the real clinical applications. These case studies manifest that the proposed method has the outstanding advantages of the rendering independency and reusability. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A multiple reflection model for the investigation of infrared transmission of a graphene/substrate system

NASA Astrophysics Data System (ADS)

Zhang, Jie; Ding, Lan; Liang, Changneng; Xiao, Yiming; Xu, Wen

2017-11-01

We develop a multiple reflection model (MRM) for the examination of infrared transmission properties of a graphene/substrate system. The incident angle and the multiple reflection beams in the substrate with finite thickness are taken into consideration. The model can be applied to predict the optical responses of graphene/substrate systems or to extract the real part of the optical conductance of graphene from the experimental measurement. As an example, we calculate the relative transmittance of graphene/quartz and graphene/sapphire systems by using MRM and provide an experimental verification in the near-infrared range. The measured results show good agreement with the calculated ones. Our method can be easily extended to accurately and non-invasively identify the layer numbers of other 2D materials, and assess the quality of them.

Gaussian process surrogates for failure detection: A Bayesian experimental design approach

NASA Astrophysics Data System (ADS)

Wang, Hongqiao; Lin, Guang; Li, Jinglai

2016-05-01

An important task of uncertainty quantification is to identify the probability of undesired events, in particular, system failures, caused by various sources of uncertainties. In this work we consider the construction of Gaussian process surrogates for failure detection and failure probability estimation. In particular, we consider the situation that the underlying computer models are extremely expensive, and in this setting, determining the sampling points in the state space is of essential importance. We formulate the problem as an optimal experimental design for Bayesian inferences of the limit state (i.e., the failure boundary) and propose an efficient numerical scheme to solve the resulting optimization problem. In particular, the proposed limit-state inference method is capable of determining multiple sampling points at a time, and thus it is well suited for problems where multiple computer simulations can be performed in parallel. The accuracy and performance of the proposed method is demonstrated by both academic and practical examples.

Deep convolutional neural network based antenna selection in multiple-input multiple-output system

NASA Astrophysics Data System (ADS)

Cai, Jiaxin; Li, Yan; Hu, Ying

2018-03-01

Antenna selection of wireless communication system has attracted increasing attention due to the challenge of keeping a balance between communication performance and computational complexity in large-scale Multiple-Input MultipleOutput antenna systems. Recently, deep learning based methods have achieved promising performance for large-scale data processing and analysis in many application fields. This paper is the first attempt to introduce the deep learning technique into the field of Multiple-Input Multiple-Output antenna selection in wireless communications. First, the label of attenuation coefficients channel matrix is generated by minimizing the key performance indicator of training antenna systems. Then, a deep convolutional neural network that explicitly exploits the massive latent cues of attenuation coefficients is learned on the training antenna systems. Finally, we use the adopted deep convolutional neural network to classify the channel matrix labels of test antennas and select the optimal antenna subset. Simulation experimental results demonstrate that our method can achieve better performance than the state-of-the-art baselines for data-driven based wireless antenna selection.

Experimental Investigation on the Detection of Multiple Surface Cracks Using Vibrothermography with a Low-Power Piezoceramic Actuator

PubMed Central

Xu, Changhang; Xie, Jing; Zhang, Wuyang; Kong, Qingzhao; Chen, Guoming; Song, Gangbing

2017-01-01

Vibrothermography often employs a high-power actuator to generate heat on a specimen to reveal damage, however, the high-power actuator brings inconvenience to the application and possibly introduces additional damage to the inspected objects. This study uses a low-power piezoceramic transducer as the actuator of vibrothermography and explores its ability to detect multiple surface cracks in a metal part. Experiments were conducted on a thin aluminum beam with three cracks in different orientations. Detailed analyses of both thermograms and temperature data are presented to validate the proposed vibrothermography method. To further investigate the performance of the proposed vibrothermography method, we experimentally studied the effects of several critical factors, including the amplitude of excitation signal, specimen constraints, relative position between the transducer and cracks (the transducer is mounted on the same or the opposite side with the cracks). The results demonstrate that all cracks can be detected conveniently and simultaneously by using the proposed low-power vibrothermography. We also found that the magnitude of excitation signal and the specimen constraints have a great influence on detection results. Combined with effective data processing methods, such as Fourier transformation employed in this study, the proposed method provides a promising potential to detect multiple cracks on a metal surface in a safe and effective manner. PMID:29168759

Face recognition system using multiple face model of hybrid Fourier feature under uncontrolled illumination variation.

PubMed

Hwang, Wonjun; Wang, Haitao; Kim, Hyunwoo; Kee, Seok-Cheol; Kim, Junmo

2011-04-01

The authors present a robust face recognition system for large-scale data sets taken under uncontrolled illumination variations. The proposed face recognition system consists of a novel illumination-insensitive preprocessing method, a hybrid Fourier-based facial feature extraction, and a score fusion scheme. First, in the preprocessing stage, a face image is transformed into an illumination-insensitive image, called an "integral normalized gradient image," by normalizing and integrating the smoothed gradients of a facial image. Then, for feature extraction of complementary classifiers, multiple face models based upon hybrid Fourier features are applied. The hybrid Fourier features are extracted from different Fourier domains in different frequency bandwidths, and then each feature is individually classified by linear discriminant analysis. In addition, multiple face models are generated by plural normalized face images that have different eye distances. Finally, to combine scores from multiple complementary classifiers, a log likelihood ratio-based score fusion scheme is applied. The proposed system using the face recognition grand challenge (FRGC) experimental protocols is evaluated; FRGC is a large available data set. Experimental results on the FRGC version 2.0 data sets have shown that the proposed method shows an average of 81.49% verification rate on 2-D face images under various environmental variations such as illumination changes, expression changes, and time elapses.

Error-based Extraction of States and Energy Landscapes from Experimental Single-Molecule Time-Series

NASA Astrophysics Data System (ADS)

Taylor, J. Nicholas; Li, Chun-Biu; Cooper, David R.; Landes, Christy F.; Komatsuzaki, Tamiki

2015-03-01

Characterization of states, the essential components of the underlying energy landscapes, is one of the most intriguing subjects in single-molecule (SM) experiments due to the existence of noise inherent to the measurements. Here we present a method to extract the underlying state sequences from experimental SM time-series. Taking into account empirical error and the finite sampling of the time-series, the method extracts a steady-state network which provides an approximation of the underlying effective free energy landscape. The core of the method is the application of rate-distortion theory from information theory, allowing the individual data points to be assigned to multiple states simultaneously. We demonstrate the method's proficiency in its application to simulated trajectories as well as to experimental SM fluorescence resonance energy transfer (FRET) trajectories obtained from isolated agonist binding domains of the AMPA receptor, an ionotropic glutamate receptor that is prevalent in the central nervous system.

Optical bandgap of single- and multi-layered amorphous germanium ultra-thin films

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

Liu, Pei; Zaslavsky, Alexander; Longo, Paolo

2016-01-07

Accurate optical methods are required to determine the energy bandgap of amorphous semiconductors and elucidate the role of quantum confinement in nanometer-scale, ultra-thin absorbing layers. Here, we provide a critical comparison between well-established methods that are generally employed to determine the optical bandgap of thin-film amorphous semiconductors, starting from normal-incidence reflectance and transmittance measurements. First, we demonstrate that a more accurate estimate of the optical bandgap can be achieved by using a multiple-reflection interference model. We show that this model generates more reliable results compared to the widely accepted single-pass absorption method. Second, we compare two most representative methods (Taucmore » and Cody plots) that are extensively used to determine the optical bandgap of thin-film amorphous semiconductors starting from the extracted absorption coefficient. Analysis of the experimental absorption data acquired for ultra-thin amorphous germanium (a-Ge) layers demonstrates that the Cody model is able to provide a less ambiguous energy bandgap value. Finally, we apply our proposed method to experimentally determine the optical bandgap of a-Ge/SiO{sub 2} superlattices with single and multiple a-Ge layers down to 2 nm thickness.« less

Multiple rotation assessment through isothetic fringes in speckle photography

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

Angel, Luciano; Tebaldi, Myrian; Bolognini, Nestor

2007-05-10

The use of different pupils for storing each speckled image in speckle photography is employed to determine multiple in-plane rotations. The method consists of recording a four-exposure specklegram where the rotations are done between exposures. This specklegram is then optically processed in a whole field approach rendering isothetic fringes, which give detailed information about the multiple rotations. It is experimentally demonstrated that the proposed arrangement permits the depiction of six isothetics in order to measure either six different angles or three nonparallel components for two local general in-plane displacements.

Experimental and evaluated photoneutron cross sections for 197Au

NASA Astrophysics Data System (ADS)

Varlamov, V.; Ishkhanov, B.; Orlin, V.

2017-10-01

There is a serious well-known problem of noticeable disagreements between the partial photoneutron cross sections obtained in various experiments. Such data were mainly determined using quasimonoenergetic annihilation photon beams and the method of neutron multiplicity sorting at Lawrence Livermore National Laboratory (USA) and Centre d'Etudes Nucleaires of Saclay (France). The analysis of experimental cross sections employing new objective physical data reliability criteria has shown that many of those are not reliable. The IAEA Coordinated Research Project (CRP) on photonuclear data evaluation was approved. The experimental and previously evaluated cross sections of the partial photoneutron reactions (γ ,1 n ) and (γ ,2 n ) on 197Au were analyzed using the new data reliability criteria. The data evaluated using the new experimental-theoretical method noticeably differ from both experimental data and data previously evaluated using nuclear modeling codes gnash, gunf, alice-f, and others. These discrepancies needed to be resolved.

Principal axis-based correspondence between multiple cameras for people tracking.

PubMed

Hu, Weiming; Hu, Min; Zhou, Xue; Tan, Tieniu; Lou, Jianguang; Maybank, Steve

2006-04-01

Visual surveillance using multiple cameras has attracted increasing interest in recent years. Correspondence between multiple cameras is one of the most important and basic problems which visual surveillance using multiple cameras brings. In this paper, we propose a simple and robust method, based on principal axes of people, to match people across multiple cameras. The correspondence likelihood reflecting the similarity of pairs of principal axes of people is constructed according to the relationship between "ground-points" of people detected in each camera view and the intersections of principal axes detected in different camera views and transformed to the same view. Our method has the following desirable properties: 1) Camera calibration is not needed. 2) Accurate motion detection and segmentation are less critical due to the robustness of the principal axis-based feature to noise. 3) Based on the fused data derived from correspondence results, positions of people in each camera view can be accurately located even when the people are partially occluded in all views. The experimental results on several real video sequences from outdoor environments have demonstrated the effectiveness, efficiency, and robustness of our method.

Monte Carlo based method for fluorescence tomographic imaging with lifetime multiplexing using time gates

PubMed Central

Chen, Jin; Venugopal, Vivek; Intes, Xavier

2011-01-01

Time-resolved fluorescence optical tomography allows 3-dimensional localization of multiple fluorophores based on lifetime contrast while providing a unique data set for improved resolution. However, to employ the full fluorescence time measurements, a light propagation model that accurately simulates weakly diffused and multiple scattered photons is required. In this article, we derive a computationally efficient Monte Carlo based method to compute time-gated fluorescence Jacobians for the simultaneous imaging of two fluorophores with lifetime contrast. The Monte Carlo based formulation is validated on a synthetic murine model simulating the uptake in the kidneys of two distinct fluorophores with lifetime contrast. Experimentally, the method is validated using capillaries filled with 2.5nmol of ICG and IRDye™800CW respectively embedded in a diffuse media mimicking the average optical properties of mice. Combining multiple time gates in one inverse problem allows the simultaneous reconstruction of multiple fluorophores with increased resolution and minimal crosstalk using the proposed formulation. PMID:21483610

Feasibility investigations on multi-cutter milling process: A novel fabrication method for microreactors with multiple microchannels

NASA Astrophysics Data System (ADS)

Pan, Minqiang; Zeng, Dehuai; Tang, Yong

A novel multi-cutter milling process for multiple parallel microchannels with manifolds is proposed to address the challenge of mass manufacture as required for cost-effective commercial applications. Several slotting cutters are stacked together to form a composite tool for machining microchannels simultaneously. The feasibility of this new fabrication process is experimentally investigated under different machining conditions and reaction characteristics of methanol steam reforming for hydrogen production. The influences of cutting parameters and the composite tool on the microchannel qualities and burr formation are analyzed. Experimental results indicate that larger cutting speed, smaller feed rate and cutting depth are in favor of obtaining relatively good microchannel qualities and small burrs. Of all the cutting parameters considered in these experiments, 94.2 m min -1 cutting speed, 23.5 mm min -1 feed rate and 0.5 mm cutting depth are found to be the optimum value. According to the comparisons of experimental results of multi-cutter milling process and estimated one of other alternative methods, it is found that multi-cutter milling process shows much shorter machining time and higher work removal rate than that of other alternative methods. Reaction characteristics of methanol steam reforming in microchannels also indicate that multi-cutter milling process is probably suitable for a commercial application.

The Effectiveness of learning materials based on multiple intelligence on the understanding of global warming

NASA Astrophysics Data System (ADS)

Liliawati, W.; Purwanto; Zulfikar, A.; Kamal, R. N.

2018-05-01

This study aims to examine the effectiveness of the use of teaching materials based on multiple intelligences on the understanding of high school students’ material on the theme of global warming. The research method used is static-group pretest-posttest design. Participants of the study were 60 high school students of XI class in one of the high schools in Bandung. Participants were divided into two classes of 30 students each for the experimental class and control class. The experimental class uses compound-based teaching materials while the experimental class does not use a compound intelligence-based teaching material. The instrument used is a test of understanding of the concept of global warming with multiple choices form amounted to 15 questions and 5 essay items. The test is given before and after it is applied to both classes. Data analysis using N-gain and effect size. The results obtained that the N-gain for both classes is in the medium category and the effectiveness of the use of teaching materials based on the results of effect-size test results obtained in the high category.

Methods for Improving Information from "Undesigned" Human Factors Experiments. Technical Report No. p75-287.

ERIC Educational Resources Information Center

Simon, Charles W.

An "undesigned" experiment is one in which the predictor variables are correlated, either due to a failure to complete a design or because the investigator was unable to select or control relevant experimental conditions. The traditional method of analyzing this class of experiment--multiple regression analysis based on a least squares…

Feature point based 3D tracking of multiple fish from multi-view images

PubMed Central

Qian, Zhi-Ming

2017-01-01

A feature point based method is proposed for tracking multiple fish in 3D space. First, a simplified representation of the object is realized through construction of two feature point models based on its appearance characteristics. After feature points are classified into occluded and non-occluded types, matching and association are performed, respectively. Finally, the object's motion trajectory in 3D space is obtained through integrating multi-view tracking results. Experimental results show that the proposed method can simultaneously track 3D motion trajectories for up to 10 fish accurately and robustly. PMID:28665966

Feature point based 3D tracking of multiple fish from multi-view images.

PubMed

Qian, Zhi-Ming; Chen, Yan Qiu

2017-01-01

A feature point based method is proposed for tracking multiple fish in 3D space. First, a simplified representation of the object is realized through construction of two feature point models based on its appearance characteristics. After feature points are classified into occluded and non-occluded types, matching and association are performed, respectively. Finally, the object's motion trajectory in 3D space is obtained through integrating multi-view tracking results. Experimental results show that the proposed method can simultaneously track 3D motion trajectories for up to 10 fish accurately and robustly.

Effectiveness of applying progressive muscle relaxation technique on quality of life of patients with multiple sclerosis.

PubMed

Ghafari, Somayeh; Ahmadi, Fazlolah; Nabavi, Masoud; Anoshirvan, Kazemnejad; Memarian, Robabe; Rafatbakhsh, Mohamad

2009-08-01

To identify the effects of applying Progressive Muscle Relaxation Technique on Quality of Life of patients with multiple Sclerosis. In view of the growing caring options in Multiple Sclerosis, improvement of quality of life has become increasingly relevant as a caring intervention. Complementary therapies are widely used by multiple sclerosis patients and Progressive Muscle Relaxation Technique is a form of complementary therapies. Quasi-experimental study. Multiple Sclerosis patients (n = 66) were selected with no probability sampling then assigned to experimental and control groups (33 patients in each group). Means of data collection included: Individual Information Questionnaire, SF-8 Health Survey, Self-reported checklist. PMRT performed for 63 sessions by experimental group during two months but no intervention was done for control group. Statistical analysis was done by SPSS software. Student t-test showed that there was no significant difference between two groups in mean scores of health-related quality of life before the study but this test showed a significant difference between two groups, one and two months after intervention (p < 0.05). anova test with repeated measurements showed that there is a significant difference in mean score of whole and dimensions of health-related quality of life between two groups in three times (p < 0.05). Although this study provides modest support for the effectiveness of Progressive Muscle Relaxation Technique on quality of life of multiple sclerosis patients, further research is required to determine better methods to promote quality of life of patients suffer multiple sclerosis and other chronic disease. Progressive Muscle Relaxation Technique is practically feasible and is associated with increase of life quality of multiple sclerosis patients; so that health professionals need to update their knowledge about complementary therapies.

Multiple-Point Temperature Gradient Algorithm for Ring Laser Gyroscope Bias Compensation

PubMed Central

Li, Geng; Zhang, Pengfei; Wei, Guo; Xie, Yuanping; Yu, Xudong; Long, Xingwu

2015-01-01

To further improve ring laser gyroscope (RLG) bias stability, a multiple-point temperature gradient algorithm is proposed for RLG bias compensation in this paper. Based on the multiple-point temperature measurement system, a complete thermo-image of the RLG block is developed. Combined with the multiple-point temperature gradients between different points of the RLG block, the particle swarm optimization algorithm is used to tune the support vector machine (SVM) parameters, and an optimized design for selecting the thermometer locations is also discussed. The experimental results validate the superiority of the introduced method and enhance the precision and generalizability in the RLG bias compensation model. PMID:26633401

Terahertz sensing of highly absorptive water-methanol mixtures with multiple resonances in metamaterials.

PubMed

Chen, Min; Singh, Leena; Xu, Ningning; Singh, Ranjan; Zhang, Weili; Xie, Lijuan

2017-06-26

Terahertz sensing of highly absorptive aqueous solutions remains challenging due to strong absorption of water in the terahertz regime. Here, we experimentally demonstrate a cost-effective metamaterial-based sensor integrated with terahertz time-domain spectroscopy for highly absorptive water-methanol mixture sensing. This metamaterial has simple asymmetric wire structures that support multiple resonances including a fundamental Fano resonance and higher order dipolar resonance in the terahertz regime. Both the resonance modes have strong intensity in the transmission spectra which we exploit for detection of the highly absorptive water-methanol mixtures. The experimentally characterized sensitivities of the Fano and dipole resonances for the water-methanol mixtures are found to be 160 and 305 GHz/RIU, respectively. This method provides a robust route for metamaterial-assisted terahertz sensing of highly absorptive chemical and biochemical materials with multiple resonances and high accuracy.

Experimental Methods for Protein Interaction Identification and Characterization

NASA Astrophysics Data System (ADS)

Uetz, Peter; Titz, Björn; Cagney, Gerard

There are dozens of methods for the detection of protein-protein interactions but they fall into a few broad categories. Fragment complementation assays such as the yeast two-hybrid (Y2H) system are based on split proteins that are functionally reconstituted by fusions of interacting proteins. Biophysical methods include structure determination and mass spectrometric (MS) identification of proteins in complexes. Biochemical methods include methods such as far western blotting and peptide arrays. Only the Y2H and protein complex purification combined with MS have been used on a larger scale. Due to the lack of data it is still difficult to compare these methods with respect to their efficiency and error rates. Current data does not favor any particular method and thus multiple experimental approaches are necessary to maximally cover the interactome of any target cell or organism.

Multivariate analysis: greater insights into complex systems

USDA-ARS?s Scientific Manuscript database

Many agronomic researchers measure and collect multiple response variables in an effort to understand the more complex nature of the system being studied. Multivariate (MV) statistical methods encompass the simultaneous analysis of all random variables (RV) measured on each experimental or sampling ...

Accurate Simulation and Detection of Coevolution Signals in Multiple Sequence Alignments

PubMed Central

Ackerman, Sharon H.; Tillier, Elisabeth R.; Gatti, Domenico L.

2012-01-01

Background While the conserved positions of a multiple sequence alignment (MSA) are clearly of interest, non-conserved positions can also be important because, for example, destabilizing effects at one position can be compensated by stabilizing effects at another position. Different methods have been developed to recognize the evolutionary relationship between amino acid sites, and to disentangle functional/structural dependencies from historical/phylogenetic ones. Methodology/Principal Findings We have used two complementary approaches to test the efficacy of these methods. In the first approach, we have used a new program, MSAvolve, for the in silico evolution of MSAs, which records a detailed history of all covarying positions, and builds a global coevolution matrix as the accumulated sum of individual matrices for the positions forced to co-vary, the recombinant coevolution, and the stochastic coevolution. We have simulated over 1600 MSAs for 8 protein families, which reflect sequences of different sizes and proteins with widely different functions. The calculated coevolution matrices were compared with the coevolution matrices obtained for the same evolved MSAs with different coevolution detection methods. In a second approach we have evaluated the capacity of the different methods to predict close contacts in the representative X-ray structures of an additional 150 protein families using only experimental MSAs. Conclusions/Significance Methods based on the identification of global correlations between pairs were found to be generally superior to methods based only on local correlations in their capacity to identify coevolving residues using either simulated or experimental MSAs. However, the significant variability in the performance of different methods with different proteins suggests that the simulation of MSAs that replicate the statistical properties of the experimental MSA can be a valuable tool to identify the coevolution detection method that is most effective in each case. PMID:23091608

[Blended-learning in psychosomatics and psychotherapy - Increasing the satisfaction and knowledge of students with a web-based e-learning tool].

PubMed

Ferber, Julia; Schneider, Gudrun; Havlik, Linda; Heuft, Gereon; Friederichs, Hendrik; Schrewe, Franz-Bernhard; Schulz-Steinel, Andrea; Burgmer, Markus

2014-01-01

To improve the synergy of established methods of teaching, the Department of Psychosomatics and Psychotherapy, University Hospital Münster, developed a web-based elearning tool using video clips of standardized patients. The effect of this blended-learning approach was evaluated. A multiple-choice test was performed by a naive (without the e-learning tool) and an experimental (with the tool) cohort of medical students to test the groups' expertise in psychosomatics. In addition, participants' satisfaction with the new tool was evaluated (numeric rating scale of 0-10). The experimental cohort was more satisfied with the curriculum and more interested in psychosomatics. Furthermore, the experimental cohort scored significantly better in the multiple-choice test. The new tool proved to be an important addition to the classical curriculum as a blended-learning approach which improves students' satisfaction and knowledge in psychosomatics.

Experimental design and multiple response optimization. Using the desirability function in analytical methods development.

PubMed

Candioti, Luciana Vera; De Zan, María M; Cámara, María S; Goicoechea, Héctor C

2014-06-01

A review about the application of response surface methodology (RSM) when several responses have to be simultaneously optimized in the field of analytical methods development is presented. Several critical issues like response transformation, multiple response optimization and modeling with least squares and artificial neural networks are discussed. Most recent analytical applications are presented in the context of analytLaboratorio de Control de Calidad de Medicamentos (LCCM), Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral, C.C. 242, S3000ZAA Santa Fe, ArgentinaLaboratorio de Control de Calidad de Medicamentos (LCCM), Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral, C.C. 242, S3000ZAA Santa Fe, Argentinaical methods development, especially in multiple response optimization procedures using the desirability function. Copyright © 2014 Elsevier B.V. All rights reserved.

Modern status of photonuclear data

NASA Astrophysics Data System (ADS)

Varlamov, V. V.; Ishkhanov, B. S.

2017-09-01

The reliability of experimental cross sections obtained for (γ, 1 n), (γ, 2 n), and (γ, 3 n) partial photoneutron reactions using beams of quasimonoenergetic annihilation photons and bremsstrahlung is analyzed by employing data for a large number of medium-heavy and heavy nuclei, including those of 63,65Cu, 80Se, 90,91,94Zr, 115In, 112-124Sn, 133Cs, 138Ba, 159Tb, 181Ta, 186-192Os, 197Au, 208Pb, and 209Bi. The ratios of the cross sections of definite partial reactions to the cross section of the neutron-yield reaction, F i = σ(γ, in)/ σ(γ, xn), are used as criteria of experimental-data reliability. By definition, positive values of these ratios should not exceed the upper limits of 1.00, 0.50, 0.33,... for i = 1, 2, 3,..., respectively. For many nuclei, unreliable values of the above ratios were found to correlate clearly in various photon-energy regions F i with physically forbidden negative values of cross sections of partial reactions. On this basis, one can conclude that correspondent experimental data are unreliable. Significant systematic uncertainties of the methods used to determine photoneutron multiplicity are shown to be the main reason for this. New partial-reaction cross sections that satisfy the above data-reliability criteria were evaluated within an experimental-theoretical method [ σ eval(γ, in) = F i theor (γ, in) × σ expt(γ, xn)] by employing the ratios F i theor (γ, in) calculated on the basis of a combined photonuclear-reaction model. It was obtained that cross sections evaluated in this way deviate substantially from the results of many experiments performed via neutron-multiplicity sorting, but, at the same time, agree with the results of alternative activation experiments. Prospects of employing methods that would provide, without recourse to photoneutron-multiplicity sorting, reliable data on cross sections of partial photoneutron reactions are discussed.

An Experimental Investigation of Intermittent Flow and Strain Burst Scaling Behavior in LiF Crystals During Microcompression Testing (Preprint)

DTIC Science & Technology

2010-01-01

or in more general terms, as a result of dislocation nucleation, motion, multiplication, and interaction). Nonetheless, state-of-the-art simulation ...computational power, together with under-developed physics within the simulation codes (i.e. cross-slip, climb, crystal rotations and patterning to...name a few), prevent realistic dislocation simulations over temporal and spatial domains that are readily accessible by experimental methods [9, 10

Experimental "Microcultures" in Young Children: Identifying Biographic, Cognitive, and Social Predictors of Information Transmission

ERIC Educational Resources Information Center

Flynn, Emma; Whiten, Andrew

2012-01-01

In one of the first open diffusion experiments with young children, a tool-use task that afforded multiple methods to extract an enclosed reward and a child model habitually using one of these methods were introduced into different playgroups. Eighty-eight children, ranging in age from 2 years 8 months to 4 years 5 months, participated. Measures…

MODELING A MIXTURE: PBPK/PD APPROACHES FOR PREDICTING CHEMICAL INTERACTIONS.

EPA Science Inventory

Since environmental chemical exposures generally involve multiple chemicals, there are both regulatory and scientific drivers to develop methods to predict outcomes of these exposures. Even using efficient statistical and experimental designs, it is not possible to test in vivo a...

Applied statistics in agricultural, biological, and environmental sciences.

USDA-ARS?s Scientific Manuscript database

Agronomic research often involves measurement and collection of multiple response variables in an effort to understand the more complex nature of the system being studied. Multivariate statistical methods encompass the simultaneous analysis of all random variables measured on each experimental or s...

Induced subgraph searching for geometric model fitting

NASA Astrophysics Data System (ADS)

Xiao, Fan; Xiao, Guobao; Yan, Yan; Wang, Xing; Wang, Hanzi

2017-11-01

In this paper, we propose a novel model fitting method based on graphs to fit and segment multiple-structure data. In the graph constructed on data, each model instance is represented as an induced subgraph. Following the idea of pursuing the maximum consensus, the multiple geometric model fitting problem is formulated as searching for a set of induced subgraphs including the maximum union set of vertices. After the generation and refinement of the induced subgraphs that represent the model hypotheses, the searching process is conducted on the "qualified" subgraphs. Multiple model instances can be simultaneously estimated by solving a converted problem. Then, we introduce the energy evaluation function to determine the number of model instances in data. The proposed method is able to effectively estimate the number and the parameters of model instances in data severely corrupted by outliers and noises. Experimental results on synthetic data and real images validate the favorable performance of the proposed method compared with several state-of-the-art fitting methods.

Joint Concept Correlation and Feature-Concept Relevance Learning for Multilabel Classification.

PubMed

Zhao, Xiaowei; Ma, Zhigang; Li, Zhi; Li, Zhihui

2018-02-01

In recent years, multilabel classification has attracted significant attention in multimedia annotation. However, most of the multilabel classification methods focus only on the inherent correlations existing among multiple labels and concepts and ignore the relevance between features and the target concepts. To obtain more robust multilabel classification results, we propose a new multilabel classification method aiming to capture the correlations among multiple concepts by leveraging hypergraph that is proved to be beneficial for relational learning. Moreover, we consider mining feature-concept relevance, which is often overlooked by many multilabel learning algorithms. To better show the feature-concept relevance, we impose a sparsity constraint on the proposed method. We compare the proposed method with several other multilabel classification methods and evaluate the classification performance by mean average precision on several data sets. The experimental results show that the proposed method outperforms the state-of-the-art methods.

The extended Beer-Lambert theory for ray tracing modeling of LED chip-scaled packaging application with multiple luminescence materials

NASA Astrophysics Data System (ADS)

Yuan, Cadmus C. A.

2015-12-01

Optical ray tracing modeling applied Beer-Lambert method in the single luminescence material system to model the white light pattern from blue LED light source. This paper extends such algorithm to a mixed multiple luminescence material system by introducing the equivalent excitation and emission spectrum of individual luminescence materials. The quantum efficiency numbers of individual material and self-absorption of the multiple luminescence material system are considered as well. By this combination, researchers are able to model the luminescence characteristics of LED chip-scaled packaging (CSP), which provides simple process steps and the freedom of the luminescence material geometrical dimension. The method will be first validated by the experimental results. Afterward, a further parametric investigation has been then conducted.

On muon energy spectrum in muon groups underground

NASA Technical Reports Server (NTRS)

Bakatanov, V. N.; Chudakov, A. E.; Novoseltsev, Y. F.; Novoseltseva, M. V.; Stenkin, Y. V.

1985-01-01

A method is described which was used to measure muon energy spectrum characteristics in muon groups underground using mu-e decays recording. The Baksan Telescope's experimental data on mu-e decays intensity in muon groups of various multiplicities are analyzed. The experimental data indicating very flat spectrum does not however represent the total spectrum in muon groups. Obviously the muon energy spectrum depends strongly on a distance from the group axis. The core attraction effect makes a significant distortion, making the spectrum flatter. After taking this into account and making corrections for this effect the integral total spectrum index in groups has a very small depencence on muon multiplicity and agrees well with expected one: beta=beta (sub expected) = 1.75.

Screen Space Ambient Occlusion Based Multiple Importance Sampling for Real-Time Rendering

NASA Astrophysics Data System (ADS)

Zerari, Abd El Mouméne; Babahenini, Mohamed Chaouki

2018-03-01

We propose a new approximation technique for accelerating the Global Illumination algorithm for real-time rendering. The proposed approach is based on the Screen-Space Ambient Occlusion (SSAO) method, which approximates the global illumination for large, fully dynamic scenes at interactive frame rates. Current algorithms that are based on the SSAO method suffer from difficulties due to the large number of samples that are required. In this paper, we propose an improvement to the SSAO technique by integrating it with a Multiple Importance Sampling technique that combines a stratified sampling method with an importance sampling method, with the objective of reducing the number of samples. Experimental evaluation demonstrates that our technique can produce high-quality images in real time and is significantly faster than traditional techniques.

EXPERIMENTAL EVALUATION OF NEW LABORATORY METHODS FOR THE STUDY OF VIRUS OF POLIOMYELITIS WITH THE AID OF TISSUE CULTURES

DTIC Science & Technology

The multiplication of poliomyelitis types I, II and III viruses in cultures with surviving and growing tissues (brain, skin and muscle) of human...embryo has been established. The virus of poliomyelitis , during multiplication of tissue cultures, caused a characteristic necrosis of the cells. The...cytopathogenic action of the virus of poliomyelitis was easily established during inspection under a microscope of the cultures with young growing cells

Flight effects on exhaust noise for turbojet and turbofan engines: Comparison of experimental data with prediction

NASA Technical Reports Server (NTRS)

Stone, J. R.

1976-01-01

It was demonstrated that static and in flight jet engine exhaust noise can be predicted with reasonable accuracy when the multiple source nature of the problem is taken into account. Jet mixing noise was predicted from the interim prediction method. Provisional methods of estimating internally generated noise and shock noise flight effects were used, based partly on existing prediction methods and partly on recent reported engine data.

Multiple nucleon knockout by Coulomb dissociation in relativistic heavy-ion collisions

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Norbury, John W.; Townsend, Lawrence W.

1988-01-01

The Coulomb dissociation contributions to fragmentation cross sections in relativistic heavy ion collisions, where more than one nucleon is removed, are estimated using the Weizsacker-Williams method of virtual quanta. Photonuclear cross sections taken from experimental results were used to fold into target photon number spectra calculated with the Weizsacker-Williams method. Calculations for several projectile target combinations over a wide range of charge numbers, and a wide range of incident projectile energies, are reported. These results suggest that multiple nucleon knockout by the Coulomb field may be of negligible importance in galactic heavy ion studies for projectiles lighter than Fe-56.

Multispectral high-resolution hologram generation using orthographic projection images

NASA Astrophysics Data System (ADS)

Muniraj, I.; Guo, C.; Sheridan, J. T.

2016-08-01

We present a new method of synthesizing a digital hologram of three-dimensional (3D) real-world objects from multiple orthographic projection images (OPI). A high-resolution multiple perspectives of 3D objects (i.e., two dimensional elemental image array) are captured under incoherent white light using synthetic aperture integral imaging (SAII) technique and their OPIs are obtained respectively. The reference beam is then multiplied with the corresponding OPI and integrated to form a Fourier hologram. Eventually, a modified phase retrieval algorithm (GS/HIO) is applied to reconstruct the hologram. The principle is validated experimentally and the results support the feasibility of the proposed method.

Ensemble-Biased Metadynamics: A Molecular Simulation Method to Sample Experimental Distributions

PubMed Central

Marinelli, Fabrizio; Faraldo-Gómez, José D.

2015-01-01

We introduce an enhanced-sampling method for molecular dynamics (MD) simulations referred to as ensemble-biased metadynamics (EBMetaD). The method biases a conventional MD simulation to sample a molecular ensemble that is consistent with one or more probability distributions known a priori, e.g., experimental intramolecular distance distributions obtained by double electron-electron resonance or other spectroscopic techniques. To this end, EBMetaD adds an adaptive biasing potential throughout the simulation that discourages sampling of configurations inconsistent with the target probability distributions. The bias introduced is the minimum necessary to fulfill the target distributions, i.e., EBMetaD satisfies the maximum-entropy principle. Unlike other methods, EBMetaD does not require multiple simulation replicas or the introduction of Lagrange multipliers, and is therefore computationally efficient and straightforward in practice. We demonstrate the performance and accuracy of the method for a model system as well as for spin-labeled T4 lysozyme in explicit water, and show how EBMetaD reproduces three double electron-electron resonance distance distributions concurrently within a few tens of nanoseconds of simulation time. EBMetaD is integrated in the open-source PLUMED plug-in (www.plumed-code.org), and can be therefore readily used with multiple MD engines. PMID:26083917

Renal cortex segmentation using optimal surface search with novel graph construction.

PubMed

Li, Xiuli; Chen, Xinjian; Yao, Jianhua; Zhang, Xing; Tian, Jie

2011-01-01

In this paper, we propose a novel approach to solve the renal cortex segmentation problem, which has rarely been studied. In this study, the renal cortex segmentation problem is handled as a multiple-surfaces extraction problem, which is solved using the optimal surface search method. We propose a novel graph construction scheme in the optimal surface search to better accommodate multiple surfaces. Different surface sub-graphs are constructed according to their properties, and inter-surface relationships are also modeled in the graph. The proposed method was tested on 17 clinical CT datasets. The true positive volume fraction (TPVF) and false positive volume fraction (FPVF) are 74.10% and 0.08%, respectively. The experimental results demonstrate the effectiveness of the proposed method.

Remote temperature distribution sensing using permanent magnets

DOE PAGES

Chen, Yi; Guba, Oksana; Brooks, Carlton F.; ...

2016-10-31

Remote temperature sensing is essential for applications in enclosed vessels where feedthroughs or optical access points are not possible. A unique sensing method for measuring the temperature of multiple closely-spaced points is proposed using permanent magnets and several three-axis magnetic field sensors. The magnetic field theory for multiple magnets is discussed and a solution technique is presented. Experimental calibration procedures, solution inversion considerations and methods for optimizing the magnet orientations are described in order to obtain low-noise temperature estimates. The experimental setup and the properties of permanent magnets are shown. Finally, experiments were conducted to determine the temperature of ninemore » magnets in different configurations over a temperature range of 5 to 60 degrees Celsius and for a sensor-to-magnet distance of up to 35 mm. Furthermore, to show the possible applications of this sensing system for measuring temperatures through metal walls, additional experiments were conducted inside an opaque 304 stainless steel cylinder.« less

Multiple graph regularized protein domain ranking.

PubMed

Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

2012-11-19

Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

Multiple graph regularized protein domain ranking

PubMed Central

2012-01-01

Background Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. Results To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. Conclusion The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. PMID:23157331

A level set method for multiple sclerosis lesion segmentation.

PubMed

Zhao, Yue; Guo, Shuxu; Luo, Min; Shi, Xue; Bilello, Michel; Zhang, Shaoxiang; Li, Chunming

2018-06-01

In this paper, we present a level set method for multiple sclerosis (MS) lesion segmentation from FLAIR images in the presence of intensity inhomogeneities. We use a three-phase level set formulation of segmentation and bias field estimation to segment MS lesions and normal tissue region (including GM and WM) and CSF and the background from FLAIR images. To save computational load, we derive a two-phase formulation from the original multi-phase level set formulation to segment the MS lesions and normal tissue regions. The derived method inherits the desirable ability to precisely locate object boundaries of the original level set method, which simultaneously performs segmentation and estimation of the bias field to deal with intensity inhomogeneity. Experimental results demonstrate the advantages of our method over other state-of-the-art methods in terms of segmentation accuracy. Copyright © 2017 Elsevier Inc. All rights reserved.

Optical levitation and translation of a microscopic particle by use of multiple beams generated by vertical-cavity surface-emitting laser array sources.

PubMed

Ogura, Yusuke; Shirai, Nobuhiro; Tanida, Jun

2002-09-20

An optical levitation and translation method for a microscopic particle by use of the resultant force induced by multiple light beams is studied. We show dependence of the radiation pressure force on the illuminating distribution by numerical calculation, and we find that the strongest axial force is obtained by a specific spacing period of illuminating beams. Extending the optical manipulation technique by means of vertical-cavity surface-emitting laser (VCSEL) array sources [Appl. Opt. 40, 5430 (2001)], we are the first, to our knowledge, to demonstrate levitation of a particle and its translation while levitated by using a VCSEL array. The vertical position of the target particle can be controlled in a range of a few tens of micrometers with an accuracy of 2 microm or less. The analytical and experimental results suggest that use of multiple beams is an effective method to levitate a particle with low total illumination power. Some issues on the manipulation method that uses multiple beams are discussed.

Driver fatigue detection through multiple entropy fusion analysis in an EEG-based system.

PubMed

Min, Jianliang; Wang, Ping; Hu, Jianfeng

2017-01-01

Driver fatigue is an important contributor to road accidents, and fatigue detection has major implications for transportation safety. The aim of this research is to analyze the multiple entropy fusion method and evaluate several channel regions to effectively detect a driver's fatigue state based on electroencephalogram (EEG) records. First, we fused multiple entropies, i.e., spectral entropy, approximate entropy, sample entropy and fuzzy entropy, as features compared with autoregressive (AR) modeling by four classifiers. Second, we captured four significant channel regions according to weight-based electrodes via a simplified channel selection method. Finally, the evaluation model for detecting driver fatigue was established with four classifiers based on the EEG data from four channel regions. Twelve healthy subjects performed continuous simulated driving for 1-2 hours with EEG monitoring on a static simulator. The leave-one-out cross-validation approach obtained an accuracy of 98.3%, a sensitivity of 98.3% and a specificity of 98.2%. The experimental results verified the effectiveness of the proposed method, indicating that the multiple entropy fusion features are significant factors for inferring the fatigue state of a driver.

Reconstituting protein interaction networks using parameter-dependent domain-domain interactions

PubMed Central

2013-01-01

Background We can describe protein-protein interactions (PPIs) as sets of distinct domain-domain interactions (DDIs) that mediate the physical interactions between proteins. Experimental data confirm that DDIs are more consistent than their corresponding PPIs, lending support to the notion that analyses of DDIs may improve our understanding of PPIs and lead to further insights into cellular function, disease, and evolution. However, currently available experimental DDI data cover only a small fraction of all existing PPIs and, in the absence of structural data, determining which particular DDI mediates any given PPI is a challenge. Results We present two contributions to the field of domain interaction analysis. First, we introduce a novel computational strategy to merge domain annotation data from multiple databases. We show that when we merged yeast domain annotations from six annotation databases we increased the average number of domains per protein from 1.05 to 2.44, bringing it closer to the estimated average value of 3. Second, we introduce a novel computational method, parameter-dependent DDI selection (PADDS), which, given a set of PPIs, extracts a small set of domain pairs that can reconstruct the original set of protein interactions, while attempting to minimize false positives. Based on a set of PPIs from multiple organisms, our method extracted 27% more experimentally detected DDIs than existing computational approaches. Conclusions We have provided a method to merge domain annotation data from multiple sources, ensuring large and consistent domain annotation for any given organism. Moreover, we provided a method to extract a small set of DDIs from the underlying set of PPIs and we showed that, in contrast to existing approaches, our method was not biased towards DDIs with low or high occurrence counts. Finally, we used these two methods to highlight the influence of the underlying annotation density on the characteristics of extracted DDIs. Although increased annotations greatly expanded the possible DDIs, the lack of knowledge of the true biological false positive interactions still prevents an unambiguous assignment of domain interactions responsible for all protein network interactions. Executable files and examples are given at: http://www.bhsai.org/downloads/padds/ PMID:23651452

The search of the anisotropy of the primary cosmic radiation by the difference method

NASA Astrophysics Data System (ADS)

Pavlyuchenko, Victor; Martirosov, Romen; Nikolskaya, Natalia; Erlykin, Anatoly

2017-06-01

On the basis of experimental data obtained in the knee energy region with the GAMMA array an anomaly has been found in the mass composition of primary cosmic rays coming from the region of the VELA cluster. We used an original difference method which has high sensitivity, stability against accidental experimental errors and the possibility to separate anomalies connected with the laboratory coordinate system from anomalies observed in the celestial coordinates. The multiple scattering of the charged particles in the galactic magnetic fields makes it possible to study regions of the sky outside the direct visibility of the array.

Dependence of the multiplicities of secondary particles on the impact parameter in collisions of high-energy neon and iron nuclei with photoemulsion nuclei

NASA Technical Reports Server (NTRS)

Dudkin, V. E.; Kovalev, E. E.; Nefedov, N. A.; Antonchik, V. A.; Bogdanov, S. D.; Kosmach, V. F.; Likhachev, A. YU.; Benton, E. V.; Crawford, H. J.

1995-01-01

A method is proposed for finding the dependence of mean multiplicities of secondaries on the nucleus-collision impact parameter from the data on the total interaction ensemble. The impact parameter has been shown to completely define the mean characteristics of an individual interaction event. A difference has been found between experimental results and the data calculated in terms of the cascade-evaporation model at impact-parameter values below 3 fm.

Testing Interaction Effects without Discarding Variance.

ERIC Educational Resources Information Center

Lopez, Kay A.

Analysis of variance (ANOVA) and multiple regression are two of the most commonly used methods of data analysis in behavioral science research. Although ANOVA was intended for use with experimental designs, educational researchers have used ANOVA extensively in aptitude-treatment interaction (ATI) research. This practice tends to make researchers…

Multiconstrained gene clustering based on generalized projections

PubMed Central

2010-01-01

Background Gene clustering for annotating gene functions is one of the fundamental issues in bioinformatics. The best clustering solution is often regularized by multiple constraints such as gene expressions, Gene Ontology (GO) annotations and gene network structures. How to integrate multiple pieces of constraints for an optimal clustering solution still remains an unsolved problem. Results We propose a novel multiconstrained gene clustering (MGC) method within the generalized projection onto convex sets (POCS) framework used widely in image reconstruction. Each constraint is formulated as a corresponding set. The generalized projector iteratively projects the clustering solution onto these sets in order to find a consistent solution included in the intersection set that satisfies all constraints. Compared with previous MGC methods, POCS can integrate multiple constraints from different nature without distorting the original constraints. To evaluate the clustering solution, we also propose a new performance measure referred to as Gene Log Likelihood (GLL) that considers genes having more than one function and hence in more than one cluster. Comparative experimental results show that our POCS-based gene clustering method outperforms current state-of-the-art MGC methods. Conclusions The POCS-based MGC method can successfully combine multiple constraints from different nature for gene clustering. Also, the proposed GLL is an effective performance measure for the soft clustering solutions. PMID:20356386

The need for precise and well-documented experimental data on prompt fission neutron spectra from neutron-induced fission of 239Pu

DOE PAGES

Neudecker, Denise; Taddeucci, Terry Nicholas; Haight, Robert Cameron; ...

2016-01-06

The spectrum of neutrons emitted promptly after 239Pu(n,f)—a so-called prompt fission neutron spectrum (PFNS)—is a quantity of high interest, for instance, for reactor physics and global security. However, there are only few experimental data sets available that are suitable for evaluations. In addition, some of those data sets differ by more than their 1-σ uncertainty boundaries. We present the results of MCNP studies indicating that these differences are partly caused by underestimated multiple scattering contributions, over-corrected background, and inconsistent deconvolution methods. A detailed uncertainty quantification for suitable experimental data was undertaken including these effects, and test-evaluations were performed with themore » improved uncertainty information. The test-evaluations illustrate that the inadequately estimated effects and detailed uncertainty quantification have an impact on the evaluated PFNS and associated uncertainties as well as the neutron multiplicity of selected critical assemblies. A summary of data and documentation needs to improve the quality of the experimental database is provided based on the results of simulations and test-evaluations. Furthermore, given the possibly substantial distortion of the PFNS by multiple scattering and background effects, special care should be taken to reduce these effects in future measurements, e.g., by measuring the 239Pu PFNS as a ratio to either the 235U or 252Cf PFNS.« less

A review of advantages of high-efficiency X-ray spectrum imaging for analysis of nanostructured ferritic alloys

DOE PAGES

Parish, Chad M.; Miller, Michael K.

2014-12-09

Nanostructured ferritic alloys (NFAs) exhibit complex microstructures consisting of 100-500 nm ferrite grains, grain boundary solute enrichment, and multiple populations of precipitates and nanoclusters (NCs). Understanding these materials' excellent creep and radiation-tolerance properties requires a combination of multiple atomic-scale experimental techniques. Recent advances in scanning transmission electron microscopy (STEM) hardware and data analysis methods have the potential to revolutionize nanometer to micrometer scale materials analysis. The application of these methods is applied to NFAs as a test case and is compared to both conventional STEM methods as well as complementary methods such as scanning electron microscopy and atom probe tomography.more » In this paper, we review past results and present new results illustrating the effectiveness of latest-generation STEM instrumentation and data analysis.« less

Algorithms for image recovery calculation in extended single-shot phase-shifting digital holography

NASA Astrophysics Data System (ADS)

Hasegawa, Shin-ya; Hirata, Ryo

2018-04-01

The single-shot phase-shifting method of image recovery using an inclined reference wave has the advantages of reducing the effects of vibration, being capable of operating in real time, and affording low-cost sensing. In this method, relatively low reference angles compared with that in the conventional method using phase shift between three or four pixels has been required. We propose an extended single-shot phase-shifting technique which uses the multiple-step phase-shifting algorithm and the corresponding multiple pixels which are the same as that of the period of an interference fringe. We have verified the theory underlying this recovery method by means of Fourier spectral analysis and its effectiveness by evaluating the visibility of the image using a high-resolution pattern. Finally, we have demonstrated high-contrast image recovery experimentally using a resolution chart. This method can be used in a variety of applications such as color holographic interferometry.

XAFS Debye-Waller Factors Temperature-Dependent Expressions for Fe+2-Porphyrin Complexes

NASA Astrophysics Data System (ADS)

Dimakis, Nicholas; Bunker, Grant

2007-02-01

We present an efficient and accurate method for directly calculating single and multiple scattering X-ray absorption fine structure (XAFS) thermal Debye-Waller factors for Fe+2 -porphiryn complexes. The number of multiple scattering Debye-Waller factors on metal porphyrin centers exceeds the number of available parameters that XAFS experimental data can support during fitting with simulated spectra. Using the Density Functional Theory (DFT) under the hybrid functional of X3LYP, phonon normal mode spectrum properties are used to express the mean square variation of the half-scattering path length for a Fe+2 -porphiryn complex as a function of temperature for the most important single and multiple scattering paths of the complex thus virtually eliminating them from the fitting procedure. Modeled calculations are compared with corresponding values obtained from DFT-built and optimized Fe+2 -porphyrin bis-histidine structure as well as from experimental XAFS spectra previously reported. An excellent agreement between calculated and reference Debye-Waller factors for Fe+2-porphyrins is obtained.

Multilayer Volume Holographic Optical Memory

NASA Technical Reports Server (NTRS)

Markov, Vladimir; Millerd, James; Trolinger, James; Norrie, Mark; Downie, John; Timucin, Dogan; Lau, Sonie (Technical Monitor)

1998-01-01

We demonstrate a scheme for volume holographic storage based on the features of shift selectivity of a speckle reference wave hologram. The proposed recording method allows more efficient use of the recording medium and increases the storage density in comparison with spherical or plane-wave reference beams. Experimental results of multiple hologram storage and replay in a photorefractive crystal of iron-doped lithium niobate are presented. The mechanism of lateral and longitudinal shift selectivity are described theoretically and shown to agree with experimental measurements.

Agroecosystem research with big data and a modified scientific method using machine learning concepts

USDA-ARS?s Scientific Manuscript database

Long-term studies of agro-ecosystems at the continental scale are providing an extraordinary understanding of regional environmental dynamics. The new Long-Term Agro-ecosystem Research (LTAR) network (established in 2013) has designed an explicit research program with multiple USDA experimental wat...

Normalized Rotational Multiple Yield Surface Framework (NRMYSF) stress-strain curve prediction method based on small strain triaxial test data on undisturbed Auckland residual clay soils

NASA Astrophysics Data System (ADS)

Noor, M. J. Md; Ibrahim, A.; Rahman, A. S. A.

2018-04-01

Small strain triaxial test measurement is considered to be significantly accurate compared to the external strain measurement using conventional method due to systematic errors normally associated with the test. Three submersible miniature linear variable differential transducer (LVDT) mounted on yokes which clamped directly onto the soil sample at equally 120° from the others. The device setup using 0.4 N resolution load cell and 16 bit AD converter was capable of consistently resolving displacement of less than 1µm and measuring axial strains ranging from less than 0.001% to 2.5%. Further analysis of small strain local measurement data was performed using new Normalized Multiple Yield Surface Framework (NRMYSF) method and compared with existing Rotational Multiple Yield Surface Framework (RMYSF) prediction method. The prediction of shear strength based on combined intrinsic curvilinear shear strength envelope using small strain triaxial test data confirmed the significant improvement and reliability of the measurement and analysis methods. Moreover, the NRMYSF method shows an excellent data prediction and significant improvement toward more reliable prediction of soil strength that can reduce the cost and time of experimental laboratory test.

Cross-Situational Learning with Bayesian Generative Models for Multimodal Category and Word Learning in Robots

PubMed Central

Taniguchi, Akira; Taniguchi, Tadahiro; Cangelosi, Angelo

2017-01-01

In this paper, we propose a Bayesian generative model that can form multiple categories based on each sensory-channel and can associate words with any of the four sensory-channels (action, position, object, and color). This paper focuses on cross-situational learning using the co-occurrence between words and information of sensory-channels in complex situations rather than conventional situations of cross-situational learning. We conducted a learning scenario using a simulator and a real humanoid iCub robot. In the scenario, a human tutor provided a sentence that describes an object of visual attention and an accompanying action to the robot. The scenario was set as follows: the number of words per sensory-channel was three or four, and the number of trials for learning was 20 and 40 for the simulator and 25 and 40 for the real robot. The experimental results showed that the proposed method was able to estimate the multiple categorizations and to learn the relationships between multiple sensory-channels and words accurately. In addition, we conducted an action generation task and an action description task based on word meanings learned in the cross-situational learning scenario. The experimental results showed that the robot could successfully use the word meanings learned by using the proposed method. PMID:29311888

A novel algorithm for solving the true coincident counting issues in Monte Carlo simulations for radiation spectroscopy.

PubMed

Guan, Fada; Johns, Jesse M; Vasudevan, Latha; Zhang, Guoqing; Tang, Xiaobin; Poston, John W; Braby, Leslie A

2015-06-01

Coincident counts can be observed in experimental radiation spectroscopy. Accurate quantification of the radiation source requires the detection efficiency of the spectrometer, which is often experimentally determined. However, Monte Carlo analysis can be used to supplement experimental approaches to determine the detection efficiency a priori. The traditional Monte Carlo method overestimates the detection efficiency as a result of omitting coincident counts caused mainly by multiple cascade source particles. In this study, a novel "multi-primary coincident counting" algorithm was developed using the Geant4 Monte Carlo simulation toolkit. A high-purity Germanium detector for ⁶⁰Co gamma-ray spectroscopy problems was accurately modeled to validate the developed algorithm. The simulated pulse height spectrum agreed well qualitatively with the measured spectrum obtained using the high-purity Germanium detector. The developed algorithm can be extended to other applications, with a particular emphasis on challenging radiation fields, such as counting multiple types of coincident radiations released from nuclear fission or used nuclear fuel.

Theory and simulations of covariance mapping in multiple dimensions for data analysis in high-event-rate experiments

NASA Astrophysics Data System (ADS)

Zhaunerchyk, V.; Frasinski, L. J.; Eland, J. H. D.; Feifel, R.

2014-05-01

Multidimensional covariance analysis and its validity for correlation of processes leading to multiple products are investigated from a theoretical point of view. The need to correct for false correlations induced by experimental parameters which fluctuate from shot to shot, such as the intensity of self-amplified spontaneous emission x-ray free-electron laser pulses, is emphasized. Threefold covariance analysis based on simple extension of the two-variable formulation is shown to be valid for variables exhibiting Poisson statistics. In this case, false correlations arising from fluctuations in an unstable experimental parameter that scale linearly with signals can be eliminated by threefold partial covariance analysis, as defined here. Fourfold covariance based on the same simple extension is found to be invalid in general. Where fluctuations in an unstable parameter induce nonlinear signal variations, a technique of contingent covariance analysis is proposed here to suppress false correlations. In this paper we also show a method to eliminate false correlations associated with fluctuations of several unstable experimental parameters.

Formation and emission mechanisms of Ag nanoclusters in the Ar matrix assembly cluster source

NASA Astrophysics Data System (ADS)

Zhao, Junlei; Cao, Lu; Palmer, Richard E.; Nordlund, Kai; Djurabekova, Flyura

2017-11-01

In this paper, we study the mechanisms of growth of Ag nanoclusters in a solid Ar matrix and the emission of these nanoclusters from the matrix by a combination of experimental and theoretical methods. The molecular dynamics simulations show that the cluster growth mechanism can be described as "thermal spike-enhanced clustering" in multiple sequential ion impact events. We further show that experimentally observed large sputtered metal clusters cannot be formed by direct sputtering of Ag mixed in the Ar. Instead, we describe the mechanism of emission of the metal nanocluster that, at first, is formed in the cryogenic matrix due to multiple ion impacts, and then is emitted as a result of the simultaneous effects of interface boiling and spring force. We also develop an analytical model describing this size-dependent cluster emission. The model bridges the atomistic simulations and experimental time and length scales, and allows increasing the controllability of fast generation of nanoclusters in experiments with a high production rate.

Quantum tomography for collider physics: illustrations with lepton-pair production

NASA Astrophysics Data System (ADS)

Martens, John C.; Ralston, John P.; Takaki, J. D. Tapia

2018-01-01

Quantum tomography is a method to experimentally extract all that is observable about a quantum mechanical system. We introduce quantum tomography to collider physics with the illustration of the angular distribution of lepton pairs. The tomographic method bypasses much of the field-theoretic formalism to concentrate on what can be observed with experimental data. We provide a practical, experimentally driven guide to model-independent analysis using density matrices at every step. Comparison with traditional methods of analyzing angular correlations of inclusive reactions finds many advantages in the tomographic method, which include manifest Lorentz covariance, direct incorporation of positivity constraints, exhaustively complete polarization information, and new invariants free from frame conventions. For example, experimental data can determine the entanglement entropy of the production process. We give reproducible numerical examples and provide a supplemental standalone computer code that implements the procedure. We also highlight a property of complex positivity that guarantees in a least-squares type fit that a local minimum of a χ 2 statistic will be a global minimum: There are no isolated local minima. This property with an automated implementation of positivity promises to mitigate issues relating to multiple minima and convention dependence that have been problematic in previous work on angular distributions.

Metainference: A Bayesian inference method for heterogeneous systems.

PubMed

Bonomi, Massimiliano; Camilloni, Carlo; Cavalli, Andrea; Vendruscolo, Michele

2016-01-01

Modeling a complex system is almost invariably a challenging task. The incorporation of experimental observations can be used to improve the quality of a model and thus to obtain better predictions about the behavior of the corresponding system. This approach, however, is affected by a variety of different errors, especially when a system simultaneously populates an ensemble of different states and experimental data are measured as averages over such states. To address this problem, we present a Bayesian inference method, called "metainference," that is able to deal with errors in experimental measurements and with experimental measurements averaged over multiple states. To achieve this goal, metainference models a finite sample of the distribution of models using a replica approach, in the spirit of the replica-averaging modeling based on the maximum entropy principle. To illustrate the method, we present its application to a heterogeneous model system and to the determination of an ensemble of structures corresponding to the thermal fluctuations of a protein molecule. Metainference thus provides an approach to modeling complex systems with heterogeneous components and interconverting between different states by taking into account all possible sources of errors.

Statistical detection of EEG synchrony using empirical bayesian inference.

PubMed

Singh, Archana K; Asoh, Hideki; Takeda, Yuji; Phillips, Steven

2015-01-01

There is growing interest in understanding how the brain utilizes synchronized oscillatory activity to integrate information across functionally connected regions. Computing phase-locking values (PLV) between EEG signals is a popular method for quantifying such synchronizations and elucidating their role in cognitive tasks. However, high-dimensionality in PLV data incurs a serious multiple testing problem. Standard multiple testing methods in neuroimaging research (e.g., false discovery rate, FDR) suffer severe loss of power, because they fail to exploit complex dependence structure between hypotheses that vary in spectral, temporal and spatial dimension. Previously, we showed that a hierarchical FDR and optimal discovery procedures could be effectively applied for PLV analysis to provide better power than FDR. In this article, we revisit the multiple comparison problem from a new Empirical Bayes perspective and propose the application of the local FDR method (locFDR; Efron, 2001) for PLV synchrony analysis to compute FDR as a posterior probability that an observed statistic belongs to a null hypothesis. We demonstrate the application of Efron's Empirical Bayes approach for PLV synchrony analysis for the first time. We use simulations to validate the specificity and sensitivity of locFDR and a real EEG dataset from a visual search study for experimental validation. We also compare locFDR with hierarchical FDR and optimal discovery procedures in both simulation and experimental analyses. Our simulation results showed that the locFDR can effectively control false positives without compromising on the power of PLV synchrony inference. Our results from the application locFDR on experiment data detected more significant discoveries than our previously proposed methods whereas the standard FDR method failed to detect any significant discoveries.

Repetition rate multiplication of frequency comb using all-pass fiber resonator

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

Yang, Lijun; Yang, Honglei; Zhang, Hongyuan

2016-09-15

We propose a stable method for repetition rate multiplication of a 250-MHz Er-fiber frequency comb by a phase-locked all-pass fiber ring resonator, whose phase-locking configuration is simple. The optical path length of the fiber ring resonator is automatically controlled to be accurately an odd multiple of half of the original cavity length using an electronical phase-locking unit with an optical delay line. As for shorter cavity length of the comb, high-order odd multiple is preferable. Because the power loss depends only on the net-attenuation of the fiber ring resonator, the energetic efficiency of the proposed method is high. The inputmore » and output optical spectrums show that the spectral width of the frequency comb is clearly preserved. Besides, experimental results show less pulse intensity fluctuation and 35 dB suppression ratio of side-modes while providing a good long-term and short-term frequency stability. Higher-order repetition rate multiplication to several GHz can be obtained by using several fiber ring resonators in cascade configuration.« less

Building Diversified Multiple Trees for classification in high dimensional noisy biomedical data.

PubMed

Li, Jiuyong; Liu, Lin; Liu, Jixue; Green, Ryan

2017-12-01

It is common that a trained classification model is applied to the operating data that is deviated from the training data because of noise. This paper will test an ensemble method, Diversified Multiple Tree (DMT), on its capability for classifying instances in a new laboratory using the classifier built on the instances of another laboratory. DMT is tested on three real world biomedical data sets from different laboratories in comparison with four benchmark ensemble methods, AdaBoost, Bagging, Random Forests, and Random Trees. Experiments have also been conducted on studying the limitation of DMT and its possible variations. Experimental results show that DMT is significantly more accurate than other benchmark ensemble classifiers on classifying new instances of a different laboratory from the laboratory where instances are used to build the classifier. This paper demonstrates that an ensemble classifier, DMT, is more robust in classifying noisy data than other widely used ensemble methods. DMT works on the data set that supports multiple simple trees.

Multiscale optical simulation settings: challenging applications handled with an iterative ray-tracing FDTD interface method.

PubMed

Leiner, Claude; Nemitz, Wolfgang; Schweitzer, Susanne; Kuna, Ladislav; Wenzl, Franz P; Hartmann, Paul; Satzinger, Valentin; Sommer, Christian

2016-03-20

We show that with an appropriate combination of two optical simulation techniques-classical ray-tracing and the finite difference time domain method-an optical device containing multiple diffractive and refractive optical elements can be accurately simulated in an iterative simulation approach. We compare the simulation results with experimental measurements of the device to discuss the applicability and accuracy of our iterative simulation procedure.

Integrated structural control design of large space structures

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

Allen, J.J.; Lauffer, J.P.

1995-01-01

Active control of structures has been under intensive development for the last ten years. Reference 2 reviews much of the identification and control technology for structural control developed during this time. The technology was initially focused on space structure and weapon applications; however, recently the technology is also being directed toward applications in manufacturing and transportation. Much of this technology focused on multiple-input/multiple-output (MIMO) identification and control methodology because many of the applications require a coordinated control involving multiple disturbances and control objectives where multiple actuators and sensors are necessary for high performance. There have been many optimal robust controlmore » methods developed for the design of MIMO robust control laws; however, there appears to be a significant gap between the theoretical development and experimental evaluation of control and identification methods to address structural control applications. Many methods have been developed for MIMO identification and control of structures, such as the Eigensystem Realization Algorithm (ERA), Q-Markov Covariance Equivalent Realization (Q-Markov COVER) for identification; and, Linear Quadratic Gaussian (LQG), Frequency Weighted LQG and H-/ii-synthesis methods for control. Upon implementation, many of the identification and control methods have shown limitations such as the excitation of unmodelled dynamics and sensitivity to system parameter variations. As a result, research on methods which address these problems have been conducted.« less

Experimental Study of Flexible Plate Vibration Control by Using Two-Loop Sliding Mode Control Strategy

NASA Astrophysics Data System (ADS)

Yang, Jingyu; Lin, Jiahui; Liu, Yuejun; Yang, Kang; Zhou, Lanwei; Chen, Guoping

2017-08-01

It is well known that intelligent control theory has been used in many research fields, novel modeling method (DROMM) is used for flexible rectangular active vibration control, and then the validity of new model is confirmed by comparing finite element model with new model. In this paper, taking advantage of the dynamics of flexible rectangular plate, a two-loop sliding mode (TSM) MIMO approach is introduced for designing multiple-input multiple-output continuous vibration control system, which can overcome uncertainties, disturbances or unstable dynamics. An illustrative example is given in order to show the feasibility of the method. Numerical simulations and experiment confirm the effectiveness of the proposed TSM MIMO controller.

Effect of acupressure on fatigue in women with multiple sclerosis.

PubMed

Bastani, Farideh; Sobhani, Marzie; Emamzadeh Ghasemi, Hormat Sadat

2015-01-26

Multiple sclerosis (MS) is the most common cause of progressive neurological disability. The prevalence of MS is much more common in women than men. The women are exposed to a variety of symptoms including fatigue. Acupressure is a noninvasive procedure that can be used to control symptoms including fatigue. The aim of the study was to evaluate the effect of acupressure on fatigue in women with multiple sclerosis. A randomized clinical trial was conducted on 100 women with MS at Tehran MS Association. The subjects were equally allocated to experimental group and a placebo group (50 women per group) by blocking randomization method. The experimental group were received acupressure, at the true points (ST36, SP6, LI4) and the placebo group, were received touching at the same points. Fatigue was measured by a Fatigue Severity Scale (FSS) in the groups at immediately prior to, two and four weeks after the beginning of the intervention. The data was analyzed using descriptive and inferential statistics by SPSS version 17. The findings indicated no differences in demographic characteristics and the severity of fatigue at the baseline in two groups (p=0.54). But there were significant reductions of the mean score of fatigue in the experimental group compared to the placebo group immediately, two and four weeks after the intervention respectively (p=0.03, p?0/001, p=0.04). According to the findings, the study provided an alternative method for health care providers including nurses to train acupressure to the clients with MS to managing their fatigue.

Theoretical and experimental investigation of multispectral photoacoustic osteoporosis detection method

NASA Astrophysics Data System (ADS)

Steinberg, Idan; Hershkovich, Hadas Sara; Gannot, Israel; Eyal, Avishay

2014-03-01

Osteoporosis is a widespread disorder, which has a catastrophic impact on patients lives and overwhelming related to healthcare costs. Recently, we proposed a multispectral photoacoustic technique for early detection of osteoporosis. Such technique has great advantages over pure ultrasonic or optical methods as it allows the deduction of both bone functionality from the bone absorption spectrum and bone resistance to fracture from the characteristics of the ultrasound propagation. We demonstrated the propagation of multiple acoustic modes in animal bones in-vitro. To further investigate the effects of multiple wavelength excitations and of induced osteoporosis on the PA signal a multispectral photoacoustic system is presented. The experimental investigation is based on measuring the interference of multiple acoustic modes. The performance of the system is evaluated and a simple two mode theoretical model is fitted to the measured phase signals. The results show that such PA technique is accurate and repeatable. Then a multiple wavelength excitation is tested. It is shown that the PA response due to different excitation wavelengths revels that absorption by the different bone constitutes has a profound effect on the mode generation. The PA response is measured in single wavelength before and after induced osteoporosis. Results show that induced osteoporosis alters the measured amplitude and phase in a consistent manner which allows the detection of the onset of osteoporosis. These results suggest that a complete characterization of the bone over a region of both acoustic and optical frequencies might be used as a powerful tool for in-vivo bone evaluation.

Manifold Regularized Multitask Feature Learning for Multimodality Disease Classification

PubMed Central

Jie, Biao; Zhang, Daoqiang; Cheng, Bo; Shen, Dinggang

2015-01-01

Multimodality based methods have shown great advantages in classification of Alzheimer’s disease (AD) and its prodromal stage, that is, mild cognitive impairment (MCI). Recently, multitask feature selection methods are typically used for joint selection of common features across multiple modalities. However, one disadvantage of existing multimodality based methods is that they ignore the useful data distribution information in each modality, which is essential for subsequent classification. Accordingly, in this paper we propose a manifold regularized multitask feature learning method to preserve both the intrinsic relatedness among multiple modalities of data and the data distribution information in each modality. Specifically, we denote the feature learning on each modality as a single task, and use group-sparsity regularizer to capture the intrinsic relatedness among multiple tasks (i.e., modalities) and jointly select the common features from multiple tasks. Furthermore, we introduce a new manifold-based Laplacian regularizer to preserve the data distribution information from each task. Finally, we use the multikernel support vector machine method to fuse multimodality data for eventual classification. Conversely, we also extend our method to the semisupervised setting, where only partial data are labeled. We evaluate our method using the baseline magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (FDG-PET), and cerebrospinal fluid (CSF) data of subjects from AD neuroimaging initiative database. The experimental results demonstrate that our proposed method can not only achieve improved classification performance, but also help to discover the disease-related brain regions useful for disease diagnosis. PMID:25277605

Study and characterization of a MEMS micromirror device

NASA Astrophysics Data System (ADS)

Furlong, Cosme; Pryputniewicz, Ryszard J.

2004-08-01

In this paper, advances in our study and characterization of a MEMS micromirror device are presented. The micromirror device, of 510 mm characteristic length, operates in a dynamic mode with a maximum displacement on the order of 10 mm along its principal optical axis and oscillation frequencies of up to 1.3 kHz. Developments are carried on by analytical, computational, and experimental methods. Analytical and computational nonlinear geometrical models are developed in order to determine the optimal loading-displacement operational characteristics of the micromirror. Due to the operational mode of the micromirror, the experimental characterization of its loading-displacement transfer function requires utilization of advanced optical metrology methods. Optoelectronic holography (OEH) methodologies based on multiple wavelengths that we are developing to perform such characterization are described. It is shown that the analytical, computational, and experimental approach is effective in our developments.

Investigation of multiple scattering effects in aerosols

NASA Technical Reports Server (NTRS)

Deepak, A.

1980-01-01

The results are presented of investigations on the various aspects of multiple scattering effects on visible and infrared laser beams transversing dense fog oil aerosols contained in a chamber (4' x 4' x 9'). The report briefly describes: (1) the experimental details and measurements; (2) analytical representation of the aerosol size distribution data by two analytical models (the regularized power law distribution and the inverse modified gamma distribution); (3) retrieval of aerosol size distributions from multispectral optical depth measurements by two methods (the two and three parameter fast table search methods and the nonlinear least squares method); (4) modeling of the effects of aerosol microphysical (coagulation and evaporation) and dynamical processes (gravitational settling) on the temporal behavior of aerosol size distribution, and hence on the extinction of four laser beams with wavelengths 0.44, 0.6328, 1.15, and 3.39 micrometers; and (5) the exact and approximate formulations for four methods for computing the effects of multiple scattering on the transmittance of laser beams in dense aerosols, all of which are based on the solution of the radiative transfer equation under the small angle approximation.

Investigation of multiple scattering effects in aerosols

NASA Astrophysics Data System (ADS)

Deepak, A.

1980-05-01

The results are presented of investigations on the various aspects of multiple scattering effects on visible and infrared laser beams transversing dense fog oil aerosols contained in a chamber (4' x 4' x 9'). The report briefly describes: (1) the experimental details and measurements; (2) analytical representation of the aerosol size distribution data by two analytical models (the regularized power law distribution and the inverse modified gamma distribution); (3) retrieval of aerosol size distributions from multispectral optical depth measurements by two methods (the two and three parameter fast table search methods and the nonlinear least squares method); (4) modeling of the effects of aerosol microphysical (coagulation and evaporation) and dynamical processes (gravitational settling) on the temporal behavior of aerosol size distribution, and hence on the extinction of four laser beams with wavelengths 0.44, 0.6328, 1.15, and 3.39 micrometers; and (5) the exact and approximate formulations for four methods for computing the effects of multiple scattering on the transmittance of laser beams in dense aerosols, all of which are based on the solution of the radiative transfer equation under the small angle approximation.

Harmonic Quantum Coherence of Multiple Excitons in PbS/CdS Core-Shell Nanocrystals

NASA Astrophysics Data System (ADS)

Tahara, Hirokazu; Sakamoto, Masanori; Teranishi, Toshiharu; Kanemitsu, Yoshihiko

2017-12-01

The generation and recombination dynamics of multiple excitons in nanocrystals (NCs) have attracted much attention from the viewpoints of fundamental physics and device applications. However, the quantum coherence of multiple exciton states in NCs still remains unclear due to a lack of experimental support. Here, we report the first observation of harmonic dipole oscillations in PbS/CdS core-shell NCs using a phase-locked interference detection method for transient absorption. From the ultrafast coherent dynamics and excitation-photon-fluence dependence of the oscillations, we found that multiple excitons cause the harmonic dipole oscillations with ω , 2 ω , and 3 ω oscillations, even though the excitation pulse energy is set to the exciton resonance frequency, ω . This observation is closely related to the quantum coherence of multiple exciton states in NCs, providing important insights into multiple exciton generation mechanisms.

GeneNetFinder2: Improved Inference of Dynamic Gene Regulatory Relations with Multiple Regulators.

PubMed

Han, Kyungsook; Lee, Jeonghoon

2016-01-01

A gene involved in complex regulatory interactions may have multiple regulators since gene expression in such interactions is often controlled by more than one gene. Another thing that makes gene regulatory interactions complicated is that regulatory interactions are not static, but change over time during the cell cycle. Most research so far has focused on identifying gene regulatory relations between individual genes in a particular stage of the cell cycle. In this study we developed a method for identifying dynamic gene regulations of several types from the time-series gene expression data. The method can find gene regulations with multiple regulators that work in combination or individually as well as those with single regulators. The method has been implemented as the second version of GeneNetFinder (hereafter called GeneNetFinder2) and tested on several gene expression datasets. Experimental results with gene expression data revealed the existence of genes that are not regulated by individual genes but rather by a combination of several genes. Such gene regulatory relations cannot be found by conventional methods. Our method finds such regulatory relations as well as those with multiple, independent regulators or single regulators, and represents gene regulatory relations as a dynamic network in which different gene regulatory relations are shown in different stages of the cell cycle. GeneNetFinder2 is available at http://bclab.inha.ac.kr/GeneNetFinder and will be useful for modeling dynamic gene regulations with multiple regulators.

Three-dimensional ordered particulate structures: Method to retrieve characteristics from photonic band gap data

NASA Astrophysics Data System (ADS)

Miskevich, Alexander A.; Loiko, Valery A.

2015-01-01

A method to retrieve characteristics of ordered particulate structures, such as photonic crystals, is proposed. It is based on the solution of the inverse problem using data on the photonic band gap (PBG). The quasicrystalline approximation (QCA) of the theory of multiple scattering of waves and the transfer matrix method (TMM) are used. Retrieval of the refractive index of particles is demonstrated. Refractive indices of the artificial opal particles are estimated using the published experimental data.

Estimating the number of people in crowded scenes

NASA Astrophysics Data System (ADS)

Kim, Minjin; Kim, Wonjun; Kim, Changick

2011-01-01

This paper presents a method to estimate the number of people in crowded scenes without using explicit object segmentation or tracking. The proposed method consists of three steps as follows: (1) extracting space-time interest points using eigenvalues of the local spatio-temporal gradient matrix, (2) generating crowd regions based on space-time interest points, and (3) estimating the crowd density based on the multiple regression. In experimental results, the efficiency and robustness of our proposed method are demonstrated by using PETS 2009 dataset.

A method for operative quantitative interpretation of multispectral images of biological tissues

NASA Astrophysics Data System (ADS)

Lisenko, S. A.; Kugeiko, M. M.

2013-10-01

A method for operative retrieval of spatial distributions of biophysical parameters of a biological tissue by using a multispectral image of it has been developed. The method is based on multiple regressions between linearly independent components of the diffuse reflection spectrum of the tissue and unknown parameters. Possibilities of the method are illustrated by an example of determining biophysical parameters of the skin (concentrations of melanin, hemoglobin and bilirubin, blood oxygenation, and scattering coefficient of the tissue). Examples of quantitative interpretation of the experimental data are presented.

On the effect of boundary layer growth on the stability of compressible flows

NASA Technical Reports Server (NTRS)

El-Hady, N. M.

1981-01-01

The method of multiple scales is used to describe a formally correct method based on the nonparallel linear stability theory, that examines the two and three dimensional stability of compressible boundary layer flows. The method is applied to the supersonic flat plate layer at Mach number 4.5. The theoretical growth rates are in good agreement with experimental results. The method is also applied to the infinite-span swept wing transonic boundary layer with suction to evaluate the effect of the nonparallel flow on the development of crossflow disturbances.

IR-IR Conformation Specific Spectroscopy of Na+(Glucose) Adducts

NASA Astrophysics Data System (ADS)

Voss, Jonathan M.; Kregel, Steven J.; Fischer, Kaitlyn C.; Garand, Etienne

2018-01-01

We report an IR-IR double resonance study of the structural landscape present in the Na+(glucose) complex. Our experimental approach involves minimal modifications to a typical IR predissociation setup, and can be carried out via ion-dip or isomer-burning methods, providing additional flexibility to suit different experimental needs. In the current study, the single-laser IR predissociation spectrum of Na+(glucose), which clearly indicates contributions from multiple structures, was experimentally disentangled to reveal the presence of three α-conformers and five β-conformers. Comparisons with calculations show that these eight conformations correspond to the lowest energy gas-phase structures with distinctive Na+ coordination. [Figure not available: see fulltext.

Experimental palaeobiomechanics: What can engineering tell us about evolution in deep time?

NASA Astrophysics Data System (ADS)

Anderson, Philip

2016-04-01

What did Tyrannosaurus rex eat? This is the sort of question that immediately bombards any palaeontologist when interacting with the general public. Even among scientists, how extinct animals moved or fed is a major objective of the palaeobiological research agenda. The last decade has seen a sharp increase in the technology and experimental methods available for collecting biomechanical data, which has greatly improved out ability to examine the function of both live and extinct animals. With new technologies and methods come new pitfalls and opportunities. In this review, I address three aspects of experimental biomechanics that exemplify the challenges and opportunities it provides for addressing deep-time problems in palaeontology. 1) Interpretation: It has never been easier to acquire large amounts of high-quality biomechanical data on extinct animals. However, the lack of behavioural information means that interpreting this data can be problematic. We will never know precisely what a dinosaur ate, but we can explore what constraints there might have been on the mechanical function of its jaws. Palaeobiomechanics defines potential function and becomes especially effective when dealing with multiple examples. 2) Comparison: Understanding the potential function of one extinct animal is interesting; however, examining mechanical features across multiple taxa allows for a greater understanding of biomechanical variation. Comparative studies help identify common trends and underlying mechanical principles which can have long reaching influences on morphological evolution. 3) Evolution: The physical principles established through comparative biomechanical studies can be utilized in phylogenetic comparative methods in order to explore evolutionary morphology across clades. Comparative evolutionary biomechanics offers potential for exploring the evolution of functional systems in deep time utilizing experimental biomechanical data.

Practical implementation of spectral-intensity dispersion-canceled optical coherence tomography with artifact suppression

NASA Astrophysics Data System (ADS)

Shirai, Tomohiro; Friberg, Ari T.

2018-04-01

Dispersion-canceled optical coherence tomography (OCT) based on spectral intensity interferometry was devised as a classical counterpart of quantum OCT to enhance the basic performance of conventional OCT. In this paper, we demonstrate experimentally that an alternative method of realizing this kind of OCT by means of two optical fiber couplers and a single spectrometer is a more practical and reliable option than the existing methods proposed previously. Furthermore, we develop a recipe for reducing multiple artifacts simultaneously on the basis of simple averaging and verify experimentally that it works successfully in the sense that all the artifacts are mitigated effectively and only the true signals carrying structural information about the sample survive.

Efficient composite broadband polarization retarders and polarization filters

NASA Astrophysics Data System (ADS)

Dimova, E.; Ivanov, S. S.; Popkirov, G.; Vitanov, N. V.

2014-12-01

A new type of broadband polarization half-wave retarder and narrowband polarization filters are described and experimentally tested. Both, the retarders and the filters are designed as composite stacks of standard optical half-wave plates, each of them twisted at specific angles. The theoretical background of the proposed optical devices was obtained by analogy with the method of composite pulses, known from the nuclear and quantum physics. We show that combining two composite filters built from different numbers and types of waveplates, the transmission spectrum is reduced from about 700 nm to about 10 nm width.We experimentally demonstrate that this method can be applied to different types of waveplates (broadband, zero-order, multiple order, etc.).

An efficient approach to understanding and predicting the effects of multiple task characteristics on performance.

PubMed

Richardson, Miles

2017-04-01

In ergonomics there is often a need to identify and predict the separate effects of multiple factors on performance. A cost-effective fractional factorial approach to understanding the relationship between task characteristics and task performance is presented. The method has been shown to provide sufficient independent variability to reveal and predict the effects of task characteristics on performance in two domains. The five steps outlined are: selection of performance measure, task characteristic identification, task design for user trials, data collection, regression model development and task characteristic analysis. The approach can be used for furthering knowledge of task performance, theoretical understanding, experimental control and prediction of task performance. Practitioner Summary: A cost-effective method to identify and predict the separate effects of multiple factors on performance is presented. The five steps allow a better understanding of task factors during the design process.

Multiple descriptions based on multirate coding for JPEG 2000 and H.264/AVC.

PubMed

Tillo, Tammam; Baccaglini, Enrico; Olmo, Gabriella

2010-07-01

Multiple description coding (MDC) makes use of redundant representations of multimedia data to achieve resiliency. Descriptions should be generated so that the quality obtained when decoding a subset of them only depends on their number and not on the particular received subset. In this paper, we propose a method based on the principle of encoding the source at several rates, and properly blending the data encoded at different rates to generate the descriptions. The aim is to achieve efficient redundancy exploitation, and easy adaptation to different network scenarios by means of fine tuning of the encoder parameters. We apply this principle to both JPEG 2000 images and H.264/AVC video data. We consider as the reference scenario the distribution of contents on application-layer overlays with multiple-tree topology. The experimental results reveal that our method favorably compares with state-of-art MDC techniques.

E-Nose Vapor Identification Based on Dempster-Shafer Fusion of Multiple Classifiers

NASA Technical Reports Server (NTRS)

Li, Winston; Leung, Henry; Kwan, Chiman; Linnell, Bruce R.

2005-01-01

Electronic nose (e-nose) vapor identification is an efficient approach to monitor air contaminants in space stations and shuttles in order to ensure the health and safety of astronauts. Data preprocessing (measurement denoising and feature extraction) and pattern classification are important components of an e-nose system. In this paper, a wavelet-based denoising method is applied to filter the noisy sensor measurements. Transient-state features are then extracted from the denoised sensor measurements, and are used to train multiple classifiers such as multi-layer perceptions (MLP), support vector machines (SVM), k nearest neighbor (KNN), and Parzen classifier. The Dempster-Shafer (DS) technique is used at the end to fuse the results of the multiple classifiers to get the final classification. Experimental analysis based on real vapor data shows that the wavelet denoising method can remove both random noise and outliers successfully, and the classification rate can be improved by using classifier fusion.

Influence of laser irradiation on demyelination of nervous fibers

NASA Astrophysics Data System (ADS)

Melnik, Nataly O.; Plaksij, Yu. S.; Mamilov, Serge A.

2000-11-01

Problem demyelinating diseases from actual in modern of neurology. Main disease of this group - multiple sclerosis, which morphological manifestation is the process demyelineation - disintegration of myelin, which covers axial cylinders of nervous filaments. The outcome of such damage is violation of realization of nervous impulses, dissonance of implement and coordination functions. Most typical the feature of a multiple sclerosis is origin of repeated remissions, which compact with indication remyelination. In development of disease the large role is played by modifications of immunological of a reactivity of an organism. The purpose of the title is development of new methods of treatment of a multiple sclerosis because of lasertherapy. For thsi purpose the influence of a laser exposure on demyelination and remyelination processes will be investigated, is investigated pathological fabrics at microscopic and submicroscopic levels. The study of proceses demyelination and remyelination will be conducted on experimental animals (rats), which are sick experimental allergic encephalomyelitis (EAE), that is the most adequate model of a multiple sclerosis. The patients' EAE animals will be subjected to treatment by a laser exposure. For want of it there will be determinate optimum lengths of waves, dozes and modes of laser radiation.

FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants.

PubMed

Bednar, David; Beerens, Koen; Sebestova, Eva; Bendl, Jaroslav; Khare, Sagar; Chaloupkova, Radka; Prokop, Zbynek; Brezovsky, Jan; Baker, David; Damborsky, Jiri

2015-11-01

There is great interest in increasing proteins' stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited reliability of predictions and potentially antagonistic effects of substitutions, only single-point mutations are usually predicted in silico, experimentally verified and then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present FireProt, a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. FireProt's reliability and applicability was demonstrated by validating its predictions against 656 mutations from the ProTherm database. We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and γ-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (ΔTm = 24°C and 21°C) by constructing and characterizing only a handful of multiple-point mutants. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications.

Simultaneous phylogeny reconstruction and multiple sequence alignment

PubMed Central

Yue, Feng; Shi, Jian; Tang, Jijun

2009-01-01

Background A phylogeny is the evolutionary history of a group of organisms. To date, sequence data is still the most used data type for phylogenetic reconstruction. Before any sequences can be used for phylogeny reconstruction, they must be aligned, and the quality of the multiple sequence alignment has been shown to affect the quality of the inferred phylogeny. At the same time, all the current multiple sequence alignment programs use a guide tree to produce the alignment and experiments showed that good guide trees can significantly improve the multiple alignment quality. Results We devise a new algorithm to simultaneously align multiple sequences and search for the phylogenetic tree that leads to the best alignment. We also implemented the algorithm as a C program package, which can handle both DNA and protein data and can take simple cost model as well as complex substitution matrices, such as PAM250 or BLOSUM62. The performance of the new method are compared with those from other popular multiple sequence alignment tools, including the widely used programs such as ClustalW and T-Coffee. Experimental results suggest that this method has good performance in terms of both phylogeny accuracy and alignment quality. Conclusion We present an algorithm to align multiple sequences and reconstruct the phylogenies that minimize the alignment score, which is based on an efficient algorithm to solve the median problems for three sequences. Our extensive experiments suggest that this method is very promising and can produce high quality phylogenies and alignments. PMID:19208110

A Multicriteria Decision Making Approach for Estimating the Number of Clusters in a Data Set

PubMed Central

Peng, Yi; Zhang, Yong; Kou, Gang; Shi, Yong

2012-01-01

Determining the number of clusters in a data set is an essential yet difficult step in cluster analysis. Since this task involves more than one criterion, it can be modeled as a multiple criteria decision making (MCDM) problem. This paper proposes a multiple criteria decision making (MCDM)-based approach to estimate the number of clusters for a given data set. In this approach, MCDM methods consider different numbers of clusters as alternatives and the outputs of any clustering algorithm on validity measures as criteria. The proposed method is examined by an experimental study using three MCDM methods, the well-known clustering algorithm–k-means, ten relative measures, and fifteen public-domain UCI machine learning data sets. The results show that MCDM methods work fairly well in estimating the number of clusters in the data and outperform the ten relative measures considered in the study. PMID:22870181

Multiple-instance ensemble learning for hyperspectral images

NASA Astrophysics Data System (ADS)

Ergul, Ugur; Bilgin, Gokhan

2017-10-01

An ensemble framework for multiple-instance (MI) learning (MIL) is introduced for use in hyperspectral images (HSIs) by inspiring the bagging (bootstrap aggregation) method in ensemble learning. Ensemble-based bagging is performed by a small percentage of training samples, and MI bags are formed by a local windowing process with variable window sizes on selected instances. In addition to bootstrap aggregation, random subspace is another method used to diversify base classifiers. The proposed method is implemented using four MIL classification algorithms. The classifier model learning phase is carried out with MI bags, and the estimation phase is performed over single-test instances. In the experimental part of the study, two different HSIs that have ground-truth information are used, and comparative results are demonstrated with state-of-the-art classification methods. In general, the MI ensemble approach produces more compact results in terms of both diversity and error compared to equipollent non-MIL algorithms.

Optimized multiple linear mappings for single image super-resolution

NASA Astrophysics Data System (ADS)

Zhang, Kaibing; Li, Jie; Xiong, Zenggang; Liu, Xiuping; Gao, Xinbo

2017-12-01

Learning piecewise linear regression has been recognized as an effective way for example learning-based single image super-resolution (SR) in literature. In this paper, we employ an expectation-maximization (EM) algorithm to further improve the SR performance of our previous multiple linear mappings (MLM) based SR method. In the training stage, the proposed method starts with a set of linear regressors obtained by the MLM-based method, and then jointly optimizes the clustering results and the low- and high-resolution subdictionary pairs for regression functions by using the metric of the reconstruction errors. In the test stage, we select the optimal regressor for SR reconstruction by accumulating the reconstruction errors of m-nearest neighbors in the training set. Thorough experimental results carried on six publicly available datasets demonstrate that the proposed SR method can yield high-quality images with finer details and sharper edges in terms of both quantitative and perceptual image quality assessments.

Weak scratch detection and defect classification methods for a large-aperture optical element

NASA Astrophysics Data System (ADS)

Tao, Xian; Xu, De; Zhang, Zheng-Tao; Zhang, Feng; Liu, Xi-Long; Zhang, Da-Peng

2017-03-01

Surface defects on optics cause optic failure and heavy loss to the optical system. Therefore, surface defects on optics must be carefully inspected. This paper proposes a coarse-to-fine detection strategy of weak scratches in complicated dark-field images. First, all possible scratches are detected based on bionic vision. Then, each possible scratch is precisely positioned and connected to a complete scratch by the LSD and a priori knowledge. Finally, multiple scratches with various types can be detected in dark-field images. To classify defects and pollutants, a classification method based on GIST features is proposed. This paper uses many real dark-field images as experimental images. The results show that this method can detect multiple types of weak scratches in complex images and that the defects can be correctly distinguished with interference. This method satisfies the real-time and accurate detection requirements of surface defects.

Improving detection of copy-number variation by simultaneous bias correction and read-depth segmentation.

PubMed

Szatkiewicz, Jin P; Wang, WeiBo; Sullivan, Patrick F; Wang, Wei; Sun, Wei

2013-02-01

Structural variation is an important class of genetic variation in mammals. High-throughput sequencing (HTS) technologies promise to revolutionize copy-number variation (CNV) detection but present substantial analytic challenges. Converging evidence suggests that multiple types of CNV-informative data (e.g. read-depth, read-pair, split-read) need be considered, and that sophisticated methods are needed for more accurate CNV detection. We observed that various sources of experimental biases in HTS confound read-depth estimation, and note that bias correction has not been adequately addressed by existing methods. We present a novel read-depth-based method, GENSENG, which uses a hidden Markov model and negative binomial regression framework to identify regions of discrete copy-number changes while simultaneously accounting for the effects of multiple confounders. Based on extensive calibration using multiple HTS data sets, we conclude that our method outperforms existing read-depth-based CNV detection algorithms. The concept of simultaneous bias correction and CNV detection can serve as a basis for combining read-depth with other types of information such as read-pair or split-read in a single analysis. A user-friendly and computationally efficient implementation of our method is freely available.

A multiple maximum scatter difference discriminant criterion for facial feature extraction.

PubMed

Song, Fengxi; Zhang, David; Mei, Dayong; Guo, Zhongwei

2007-12-01

Maximum scatter difference (MSD) discriminant criterion was a recently presented binary discriminant criterion for pattern classification that utilizes the generalized scatter difference rather than the generalized Rayleigh quotient as a class separability measure, thereby avoiding the singularity problem when addressing small-sample-size problems. MSD classifiers based on this criterion have been quite effective on face-recognition tasks, but as they are binary classifiers, they are not as efficient on large-scale classification tasks. To address the problem, this paper generalizes the classification-oriented binary criterion to its multiple counterpart--multiple MSD (MMSD) discriminant criterion for facial feature extraction. The MMSD feature-extraction method, which is based on this novel discriminant criterion, is a new subspace-based feature-extraction method. Unlike most other subspace-based feature-extraction methods, the MMSD computes its discriminant vectors from both the range of the between-class scatter matrix and the null space of the within-class scatter matrix. The MMSD is theoretically elegant and easy to calculate. Extensive experimental studies conducted on the benchmark database, FERET, show that the MMSD out-performs state-of-the-art facial feature-extraction methods such as null space method, direct linear discriminant analysis (LDA), eigenface, Fisherface, and complete LDA.

Parametric optimization of multiple quality characteristics in laser cutting of Inconel-718 by using hybrid approach of multiple regression analysis and genetic algorithm

NASA Astrophysics Data System (ADS)

Shrivastava, Prashant Kumar; Pandey, Arun Kumar

2018-06-01

Inconel-718 has found high demand in different industries due to their superior mechanical properties. The traditional cutting methods are facing difficulties for cutting these alloys due to their low thermal potential, lower elasticity and high chemical compatibility at inflated temperature. The challenges of machining and/or finishing of unusual shapes and/or sizes in these materials have also faced by traditional machining. Laser beam cutting may be applied for the miniaturization and ultra-precision cutting and/or finishing by appropriate control of different process parameter. This paper present multi-objective optimization the kerf deviation, kerf width and kerf taper in the laser cutting of Incone-718 sheet. The second order regression models have been developed for different quality characteristics by using the experimental data obtained through experimentation. The regression models have been used as objective function for multi-objective optimization based on the hybrid approach of multiple regression analysis and genetic algorithm. The comparison of optimization results to experimental results shows an improvement of 88%, 10.63% and 42.15% in kerf deviation, kerf width and kerf taper, respectively. Finally, the effects of different process parameters on quality characteristics have also been discussed.

Improving homology modeling of G-protein coupled receptors through multiple-template derived conserved inter-residue interactions

NASA Astrophysics Data System (ADS)

Chaudhari, Rajan; Heim, Andrew J.; Li, Zhijun

2015-05-01

Evidenced by the three-rounds of G-protein coupled receptors (GPCR) Dock competitions, improving homology modeling methods of helical transmembrane proteins including the GPCRs, based on templates of low sequence identity, remains an eminent challenge. Current approaches addressing this challenge adopt the philosophy of "modeling first, refinement next". In the present work, we developed an alternative modeling approach through the novel application of available multiple templates. First, conserved inter-residue interactions are derived from each additional template through conservation analysis of each template-target pairwise alignment. Then, these interactions are converted into distance restraints and incorporated in the homology modeling process. This approach was applied to modeling of the human β2 adrenergic receptor using the bovin rhodopsin and the human protease-activated receptor 1 as templates and improved model quality was demonstrated compared to the homology model generated by standard single-template and multiple-template methods. This method of "refined restraints first, modeling next", provides a fast and complementary way to the current modeling approaches. It allows rational identification and implementation of additional conserved distance restraints extracted from multiple templates and/or experimental data, and has the potential to be applicable to modeling of all helical transmembrane proteins.

Driver fatigue detection through multiple entropy fusion analysis in an EEG-based system

PubMed Central

Min, Jianliang; Wang, Ping

2017-01-01

Driver fatigue is an important contributor to road accidents, and fatigue detection has major implications for transportation safety. The aim of this research is to analyze the multiple entropy fusion method and evaluate several channel regions to effectively detect a driver's fatigue state based on electroencephalogram (EEG) records. First, we fused multiple entropies, i.e., spectral entropy, approximate entropy, sample entropy and fuzzy entropy, as features compared with autoregressive (AR) modeling by four classifiers. Second, we captured four significant channel regions according to weight-based electrodes via a simplified channel selection method. Finally, the evaluation model for detecting driver fatigue was established with four classifiers based on the EEG data from four channel regions. Twelve healthy subjects performed continuous simulated driving for 1–2 hours with EEG monitoring on a static simulator. The leave-one-out cross-validation approach obtained an accuracy of 98.3%, a sensitivity of 98.3% and a specificity of 98.2%. The experimental results verified the effectiveness of the proposed method, indicating that the multiple entropy fusion features are significant factors for inferring the fatigue state of a driver. PMID:29220351

CARS Spectral Fitting with Multiple Resonant Species using Sparse Libraries

NASA Technical Reports Server (NTRS)

Cutler, Andrew D.; Magnotti, Gaetano

2010-01-01

The dual pump CARS technique is often used in the study of turbulent flames. Fast and accurate algorithms are needed for fitting dual-pump CARS spectra for temperature and multiple chemical species. This paper describes the development of such an algorithm. The algorithm employs sparse libraries, whose size grows much more slowly with number of species than a conventional library. The method was demonstrated by fitting synthetic "experimental" spectra containing 4 resonant species (N2, O2, H2 and CO2), both with noise and without it, and by fitting experimental spectra from a H2-air flame produced by a Hencken burner. In both studies, weighted least squares fitting of signal, as opposed to least squares fitting signal or square-root signal, was shown to produce the least random error and minimize bias error in the fitted parameters.

Lattice Calibration with Turn-By-Turn BPM Data

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

Huang, Xiaobiao; /SLAC; Sebek, James

2012-07-02

Turn-by-turn beam position monitor (BPM) data from multiple BPMs are fitted with a tracking code to calibrate magnet strengths in a manner similar to the well known LOCO code. Simulation shows that this turn-by-turn method can be a quick and efficient way for optics calibration. The method is applicable to both linacs and ring accelerators. Experimental results for a section of the SPEAR3 ring is also shown.

Kinematic control of redundant robots and the motion optimizability measure.

PubMed

Li, L; Gruver, W A; Zhang, Q; Yang, Z

2001-01-01

This paper treats the kinematic control of manipulators with redundant degrees of freedom. We derive an analytical solution for the inverse kinematics that provides a means for accommodating joint velocity constraints in real time. We define the motion optimizability measure and use it to develop an efficient method for the optimization of joint trajectories subject to multiple criteria. An implementation of the method for a 7-dof experimental redundant robot is present.

Learning to rank atlases for multiple-atlas segmentation.

PubMed

Sanroma, Gerard; Wu, Guorong; Gao, Yaozong; Shen, Dinggang

2014-10-01

Recently, multiple-atlas segmentation (MAS) has achieved a great success in the medical imaging area. The key assumption is that multiple atlases have greater chances of correctly labeling a target image than a single atlas. However, the problem of atlas selection still remains unexplored. Traditionally, image similarity is used to select a set of atlases. Unfortunately, this heuristic criterion is not necessarily related to the final segmentation performance. To solve this seemingly simple but critical problem, we propose a learning-based atlas selection method to pick up the best atlases that would lead to a more accurate segmentation. Our main idea is to learn the relationship between the pairwise appearance of observed instances (i.e., a pair of atlas and target images) and their final labeling performance (e.g., using the Dice ratio). In this way, we select the best atlases based on their expected labeling accuracy. Our atlas selection method is general enough to be integrated with any existing MAS method. We show the advantages of our atlas selection method in an extensive experimental evaluation in the ADNI, SATA, IXI, and LONI LPBA40 datasets. As shown in the experiments, our method can boost the performance of three widely used MAS methods, outperforming other learning-based and image-similarity-based atlas selection methods.

Raman Spectroscopy as the Method of Detection for Constructing a Binary Liquid-Vapor Phase Diagram

ERIC Educational Resources Information Center

Scardino, Debra J.; Howard, Austin A.; McDowell, Matthew D.; Hammer, Nathan I.

2011-01-01

The physical chemistry laboratory is sometimes constrained to one semester, resulting in pedagogical deficiencies for the students taking the course. The use of a multidimensional laboratory exercise offers students the opportunity to encounter multiple experimental techniques and physical chemistry concepts while not sacrificing a significant…

Thermal Response Of Composite Insulation

NASA Technical Reports Server (NTRS)

Stewart, David A.; Leiser, Daniel B.; Smith, Marnell; Kolodziej, Paul

1988-01-01

Engineering model gives useful predictions. Pair of reports presents theoretical and experimental analyses of thermal responses of multiple-component, lightweight, porous, ceramic insulators. Particular materials examined destined for use in Space Shuttle thermal protection system, test methods and heat-transfer theory useful to chemical, metallurgical, and ceramic engineers needing to calculate transient thermal responses of refractory composites.

Evaluating the Performance of Repeated Measures Approaches in Replicating Experimental Benchmark Results

ERIC Educational Resources Information Center

McConeghy, Kevin; Wing, Coady; Wong, Vivian C.

2015-01-01

Randomized experiments have long been established as the gold standard for addressing causal questions. However, experiments are not always feasible or desired, so observational methods are also needed. When multiple observations on the same variable are available, a repeated measures design may be used to assess whether a treatment administered…

A Powerful, Potential Outcomes Method for Estimating Any Estimand across Multiple Groups

ERIC Educational Resources Information Center

Pattanayak, Cassandra W.; Rubin, Donald B.; Zell, Elizabeth R.

2013-01-01

In educational research, outcome measures are often estimated across separate studies or across schools, districts, or other subgroups to assess the overall causal effect of an active treatment versus a control treatment. Students may be partitioned into such strata or blocks by experimental design, or separated into studies within a…

Multiple Objectives Achieved with a Germination Experiment in a Science Education Biology Class

ERIC Educational Resources Information Center

Bergwerff, Ken; Warners, David

2007-01-01

In our college course, "Life Science for Elementary School Teachers," our investigation assesses the germination success of an invasive plant, purple loosestrife, compared to native wildflowers. Topics addressed include the scientific method, experimental design, seed dormancy, plant competition, ethno-botany, and success of non-native plants. The…

Lightweight Biometric Sensing for Walker Classification Using Narrowband RF Links

PubMed Central

Liang, Zhuo-qian

2017-01-01

This article proposes a lightweight biometric sensing system using ubiquitous narrowband radio frequency (RF) links for path-dependent walker classification. The fluctuated received signal strength (RSS) sequence generated by human motion is used for feature representation. To capture the most discriminative characteristics of individuals, a three-layer RF sensing network is organized for building multiple sampling links at the most common heights of upper limbs, thighs, and lower legs. The optimal parameters of sensing configuration, such as the height of link location and number of fused links, are investigated to improve sensory data distinctions among subjects, and the experimental results suggest that the synergistic sensing by using multiple links can contribute a better performance. This is the new consideration of using RF links in building a biometric sensing system. In addition, two types of classification methods involving vector quantization (VQ) and hidden Markov models (HMMs) are developed and compared for closed-set walker recognition and verification. Experimental studies in indoor line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios are conducted to validate the proposed method. PMID:29206188

Lightweight Biometric Sensing for Walker Classification Using Narrowband RF Links.

PubMed

Liu, Tong; Liang, Zhuo-Qian

2017-12-05

This article proposes a lightweight biometric sensing system using ubiquitous narrowband radio frequency (RF) links for path-dependent walker classification. The fluctuated received signal strength (RSS) sequence generated by human motion is used for feature representation. To capture the most discriminative characteristics of individuals, a three-layer RF sensing network is organized for building multiple sampling links at the most common heights of upper limbs, thighs, and lower legs. The optimal parameters of sensing configuration, such as the height of link location and number of fused links, are investigated to improve sensory data distinctions among subjects, and the experimental results suggest that the synergistic sensing by using multiple links can contribute a better performance. This is the new consideration of using RF links in building a biometric sensing system. In addition, two types of classification methods involving vector quantization (VQ) and hidden Markov models (HMMs) are developed and compared for closed-set walker recognition and verification. Experimental studies in indoor line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios are conducted to validate the proposed method.

Tracking motor units longitudinally across experimental sessions with high‐density surface electromyography

PubMed Central

Martinez‐Valdes, E.; Negro, F.; Laine, C. M.; Falla, D.; Mayer, F.

2017-01-01

Key points Classic motor unit (MU) recording and analysis methods do not allow the same MUs to be tracked across different experimental sessions, and therefore, there is limited experimental evidence on the adjustments in MU properties following training or during the progression of neuromuscular disorders.We propose a new processing method to track the same MUs across experimental sessions (separated by weeks) by using high‐density surface electromyography.The application of the proposed method in two experiments showed that individual MUs can be identified reliably in measurements separated by weeks and that changes in properties of the tracked MUs across experimental sessions can be identified with high sensitivity.These results indicate that the behaviour and properties of the same MUs can be monitored across multiple testing sessions.The proposed method opens new possibilities in the understanding of adjustments in motor unit properties due to training interventions or the progression of pathologies. Abstract A new method is proposed for tracking individual motor units (MUs) across multiple experimental sessions on different days. The technique is based on a novel decomposition approach for high‐density surface electromyography and was tested with two experimental studies for reliability and sensitivity. Experiment I (reliability): ten participants performed isometric knee extensions at 10, 30, 50 and 70% of their maximum voluntary contraction (MVC) force in three sessions, each separated by 1 week. Experiment II (sensitivity): seven participants performed 2 weeks of endurance training (cycling) and were tested pre–post intervention during isometric knee extensions at 10 and 30% MVC. The reliability (Experiment I) and sensitivity (Experiment II) of the measured MU properties were compared for the MUs tracked across sessions, with respect to all MUs identified in each session. In Experiment I, on average 38.3% and 40.1% of the identified MUs could be tracked across two sessions (1 and 2 weeks apart), for the vastus medialis and vastus lateralis, respectively. Moreover, the properties of the tracked MUs were more reliable across sessions than those of the full set of identified MUs (intra‐class correlation coefficients ranged between 0.63—0.99 and 0.39–0.95, respectively). In Experiment II, ∼40% of the MUs could be tracked before and after the training intervention and training‐induced changes in MU conduction velocity had an effect size of 2.1 (tracked MUs) and 1.5 (group of all identified motor units). These results show the possibility of monitoring MU properties longitudinally to document the effect of interventions or the progression of neuromuscular disorders. PMID:28032343

MGUPGMA: A Fast UPGMA Algorithm With Multiple Graphics Processing Units Using NCCL

PubMed Central

Hua, Guan-Jie; Hung, Che-Lun; Lin, Chun-Yuan; Wu, Fu-Che; Chan, Yu-Wei; Tang, Chuan Yi

2017-01-01

A phylogenetic tree is a visual diagram of the relationship between a set of biological species. The scientists usually use it to analyze many characteristics of the species. The distance-matrix methods, such as Unweighted Pair Group Method with Arithmetic Mean and Neighbor Joining, construct a phylogenetic tree by calculating pairwise genetic distances between taxa. These methods have the computational performance issue. Although several new methods with high-performance hardware and frameworks have been proposed, the issue still exists. In this work, a novel parallel Unweighted Pair Group Method with Arithmetic Mean approach on multiple Graphics Processing Units is proposed to construct a phylogenetic tree from extremely large set of sequences. The experimental results present that the proposed approach on a DGX-1 server with 8 NVIDIA P100 graphic cards achieves approximately 3-fold to 7-fold speedup over the implementation of Unweighted Pair Group Method with Arithmetic Mean on a modern CPU and a single GPU, respectively. PMID:29051701

MGUPGMA: A Fast UPGMA Algorithm With Multiple Graphics Processing Units Using NCCL.

PubMed

Hua, Guan-Jie; Hung, Che-Lun; Lin, Chun-Yuan; Wu, Fu-Che; Chan, Yu-Wei; Tang, Chuan Yi

2017-01-01

A phylogenetic tree is a visual diagram of the relationship between a set of biological species. The scientists usually use it to analyze many characteristics of the species. The distance-matrix methods, such as Unweighted Pair Group Method with Arithmetic Mean and Neighbor Joining, construct a phylogenetic tree by calculating pairwise genetic distances between taxa. These methods have the computational performance issue. Although several new methods with high-performance hardware and frameworks have been proposed, the issue still exists. In this work, a novel parallel Unweighted Pair Group Method with Arithmetic Mean approach on multiple Graphics Processing Units is proposed to construct a phylogenetic tree from extremely large set of sequences. The experimental results present that the proposed approach on a DGX-1 server with 8 NVIDIA P100 graphic cards achieves approximately 3-fold to 7-fold speedup over the implementation of Unweighted Pair Group Method with Arithmetic Mean on a modern CPU and a single GPU, respectively.

A visual tracking method based on improved online multiple instance learning

NASA Astrophysics Data System (ADS)

He, Xianhui; Wei, Yuxing

2016-09-01

Visual tracking is an active research topic in the field of computer vision and has been well studied in the last decades. The method based on multiple instance learning (MIL) was recently introduced into the tracking task, which can solve the problem that template drift well. However, MIL method has relatively poor performance in running efficiency and accuracy, due to its strong classifiers updating strategy is complicated, and the speed of the classifiers update is not always same with the change of the targets' appearance. In this paper, we present a novel online effective MIL (EMIL) tracker. A new update strategy for strong classifier was proposed to improve the running efficiency of MIL method. In addition, to improve the t racking accuracy and stability of the MIL method, a new dynamic mechanism for learning rate renewal of the classifier and variable search window were proposed. Experimental results show that our method performs good performance under the complex scenes, with strong stability and high efficiency.

[A novel method of multi-channel feature extraction combining multivariate autoregression and multiple-linear principal component analysis].

PubMed

Wang, Jinjia; Zhang, Yanna

2015-02-01

Brain-computer interface (BCI) systems identify brain signals through extracting features from them. In view of the limitations of the autoregressive model feature extraction method and the traditional principal component analysis to deal with the multichannel signals, this paper presents a multichannel feature extraction method that multivariate autoregressive (MVAR) model combined with the multiple-linear principal component analysis (MPCA), and used for magnetoencephalography (MEG) signals and electroencephalograph (EEG) signals recognition. Firstly, we calculated the MVAR model coefficient matrix of the MEG/EEG signals using this method, and then reduced the dimensions to a lower one, using MPCA. Finally, we recognized brain signals by Bayes Classifier. The key innovation we introduced in our investigation showed that we extended the traditional single-channel feature extraction method to the case of multi-channel one. We then carried out the experiments using the data groups of IV-III and IV - I. The experimental results proved that the method proposed in this paper was feasible.

Counterbalancing for serial order carryover effects in experimental condition orders.

PubMed

Brooks, Joseph L

2012-12-01

Reactions of neural, psychological, and social systems are rarely, if ever, independent of previous inputs and states. The potential for serial order carryover effects from one condition to the next in a sequence of experimental trials makes counterbalancing of condition order an essential part of experimental design. Here, a method is proposed for generating counterbalanced sequences for repeated-measures designs including those with multiple observations of each condition on one participant and self-adjacencies of conditions. Condition ordering is reframed as a graph theory problem. Experimental conditions are represented as vertices in a graph and directed edges between them represent temporal relationships between conditions. A counterbalanced trial order results from traversing an Euler circuit through such a graph in which each edge is traversed exactly once. This method can be generalized to counterbalance for higher order serial order carryover effects as well as to create intentional serial order biases. Modern graph theory provides tools for finding other types of paths through such graph representations, providing a tool for generating experimental condition sequences with useful properties. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Statistical methods and neural network approaches for classification of data from multiple sources

NASA Technical Reports Server (NTRS)

Benediktsson, Jon Atli; Swain, Philip H.

1990-01-01

Statistical methods for classification of data from multiple data sources are investigated and compared to neural network models. A problem with using conventional multivariate statistical approaches for classification of data of multiple types is in general that a multivariate distribution cannot be assumed for the classes in the data sources. Another common problem with statistical classification methods is that the data sources are not equally reliable. This means that the data sources need to be weighted according to their reliability but most statistical classification methods do not have a mechanism for this. This research focuses on statistical methods which can overcome these problems: a method of statistical multisource analysis and consensus theory. Reliability measures for weighting the data sources in these methods are suggested and investigated. Secondly, this research focuses on neural network models. The neural networks are distribution free since no prior knowledge of the statistical distribution of the data is needed. This is an obvious advantage over most statistical classification methods. The neural networks also automatically take care of the problem involving how much weight each data source should have. On the other hand, their training process is iterative and can take a very long time. Methods to speed up the training procedure are introduced and investigated. Experimental results of classification using both neural network models and statistical methods are given, and the approaches are compared based on these results.

The Need for Precise and Well-documented Experimental Data on Prompt Fission Neutron Spectra from Neutron-induced Fission of {sup 239}Pu

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

Neudecker, D., E-mail: dneudecker@lanl.gov; Taddeucci, T.N.; Haight, R.C.

2016-01-15

The spectrum of neutrons emitted promptly after {sup 239}Pu(n,f)—a so-called prompt fission neutron spectrum (PFNS)—is a quantity of high interest, for instance, for reactor physics and global security. However, there are only few experimental data sets available that are suitable for evaluations. In addition, some of those data sets differ by more than their 1-σ uncertainty boundaries. We present the results of MCNP studies indicating that these differences are partly caused by underestimated multiple scattering contributions, over-corrected background, and inconsistent deconvolution methods. A detailed uncertainty quantification for suitable experimental data was undertaken including these effects, and test-evaluations were performed withmore » the improved uncertainty information. The test-evaluations illustrate that the inadequately estimated effects and detailed uncertainty quantification have an impact on the evaluated PFNS and associated uncertainties as well as the neutron multiplicity of selected critical assemblies. A summary of data and documentation needs to improve the quality of the experimental database is provided based on the results of simulations and test-evaluations. Given the possibly substantial distortion of the PFNS by multiple scattering and background effects, special care should be taken to reduce these effects in future measurements, e.g., by measuring the {sup 239}Pu PFNS as a ratio to either the {sup 235}U or {sup 252}Cf PFNS.« less

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Credit allocation for research institutes

NASA Astrophysics Data System (ADS)

Wang, J.-P.; Guo, Q.; Yang, K.; Han, J.-T.; Liu, J.-G.

2017-05-01

It is a challenging work to assess research performance of multiple institutes. Considering that it is unfair to average the credit to the institutes which is in the different order from a paper, in this paper, we present a credit allocation method (CAM) with a weighted order coefficient for multiple institutes. The results for the APS dataset with 18987 institutes show that top-ranked institutes obtained by the CAM method correspond to well-known universities or research labs with high reputation in physics. Moreover, we evaluate the performance of the CAM method when citation links are added or rewired randomly quantified by the Kendall's Tau and Jaccard index. The experimental results indicate that the CAM method has better performance in robustness compared with the total number of citations (TC) method and Shen's method. Finally, we give the first 20 Chinese universities in physics obtained by the CAM method. However, this method is valid for any other branch of sciences, not just for physics. The proposed method also provides universities and policy makers an effective tool to quantify and balance the academic performance of university.

A multiplicative regularization for force reconstruction

NASA Astrophysics Data System (ADS)

Aucejo, M.; De Smet, O.

2017-02-01

Additive regularizations, such as Tikhonov-like approaches, are certainly the most popular methods for reconstructing forces acting on a structure. These approaches require, however, the knowledge of a regularization parameter, that can be numerically computed using specific procedures. Unfortunately, these procedures are generally computationally intensive. For this particular reason, it could be of primary interest to propose a method able to proceed without defining any regularization parameter beforehand. In this paper, a multiplicative regularization is introduced for this purpose. By construction, the regularized solution has to be calculated in an iterative manner. In doing so, the amount of regularization is automatically adjusted throughout the resolution process. Validations using synthetic and experimental data highlight the ability of the proposed approach in providing consistent reconstructions.

Image Size Scalable Full-parallax Coloured Three-dimensional Video by Electronic Holography

NASA Astrophysics Data System (ADS)

Sasaki, Hisayuki; Yamamoto, Kenji; Ichihashi, Yasuyuki; Senoh, Takanori

2014-02-01

In electronic holography, various methods have been considered for using multiple spatial light modulators (SLM) to increase the image size. In a previous work, we used a monochrome light source for a method that located an optical system containing lens arrays and other components in front of multiple SLMs. This paper proposes a colourization technique for that system based on time division multiplexing using laser light sources of three colours (red, green, and blue). The experimental device we constructed was able to perform video playback (20 fps) in colour of full parallax holographic three-dimensional (3D) images with an image size of 63 mm and a viewing-zone angle of 5.6 degrees without losing any part of the 3D image.

Optimal Objective-Based Experimental Design for Uncertain Dynamical Gene Networks with Experimental Error.

PubMed

Mohsenizadeh, Daniel N; Dehghannasiri, Roozbeh; Dougherty, Edward R

2018-01-01

In systems biology, network models are often used to study interactions among cellular components, a salient aim being to develop drugs and therapeutic mechanisms to change the dynamical behavior of the network to avoid undesirable phenotypes. Owing to limited knowledge, model uncertainty is commonplace and network dynamics can be updated in different ways, thereby giving multiple dynamic trajectories, that is, dynamics uncertainty. In this manuscript, we propose an experimental design method that can effectively reduce the dynamics uncertainty and improve performance in an interaction-based network. Both dynamics uncertainty and experimental error are quantified with respect to the modeling objective, herein, therapeutic intervention. The aim of experimental design is to select among a set of candidate experiments the experiment whose outcome, when applied to the network model, maximally reduces the dynamics uncertainty pertinent to the intervention objective.

Work Stress Interventions in Hospital Care: Effectiveness of the DISCovery Method

PubMed Central

Niks, Irene; Gevers, Josette

2018-01-01

Effective interventions to prevent work stress and to improve health, well-being, and performance of employees are of the utmost importance. This quasi-experimental intervention study presents a specific method for diagnosis of psychosocial risk factors at work and subsequent development and implementation of tailored work stress interventions, the so-called DISCovery method. This method aims at improving employee health, well-being, and performance by optimizing the balance between job demands, job resources, and recovery from work. The aim of the study is to quantitatively assess the effectiveness of the DISCovery method in hospital care. Specifically, we used a three-wave longitudinal, quasi-experimental multiple-case study approach with intervention and comparison groups in health care work. Positive changes were found for members of the intervention groups, relative to members of the corresponding comparison groups, with respect to targeted work-related characteristics and targeted health, well-being, and performance outcomes. Overall, results lend support for the effectiveness of the DISCovery method in hospital care. PMID:29438350

Work Stress Interventions in Hospital Care: Effectiveness of the DISCovery Method.

PubMed

Niks, Irene; de Jonge, Jan; Gevers, Josette; Houtman, Irene

2018-02-13

Effective interventions to prevent work stress and to improve health, well-being, and performance of employees are of the utmost importance. This quasi-experimental intervention study presents a specific method for diagnosis of psychosocial risk factors at work and subsequent development and implementation of tailored work stress interventions, the so-called DISCovery method. This method aims at improving employee health, well-being, and performance by optimizing the balance between job demands, job resources, and recovery from work. The aim of the study is to quantitatively assess the effectiveness of the DISCovery method in hospital care. Specifically, we used a three-wave longitudinal, quasi-experimental multiple-case study approach with intervention and comparison groups in health care work. Positive changes were found for members of the intervention groups, relative to members of the corresponding comparison groups, with respect to targeted work-related characteristics and targeted health, well-being, and performance outcomes. Overall, results lend support for the effectiveness of the DISCovery method in hospital care.

Multiple autoclave cycle effects on cyclic fatigue of nickel-titanium rotary files produced by new manufacturing methods.

PubMed

Hilfer, Paul B; Bergeron, Brian E; Mayerchak, Michael J; Roberts, Howard W; Jeansonne, Billie G

2011-01-01

Novel nickel-titanium rotary files with proprietary manufacturing techniques have recently been marketed. The purpose of this study was to assess multiple autoclave cycle effects on cyclic fatigue of GT Series X files (Dentsply Tulsa Dental Specialties, Tulsa, OK) and Twisted Files (SybronEndo, Orange, CA) METHODS: A jig using a 5-mm radius curve with 90° of maximum file flexure was used to induce cyclic fatigue failure. Files (n = 10) representing each experimental group (GT Series X 20/.04 and 20/.06; Twisted Files 25/.04 and 25/.06) were first tested to establish baseline mean cycles to failure (MCF). Experimental groups (n = 20) were then cycled to 25% of the established baseline MCF and then autoclaved. Additional autoclaving was accomplished at 50% and 75% of MCF followed by continual testing until failure. Control groups (n = 20) underwent the same procedures except autoclaving was not accomplished. The GT Series X (20/.04 and 20/.06) files showed no significant difference (p = 0.918/p = 0.096) in MCF for experimental versus control files. Twisted Files (25/.04) showed no significant difference (p = 0.432) in MCF between experimental and control groups. However, the Twisted Files (25/.06) experimental group showed a significantly lower (p = 0.0175) MCF compared with the controls. Under the conditions of this evaluation, autoclave sterilization significantly decreased cyclic fatigue resistance of one of the four file groups tested. Repeated autoclaving significantly reduced the MCF of 25/.06 Twisted Files; however, 25/.04 Twisted Files and both GT Series X files tested were not significantly affected by the same conditions. Published by Elsevier Inc.

Vernier effect-based multiplication of the Sagnac beating frequency in ring laser gyroscope sensors

NASA Astrophysics Data System (ADS)

Adib, George A.; Sabry, Yasser M.; Khalil, Diaa

2018-02-01

A multiplication method of the Sagnac effect scale factor in ring laser gyroscopes is presented based on the Vernier effect of a dual-coupler passive ring resonator coupled to the active ring. The multiplication occurs when the two rings have comparable lengths or integer multiples and their scale factors have opposite signs. In this case, and when the rings have similar areas, the scale factor is multiplied by ratio of their length to their length difference. The scale factor of the presented configuration is derived analytically and the lock-in effect is analyzed. The principle is demonstrated using optical fiber rings and semiconductor optical amplifier as gain medium. A scale factor multiplication by about 175 is experimentally measured, demonstrating larger than two orders of magnitude enhancement in the Sagnac effect scale factor for the first time in literature, up to the authors' knowledge.

Quantification of Peptides from Immunoglobulin Constant and Variable Regions by Liquid Chromatography-Multiple Reaction Monitoring Mass Spectrometry for Assessment of Multiple Myeloma Patients

PubMed Central

Remily-Wood, Elizabeth R.; Benson, Kaaron; Baz, Rachid C.; Chen, Y. Ann; Hussein, Mohamad; Hartley-Brown, Monique A.; Sprung, Robert W.; Perez, Brianna; Liu, Richard Z.; Yoder, Sean; Teer, Jamie; Eschrich, Steven A.; Koomen, John M.

2014-01-01

Purpose Quantitative mass spectrometry assays for immunoglobulins (Igs) are compared with existing clinical methods in samples from patients with plasma cell dyscrasias, e.g. multiple myeloma. Experimental design Using LC-MS/MS data, Ig constant region peptides and transitions were selected for liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM). Quantitative assays were used to assess Igs in serum from 83 patients. Results LC-MRM assays quantify serum levels of Igs and their isoforms (IgG1–4, IgA1–2, IgM, IgD, and IgE, as well as kappa(κ) and lambda(λ) light chains). LC-MRM quantification has been applied to single samples from a patient cohort and a longitudinal study of an IgE patient undergoing treatment, to enable comparison with existing clinical methods. Proof-of-concept data for defining and monitoring variable region peptides are provided using the H929 multiple myeloma cell line and two MM patients. Conclusions and Clinical Relevance LC-MRM assays targeting constant region peptides determine the type and isoform of the involved immunoglobulin and quantify its expression; the LC-MRM approach has improved sensitivity compared with the current clinical method, but slightly higher interassay variability. Detection of variable region peptides is a promising way to improve Ig quantification, which could produce a dramatic increase in sensitivity over existing methods, and could further complement current clinical techniques. PMID:24723328

Comparison of single cell sequencing data between two whole genome amplification methods on two sequencing platforms.

PubMed

Chen, DaYang; Zhen, HeFu; Qiu, Yong; Liu, Ping; Zeng, Peng; Xia, Jun; Shi, QianYu; Xie, Lin; Zhu, Zhu; Gao, Ya; Huang, GuoDong; Wang, Jian; Yang, HuanMing; Chen, Fang

2018-03-21

Research based on a strategy of single-cell low-coverage whole genome sequencing (SLWGS) has enabled better reproducibility and accuracy for detection of copy number variations (CNVs). The whole genome amplification (WGA) method and sequencing platform are critical factors for successful SLWGS (<0.1 × coverage). In this study, we compared single cell and multiple cells sequencing data produced by the HiSeq2000 and Ion Proton platforms using two WGA kits and then comprehensively evaluated the GC-bias, reproducibility, uniformity and CNV detection among different experimental combinations. Our analysis demonstrated that the PicoPLEX WGA Kit resulted in higher reproducibility, lower sequencing error frequency but more GC-bias than the GenomePlex Single Cell WGA Kit (WGA4 kit) independent of the cell number on the HiSeq2000 platform. While on the Ion Proton platform, the WGA4 kit (both single cell and multiple cells) had higher uniformity and less GC-bias but lower reproducibility than those of the PicoPLEX WGA Kit. Moreover, on these two sequencing platforms, depending on cell number, the performance of the two WGA kits was different for both sensitivity and specificity on CNV detection. The results can help researchers who plan to use SLWGS on single or multiple cells to select appropriate experimental conditions for their applications.

Dynamic analysis of periodic vibration suppressors with multiple secondary oscillators

NASA Astrophysics Data System (ADS)

Ma, Jiangang; Sheng, Meiping; Guo, Zhiwei; Qin, Qi

2018-06-01

A periodic vibration suppressor with multiple secondary oscillators is examined in this paper to reduce the low-frequency vibration. The band-gap properties of infinite periodic structure and vibration transmission properties of finite periodic structure attached with secondary oscillators with arbitrary degree of freedom are thoroughly analyzed by the plane-wave-expansion method. A simply supported plate with a periodic rectangular array of vibration suppressors is considered. The dynamic model of this periodic structure is established and the equation of harmonic vibration response is theoretically derived and numerically examined. Compared with the simply supported plate without attached suppressors, the proposed plate can obtain better vibration control, and the vibration response can be effectively reduced in several frequency bands owing to the multiple band-gap property. By analyzing the modal properties of the periodic vibration suppressors, the relationship between modal frequencies and the parameters of spring stiffness and mass is established. With the numerical results, the design guidance of the locally resonant structure with multiple secondary oscillators is proposed to provide practical guidance for application. Finally, a practical periodic specimen is designed and fabricated, and then an experiment is carried out to validate the effectiveness of periodic suppressors in the reality. The results show that the experimental band gaps have a good coincidence with those in the theoretical model, and the low-frequency vibration of the plate with periodic suppressors can be effectively reduced in the tuned band gaps. Both the theoretical results and experimental results prove that the design method is effective and the structure with periodic suppressors has a promising application in engineering.

Chemical purity using quantitative 1H-nuclear magnetic resonance: a hierarchical Bayesian approach for traceable calibrations

NASA Astrophysics Data System (ADS)

Toman, Blaza; Nelson, Michael A.; Lippa, Katrice A.

2016-10-01

Chemical purity assessment using quantitative 1H-nuclear magnetic resonance spectroscopy is a method based on ratio references of mass and signal intensity of the analyte species to that of chemical standards of known purity. As such, it is an example of a calculation using a known measurement equation with multiple inputs. Though multiple samples are often analyzed during purity evaluations in order to assess measurement repeatability, the uncertainty evaluation must also account for contributions from inputs to the measurement equation. Furthermore, there may be other uncertainty components inherent in the experimental design, such as independent implementation of multiple calibration standards. As such, the uncertainty evaluation is not purely bottom up (based on the measurement equation) or top down (based on the experimental design), but inherently contains elements of both. This hybrid form of uncertainty analysis is readily implemented with Bayesian statistical analysis. In this article we describe this type of analysis in detail and illustrate it using data from an evaluation of chemical purity and its uncertainty for a folic acid material.

Triple-Label β Liquid Scintillation Counting

PubMed Central

Bukowski, Thomas R.; Moffett, Tyler C.; Revkin, James H.; Ploger, James D.; Bassingthwaighte, James B.

2010-01-01

The detection of radioactive compounds by liquid scintillation has revolutionized modern biology, yet few investigators make full use of the power of this technique. Even though multiple isotope counting is considerably more difficult than single isotope counting, many experimental designs would benefit from using more than one isotope. The development of accurate isotope counting techniques enabling the simultaneous use of three β-emitting tracers has facilitated studies in our laboratory using the multiple tracer indicator dilution technique for assessing rates of transmembrane transport and cellular metabolism. The details of sample preparation, and of stabilizing the liquid scintillation spectra of the tracers, are critical to obtaining good accuracy. Reproducibility is enhanced by obtaining detailed efficiency/quench curves for each particular set of tracers and solvent media. The numerical methods for multiple-isotope quantitation depend on avoiding error propagation (inherent to successive subtraction techniques) by using matrix inversion. Experimental data obtained from triple-label β counting illustrate reproducibility and good accuracy even when the relative amounts of different tracers in samples of protein/electrolyte solutions, plasma, and blood are changed. PMID:1514684

Quantifying properties of hot and dense QCD matter through systematic model-to-data comparison

DOE PAGES

Bernhard, Jonah E.; Marcy, Peter W.; Coleman-Smith, Christopher E.; ...

2015-05-22

We systematically compare an event-by-event heavy-ion collision model to data from the CERN Large Hadron Collider. Using a general Bayesian method, we probe multiple model parameters including fundamental quark-gluon plasma properties such as the specific shear viscosity η/s, calibrate the model to optimally reproduce experimental data, and extract quantitative constraints for all parameters simultaneously. Furthermore, the method is universal and easily extensible to other data and collision models.

Metainference: A Bayesian inference method for heterogeneous systems

PubMed Central

Bonomi, Massimiliano; Camilloni, Carlo; Cavalli, Andrea; Vendruscolo, Michele

2016-01-01

Modeling a complex system is almost invariably a challenging task. The incorporation of experimental observations can be used to improve the quality of a model and thus to obtain better predictions about the behavior of the corresponding system. This approach, however, is affected by a variety of different errors, especially when a system simultaneously populates an ensemble of different states and experimental data are measured as averages over such states. To address this problem, we present a Bayesian inference method, called “metainference,” that is able to deal with errors in experimental measurements and with experimental measurements averaged over multiple states. To achieve this goal, metainference models a finite sample of the distribution of models using a replica approach, in the spirit of the replica-averaging modeling based on the maximum entropy principle. To illustrate the method, we present its application to a heterogeneous model system and to the determination of an ensemble of structures corresponding to the thermal fluctuations of a protein molecule. Metainference thus provides an approach to modeling complex systems with heterogeneous components and interconverting between different states by taking into account all possible sources of errors. PMID:26844300

IR-IR Conformation Specific Spectroscopy of Na +(Glucose) Adducts

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

Voss, Jonathan M.; Kregel, Steven J.; Fischer, Kaitlyn C.

Here in this paper we report an IR-IR double resonance study of the structural landscape present in the Na +(glucose) complex. Our experimental approach involves minimal modifications to a typical IR predissociation setup, and can be carried out via ion-dip or isomer-burning methods, providing additional flexibility to suit different experimental needs. In the current study, the single-laser IR predissociation spectrum of Na +(glucose), which clearly indicates contributions from multiple structures, was experimentally disentangled to reveal the presence of three α-conformers and five β-conformers. Comparisons with calculations show that these eight conformations correspond to the lowest energy gas-phase structures with distinctivemore » Na+ coordination.« less

IR-IR Conformation Specific Spectroscopy of Na +(Glucose) Adducts

DOE PAGES

Voss, Jonathan M.; Kregel, Steven J.; Fischer, Kaitlyn C.; ...

2017-09-27

Here in this paper we report an IR-IR double resonance study of the structural landscape present in the Na +(glucose) complex. Our experimental approach involves minimal modifications to a typical IR predissociation setup, and can be carried out via ion-dip or isomer-burning methods, providing additional flexibility to suit different experimental needs. In the current study, the single-laser IR predissociation spectrum of Na +(glucose), which clearly indicates contributions from multiple structures, was experimentally disentangled to reveal the presence of three α-conformers and five β-conformers. Comparisons with calculations show that these eight conformations correspond to the lowest energy gas-phase structures with distinctivemore » Na+ coordination.« less

The Computational Complexity of Valuation and Motivational Forces in Decision-Making Processes.

PubMed

Redish, A David; Schultheiss, Nathan W; Carter, Evan C

2016-01-01

The concept of value is fundamental to most theories of motivation and decision making. However, value has to be measured experimentally. Different methods of measuring value produce incompatible valuation hierarchies. Taking the agent's perspective (rather than the experimenter's), we interpret the different valuation measurement methods as accessing different decision-making systems and show how these different systems depend on different information processing algorithms. This identifies the translation from these multiple decision-making systems into a single action taken by a given agent as one of the most important open questions in decision making today. We conclude by looking at how these different valuation measures accessing different decision-making systems can be used to understand and treat decision dysfunction such as in addiction.

A group LASSO-based method for robustly inferring gene regulatory networks from multiple time-course datasets.

PubMed

Liu, Li-Zhi; Wu, Fang-Xiang; Zhang, Wen-Jun

2014-01-01

As an abstract mapping of the gene regulations in the cell, gene regulatory network is important to both biological research study and practical applications. The reverse engineering of gene regulatory networks from microarray gene expression data is a challenging research problem in systems biology. With the development of biological technologies, multiple time-course gene expression datasets might be collected for a specific gene network under different circumstances. The inference of a gene regulatory network can be improved by integrating these multiple datasets. It is also known that gene expression data may be contaminated with large errors or outliers, which may affect the inference results. A novel method, Huber group LASSO, is proposed to infer the same underlying network topology from multiple time-course gene expression datasets as well as to take the robustness to large error or outliers into account. To solve the optimization problem involved in the proposed method, an efficient algorithm which combines the ideas of auxiliary function minimization and block descent is developed. A stability selection method is adapted to our method to find a network topology consisting of edges with scores. The proposed method is applied to both simulation datasets and real experimental datasets. It shows that Huber group LASSO outperforms the group LASSO in terms of both areas under receiver operating characteristic curves and areas under the precision-recall curves. The convergence analysis of the algorithm theoretically shows that the sequence generated from the algorithm converges to the optimal solution of the problem. The simulation and real data examples demonstrate the effectiveness of the Huber group LASSO in integrating multiple time-course gene expression datasets and improving the resistance to large errors or outliers.

Red blood cells aggregability measurement of coagulating blood in extracorporeal circulation system with multiple-frequency electrical impedance spectroscopy.

PubMed

Li, Jianping; Sapkota, Achyut; Kikuchi, Daisuke; Sakota, Daisuke; Maruyama, Osamu; Takei, Masahiro

2018-07-30

Red blood cells (RBCs) aggregability A G of coagulating blood in extracorporeal circulation system has been investigated under the condition of pulsatile flow. Relaxation frequency f c from the multiple-frequency electrical impedance spectroscopy is utilized to obtain RBCs aggregability A G . Compared with other methods, the proposed multiple-frequency electrical impedance method is much easier to obtain non-invasive measurement with high speed and good penetrability performance in biology tissues. Experimental results show that, RBCs aggregability A G in coagulating blood falls down with the thrombus formation while that in non-coagulation blood almost keeps the same value, which has a great agreement with the activated clotting time (ACT) fibrinogen concertation (F bg ) tests. Modified Hanai formula is proposed to quantitatively analyze the influence of RBCs aggregation on multiple-frequency electrical impedance measurement. The reduction of RBCs aggregability A G is associated with blood coagulation reaction, which indicates the feasibility of the high speed, compact and cheap on-line thrombus measurement biosensors in extracorporeal circulation systems. Copyright © 2018 Elsevier B.V. All rights reserved.

SAR Speckle Noise Reduction Using Wiener Filter

NASA Technical Reports Server (NTRS)

Joo, T. H.; Held, D. N.

1983-01-01

Synthetic aperture radar (SAR) images are degraded by speckle. A multiplicative speckle noise model for SAR images is presented. Using this model, a Wiener filter is derived by minimizing the mean-squared error using the known speckle statistics. Implementation of the Wiener filter is discussed and experimental results are presented. Finally, possible improvements to this method are explored.

Direct adaptive fuzzy control of a translating piezoelectric flexible manipulator driven by a pneumatic rodless cylinder

NASA Astrophysics Data System (ADS)

Qiu, Zhi-cheng; Wang, Bin; Zhang, Xian-min; Han, Jian-da

2013-04-01

This study presents a novel translating piezoelectric flexible manipulator driven by a rodless cylinder. Simultaneous positioning control and vibration suppression of the flexible manipulator is accomplished by using a hybrid driving scheme composed of the pneumatic cylinder and a piezoelectric actuator. Pulse code modulation (PCM) method is utilized for the cylinder. First, the system dynamics model is derived, and its standard multiple input multiple output (MIMO) state-space representation is provided. Second, a composite proportional derivative (PD) control algorithms and a direct adaptive fuzzy control method are designed for the MIMO system. Also, a time delay compensation algorithm, bandstop and low-pass filters are utilized, under consideration of the control hysteresis and the caused high-frequency modal vibration due to the long stroke of the cylinder, gas compression and nonlinear factors of the pneumatic system. The convergence of the closed loop system is analyzed. Finally, experimental apparatus is constructed and experiments are conducted. The effectiveness of the designed controllers and the hybrid driving scheme is verified through simulation and experimental comparison studies. The numerical simulation and experimental results demonstrate that the proposed system scheme of employing the pneumatic drive and piezoelectric actuator can suppress the vibration and achieve the desired positioning location simultaneously. Furthermore, the adopted adaptive fuzzy control algorithms can significantly enhance the control performance.

Reconstruction of the in-plane mode shape of a rotating tire with a continuous scanning measurement using the Hilbert-Huang transform.

PubMed

Lee, Jongsuh; Wang, Semyung; Pluymers, Bert; Desmet, Wim; Kindt, Peter

2015-02-01

Generally, the dynamic characteristics (natural frequency, damping, and mode shape) of a structure can be estimated by experimental modal analysis. Among these dynamic characteristics, mode shape requires multiple measurements of the structure at different positions, which increases the experimental cost and time. Recently, the Hilbert-Huang transform (HHT) method has been introduced to extract mode-shape information from a continuous measurement, which requires vibration measurements from one position to another position continuously with a non-contact sensor. In this research study, an effort has been made to estimate the mode shapes of a rolling tire with a single measurement instead of using the conventional experimental setup (i.e., measurement of the vibration of a rolling tire at multiple positions similar to the case of a non-rotating structure), which is used to estimate the dynamic behavior of a rolling tire. For this purpose, HHT, which was used in the continuous measurement of a non-rotating structure in previous research studies, has been used for the case of a rotating system in this study. Ambiguous mode combinations can occur in this rotating system, and therefore, a method to overcome this ambiguity is proposed in this study. In addition, the specific phenomenon for a rotating system is introduced, and the effect of this phenomenon with regard to the obtained results through HHT is investigated.

Large size three-dimensional video by electronic holography using multiple spatial light modulators

PubMed Central

Sasaki, Hisayuki; Yamamoto, Kenji; Wakunami, Koki; Ichihashi, Yasuyuki; Oi, Ryutaro; Senoh, Takanori

2014-01-01

In this paper, we propose a new method of using multiple spatial light modulators (SLMs) to increase the size of three-dimensional (3D) images that are displayed using electronic holography. The scalability of images produced by the previous method had an upper limit that was derived from the path length of the image-readout part. We were able to produce larger colour electronic holographic images with a newly devised space-saving image-readout optical system for multiple reflection-type SLMs. This optical system is designed so that the path length of the image-readout part is half that of the previous method. It consists of polarization beam splitters (PBSs), half-wave plates (HWPs), and polarizers. We used 16 (4 × 4) 4K×2K-pixel SLMs for displaying holograms. The experimental device we constructed was able to perform 20 fps video reproduction in colour of full-parallax holographic 3D images with a diagonal image size of 85 mm and a horizontal viewing-zone angle of 5.6 degrees. PMID:25146685

Large size three-dimensional video by electronic holography using multiple spatial light modulators.

PubMed

Sasaki, Hisayuki; Yamamoto, Kenji; Wakunami, Koki; Ichihashi, Yasuyuki; Oi, Ryutaro; Senoh, Takanori

2014-08-22

In this paper, we propose a new method of using multiple spatial light modulators (SLMs) to increase the size of three-dimensional (3D) images that are displayed using electronic holography. The scalability of images produced by the previous method had an upper limit that was derived from the path length of the image-readout part. We were able to produce larger colour electronic holographic images with a newly devised space-saving image-readout optical system for multiple reflection-type SLMs. This optical system is designed so that the path length of the image-readout part is half that of the previous method. It consists of polarization beam splitters (PBSs), half-wave plates (HWPs), and polarizers. We used 16 (4 × 4) 4K×2K-pixel SLMs for displaying holograms. The experimental device we constructed was able to perform 20 fps video reproduction in colour of full-parallax holographic 3D images with a diagonal image size of 85 mm and a horizontal viewing-zone angle of 5.6 degrees.

Reconstruction From Multiple Particles for 3D Isotropic Resolution in Fluorescence Microscopy.

PubMed

Fortun, Denis; Guichard, Paul; Hamel, Virginie; Sorzano, Carlos Oscar S; Banterle, Niccolo; Gonczy, Pierre; Unser, Michael

2018-05-01

The imaging of proteins within macromolecular complexes has been limited by the low axial resolution of optical microscopes. To overcome this problem, we propose a novel computational reconstruction method that yields isotropic resolution in fluorescence imaging. The guiding principle is to reconstruct a single volume from the observations of multiple rotated particles. Our new operational framework detects particles, estimates their orientation, and reconstructs the final volume. The main challenge comes from the absence of initial template and a priori knowledge about the orientations. We formulate the estimation as a blind inverse problem, and propose a block-coordinate stochastic approach to solve the associated non-convex optimization problem. The reconstruction is performed jointly in multiple channels. We demonstrate that our method is able to reconstruct volumes with 3D isotropic resolution on simulated data. We also perform isotropic reconstructions from real experimental data of doubly labeled purified human centrioles. Our approach revealed the precise localization of the centriolar protein Cep63 around the centriole microtubule barrel. Overall, our method offers new perspectives for applications in biology that require the isotropic mapping of proteins within macromolecular assemblies.

Multiple Hypothesis Testing for Experimental Gingivitis Based on Wilcoxon Signed Rank Statistics

PubMed Central

Preisser, John S.; Sen, Pranab K.; Offenbacher, Steven

2011-01-01

Dental research often involves repeated multivariate outcomes on a small number of subjects for which there is interest in identifying outcomes that exhibit change in their levels over time as well as to characterize the nature of that change. In particular, periodontal research often involves the analysis of molecular mediators of inflammation for which multivariate parametric methods are highly sensitive to outliers and deviations from Gaussian assumptions. In such settings, nonparametric methods may be favored over parametric ones. Additionally, there is a need for statistical methods that control an overall error rate for multiple hypothesis testing. We review univariate and multivariate nonparametric hypothesis tests and apply them to longitudinal data to assess changes over time in 31 biomarkers measured from the gingival crevicular fluid in 22 subjects whereby gingivitis was induced by temporarily withholding tooth brushing. To identify biomarkers that can be induced to change, multivariate Wilcoxon signed rank tests for a set of four summary measures based upon area under the curve are applied for each biomarker and compared to their univariate counterparts. Multiple hypothesis testing methods with choice of control of the false discovery rate or strong control of the family-wise error rate are examined. PMID:21984957

SD-MSAEs: Promoter recognition in human genome based on deep feature extraction.

PubMed

Xu, Wenxuan; Zhang, Li; Lu, Yaping

2016-06-01

The prediction and recognition of promoter in human genome play an important role in DNA sequence analysis. Entropy, in Shannon sense, of information theory is a multiple utility in bioinformatic details analysis. The relative entropy estimator methods based on statistical divergence (SD) are used to extract meaningful features to distinguish different regions of DNA sequences. In this paper, we choose context feature and use a set of methods of SD to select the most effective n-mers distinguishing promoter regions from other DNA regions in human genome. Extracted from the total possible combinations of n-mers, we can get four sparse distributions based on promoter and non-promoters training samples. The informative n-mers are selected by optimizing the differentiating extents of these distributions. Specially, we combine the advantage of statistical divergence and multiple sparse auto-encoders (MSAEs) in deep learning to extract deep feature for promoter recognition. And then we apply multiple SVMs and a decision model to construct a human promoter recognition method called SD-MSAEs. Framework is flexible that it can integrate new feature extraction or new classification models freely. Experimental results show that our method has high sensitivity and specificity. Copyright © 2016 Elsevier Inc. All rights reserved.

Evaluating the decision accuracy and speed of clinical data visualizations.

PubMed

Pieczkiewicz, David S; Finkelstein, Stanley M

2010-01-01

Clinicians face an increasing volume of biomedical data. Assessing the efficacy of systems that enable accurate and timely clinical decision making merits corresponding attention. This paper discusses the multiple-reader multiple-case (MRMC) experimental design and linear mixed models as means of assessing and comparing decision accuracy and latency (time) for decision tasks in which clinician readers must interpret visual displays of data. These tools can assess and compare decision accuracy and latency (time). These experimental and statistical techniques, used extensively in radiology imaging studies, offer a number of practical and analytic advantages over more traditional quantitative methods such as percent-correct measurements and ANOVAs, and are recommended for their statistical efficiency and generalizability. An example analysis using readily available, free, and commercial statistical software is provided as an appendix. While these techniques are not appropriate for all evaluation questions, they can provide a valuable addition to the evaluative toolkit of medical informatics research.

Dissociative electron attachment to C{sub 2}F{sub 5} radicals

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

Haughey, Sean A.; Field, Thomas A.; Langer, Judith

Dissociative electron attachment to the reactive C{sub 2}F{sub 5} molecular radical has been investigated with two complimentary experimental methods; a single collision beam experiment and a new flowing afterglow Langmuir probe technique. The beam results show that F{sup -} is formed close to zero electron energy in dissociative electron attachment to C{sub 2}F{sub 5}. The afterglow measurements also show that F{sup -} is formed in collisions between electrons and C{sub 2}F{sub 5} molecules with rate constants of 3.7 Multiplication-Sign 10{sup -9} cm{sup 3} s{sup -1} to 4.7 Multiplication-Sign 10{sup -9} cm{sup 3} s{sup -1} at temperatures of 300-600 K. Themore » rate constant increases slowly with increasing temperature, but the rise observed is smaller than the experimental uncertainty of 35%.« less

Replicates in high dimensions, with applications to latent variable graphical models.

PubMed

Tan, Kean Ming; Ning, Yang; Witten, Daniela M; Liu, Han

2016-12-01

In classical statistics, much thought has been put into experimental design and data collection. In the high-dimensional setting, however, experimental design has been less of a focus. In this paper, we stress the importance of collecting multiple replicates for each subject in this setting. We consider learning the structure of a graphical model with latent variables, under the assumption that these variables take a constant value across replicates within each subject. By collecting multiple replicates for each subject, we are able to estimate the conditional dependence relationships among the observed variables given the latent variables. To test the null hypothesis of conditional independence between two observed variables, we propose a pairwise decorrelated score test. Theoretical guarantees are established for parameter estimation and for this test. We show that our proposal is able to estimate latent variable graphical models more accurately than some existing proposals, and apply the proposed method to a brain imaging dataset.

Immunopharmacological role of the leukotriene receptor antagonists and inhibitors of leukotrienes generating enzymes in multiple sclerosis.

PubMed

Mirshafiey, Abbas; Jadidi-Niaragh, Farhad

2010-06-01

Multiple sclerosis (MS) is a chronic inflammatory disease that involves central nervous system, and is generally associated with demyelination and axonal lesion. The effective factors for initiation of the inflammatory responses have not been known precisely so far. Leukotrienes (LTs) are inflammatory mediators with increased levels in the cerebrospinal fluid of MS patients and in experimental models of multiple sclerosis. Inhibition of LT receptors with specific antagonists can decrease inflammatory responses. In this review article we try to clarify the role of LT receptor antagonists and also inhibitors of enzymes which are involved in LTs generating pathway for treating multiple sclerosis as new targets for MS therapy. Moreover, we suggest that blockage of LT receptors by potent specific antagonists and/or agonists can be as a novel useful method in treatment of MS.

A survey of urban climate change experiments in 100 cities

PubMed Central

Castán Broto, Vanesa; Bulkeley, Harriet

2013-01-01

Cities are key sites where climate change is being addressed. Previous research has largely overlooked the multiplicity of climate change responses emerging outside formal contexts of decision-making and led by actors other than municipal governments. Moreover, existing research has largely focused on case studies of climate change mitigation in developed economies. The objective of this paper is to uncover the heterogeneous mix of actors, settings, governance arrangements and technologies involved in the governance of climate change in cities in different parts of the world. The paper focuses on urban climate change governance as a process of experimentation. Climate change experiments are presented here as interventions to try out new ideas and methods in the context of future uncertainties. They serve to understand how interventions work in practice, in new contexts where they are thought of as innovative. To study experimentation, the paper presents evidence from the analysis of a database of 627 urban climate change experiments in a sample of 100 global cities. The analysis suggests that, since 2005, experimentation is a feature of urban responses to climate change across different world regions and multiple sectors. Although experimentation does not appear to be related to particular kinds of urban economic and social conditions, some of its core features are visible. For example, experimentation tends to focus on energy. Also, both social and technical forms of experimentation are visible, but technical experimentation is more common in urban infrastructure systems. While municipal governments have a critical role in climate change experimentation, they often act alongside other actors and in a variety of forms of partnership. These findings point at experimentation as a key tool to open up new political spaces for governing climate change in the city. PMID:23805029

An exploratory trial exploring the use of a multiple intelligences teaching approach (MITA) for teaching clinical skills to first year undergraduate nursing students.

PubMed

Sheahan, Linda; While, Alison; Bloomfield, Jacqueline

2015-12-01

The teaching and learning of clinical skills is a key component of nurse education programmes. The clinical competency of pre-registration nursing students has raised questions about the proficiency of teaching strategies for clinical skill acquisition within pre-registration education. This study aimed to test the effectiveness of teaching clinical skills using a multiple intelligences teaching approach (MITA) compared with the conventional teaching approach. A randomised controlled trial was conducted. Participants were randomly allocated to an experimental group (MITA intervention) (n=46) and a control group (conventional teaching) (n=44) to learn clinical skills. Setting was in one Irish third-level educational institution. Participants were all first year nursing students (n=90) in one institution. The experimental group was taught using MITA delivered by the researcher while the control group was taught by a team of six experienced lecturers. Participant preference for learning was measured by the Index of Learning Styles (ILS). Participants' multiple intelligence (MI) preferences were measured with a multiple intelligences development assessment scale (MIDAS). All participants were assessed using the same objective structured clinical examination (OSCE) at the end of semester one and semester two. MI assessment preferences were measured by a multiple intelligences assessment preferences questionnaire. The MITA intervention was evaluated using a questionnaire. The strongest preference on ILS for both groups was the sensing style. The highest MI was interpersonal intelligence. Participants in the experimental group had higher scores in all three OSCEs (p<0.05) at Time 1, suggesting that MITA had a positive effect on clinical skill acquisition. Most participants favoured practical examinations, followed by multiple choice questions as methods of assessment. MITA was evaluated positively. The study findings support the use of MITA for clinical skills teaching and advance the understanding of how MI teaching approaches may be used in nursing education. Copyright © 2015 Elsevier Ltd. All rights reserved.

Emotion recognition based on multiple order features using fractional Fourier transform

NASA Astrophysics Data System (ADS)

Ren, Bo; Liu, Deyin; Qi, Lin

2017-07-01

In order to deal with the insufficiency of recently algorithms based on Two Dimensions Fractional Fourier Transform (2D-FrFT), this paper proposes a multiple order features based method for emotion recognition. Most existing methods utilize the feature of single order or a couple of orders of 2D-FrFT. However, different orders of 2D-FrFT have different contributions on the feature extraction of emotion recognition. Combination of these features can enhance the performance of an emotion recognition system. The proposed approach obtains numerous features that extracted in different orders of 2D-FrFT in the directions of x-axis and y-axis, and uses the statistical magnitudes as the final feature vectors for recognition. The Support Vector Machine (SVM) is utilized for the classification and RML Emotion database and Cohn-Kanade (CK) database are used for the experiment. The experimental results demonstrate the effectiveness of the proposed method.

Pathway-based analyses.

PubMed

Kent, Jack W

2016-02-03

New technologies for acquisition of genomic data, while offering unprecedented opportunities for genetic discovery, also impose severe burdens of interpretation and penalties for multiple testing. The Pathway-based Analyses Group of the Genetic Analysis Workshop 19 (GAW19) sought reduction of multiple-testing burden through various approaches to aggregation of highdimensional data in pathways informed by prior biological knowledge. Experimental methods testedincluded the use of "synthetic pathways" (random sets of genes) to estimate power and false-positive error rate of methods applied to simulated data; data reduction via independent components analysis, single-nucleotide polymorphism (SNP)-SNP interaction, and use of gene sets to estimate genetic similarity; and general assessment of the efficacy of prior biological knowledge to reduce the dimensionality of complex genomic data. The work of this group explored several promising approaches to managing high-dimensional data, with the caveat that these methods are necessarily constrained by the quality of external bioinformatic annotation.

High Dynamic Range Imaging Using Multiple Exposures

NASA Astrophysics Data System (ADS)

Hou, Xinglin; Luo, Haibo; Zhou, Peipei; Zhou, Wei

2017-06-01

It is challenging to capture a high-dynamic range (HDR) scene using a low-dynamic range (LDR) camera. This paper presents an approach for improving the dynamic range of cameras by using multiple exposure images of same scene taken under different exposure times. First, the camera response function (CRF) is recovered by solving a high-order polynomial in which only the ratios of the exposures are used. Then, the HDR radiance image is reconstructed by weighted summation of the each radiance maps. After that, a novel local tone mapping (TM) operator is proposed for the display of the HDR radiance image. By solving the high-order polynomial, the CRF can be recovered quickly and easily. Taken the local image feature and characteristic of histogram statics into consideration, the proposed TM operator could preserve the local details efficiently. Experimental result demonstrates the effectiveness of our method. By comparison, the method outperforms other methods in terms of imaging quality.

Convex formulation of multiple instance learning from positive and unlabeled bags.

PubMed

Bao, Han; Sakai, Tomoya; Sato, Issei; Sugiyama, Masashi

2018-05-24

Multiple instance learning (MIL) is a variation of traditional supervised learning problems where data (referred to as bags) are composed of sub-elements (referred to as instances) and only bag labels are available. MIL has a variety of applications such as content-based image retrieval, text categorization, and medical diagnosis. Most of the previous work for MIL assume that training bags are fully labeled. However, it is often difficult to obtain an enough number of labeled bags in practical situations, while many unlabeled bags are available. A learning framework called PU classification (positive and unlabeled classification) can address this problem. In this paper, we propose a convex PU classification method to solve an MIL problem. We experimentally show that the proposed method achieves better performance with significantly lower computation costs than an existing method for PU-MIL. Copyright © 2018 Elsevier Ltd. All rights reserved.

Difference method to search for the anisotropy of primary cosmic radiation

NASA Astrophysics Data System (ADS)

Pavlyuchenko, V. P.; Martirosov, R. M.; Nikolskaya, N. M.; Erlykin, A. D.

2018-01-01

The original difference method used in the search for an anisotropy of primary cosmic radiation at the knee region of its energy spectrum is considered. Its methodical features and properties are analyzed. It is shown that this method, in which properties of particle fluxes (rather than an intensity) are investigated, is stable against random experimental errors and allows one to separate anomalies connected with the laboratory coordinate system from anomalies in the celestial coordinate system. The method uses the multiple scattering of charged particles in the magnetic fields of the Galaxy to study the whole celestial sphere, including the regions outside the line of sight of the installation.

Optimization of multi response in end milling process of ASSAB XW-42 tool steel with liquid nitrogen cooling using Taguchi-grey relational analysis

NASA Astrophysics Data System (ADS)

Norcahyo, Rachmadi; Soepangkat, Bobby O. P.

2017-06-01

A research was conducted for the optimization of the end milling process of ASSAB XW-42 tool steel with multiple performance characteristics based on the orthogonal array with Taguchi-grey relational analysis method. Liquid nitrogen was applied as a coolant. The experimental studies were conducted under varying the liquid nitrogen cooling flow rates (FL), and the end milling process variables, i.e., cutting speed (Vc), feeding speed (Vf), and axial depth of cut (Aa). The optimized multiple performance characteristics were surface roughness (SR), flank wear (VB), and material removal rate (MRR). An orthogonal array, signal-to-noise (S/N) ratio, grey relational analysis, grey relational grade, and analysis of variance were employed to study the multiple performance characteristics. Experimental results showed that flow rate gave the highest contribution for reducing the total variation of the multiple responses, followed by cutting speed, feeding speed, and axial depth of cut. The minimum surface roughness, flank wear, and maximum material removal rate could be obtained by using the values of flow rate, cutting speed, feeding speed, and axial depth of cut of 0.5 l/minute, 109.9 m/minute, 440 mm/minute, and 0.9 mm, respectively.

Markov chains for testing redundant software

NASA Technical Reports Server (NTRS)

White, Allan L.; Sjogren, Jon A.

1988-01-01

A preliminary design for a validation experiment has been developed that addresses several problems unique to assuring the extremely high quality of multiple-version programs in process-control software. The procedure uses Markov chains to model the error states of the multiple version programs. The programs are observed during simulated process-control testing, and estimates are obtained for the transition probabilities between the states of the Markov chain. The experimental Markov chain model is then expanded into a reliability model that takes into account the inertia of the system being controlled. The reliability of the multiple version software is computed from this reliability model at a given confidence level using confidence intervals obtained for the transition probabilities during the experiment. An example demonstrating the method is provided.

Palmprint authentication using multiple classifiers

NASA Astrophysics Data System (ADS)

Kumar, Ajay; Zhang, David

2004-08-01

This paper investigates the performance improvement for palmprint authentication using multiple classifiers. The proposed methods on personal authentication using palmprints can be divided into three categories; appearance- , line -, and texture-based. A combination of these approaches can be used to achieve higher performance. We propose to simultaneously extract palmprint features from PCA, Line detectors and Gabor-filters and combine their corresponding matching scores. This paper also investigates the comparative performance of simple combination rules and the hybrid fusion strategy to achieve performance improvement. Our experimental results on the database of 100 users demonstrate the usefulness of such approach over those based on individual classifiers.

A novel statistical method for quantitative comparison of multiple ChIP-seq datasets.

PubMed

Chen, Li; Wang, Chi; Qin, Zhaohui S; Wu, Hao

2015-06-15

ChIP-seq is a powerful technology to measure the protein binding or histone modification strength in the whole genome scale. Although there are a number of methods available for single ChIP-seq data analysis (e.g. 'peak detection'), rigorous statistical method for quantitative comparison of multiple ChIP-seq datasets with the considerations of data from control experiment, signal to noise ratios, biological variations and multiple-factor experimental designs is under-developed. In this work, we develop a statistical method to perform quantitative comparison of multiple ChIP-seq datasets and detect genomic regions showing differential protein binding or histone modification. We first detect peaks from all datasets and then union them to form a single set of candidate regions. The read counts from IP experiment at the candidate regions are assumed to follow Poisson distribution. The underlying Poisson rates are modeled as an experiment-specific function of artifacts and biological signals. We then obtain the estimated biological signals and compare them through the hypothesis testing procedure in a linear model framework. Simulations and real data analyses demonstrate that the proposed method provides more accurate and robust results compared with existing ones. An R software package ChIPComp is freely available at http://web1.sph.emory.edu/users/hwu30/software/ChIPComp.html. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Exploring effective multiplicity in multichannel functional near-infrared spectroscopy using eigenvalues of correlation matrices

PubMed Central

Uga, Minako; Dan, Ippeita; Dan, Haruka; Kyutoku, Yasushi; Taguchi, Y-h; Watanabe, Eiju

2015-01-01

Abstract. Recent advances in multichannel functional near-infrared spectroscopy (fNIRS) allow wide coverage of cortical areas while entailing the necessity to control family-wise errors (FWEs) due to increased multiplicity. Conventionally, the Bonferroni method has been used to control FWE. While Type I errors (false positives) can be strictly controlled, the application of a large number of channel settings may inflate the chance of Type II errors (false negatives). The Bonferroni-based methods are especially stringent in controlling Type I errors of the most activated channel with the smallest p value. To maintain a balance between Types I and II errors, effective multiplicity (Meff) derived from the eigenvalues of correlation matrices is a method that has been introduced in genetic studies. Thus, we explored its feasibility in multichannel fNIRS studies. Applying the Meff method to three kinds of experimental data with different activation profiles, we performed resampling simulations and found that Meff was controlled at 10 to 15 in a 44-channel setting. Consequently, the number of significantly activated channels remained almost constant regardless of the number of measured channels. We demonstrated that the Meff approach can be an effective alternative to Bonferroni-based methods for multichannel fNIRS studies. PMID:26157982

Quantized phase coding and connected region labeling for absolute phase retrieval.

PubMed

Chen, Xiangcheng; Wang, Yuwei; Wang, Yajun; Ma, Mengchao; Zeng, Chunnian

2016-12-12

This paper proposes an absolute phase retrieval method for complex object measurement based on quantized phase-coding and connected region labeling. A specific code sequence is embedded into quantized phase of three coded fringes. Connected regions of different codes are labeled and assigned with 3-digit-codes combining the current period and its neighbors. Wrapped phase, more than 36 periods, can be restored with reference to the code sequence. Experimental results verify the capability of the proposed method to measure multiple isolated objects.

Modeling the interaction of biological cells with a solidifying interface

NASA Astrophysics Data System (ADS)

Chang, Anthony; Dantzig, Jonathan A.; Darr, Brian T.; Hubel, Allison

2007-10-01

In this article, we develop a modified level set method for modeling the interaction of particles with a solidifying interface. The dynamic computation of the van der Waals and drag forces between the particles and the solidification front leads to a problem of multiple length scales, which we resolve using adaptive grid techniques. We present a variety of example problems to demonstrate the accuracy and utility of the method. We also use the model to interpret experimental results obtained using directional solidification in a cryomicroscope.

Experimental Validation of Normalized Uniform Load Surface Curvature Method for Damage Localization

PubMed Central

Jung, Ho-Yeon; Sung, Seung-Hoon; Jung, Hyung-Jo

2015-01-01

In this study, we experimentally validated the normalized uniform load surface (NULS) curvature method, which has been developed recently to assess damage localization in beam-type structures. The normalization technique allows for the accurate assessment of damage localization with greater sensitivity irrespective of the damage location. In this study, damage to a simply supported beam was numerically and experimentally investigated on the basis of the changes in the NULS curvatures, which were estimated from the modal flexibility matrices obtained from the acceleration responses under an ambient excitation. Two damage scenarios were considered for the single damage case as well as the multiple damages case by reducing the bending stiffness (EI) of the affected element(s). Numerical simulations were performed using MATLAB as a preliminary step. During the validation experiments, a series of tests were performed. It was found that the damage locations could be identified successfully without any false-positive or false-negative detections using the proposed method. For comparison, the damage detection performances were compared with those of two other well-known methods based on the modal flexibility matrix, namely, the uniform load surface (ULS) method and the ULS curvature method. It was confirmed that the proposed method is more effective for investigating the damage locations of simply supported beams than the two conventional methods in terms of sensitivity to damage under measurement noise. PMID:26501286

Detection of Road Surface States from Tire Noise Using Neural Network Analysis

NASA Astrophysics Data System (ADS)

Kongrattanaprasert, Wuttiwat; Nomura, Hideyuki; Kamakura, Tomoo; Ueda, Koji

This report proposes a new processing method for automatically detecting the states of road surfaces from tire noises of passing vehicles. In addition to multiple indicators of the signal features in the frequency domain, we propose a few feature indicators in the time domain to successfully classify the road states into four categories: snowy, slushy, wet, and dry states. The method is based on artificial neural networks. The proposed classification is carried out in multiple neural networks using learning vector quantization. The outcomes of the networks are then integrated by the voting decision-making scheme. Experimental results obtained from recorded signals for ten days in the snowy season demonstrated that an accuracy of approximately 90% can be attained for predicting road surface states using only tire noise data.

Probabilistic Low-Rank Multitask Learning.

PubMed

Kong, Yu; Shao, Ming; Li, Kang; Fu, Yun

2018-03-01

In this paper, we consider the problem of learning multiple related tasks simultaneously with the goal of improving the generalization performance of individual tasks. The key challenge is to effectively exploit the shared information across multiple tasks as well as preserve the discriminative information for each individual task. To address this, we propose a novel probabilistic model for multitask learning (MTL) that can automatically balance between low-rank and sparsity constraints. The former assumes a low-rank structure of the underlying predictive hypothesis space to explicitly capture the relationship of different tasks and the latter learns the incoherent sparse patterns private to each task. We derive and perform inference via variational Bayesian methods. Experimental results on both regression and classification tasks on real-world applications demonstrate the effectiveness of the proposed method in dealing with the MTL problems.

Retrieval of Droplet size Density Distribution from Multiple field of view Cross polarized Lidar Signals: Theory and Experimental Validation

DTIC Science & Technology

2016-06-02

Retrieval of droplet-size density distribution from multiple-field-of-view cross-polarized lidar signals: theory and experimental validation...theoretical and experimental studies of mul- tiple scattering and multiple-field-of-view (MFOV) li- dar detection have made possible the retrieval of cloud...droplet cloud are typical of Rayleigh scattering, with a signature close to a dipole (phase function quasi -flat and a zero-depolarization ratio

Ligand-biased ensemble receptor docking (LigBEnD): a hybrid ligand/receptor structure-based approach

NASA Astrophysics Data System (ADS)

Lam, Polo C.-H.; Abagyan, Ruben; Totrov, Maxim

2018-01-01

Ligand docking to flexible protein molecules can be efficiently carried out through ensemble docking to multiple protein conformations, either from experimental X-ray structures or from in silico simulations. The success of ensemble docking often requires the careful selection of complementary protein conformations, through docking and scoring of known co-crystallized ligands. False positives, in which a ligand in a wrong pose achieves a better docking score than that of native pose, arise as additional protein conformations are added. In the current study, we developed a new ligand-biased ensemble receptor docking method and composite scoring function which combine the use of ligand-based atomic property field (APF) method with receptor structure-based docking. This method helps us to correctly dock 30 out of 36 ligands presented by the D3R docking challenge. For the six mis-docked ligands, the cognate receptor structures prove to be too different from the 40 available experimental Pocketome conformations used for docking and could be identified only by receptor sampling beyond experimentally explored conformational subspace.

Use of diaminofluoresceins to detect and measure nitric oxide in low level generating human immune cells.

PubMed

Tiscornia, Adriana; Cairoli, Ernesto; Marquez, Maria; Denicola, Ana; Pritsch, Otto; Cayota, Alfonso

2009-03-15

Nitric oxide ((*)NO) has been implicated in multiple physiological and pathological immune processes. Different methods have been developed to detect and quantify (*)NO, where one of the principal difficulties are the accurately detection in cellular system with low levels of (*)NO production. The choice of the (*)NO detection method to be used depends on the characteristics of the experimental system and the levels of (*)NO production which depend on either the organism source of samples or the experimental conditions. Recently, high sensitive methods to detect and image (*)NO have been reported using 4,5-diaminofluorescein-based fluorescent probes (DAF) and its derivate 4,5-diaminofluorescein diacetate (DAF-2 DA). This work was aimed to adapt and optimize the use of DAF probes to detect and quantify the (*)NO production in systems of high, moderate and low out-put production, especially in human PBMC and their subpopulations. Here, we report an original experimental design which is useful to detect and estimate (*)NO fluxes in human PBMC and their subpopulations with high specificity and sensitivity.

Accelerated SPECT Monte Carlo Simulation Using Multiple Projection Sampling and Convolution-Based Forced Detection

NASA Astrophysics Data System (ADS)

Liu, Shaoying; King, Michael A.; Brill, Aaron B.; Stabin, Michael G.; Farncombe, Troy H.

2008-02-01

Monte Carlo (MC) is a well-utilized tool for simulating photon transport in single photon emission computed tomography (SPECT) due to its ability to accurately model physical processes of photon transport. As a consequence of this accuracy, it suffers from a relatively low detection efficiency and long computation time. One technique used to improve the speed of MC modeling is the effective and well-established variance reduction technique (VRT) known as forced detection (FD). With this method, photons are followed as they traverse the object under study but are then forced to travel in the direction of the detector surface, whereby they are detected at a single detector location. Another method, called convolution-based forced detection (CFD), is based on the fundamental idea of FD with the exception that detected photons are detected at multiple detector locations and determined with a distance-dependent blurring kernel. In order to further increase the speed of MC, a method named multiple projection convolution-based forced detection (MP-CFD) is presented. Rather than forcing photons to hit a single detector, the MP-CFD method follows the photon transport through the object but then, at each scatter site, forces the photon to interact with a number of detectors at a variety of angles surrounding the object. This way, it is possible to simulate all the projection images of a SPECT simulation in parallel, rather than as independent projections. The result of this is vastly improved simulation time as much of the computation load of simulating photon transport through the object is done only once for all projection angles. The results of the proposed MP-CFD method agrees well with the experimental data in measurements of point spread function (PSF), producing a correlation coefficient (r2) of 0.99 compared to experimental data. The speed of MP-CFD is shown to be about 60 times faster than a regular forced detection MC program with similar results.

Uncovering noisy social signals: Using optimization methods from experimental physics to study social phenomena.

PubMed

Kaptein, Maurits; van Emden, Robin; Iannuzzi, Davide

2017-01-01

Due to the ubiquitous presence of treatment heterogeneity, measurement error, and contextual confounders, numerous social phenomena are hard to study. Precise control of treatment variables and possible confounders is often key to the success of studies in the social sciences, yet often proves out of the realm of control of the experimenter. To amend this situation we propose a novel approach coined "lock-in feedback" which is based on a method that is routinely used in high-precision physics experiments to extract small signals out of a noisy environment. Here, we adapt the method to noisy social signals in multiple dimensions and evaluate it by studying an inherently noisy topic: the perception of (subjective) beauty. We show that the lock-in feedback approach allows one to select optimal treatment levels despite the presence of considerable noise. Furthermore, through the introduction of an external contextual shock we demonstrate that we can find relationships between noisy variables that were hitherto unknown. We therefore argue that lock-in methods may provide a valuable addition to the social scientist's experimental toolbox and we explicitly discuss a number of future applications.

Full-degrees-of-freedom frequency based substructuring

NASA Astrophysics Data System (ADS)

Drozg, Armin; Čepon, Gregor; Boltežar, Miha

2018-01-01

Dividing the whole system into multiple subsystems and a separate dynamic analysis is common practice in the field of structural dynamics. The substructuring process improves the computational efficiency and enables an effective realization of the local optimization, modal updating and sensitivity analyses. This paper focuses on frequency-based substructuring methods using experimentally obtained data. An efficient substructuring process has already been demonstrated using numerically obtained frequency-response functions (FRFs). However, the experimental process suffers from several difficulties, among which, many of them are related to the rotational degrees of freedom. Thus, several attempts have been made to measure, expand or combine numerical correction methods in order to obtain a complete response model. The proposed methods have numerous limitations and are not yet generally applicable. Therefore, in this paper an alternative approach based on experimentally obtained data only, is proposed. The force-excited part of the FRF matrix is measured with piezoelectric translational and rotational direct accelerometers. The incomplete moment-excited part of the FRF matrix is expanded, based on the modal model. The proposed procedure is integrated in a Lagrange Multiplier Frequency Based Substructuring method and demonstrated on a simple beam structure, where the connection coordinates are mainly associated with the rotational degrees of freedom.

Uncovering noisy social signals: Using optimization methods from experimental physics to study social phenomena

PubMed Central

2017-01-01

Due to the ubiquitous presence of treatment heterogeneity, measurement error, and contextual confounders, numerous social phenomena are hard to study. Precise control of treatment variables and possible confounders is often key to the success of studies in the social sciences, yet often proves out of the realm of control of the experimenter. To amend this situation we propose a novel approach coined “lock-in feedback” which is based on a method that is routinely used in high-precision physics experiments to extract small signals out of a noisy environment. Here, we adapt the method to noisy social signals in multiple dimensions and evaluate it by studying an inherently noisy topic: the perception of (subjective) beauty. We show that the lock-in feedback approach allows one to select optimal treatment levels despite the presence of considerable noise. Furthermore, through the introduction of an external contextual shock we demonstrate that we can find relationships between noisy variables that were hitherto unknown. We therefore argue that lock-in methods may provide a valuable addition to the social scientist’s experimental toolbox and we explicitly discuss a number of future applications. PMID:28306728

Experimental results of use of triple-energy X-ray beam with K-edge filter in multi-energy imaging

NASA Astrophysics Data System (ADS)

Kim, D.; Lee, S.; Jeon, P.-H.

2016-04-01

Multi-energy imaging is useful for contrast enhancement of lesions, quantitative analysis of specific materials and material separation in the human body. Generally, dual-energy methods are applied to discriminating two materials, but this method cannot discriminate more than two materials. Photon-counting detectors provide spectral information from polyenergetic X-rays using multiple energy bins. In this work, we developed triple-energy X-ray beams using a filter with K-edge energy and applied them experimentally. The energy spectra of triple-energy X-ray beams were assessed by using a spectrometer. The designed triple-energy X-ray beams were validated by measuring quantitative evaluations with mean energy ratio (MER), contrast variation ratio (CVR) and exposure efficiency (EE). Then, triple-energy X-ray beams were used to extract density map of three materials, iodine (I), aluminum (Al) and polymethyl methacrylate (PMMA). The results of the thickness density maps obtained with the developed triple-energy X-ray beams were compared to those acquired using the photon-counting method. As a result, it was found experimentally that the proposed triple-energy X-ray beam technique can separate the three materials as well as the photon-counting method.

Multiple sound source localization using gammatone auditory filtering and direct sound componence detection

NASA Astrophysics Data System (ADS)

Chen, Huaiyu; Cao, Li

2017-06-01

In order to research multiple sound source localization with room reverberation and background noise, we analyze the shortcomings of traditional broadband MUSIC and ordinary auditory filtering based broadband MUSIC method, then a new broadband MUSIC algorithm with gammatone auditory filtering of frequency component selection control and detection of ascending segment of direct sound componence is proposed. The proposed algorithm controls frequency component within the interested frequency band in multichannel bandpass filter stage. Detecting the direct sound componence of the sound source for suppressing room reverberation interference is also proposed, whose merits are fast calculation and avoiding using more complex de-reverberation processing algorithm. Besides, the pseudo-spectrum of different frequency channels is weighted by their maximum amplitude for every speech frame. Through the simulation and real room reverberation environment experiments, the proposed method has good performance. Dynamic multiple sound source localization experimental results indicate that the average absolute error of azimuth estimated by the proposed algorithm is less and the histogram result has higher angle resolution.

Imaging complex objects using learning tomography

NASA Astrophysics Data System (ADS)

Lim, JooWon; Goy, Alexandre; Shoreh, Morteza Hasani; Unser, Michael; Psaltis, Demetri

2018-02-01

Optical diffraction tomography (ODT) can be described using the scattering process through an inhomogeneous media. An inherent nonlinearity exists relating the scattering medium and the scattered field due to multiple scattering. Multiple scattering is often assumed to be negligible in weakly scattering media. This assumption becomes invalid as the sample gets more complex resulting in distorted image reconstructions. This issue becomes very critical when we image a complex sample. Multiple scattering can be simulated using the beam propagation method (BPM) as the forward model of ODT combined with an iterative reconstruction scheme. The iterative error reduction scheme and the multi-layer structure of BPM are similar to neural networks. Therefore we refer to our imaging method as learning tomography (LT). To fairly assess the performance of LT in imaging complex samples, we compared LT with the conventional iterative linear scheme using Mie theory which provides the ground truth. We also demonstrate the capacity of LT to image complex samples using experimental data of a biological cell.

Neural-Fuzzy model Based Steel Pipeline Multiple Cracks Classification

NASA Astrophysics Data System (ADS)

Elwalwal, Hatem Mostafa; Mahzan, Shahruddin Bin Hj.; Abdalla, Ahmed N.

2017-10-01

While pipes are cheaper than other means of transportation, this cost saving comes with a major price: pipes are subject to cracks, corrosion etc., which in turn can cause leakage and environmental damage. In this paper, Neural-Fuzzy model for multiple cracks classification based on Lamb Guide Wave. Simulation results for 42 sample were collected using ANSYS software. The current research object to carry on the numerical simulation and experimental study, aiming at finding an effective way to detection and the localization of cracks and holes defects in the main body of pipeline. Considering the damage form of multiple cracks and holes which may exist in pipeline, to determine the respective position in the steel pipe. In addition, the technique used in this research a guided lamb wave based structural health monitoring method whereas piezoelectric transducers will use as exciting and receiving sensors by Pitch-Catch method. Implementation of simple learning mechanism has been developed specially for the ANN for fuzzy the system represented.

Mixture-based gatekeeping procedures in adaptive clinical trials.

PubMed

Kordzakhia, George; Dmitrienko, Alex; Ishida, Eiji

2018-01-01

Clinical trials with data-driven decision rules often pursue multiple clinical objectives such as the evaluation of several endpoints or several doses of an experimental treatment. These complex analysis strategies give rise to "multivariate" multiplicity problems with several components or sources of multiplicity. A general framework for defining gatekeeping procedures in clinical trials with adaptive multistage designs is proposed in this paper. The mixture method is applied to build a gatekeeping procedure at each stage and inferences at each decision point (interim or final analysis) are performed using the combination function approach. An advantage of utilizing the mixture method is that it enables powerful gatekeeping procedures applicable to a broad class of settings with complex logical relationships among the hypotheses of interest. Further, the combination function approach supports flexible data-driven decisions such as a decision to increase the sample size or remove a treatment arm. The paper concludes with a clinical trial example that illustrates the methodology by applying it to develop an adaptive two-stage design with a mixture-based gatekeeping procedure.

Perturbation Theory/Machine Learning Model of ChEMBL Data for Dopamine Targets: Docking, Synthesis, and Assay of New l-Prolyl-l-leucyl-glycinamide Peptidomimetics.

PubMed

Ferreira da Costa, Joana; Silva, David; Caamaño, Olga; Brea, José M; Loza, Maria Isabel; Munteanu, Cristian R; Pazos, Alejandro; García-Mera, Xerardo; González-Díaz, Humbert

2018-06-25

Predicting drug-protein interactions (DPIs) for target proteins involved in dopamine pathways is a very important goal in medicinal chemistry. We can tackle this problem using Molecular Docking or Machine Learning (ML) models for one specific protein. Unfortunately, these models fail to account for large and complex big data sets of preclinical assays reported in public databases. This includes multiple conditions of assays, such as different experimental parameters, biological assays, target proteins, cell lines, organism of the target, or organism of assay. On the other hand, perturbation theory (PT) models allow us to predict the properties of a query compound or molecular system in experimental assays with multiple boundary conditions based on a previously known case of reference. In this work, we report the first PTML (PT + ML) study of a large ChEMBL data set of preclinical assays of compounds targeting dopamine pathway proteins. The best PTML model found predicts 50000 cases with accuracy of 70-91% in training and external validation series. We also compared the linear PTML model with alternative PTML models trained with multiple nonlinear methods (artificial neural network (ANN), Random Forest, Deep Learning, etc.). Some of the nonlinear methods outperform the linear model but at the cost of a notable increment of the complexity of the model. We illustrated the practical use of the new model with a proof-of-concept theoretical-experimental study. We reported for the first time the organic synthesis, chemical characterization, and pharmacological assay of a new series of l-prolyl-l-leucyl-glycinamide (PLG) peptidomimetic compounds. In addition, we performed a molecular docking study for some of these compounds with the software Vina AutoDock. The work ends with a PTML model predictive study of the outcomes of the new compounds in a large number of assays. Therefore, this study offers a new computational methodology for predicting the outcome for any compound in new assays. This PTML method focuses on the prediction with a simple linear model of multiple pharmacological parameters (IC 50 , EC 50 , K i , etc.) for compounds in assays involving different cell lines used, organisms of the protein target, or organism of assay for proteins in the dopamine pathway.

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

PubMed

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

2017-05-11

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

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

PubMed Central

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

2017-01-01

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

Automatically generated acceptance test: A software reliability experiment

NASA Technical Reports Server (NTRS)

Protzel, Peter W.

1988-01-01

This study presents results of a software reliability experiment investigating the feasibility of a new error detection method. The method can be used as an acceptance test and is solely based on empirical data about the behavior of internal states of a program. The experimental design uses the existing environment of a multi-version experiment previously conducted at the NASA Langley Research Center, in which the launch interceptor problem is used as a model. This allows the controlled experimental investigation of versions with well-known single and multiple faults, and the availability of an oracle permits the determination of the error detection performance of the test. Fault interaction phenomena are observed that have an amplifying effect on the number of error occurrences. Preliminary results indicate that all faults examined so far are detected by the acceptance test. This shows promise for further investigations, and for the employment of this test method on other applications.

Reaction Mechanisms on Multiwell Potential Energy Surfaces in Combustion (and Atmospheric) Chemistry

DOE PAGES

Osborn, David L.

2017-03-15

Chemical reactions occurring on a potential energy surface with multiple wells are ubiquitous in low temperature combustion and the oxidation of volatile organic compounds in earth’s atmosphere. The rich variety of structural isomerizations that compete with collisional stabilization make characterizing such complex-forming reactions challenging. This review describes recent experimental and theoretical advances that deliver increasingly complete views of their reaction mechanisms. New methods for creating reactive intermediates coupled with multiplexed measurements provide many experimental observables simultaneously. Automated methods to explore potential energy surfaces can uncover hidden reactive pathways, while master equation methods enable a holistic treatment of both sequential andmore » well-skipping pathways. Our ability to probe and understand nonequilibrium effects and reaction sequences is increasing. These advances provide the fundamental science base for predictive models of combustion and the atmosphere that are crucial to address global challenges.« less

Reaction Mechanisms on Multiwell Potential Energy Surfaces in Combustion (and Atmospheric) Chemistry

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

Osborn, David L.

Chemical reactions occurring on a potential energy surface with multiple wells are ubiquitous in low temperature combustion and the oxidation of volatile organic compounds in earth’s atmosphere. The rich variety of structural isomerizations that compete with collisional stabilization make characterizing such complex-forming reactions challenging. This review describes recent experimental and theoretical advances that deliver increasingly complete views of their reaction mechanisms. New methods for creating reactive intermediates coupled with multiplexed measurements provide many experimental observables simultaneously. Automated methods to explore potential energy surfaces can uncover hidden reactive pathways, while master equation methods enable a holistic treatment of both sequential andmore » well-skipping pathways. Our ability to probe and understand nonequilibrium effects and reaction sequences is increasing. These advances provide the fundamental science base for predictive models of combustion and the atmosphere that are crucial to address global challenges.« less

A community computational challenge to predict the activity of pairs of compounds.

PubMed

Bansal, Mukesh; Yang, Jichen; Karan, Charles; Menden, Michael P; Costello, James C; Tang, Hao; Xiao, Guanghua; Li, Yajuan; Allen, Jeffrey; Zhong, Rui; Chen, Beibei; Kim, Minsoo; Wang, Tao; Heiser, Laura M; Realubit, Ronald; Mattioli, Michela; Alvarez, Mariano J; Shen, Yao; Gallahan, Daniel; Singer, Dinah; Saez-Rodriguez, Julio; Xie, Yang; Stolovitzky, Gustavo; Califano, Andrea

2014-12-01

Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction.

Designing Studies That Would Address the Multilayered Nature of Health Care

PubMed Central

Pennell, Michael; Rhoda, Dale; Hade, Erinn M.; Paskett, Electra D.

2010-01-01

We review design and analytic methods available for multilevel interventions in cancer research with particular attention to study design, sample size requirements, and potential to provide statistical evidence for causal inference. The most appropriate methods will depend on the stage of development of the research and whether randomization is possible. Early on, fractional factorial designs may be used to screen intervention components, particularly when randomization of individuals is possible. Quasi-experimental designs, including time-series and multiple baseline designs, can be useful once the intervention is designed because they require few sites and can provide the preliminary evidence to plan efficacy studies. In efficacy and effectiveness studies, group-randomized trials are preferred when randomization is possible and regression discontinuity designs are preferred otherwise if assignment based on a quantitative score is possible. Quasi-experimental designs may be used, especially when combined with recent developments in analytic methods to reduce bias in effect estimates. PMID:20386057

FMC/TFM experimental comparisons

NASA Astrophysics Data System (ADS)

Spencer, Roger; Sunderman, Ruth; Todorov, Evgueni

2018-04-01

Ultrasonic full matrix capture/total focusing method (FMC/TFM) technology has progressed significantly over the past few years and has seen increased use in industry. The technology has the potential to provide better detection and measurement capabilities for weld flaws, as well as, many other applications including additive manufacturing. This project looked at the effectiveness of FMC/TFM for detection and sizing of both planar and volumetric flaw types. FMC/TFM experimental data was collected and processed using multiple combinations of probe types and wave propagation modes. The data was then compared to typical ultrasonic phased-array results, as well as FMC/TFM inspection simulations.

Acoustic Source Localization in Aircraft Interiors Using Microphone Array Technologies

NASA Technical Reports Server (NTRS)

Sklanka, Bernard J.; Tuss, Joel R.; Buehrle, Ralph D.; Klos, Jacob; Williams, Earl G.; Valdivia, Nicolas

2006-01-01

Using three microphone array configurations at two aircraft body stations on a Boeing 777-300ER flight test, the acoustic radiation characteristics of the sidewall and outboard floor system are investigated by experimental measurement. Analysis of the experimental data is performed using sound intensity calculations for closely spaced microphones, PATCH Inverse Boundary Element Nearfield Acoustic Holography, and Spherical Nearfield Acoustic Holography. Each method is compared assessing strengths and weaknesses, evaluating source identification capability for both broadband and narrowband sources, evaluating sources during transient and steady-state conditions, and quantifying field reconstruction continuity using multiple array positions.

Multiple Active Contours Guided by Differential Evolution for Medical Image Segmentation

PubMed Central

Cruz-Aceves, I.; Avina-Cervantes, J. G.; Lopez-Hernandez, J. M.; Rostro-Gonzalez, H.; Garcia-Capulin, C. H.; Torres-Cisneros, M.; Guzman-Cabrera, R.

2013-01-01

This paper presents a new image segmentation method based on multiple active contours guided by differential evolution, called MACDE. The segmentation method uses differential evolution over a polar coordinate system to increase the exploration and exploitation capabilities regarding the classical active contour model. To evaluate the performance of the proposed method, a set of synthetic images with complex objects, Gaussian noise, and deep concavities is introduced. Subsequently, MACDE is applied on datasets of sequential computed tomography and magnetic resonance images which contain the human heart and the human left ventricle, respectively. Finally, to obtain a quantitative and qualitative evaluation of the medical image segmentations compared to regions outlined by experts, a set of distance and similarity metrics has been adopted. According to the experimental results, MACDE outperforms the classical active contour model and the interactive Tseng method in terms of efficiency and robustness for obtaining the optimal control points and attains a high accuracy segmentation. PMID:23983809

Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling

NASA Astrophysics Data System (ADS)

Bhakat, Soumendranath; Åberg, Emil; Söderhjelm, Pär

2018-01-01

Advanced molecular docking methods often aim at capturing the flexibility of the protein upon binding to the ligand. In this study, we investigate whether instead a simple rigid docking method can be applied, if combined with multiple target structures to model the backbone flexibility and molecular dynamics simulations to model the sidechain and ligand flexibility. The methods are tested for the binding of 35 ligands to FXR as part of the first stage of the Drug Design Data Resource (D3R) Grand Challenge 2 blind challenge. The results show that the multiple-target docking protocol performs surprisingly well, with correct poses found for 21 of the ligands. MD simulations started on the docked structures are remarkably stable, but show almost no tendency of refining the structure closer to the experimentally found binding pose. Reconnaissance metadynamics enhances the exploration of new binding poses, but additional collective variables involving the protein are needed to exploit the full potential of the method.

Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling.

PubMed

Bhakat, Soumendranath; Åberg, Emil; Söderhjelm, Pär

2018-01-01

Advanced molecular docking methods often aim at capturing the flexibility of the protein upon binding to the ligand. In this study, we investigate whether instead a simple rigid docking method can be applied, if combined with multiple target structures to model the backbone flexibility and molecular dynamics simulations to model the sidechain and ligand flexibility. The methods are tested for the binding of 35 ligands to FXR as part of the first stage of the Drug Design Data Resource (D3R) Grand Challenge 2 blind challenge. The results show that the multiple-target docking protocol performs surprisingly well, with correct poses found for 21 of the ligands. MD simulations started on the docked structures are remarkably stable, but show almost no tendency of refining the structure closer to the experimentally found binding pose. Reconnaissance metadynamics enhances the exploration of new binding poses, but additional collective variables involving the protein are needed to exploit the full potential of the method.

Method for Calculating the Optical Diffuse Reflection Coefficient for the Ocular Fundus

NASA Astrophysics Data System (ADS)

Lisenko, S. A.; Kugeiko, M. M.

2016-07-01

We have developed a method for calculating the optical diffuse reflection coefficient for the ocular fundus, taking into account multiple scattering of light in its layers (retina, epithelium, choroid) and multiple refl ection of light between layers. The method is based on the formulas for optical "combination" of the layers of the medium, in which the optical parameters of the layers (absorption and scattering coefficients) are replaced by some effective values, different for cases of directional and diffuse illumination of the layer. Coefficients relating the effective optical parameters of the layers and the actual values were established based on the results of a Monte Carlo numerical simulation of radiation transport in the medium. We estimate the uncertainties in retrieval of the structural and morphological parameters for the fundus from its diffuse reflectance spectrum using our method. We show that the simulated spectra correspond to the experimental data and that the estimates of the fundus parameters obtained as a result of solving the inverse problem are reasonable.

Experimental treatment of neoplasic diseases and tumors with iono magnetic therapy

NASA Astrophysics Data System (ADS)

Rizsanyi, Elek Karsay; Quiróz, David Lavan; Huamaccto, Carlos Levano; Marroquín, Erwin Guerra

2001-10-01

The Iono Magnetic Therapy is a alternative control method for cell growth population in pancreas and cerebral cancer. The magnetic field applied to cells with cancer decrease the growth of this cells or their multiplication. We observed a potential difference opposite to cell potential and propose that the ionic interchange is very slow tampering with cell growth in cancer.

Advanced Antenna Measurement Processing

DTIC Science & Technology

2014-06-18

reflector antenna where the reflector functions as a passive scatterer. Here we proposed to demonstrate this separation scheme using experimentally derived...orders in the multiple reflections between these antennas . The nature of these composite patterns is not known a priori so one cannot know the accuracy...SECURITY CLASSIFICATION OF: This research project is focused on the advancement of methods of post measurement processing of antenna pattern

The Question-Driven Laboratory Exercise: A New Pedagogy Applied to a Green Modification of Grignard Reagent Formation and Reaction

ERIC Educational Resources Information Center

Teixeira, Jennifer M.; Byers, Jessie Nedrow; Perez, Marilu G.; Holman, R. W.

2010-01-01

Experimental exercises within second-year-level organic laboratory manuals typically involve a statement of a principle that is then validated by student generation of data in a single experiment. These experiments are structured in the exact opposite order of the scientific method, in which data interpretation, typically from multiple related…

Combining Randomized and Non-Randomized Evidence in Clinical Research: A Review of Methods and Applications

ERIC Educational Resources Information Center

Verde, Pablo E.; Ohmann, Christian

2015-01-01

Researchers may have multiple motivations for combining disparate pieces of evidence in a meta-analysis, such as generalizing experimental results or increasing the power to detect an effect that a single study is not able to detect. However, while in meta-analysis, the main question may be simple, the structure of evidence available to answer it…

GalaxyTBM: template-based modeling by building a reliable core and refining unreliable local regions.

PubMed

Ko, Junsu; Park, Hahnbeom; Seok, Chaok

2012-08-10

Protein structures can be reliably predicted by template-based modeling (TBM) when experimental structures of homologous proteins are available. However, it is challenging to obtain structures more accurate than the single best templates by either combining information from multiple templates or by modeling regions that vary among templates or are not covered by any templates. We introduce GalaxyTBM, a new TBM method in which the more reliable core region is modeled first from multiple templates and less reliable, variable local regions, such as loops or termini, are then detected and re-modeled by an ab initio method. This TBM method is based on "Seok-server," which was tested in CASP9 and assessed to be amongst the top TBM servers. The accuracy of the initial core modeling is enhanced by focusing on more conserved regions in the multiple-template selection and multiple sequence alignment stages. Additional improvement is achieved by ab initio modeling of up to 3 unreliable local regions in the fixed framework of the core structure. Overall, GalaxyTBM reproduced the performance of Seok-server, with GalaxyTBM and Seok-server resulting in average GDT-TS of 68.1 and 68.4, respectively, when tested on 68 single-domain CASP9 TBM targets. For application to multi-domain proteins, GalaxyTBM must be combined with domain-splitting methods. Application of GalaxyTBM to CASP9 targets demonstrates that accurate protein structure prediction is possible by use of a multiple-template-based approach, and ab initio modeling of variable regions can further enhance the model quality.

Review of possible applications of cosmic muon tomography

NASA Astrophysics Data System (ADS)

Checchia, P.

2016-12-01

Muon radiographic methods can be used to explore inaccessible volumes profiting of the property of muons to penetrate thick materials. An extension of the muon radiographic methods, the muon scattering tomography, was proposed for the first time in 2003 and it is based on the measurement of the multiple Coulomb scattering of muons crossing the volume under investigation. In this talk, the principles of tomographic image reconstruction are first outlined and then the experimental setup and the most adequate detectors are described. A review of the possible applications of this technique is reported, with specific reference to security in transports and monitoring of industrial processes. The technique can also be used to provide precise measurements of the properties of various materials. The experimental challenge related to this activity is discussed.

Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing

PubMed Central

Zhang, Fan; Li, Guojun; Li, Wei; Hu, Wei; Hu, Yuxin

2016-01-01

With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate. PMID:27070606

Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing.

PubMed

Zhang, Fan; Li, Guojun; Li, Wei; Hu, Wei; Hu, Yuxin

2016-04-07

With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.

Dual-Chamber/Dual-Anode Proportional Counter Incorporating an Intervening Thin-Foil Solid Neutron Converter

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

Boatner, Lynn A; Neal, John S; Blackston, Matthew A

2012-01-01

A dual-chamber/dual-anode gas proportional counter utilizing thin solid 6LiF or 10B neutron converters coated on a 2-micon-thick Mylar film that is positioned between the two counter chambers and anodes has been designed, fabricated, and tested using a variety of fill gases including naturally abundant helium. In this device, neutron conversion products emitted from both sides of the coated converter foil are detected rather than having half of the products absorbed in the wall of a conventional tube type counter where the solid neutron converter is deposited on the tube wall. Geant4-based radiation transport calculations were used to determine the optimummore » neutron converter coating thickness for both isotopes. Solution methods for applying these optimized-thickness coatings on a Mylar film were developed that were carried out at room temperature without any specialized equipment and that can be adapted to standard coating methods such as silk screen or ink jet printing. The performance characteristics of the dual-chamber/dual-anode neutron detector were determined for both types of isotopically enriched converters. The experimental performance of the 6LiF converter-based detector was described well by modeling results from Geant4. Additional modeling studies of multiple-foil/multiple-chamber/anode configurations addressed the basic issue of the relatively longer absorption range of neutrons versus the shorter range of the conversion products for 6LiF and 10B. Combined with the experimental results, these simulations indicate that a high-performance neutron detector can be realized in a single device through the application of these multiple-foil/solid converter, multiple-chamber detector concepts.« less

Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis.

PubMed

You, Zhu-Hong; Lei, Ying-Ke; Zhu, Lin; Xia, Junfeng; Wang, Bing

2013-01-01

Protein-protein interactions (PPIs) play crucial roles in the execution of various cellular processes and form the basis of biological mechanisms. Although large amount of PPIs data for different species has been generated by high-throughput experimental techniques, current PPI pairs obtained with experimental methods cover only a fraction of the complete PPI networks, and further, the experimental methods for identifying PPIs are both time-consuming and expensive. Hence, it is urgent and challenging to develop automated computational methods to efficiently and accurately predict PPIs. We present here a novel hierarchical PCA-EELM (principal component analysis-ensemble extreme learning machine) model to predict protein-protein interactions only using the information of protein sequences. In the proposed method, 11188 protein pairs retrieved from the DIP database were encoded into feature vectors by using four kinds of protein sequences information. Focusing on dimension reduction, an effective feature extraction method PCA was then employed to construct the most discriminative new feature set. Finally, multiple extreme learning machines were trained and then aggregated into a consensus classifier by majority voting. The ensembling of extreme learning machine removes the dependence of results on initial random weights and improves the prediction performance. When performed on the PPI data of Saccharomyces cerevisiae, the proposed method achieved 87.00% prediction accuracy with 86.15% sensitivity at the precision of 87.59%. Extensive experiments are performed to compare our method with state-of-the-art techniques Support Vector Machine (SVM). Experimental results demonstrate that proposed PCA-EELM outperforms the SVM method by 5-fold cross-validation. Besides, PCA-EELM performs faster than PCA-SVM based method. Consequently, the proposed approach can be considered as a new promising and powerful tools for predicting PPI with excellent performance and less time.

SAW based micro- and acousto-fluidics in biomedicine

NASA Astrophysics Data System (ADS)

Ramasamy, Mouli; Varadan, Vijay K.

2017-04-01

Protein association starts with random collisions of individual proteins. Multiple collisions and rotational diffusion brings the molecules to a state of orientation. Majority of the protein associations are influenced by electrostatic interactions. To introduce: electrostatic rate enhancement, Brownian dynamics and transient complex theory has been traditionally used. Due to the recent advances in interdisciplinary sciences, an array of molecular assembly methods is being studied. Protein nanostructural assembly and macromolecular crowding are derived from the subsets of biochemistry to study protein-protein interactions and protein self-assembly. This paper tries to investigate the issue of enhancing the protein self-association rate, and bridging the gap between the simulations and experimental results. The methods proposed here include: electrostatic rate enhancement, macromolecular crowing, nanostructural protein assembly, microfluidics based approaches and magnetic force based approaches. Despite the suggestions of several methods, microfluidic and magnetic force based approaches seem to serve the need of protein assembly in a wider scale. Congruence of these approaches may also yield better results. Even though, these methods prove to be conceptually strong, to prevent the disagreement of theory and practice, a wide range of experiments is required. This proposal intends to study theoretical and experimental methods to successfully implement the aforementioned assembly strategies, and conclude with an extensive analysis of experimental data to address practical feasibility.

Source-based neurofeedback methods using EEG recordings: training altered brain activity in a functional brain source derived from blind source separation

PubMed Central

White, David J.; Congedo, Marco; Ciorciari, Joseph

2014-01-01

A developing literature explores the use of neurofeedback in the treatment of a range of clinical conditions, particularly ADHD and epilepsy, whilst neurofeedback also provides an experimental tool for studying the functional significance of endogenous brain activity. A critical component of any neurofeedback method is the underlying physiological signal which forms the basis for the feedback. While the past decade has seen the emergence of fMRI-based protocols training spatially confined BOLD activity, traditional neurofeedback has utilized a small number of electrode sites on the scalp. As scalp EEG at a given electrode site reflects a linear mixture of activity from multiple brain sources and artifacts, efforts to successfully acquire some level of control over the signal may be confounded by these extraneous sources. Further, in the event of successful training, these traditional neurofeedback methods are likely influencing multiple brain regions and processes. The present work describes the use of source-based signal processing methods in EEG neurofeedback. The feasibility and potential utility of such methods were explored in an experiment training increased theta oscillatory activity in a source derived from Blind Source Separation (BSS) of EEG data obtained during completion of a complex cognitive task (spatial navigation). Learned increases in theta activity were observed in two of the four participants to complete 20 sessions of neurofeedback targeting this individually defined functional brain source. Source-based EEG neurofeedback methods using BSS may offer important advantages over traditional neurofeedback, by targeting the desired physiological signal in a more functionally and spatially specific manner. Having provided preliminary evidence of the feasibility of these methods, future work may study a range of clinically and experimentally relevant brain processes where individual brain sources may be targeted by source-based EEG neurofeedback. PMID:25374520

Open Rotor Tone Shielding Methods for System Noise Assessments Using Multiple Databases

NASA Technical Reports Server (NTRS)

Bahr, Christopher J.; Thomas, Russell H.; Lopes, Leonard V.; Burley, Casey L.; Van Zante, Dale E.

2014-01-01

Advanced aircraft designs such as the hybrid wing body, in conjunction with open rotor engines, may allow for significant improvements in the environmental impact of aviation. System noise assessments allow for the prediction of the aircraft noise of such designs while they are still in the conceptual phase. Due to significant requirements of computational methods, these predictions still rely on experimental data to account for the interaction of the open rotor tones with the hybrid wing body airframe. Recently, multiple aircraft system noise assessments have been conducted for hybrid wing body designs with open rotor engines. These assessments utilized measured benchmark data from a Propulsion Airframe Aeroacoustic interaction effects test. The measured data demonstrated airframe shielding of open rotor tonal and broadband noise with legacy F7/A7 open rotor blades. Two methods are proposed for improving the use of these data on general open rotor designs in a system noise assessment. The first, direct difference, is a simple octave band subtraction which does not account for tone distribution within the rotor acoustic signal. The second, tone matching, is a higher-fidelity process incorporating additional physical aspects of the problem, where isolated rotor tones are matched by their directivity to determine tone-by-tone shielding. A case study is conducted with the two methods to assess how well each reproduces the measured data and identify the merits of each. Both methods perform similarly for system level results and successfully approach the experimental data for the case study. The tone matching method provides additional tools for assessing the quality of the match to the data set. Additionally, a potential path to improve the tone matching method is provided.

Pulse patterning effect in optical pulse division multiplexing for flexible single wavelength multiple access optical network

NASA Astrophysics Data System (ADS)

Jung, Sun-Young; Kim, Chang-Hun; Han, Sang-Kook

2018-05-01

A demand for high spectral efficiency requires multiple access within a single wavelength, but the uplink signals are significantly degraded because of optical beat interference (OBI) in intensity modulation/direct detection system. An optical pulse division multiplexing (OPDM) technique was proposed that could effectively reduce the OBI via a simple method as long as near-orthogonality is satisfied, but the condition was strict, and thus, the number of multiplexing units was very limited. We propose pulse pattern enhanced OPDM (e-OPDM) to reduce the OBI and improve the flexibility in multiple access within a single wavelength. The performance of the e-OPDM and patterning effect are experimentally verified after 23-km single mode fiber transmission. By employing pulse patterning in OPDM, the tight requirement was relaxed by extending the optical delay dynamic range. This could support more number of access with reduced OBI, which could eventually enhance a multiple access function.

Focusing of light energy inside a scattering medium by controlling the time-gated multiple light scattering

NASA Astrophysics Data System (ADS)

Jeong, Seungwon; Lee, Ye-Ryoung; Choi, Wonjun; Kang, Sungsam; Hong, Jin Hee; Park, Jin-Sung; Lim, Yong-Sik; Park, Hong-Gyu; Choi, Wonshik

2018-05-01

The efficient delivery of light energy is a prerequisite for the non-invasive imaging and stimulating of target objects embedded deep within a scattering medium. However, the injected waves experience random diffusion by multiple light scattering, and only a small fraction reaches the target object. Here, we present a method to counteract wave diffusion and to focus multiple-scattered waves at the deeply embedded target. To realize this, we experimentally inject light into the reflection eigenchannels of a specific flight time to preferably enhance the intensity of those multiple-scattered waves that have interacted with the target object. For targets that are too deep to be visible by optical imaging, we demonstrate a more than tenfold enhancement in light energy delivery in comparison with ordinary wave diffusion cases. This work will lay a foundation to enhance the working depth of imaging, sensing and light stimulation.

Direct system parameter identification of mechanical structures with application to modal analysis

NASA Technical Reports Server (NTRS)

Leuridan, J. M.; Brown, D. L.; Allemang, R. J.

1982-01-01

In this paper a method is described to estimate mechanical structure characteristics in terms of mass, stiffness and damping matrices using measured force input and response data. The estimated matrices can be used to calculate a consistent set of damped natural frequencies and damping values, mode shapes and modal scale factors for the structure. The proposed technique is attractive as an experimental modal analysis method since the estimation of the matrices does not require previous estimation of frequency responses and since the method can be used, without any additional complications, for multiple force input structure testing.

Effects of serial and concurrent training on receptive identification tasks: A Systematic replication.

PubMed

Wunderlich, Kara L; Vollmer, Timothy R

2017-07-01

The current study compared the use of serial and concurrent methods to train multiple exemplars when teaching receptive language skills, providing a systematic replication of Wunderlich, Vollmer, Donaldson, and Phillips (2014). Five preschoolers diagnosed with developmental delays or autism spectrum disorders were taught to receptively identify letters or letter sounds. Subjects learned the target stimuli slightly faster in concurrent training and a high degree of generalization was obtained following both methods of training, indicating that both the serial and concurrent methods of training are efficient and effective instructional procedures. © 2017 Society for the Experimental Analysis of Behavior.

Modal testing with Asher's method using a Fourier analyzer and curve fitting

NASA Technical Reports Server (NTRS)

Gold, R. R.; Hallauer, W. L., Jr.

1979-01-01

An unusual application of the method proposed by Asher (1958) for structural dynamic and modal testing is discussed. Asher's method has the capability, using the admittance matrix and multiple-shaker sinusoidal excitation, of separating structural modes having indefinitely close natural frequencies. The present application uses Asher's method in conjunction with a modern Fourier analyzer system but eliminates the necessity of exciting the test structure simultaneously with several shakers. Evaluation of this approach with numerically simulated data demonstrated its effectiveness; the parameters of two modes having almost identical natural frequencies were accurately identified. Laboratory evaluation of this approach was inconclusive because of poor experimental input data.

Improved Statistical Methods Enable Greater Sensitivity in Rhythm Detection for Genome-Wide Data

PubMed Central

Hutchison, Alan L.; Maienschein-Cline, Mark; Chiang, Andrew H.; Tabei, S. M. Ali; Gudjonson, Herman; Bahroos, Neil; Allada, Ravi; Dinner, Aaron R.

2015-01-01

Robust methods for identifying patterns of expression in genome-wide data are important for generating hypotheses regarding gene function. To this end, several analytic methods have been developed for detecting periodic patterns. We improve one such method, JTK_CYCLE, by explicitly calculating the null distribution such that it accounts for multiple hypothesis testing and by including non-sinusoidal reference waveforms. We term this method empirical JTK_CYCLE with asymmetry search, and we compare its performance to JTK_CYCLE with Bonferroni and Benjamini-Hochberg multiple hypothesis testing correction, as well as to five other methods: cyclohedron test, address reduction, stable persistence, ANOVA, and F24. We find that ANOVA, F24, and JTK_CYCLE consistently outperform the other three methods when data are limited and noisy; empirical JTK_CYCLE with asymmetry search gives the greatest sensitivity while controlling for the false discovery rate. Our analysis also provides insight into experimental design and we find that, for a fixed number of samples, better sensitivity and specificity are achieved with higher numbers of replicates than with higher sampling density. Application of the methods to detecting circadian rhythms in a metadataset of microarrays that quantify time-dependent gene expression in whole heads of Drosophila melanogaster reveals annotations that are enriched among genes with highly asymmetric waveforms. These include a wide range of oxidation reduction and metabolic genes, as well as genes with transcripts that have multiple splice forms. PMID:25793520

Electrical detection and analysis of surface acoustic wave in line-defect two-dimensional piezoelectric phononic crystals

NASA Astrophysics Data System (ADS)

Cai, Feida; Li, Honglang; Tian, Yahui; Ke, Yabing; Cheng, Lina; Lou, Wei; He, Shitang

2018-03-01

Line-defect piezoelectric phononic crystals (PCs) show good potential applications in surface acoustic wave (SAW) MEMS devices for RF communication systems. To analyze the SAW characteristics in line-defect two-dimensional (2D) piezoelectric PCs, optical methods are commonly used. However, the optical instruments are complex and expensive, whereas conventional electrical methods can only measure SAW transmission of the whole device and lack spatial resolution. In this paper, we propose a new electrical experimental method with multiple receiving interdigital transducers (IDTs) to detect the SAW field distribution, in which an array of receiving IDTs of equal aperture was used to receive the SAW. For this new method, SAW delay lines with perfect and line-defect 2D Al/128°YXLiNbO3 piezoelectric PCs on the transmitting path were designed and fabricated. The experimental results showed that the SAW distributed mainly in the line-defect region, which agrees with the theoretical results.

Compound image segmentation of published biomedical figures.

PubMed

Li, Pengyuan; Jiang, Xiangying; Kambhamettu, Chandra; Shatkay, Hagit

2018-04-01

Images convey essential information in biomedical publications. As such, there is a growing interest within the bio-curation and the bio-databases communities, to store images within publications as evidence for biomedical processes and for experimental results. However, many of the images in biomedical publications are compound images consisting of multiple panels, where each individual panel potentially conveys a different type of information. Segmenting such images into constituent panels is an essential first step toward utilizing images. In this article, we develop a new compound image segmentation system, FigSplit, which is based on Connected Component Analysis. To overcome shortcomings typically manifested by existing methods, we develop a quality assessment step for evaluating and modifying segmentations. Two methods are proposed to re-segment the images if the initial segmentation is inaccurate. Experimental results show the effectiveness of our method compared with other methods. The system is publicly available for use at: https://www.eecis.udel.edu/~compbio/FigSplit. The code is available upon request. shatkay@udel.edu. Supplementary data are available online at Bioinformatics.

[A Feature Extraction Method for Brain Computer Interface Based on Multivariate Empirical Mode Decomposition].

PubMed

Wang, Jinjia; Liu, Yuan

2015-04-01

This paper presents a feature extraction method based on multivariate empirical mode decomposition (MEMD) combining with the power spectrum feature, and the method aims at the non-stationary electroencephalogram (EEG) or magnetoencephalogram (MEG) signal in brain-computer interface (BCI) system. Firstly, we utilized MEMD algorithm to decompose multichannel brain signals into a series of multiple intrinsic mode function (IMF), which was proximate stationary and with multi-scale. Then we extracted and reduced the power characteristic from each IMF to a lower dimensions using principal component analysis (PCA). Finally, we classified the motor imagery tasks by linear discriminant analysis classifier. The experimental verification showed that the correct recognition rates of the two-class and four-class tasks of the BCI competition III and competition IV reached 92.0% and 46.2%, respectively, which were superior to the winner of the BCI competition. The experimental proved that the proposed method was reasonably effective and stable and it would provide a new way for feature extraction.

Ensemble positive unlabeled learning for disease gene identification.

PubMed

Yang, Peng; Li, Xiaoli; Chua, Hon-Nian; Kwoh, Chee-Keong; Ng, See-Kiong

2014-01-01

An increasing number of genes have been experimentally confirmed in recent years as causative genes to various human diseases. The newly available knowledge can be exploited by machine learning methods to discover additional unknown genes that are likely to be associated with diseases. In particular, positive unlabeled learning (PU learning) methods, which require only a positive training set P (confirmed disease genes) and an unlabeled set U (the unknown candidate genes) instead of a negative training set N, have been shown to be effective in uncovering new disease genes in the current scenario. Using only a single source of data for prediction can be susceptible to bias due to incompleteness and noise in the genomic data and a single machine learning predictor prone to bias caused by inherent limitations of individual methods. In this paper, we propose an effective PU learning framework that integrates multiple biological data sources and an ensemble of powerful machine learning classifiers for disease gene identification. Our proposed method integrates data from multiple biological sources for training PU learning classifiers. A novel ensemble-based PU learning method EPU is then used to integrate multiple PU learning classifiers to achieve accurate and robust disease gene predictions. Our evaluation experiments across six disease groups showed that EPU achieved significantly better results compared with various state-of-the-art prediction methods as well as ensemble learning classifiers. Through integrating multiple biological data sources for training and the outputs of an ensemble of PU learning classifiers for prediction, we are able to minimize the potential bias and errors in individual data sources and machine learning algorithms to achieve more accurate and robust disease gene predictions. In the future, our EPU method provides an effective framework to integrate the additional biological and computational resources for better disease gene predictions.

Multiple oxygen entry pathways in globin proteins revealed by intrinsic pathway identification method

NASA Astrophysics Data System (ADS)

Takayanagi, Masayoshi; Kurisaki, Ikuo; Nagaoka, Masataka

2015-12-01

Each subunit of human hemoglobin (HbA) stores an oxygen molecule (O2) in the binding site (BS) cavity near the heme group. The BS is buried in the interior of the subunit so that there is a debate over the O2 entry pathways from solvent to the BS; histidine gate or multiple pathways. To elucidate the O2 entry pathways, we executed ensemble molecular dynamics (MD) simulations of T-state tetramer HbA in high concentration O2 solvent to simulate spontaneous O2 entry from solvent into the BS. By analyzing 128 independent 8 ns MD trajectories by intrinsic pathway identification by clustering (IPIC) method, we found 141 and 425 O2 entry events into the BS of the α and β subunits, respectively. In both subunits, we found that multiple O2 entry pathways through inside cavities play a significant role for O2 entry process of HbA. The rate constants of O2 entry estimated from the MD trajectories correspond to the experimentally observed values. In addition, by analyzing monomer myoglobin, we verified that the high O2 concentration condition can reproduce the ratios of each multiple pathway in the one-tenth lower O2 concentration condition. These indicate the validity of the multiple pathways obtained in our MD simulations.

Least-squares deconvolution of evoked potentials and sequence optimization for multiple stimuli under low-jitter conditions.

PubMed

Bardy, Fabrice; Dillon, Harvey; Van Dun, Bram

2014-04-01

Rapid presentation of stimuli in an evoked response paradigm can lead to overlap of multiple responses and consequently difficulties interpreting waveform morphology. This paper presents a deconvolution method allowing overlapping multiple responses to be disentangled. The deconvolution technique uses a least-squared error approach. A methodology is proposed to optimize the stimulus sequence associated with the deconvolution technique under low-jitter conditions. It controls the condition number of the matrices involved in recovering the responses. Simulations were performed using the proposed deconvolution technique. Multiple overlapping responses can be recovered perfectly in noiseless conditions. In the presence of noise, the amount of error introduced by the technique can be controlled a priori by the condition number of the matrix associated with the used stimulus sequence. The simulation results indicate the need for a minimum amount of jitter, as well as a sufficient number of overlap combinations to obtain optimum results. An aperiodic model is recommended to improve reconstruction. We propose a deconvolution technique allowing multiple overlapping responses to be extracted and a method of choosing the stimulus sequence optimal for response recovery. This technique may allow audiologists, psychologists, and electrophysiologists to optimize their experimental designs involving rapidly presented stimuli, and to recover evoked overlapping responses. Copyright © 2013 International Federation of Clinical Neurophysiology. All rights reserved.

The Influence of an Extensive Inquiry-Based Field Experience on Pre-Service Elementary Student Teachers' Science Teaching Beliefs

NASA Astrophysics Data System (ADS)

Bhattacharyya, Sumita; Volk, Trudi; Lumpe, Andrew

2009-06-01

This study examined the effects of an extensive inquiry-based field experience on pre service elementary teachers’ personal agency beliefs, a composite measure of context beliefs and capability beliefs related to teaching science. The research combined quantitative and qualitative approaches and included an experimental group that utilized the inquiry method and a control group that used traditional teaching methods. Pre- and post-test scores for the experimental and control groups were compared. The context beliefs of both groups showed no significant change as a result of the experience. However, the control group’s capability belief scores, lower than those of the experimental group to start with, declined significantly; the experimental group’s scores remained unchanged. Thus, the inquiry-based field experience led to an increase in personal agency beliefs. The qualitative data suggested a new hypothesis that there is a spiral relationship among teachers’ ability to establish communicative relationships with students, desire for personal growth and improvement, ability to implement multiple instructional strategies, and possession of substantive content knowledge. The study concludes that inquiry-based student teaching should be encouraged in the training of elementary school science teachers. However, the meaning and practice of the inquiry method should be clearly delineated to ensure its correct implementation in the classroom.

Modeling Photoelectron Spectra of CuO, Cu2O, and CuO2 Anions with Equation-of-Motion Coupled-Cluster Methods: An Adventure in Fock Space.

PubMed

Orms, Natalie; Krylov, Anna I

2018-04-12

The experimental photoelectron spectra of di- and triatomic copper oxide anions have been reported previously. We present an analysis of the experimental spectra of the CuO - , Cu 2 O - , and CuO 2 - anions using equation-of-motion coupled-cluster (EOM-CC) methods. The open-shell electronic structure of each molecule demands a unique combination of EOM-CC methods to achieve an accurate and balanced representation of the multiconfigurational anionic- and neutral-state manifolds. Analysis of the Dyson orbitals associated with photodetachment from CuO - reveals the strong non-Koopmans character of the CuO states. For the lowest detachment energy, a good agreement between theoretical and experimental values is obtained with CCSD(T) (coupled-cluster with single and double excitations and perturbative account of triple excitations). The (T) correction is particularly important for Cu 2 O - . Use of a relativistic pseudopotential and matching basis set improves the quality of results in most cases. EOM-DIP-CCSD analysis of the low-lying states of CuO 2 - reveals multiple singlet and triplet anionic states near the triplet ground state, adding an extra layer of complexity to the interpretation of the experimental CuO 2 - photoelectron spectrum.

Experimental Design and Primary Data Analysis Methods for Comparing Adaptive Interventions

PubMed Central

Nahum-Shani, Inbal; Qian, Min; Almirall, Daniel; Pelham, William E.; Gnagy, Beth; Fabiano, Greg; Waxmonsky, Jim; Yu, Jihnhee; Murphy, Susan

2013-01-01

In recent years, research in the area of intervention development is shifting from the traditional fixed-intervention approach to adaptive interventions, which allow greater individualization and adaptation of intervention options (i.e., intervention type and/or dosage) over time. Adaptive interventions are operationalized via a sequence of decision rules that specify how intervention options should be adapted to an individual’s characteristics and changing needs, with the general aim to optimize the long-term effectiveness of the intervention. Here, we review adaptive interventions, discussing the potential contribution of this concept to research in the behavioral and social sciences. We then propose the sequential multiple assignment randomized trial (SMART), an experimental design useful for addressing research questions that inform the construction of high-quality adaptive interventions. To clarify the SMART approach and its advantages, we compare SMART with other experimental approaches. We also provide methods for analyzing data from SMART to address primary research questions that inform the construction of a high-quality adaptive intervention. PMID:23025433

Stochastic Time Models of Syllable Structure

PubMed Central

Shaw, Jason A.; Gafos, Adamantios I.

2015-01-01

Drawing on phonology research within the generative linguistics tradition, stochastic methods, and notions from complex systems, we develop a modelling paradigm linking phonological structure, expressed in terms of syllables, to speech movement data acquired with 3D electromagnetic articulography and X-ray microbeam methods. The essential variable in the models is syllable structure. When mapped to discrete coordination topologies, syllabic organization imposes systematic patterns of variability on the temporal dynamics of speech articulation. We simulated these dynamics under different syllabic parses and evaluated simulations against experimental data from Arabic and English, two languages claimed to parse similar strings of segments into different syllabic structures. Model simulations replicated several key experimental results, including the fallibility of past phonetic heuristics for syllable structure, and exposed the range of conditions under which such heuristics remain valid. More importantly, the modelling approach consistently diagnosed syllable structure proving resilient to multiple sources of variability in experimental data including measurement variability, speaker variability, and contextual variability. Prospects for extensions of our modelling paradigm to acoustic data are also discussed. PMID:25996153

Machine learning algorithms for the creation of clinical healthcare enterprise systems

NASA Astrophysics Data System (ADS)

Mandal, Indrajit

2017-10-01

Clinical recommender systems are increasingly becoming popular for improving modern healthcare systems. Enterprise systems are persuasively used for creating effective nurse care plans to provide nurse training, clinical recommendations and clinical quality control. A novel design of a reliable clinical recommender system based on multiple classifier system (MCS) is implemented. A hybrid machine learning (ML) ensemble based on random subspace method and random forest is presented. The performance accuracy and robustness of proposed enterprise architecture are quantitatively estimated to be above 99% and 97%, respectively (above 95% confidence interval). The study then extends to experimental analysis of the clinical recommender system with respect to the noisy data environment. The ranking of items in nurse care plan is demonstrated using machine learning algorithms (MLAs) to overcome the drawback of the traditional association rule method. The promising experimental results are compared against the sate-of-the-art approaches to highlight the advancement in recommendation technology. The proposed recommender system is experimentally validated using five benchmark clinical data to reinforce the research findings.

A multiple distributed representation method based on neural network for biomedical event extraction.

PubMed

Wang, Anran; Wang, Jian; Lin, Hongfei; Zhang, Jianhai; Yang, Zhihao; Xu, Kan

2017-12-20

Biomedical event extraction is one of the most frontier domains in biomedical research. The two main subtasks of biomedical event extraction are trigger identification and arguments detection which can both be considered as classification problems. However, traditional state-of-the-art methods are based on support vector machine (SVM) with massive manually designed one-hot represented features, which require enormous work but lack semantic relation among words. In this paper, we propose a multiple distributed representation method for biomedical event extraction. The method combines context consisting of dependency-based word embedding, and task-based features represented in a distributed way as the input of deep learning models to train deep learning models. Finally, we used softmax classifier to label the example candidates. The experimental results on Multi-Level Event Extraction (MLEE) corpus show higher F-scores of 77.97% in trigger identification and 58.31% in overall compared to the state-of-the-art SVM method. Our distributed representation method for biomedical event extraction avoids the problems of semantic gap and dimension disaster from traditional one-hot representation methods. The promising results demonstrate that our proposed method is effective for biomedical event extraction.

Video-Based Fingerprint Verification

PubMed Central

Qin, Wei; Yin, Yilong; Liu, Lili

2013-01-01

Conventional fingerprint verification systems use only static information. In this paper, fingerprint videos, which contain dynamic information, are utilized for verification. Fingerprint videos are acquired by the same capture device that acquires conventional fingerprint images, and the user experience of providing a fingerprint video is the same as that of providing a single impression. After preprocessing and aligning processes, “inside similarity” and “outside similarity” are defined and calculated to take advantage of both dynamic and static information contained in fingerprint videos. Match scores between two matching fingerprint videos are then calculated by combining the two kinds of similarity. Experimental results show that the proposed video-based method leads to a relative reduction of 60 percent in the equal error rate (EER) in comparison to the conventional single impression-based method. We also analyze the time complexity of our method when different combinations of strategies are used. Our method still outperforms the conventional method, even if both methods have the same time complexity. Finally, experimental results demonstrate that the proposed video-based method can lead to better accuracy than the multiple impressions fusion method, and the proposed method has a much lower false acceptance rate (FAR) when the false rejection rate (FRR) is quite low. PMID:24008283

Experimental models of demyelination and remyelination.

PubMed

Torre-Fuentes, L; Moreno-Jiménez, L; Pytel, V; Matías-Guiu, J A; Gómez-Pinedo, U; Matías-Guiu, J

2017-08-29

Experimental animal models constitute a useful tool to deepen our knowledge of central nervous system disorders. In the case of multiple sclerosis, however, there is no such specific model able to provide an overview of the disease; multiple models covering the different pathophysiological features of the disease are therefore necessary. We reviewed the different in vitro and in vivo experimental models used in multiple sclerosis research. Concerning in vitro models, we analysed cell cultures and slice models. As for in vivo models, we examined such models of autoimmunity and inflammation as experimental allergic encephalitis in different animals and virus-induced demyelinating diseases. Furthermore, we analysed models of demyelination and remyelination, including chemical lesions caused by cuprizone, lysolecithin, and ethidium bromide; zebrafish; and transgenic models. Experimental models provide a deeper understanding of the different pathogenic mechanisms involved in multiple sclerosis. Choosing one model or another depends on the specific aims of the study. Copyright © 2017 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

Multiple Linear Regression for Reconstruction of Gene Regulatory Networks in Solving Cascade Error Problems

PubMed Central

Zainudin, Suhaila; Arif, Shereena M.

2017-01-01

Gene regulatory network (GRN) reconstruction is the process of identifying regulatory gene interactions from experimental data through computational analysis. One of the main reasons for the reduced performance of previous GRN methods had been inaccurate prediction of cascade motifs. Cascade error is defined as the wrong prediction of cascade motifs, where an indirect interaction is misinterpreted as a direct interaction. Despite the active research on various GRN prediction methods, the discussion on specific methods to solve problems related to cascade errors is still lacking. In fact, the experiments conducted by the past studies were not specifically geared towards proving the ability of GRN prediction methods in avoiding the occurrences of cascade errors. Hence, this research aims to propose Multiple Linear Regression (MLR) to infer GRN from gene expression data and to avoid wrongly inferring of an indirect interaction (A → B → C) as a direct interaction (A → C). Since the number of observations of the real experiment datasets was far less than the number of predictors, some predictors were eliminated by extracting the random subnetworks from global interaction networks via an established extraction method. In addition, the experiment was extended to assess the effectiveness of MLR in dealing with cascade error by using a novel experimental procedure that had been proposed in this work. The experiment revealed that the number of cascade errors had been very minimal. Apart from that, the Belsley collinearity test proved that multicollinearity did affect the datasets used in this experiment greatly. All the tested subnetworks obtained satisfactory results, with AUROC values above 0.5. PMID:28250767

Uniaxial Compressive Constitutive Relationship of Concrete Confined by Special-Shaped Steel Tube Coupled with Multiple Cavities

PubMed Central

Wu, Haipeng; Cao, Wanlin; Qiao, Qiyun; Dong, Hongying

2016-01-01

A method is presented to predict the complete stress-strain curves of concrete subjected to triaxial stresses, which were caused by axial load and lateral force. The stress can be induced due to the confinement action inside a special-shaped steel tube having multiple cavities. The existing reinforced confined concrete formulas have been improved to determine the confinement action. The influence of cross-sectional shape, of cavity construction, of stiffening ribs and of reinforcement in cavities has been considered in the model. The parameters of the model are determined on the basis of experimental results of an axial compression test for two different kinds of special-shaped concrete filled steel tube (CFT) columns with multiple cavities. The complete load-strain curves of the special-shaped CFT columns are estimated. The predicted concrete strength and the post-peak behavior are found to show good agreement within the accepted limits, compared with the experimental results. In addition, the parameters of proposed model are taken from two kinds of totally different CFT columns, so that it can be concluded that this model is also applicable to concrete confined by other special-shaped steel tubes. PMID:28787886

Uniaxial Compressive Constitutive Relationship of Concrete Confined by Special-Shaped Steel Tube Coupled with Multiple Cavities.

PubMed

Wu, Haipeng; Cao, Wanlin; Qiao, Qiyun; Dong, Hongying

2016-01-29

A method is presented to predict the complete stress-strain curves of concrete subjected to triaxial stresses, which were caused by axial load and lateral force. The stress can be induced due to the confinement action inside a special-shaped steel tube having multiple cavities. The existing reinforced confined concrete formulas have been improved to determine the confinement action. The influence of cross-sectional shape, of cavity construction, of stiffening ribs and of reinforcement in cavities has been considered in the model. The parameters of the model are determined on the basis of experimental results of an axial compression test for two different kinds of special-shaped concrete filled steel tube (CFT) columns with multiple cavities. The complete load-strain curves of the special-shaped CFT columns are estimated. The predicted concrete strength and the post-peak behavior are found to show good agreement within the accepted limits, compared with the experimental results. In addition, the parameters of proposed model are taken from two kinds of totally different CFT columns, so that it can be concluded that this model is also applicable to concrete confined by other special-shaped steel tubes.

Numerical simulation and experimental validation of the dynamics of multiple bubble merger during pool boiling under microgravity conditions.

PubMed

Abarajith, H S; Dhir, V K; Warrier, G; Son, G

2004-11-01

Numerical simulation and experimental validation of the growth and departure of multiple merging bubbles and associated heat transfer on a horizontal heated surface during pool boiling under variable gravity conditions have been performed. A finite difference scheme is used to solve the equations governing mass, momentum, and energy in the vapor liquid phases. The vapor-liquid interface is captured by a level set method that is modified to include the influence of phase change at the liquid-vapor interface. Water is used as test liquid. The effects of reduced gravity condition and orientation of the bubbles on the bubble diameter, interfacial structure, bubble merger time, and departure time, as well as local heat fluxes, are studied. In the experiments, multiple vapor bubbles are produced on artificial cavities in the 2-10 micrometer diameter range, microfabricated on the polished silicon wafer with given spacing. The wafer was heated electrically from the back with miniature strain gage type heating elements in order to control the nucleation superheat. The experiments conducted in normal Earth gravity and in the low gravity environment of KC-135 aircraft are used to validate the numerical simulations.

Are symptoms of spirit possessed patients covered by the DSM-IV or DSM-5 criteria for possession trance disorder? A mixed-method explorative study in Uganda.

PubMed

van Duijl, Marjolein; Kleijn, Wim; de Jong, Joop

2013-09-01

As in many cultures, spirit possession is a common idiom of distress in Uganda. The DSM-IV contains experimental research criteria for dissociative and possession trance disorder (DTD and PTD), which are under review for the DSM-5. In the current proposed categories of the DSM-5, PTD is subsumed under dissociative identity disorder (DID) and DTD under dissociative disorders not elsewhere classified. Evaluation of these criteria is currently urgently required. This study explores the match between local symptoms of spirit possession in Uganda and experimental research criteria for PTD in the DSM-IV and proposed criteria for DID in the DSM-5. A mixed-method approach was used combining qualitative and quantitative research methods. Local symptoms were explored of 119 spirit possessed patients, using illness narratives and a cultural dissociative symptoms' checklist. Possible meaningful clusters of symptoms were inventoried through multiple correspondence analysis. Finally, local symptoms were compared with experimental criteria for PTD in the DSM-IV and proposed criteria for DID in the DSM-5. Illness narratives revealed different phases of spirit possession, with passive-influence experiences preceding the actual possession states. Multiple correspondence analysis of symptoms revealed two dimensions: 'passive' and 'active' symptoms. Local symptoms, such as changes in consciousness, shaking movements, and talking in a voice attributed to spirits, match with DSM-IV-PTD and DSM-5-DID criteria. Passive-influence experiences, such as feeling influenced or held by powers from outside, strange dreams, and hearing voices, deserve to be more explicitly described in the proposed criteria for DID in the DSM-5. The suggested incorporation of PTD in DID in the DSM-5 and the envisioned separation of DTD and PTD in two distinctive categories have disputable aspects.

Impact of an engineering design-based curriculum compared to an inquiry-based curriculum on fifth graders' content learning of simple machines

NASA Astrophysics Data System (ADS)

Marulcu, Ismail; Barnett, Michael

2016-01-01

Background: Elementary Science Education is struggling with multiple challenges. National and State test results confirm the need for deeper understanding in elementary science education. Moreover, national policy statements and researchers call for increased exposure to engineering and technology in elementary science education. The basic motivation of this study is to suggest a solution to both improving elementary science education and increasing exposure to engineering and technology in it. Purpose/Hypothesis: This mixed-method study examined the impact of an engineering design-based curriculum compared to an inquiry-based curriculum on fifth graders' content learning of simple machines. We hypothesize that the LEGO-engineering design unit is as successful as the inquiry-based unit in terms of students' science content learning of simple machines. Design/Method: We used a mixed-methods approach to investigate our research questions; we compared the control and the experimental groups' scores from the tests and interviews by using Analysis of Covariance (ANCOVA) and compared each group's pre- and post-scores by using paired t-tests. Results: Our findings from the paired t-tests show that both the experimental and comparison groups significantly improved their scores from the pre-test to post-test on the multiple-choice, open-ended, and interview items. Moreover, ANCOVA results show that students in the experimental group, who learned simple machines with the design-based unit, performed significantly better on the interview questions. Conclusions: Our analyses revealed that the design-based Design a people mover: Simple machines unit was, if not better, as successful as the inquiry-based FOSS Levers and pulleys unit in terms of students' science content learning.

Design of a multiple kernel learning algorithm for LS-SVM by convex programming.

PubMed

Jian, Ling; Xia, Zhonghang; Liang, Xijun; Gao, Chuanhou

2011-06-01

As a kernel based method, the performance of least squares support vector machine (LS-SVM) depends on the selection of the kernel as well as the regularization parameter (Duan, Keerthi, & Poo, 2003). Cross-validation is efficient in selecting a single kernel and the regularization parameter; however, it suffers from heavy computational cost and is not flexible to deal with multiple kernels. In this paper, we address the issue of multiple kernel learning for LS-SVM by formulating it as semidefinite programming (SDP). Furthermore, we show that the regularization parameter can be optimized in a unified framework with the kernel, which leads to an automatic process for model selection. Extensive experimental validations are performed and analyzed. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Quasi-Experimental Study Investigating the Effect of Scent on Students' Memory of Multiplication Facts and Math Anxiety

ERIC Educational Resources Information Center

Leap, Evelyn M.

2013-01-01

This quasi-experimental study was conducted with two fifth grade classrooms to investigate the effect of scent on students' acquisition and retention of multiplication facts and math anxiety. Forty participants received daily instruction for nine weeks, using a strategy-rich multiplication program called Factivation. Students in the Double Smencil…

DrugE-Rank: improving drug–target interaction prediction of new candidate drugs or targets by ensemble learning to rank

PubMed Central

Yuan, Qingjun; Gao, Junning; Wu, Dongliang; Zhang, Shihua; Mamitsuka, Hiroshi; Zhu, Shanfeng

2016-01-01

Motivation: Identifying drug–target interactions is an important task in drug discovery. To reduce heavy time and financial cost in experimental way, many computational approaches have been proposed. Although these approaches have used many different principles, their performance is far from satisfactory, especially in predicting drug–target interactions of new candidate drugs or targets. Methods: Approaches based on machine learning for this problem can be divided into two types: feature-based and similarity-based methods. Learning to rank is the most powerful technique in the feature-based methods. Similarity-based methods are well accepted, due to their idea of connecting the chemical and genomic spaces, represented by drug and target similarities, respectively. We propose a new method, DrugE-Rank, to improve the prediction performance by nicely combining the advantages of the two different types of methods. That is, DrugE-Rank uses LTR, for which multiple well-known similarity-based methods can be used as components of ensemble learning. Results: The performance of DrugE-Rank is thoroughly examined by three main experiments using data from DrugBank: (i) cross-validation on FDA (US Food and Drug Administration) approved drugs before March 2014; (ii) independent test on FDA approved drugs after March 2014; and (iii) independent test on FDA experimental drugs. Experimental results show that DrugE-Rank outperforms competing methods significantly, especially achieving more than 30% improvement in Area under Prediction Recall curve for FDA approved new drugs and FDA experimental drugs. Availability: http://datamining-iip.fudan.edu.cn/service/DrugE-Rank Contact: zhusf@fudan.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307615

Multiscale Medical Image Fusion in Wavelet Domain

PubMed Central

Khare, Ashish

2013-01-01

Wavelet transforms have emerged as a powerful tool in image fusion. However, the study and analysis of medical image fusion is still a challenging area of research. Therefore, in this paper, we propose a multiscale fusion of multimodal medical images in wavelet domain. Fusion of medical images has been performed at multiple scales varying from minimum to maximum level using maximum selection rule which provides more flexibility and choice to select the relevant fused images. The experimental analysis of the proposed method has been performed with several sets of medical images. Fusion results have been evaluated subjectively and objectively with existing state-of-the-art fusion methods which include several pyramid- and wavelet-transform-based fusion methods and principal component analysis (PCA) fusion method. The comparative analysis of the fusion results has been performed with edge strength (Q), mutual information (MI), entropy (E), standard deviation (SD), blind structural similarity index metric (BSSIM), spatial frequency (SF), and average gradient (AG) metrics. The combined subjective and objective evaluations of the proposed fusion method at multiple scales showed the effectiveness and goodness of the proposed approach. PMID:24453868

Automatic detection of multiple UXO-like targets using magnetic anomaly inversion and self-adaptive fuzzy c-means clustering

NASA Astrophysics Data System (ADS)

Yin, Gang; Zhang, Yingtang; Fan, Hongbo; Ren, Guoquan; Li, Zhining

2017-12-01

We have developed a method for automatically detecting UXO-like targets based on magnetic anomaly inversion and self-adaptive fuzzy c-means clustering. Magnetic anomaly inversion methods are used to estimate the initial locations of multiple UXO-like sources. Although these initial locations have some errors with respect to the real positions, they form dense clouds around the actual positions of the magnetic sources. Then we use the self-adaptive fuzzy c-means clustering algorithm to cluster these initial locations. The estimated number of cluster centroids represents the number of targets and the cluster centroids are regarded as the locations of magnetic targets. Effectiveness of the method has been demonstrated using synthetic datasets. Computational results show that the proposed method can be applied to the case of several UXO-like targets that are randomly scattered within in a confined, shallow subsurface, volume. A field test was carried out to test the validity of the proposed method and the experimental results show that the prearranged magnets can be detected unambiguously and located precisely.

Simplified multiple headspace extraction gas chromatographic technique for determination of monomer solubility in water.

PubMed

Chai, X S; Schork, F J; DeCinque, Anthony

2005-04-08

This paper reports an improved headspace gas chromatographic (GC) technique for determination of monomer solubilities in water. The method is based on a multiple headspace extraction GC technique developed previously [X.S. Chai, Q.X. Hou, F.J. Schork, J. Appl. Polym. Sci., in press], but with the major modification in the method calibration technique. As a result, only a few iterations of headspace extraction and GC measurement are required, which avoids the "exhaustive" headspace extraction, and thus the experimental time for each analysis. For highly insoluble monomers, effort must be made to minimize adsorption in the headspace sampling channel, transportation conduit and capillary column by using higher operating temperature and a short capillary column in the headspace sampler and GC system. For highly water soluble monomers, a new calibration method is proposed. The combinations of these technique modifications results in a method that is simple, rapid and automated. While the current focus of the authors is on the determination of monomer solubility in aqueous solutions, the method should be applicable to determination of solubility of any organic in water.

A Multi-Objective Partition Method for Marine Sensor Networks Based on Degree of Event Correlation.

PubMed

Huang, Dongmei; Xu, Chenyixuan; Zhao, Danfeng; Song, Wei; He, Qi

2017-09-21

Existing marine sensor networks acquire data from sea areas that are geographically divided, and store the data independently in their affiliated sea area data centers. In the case of marine events across multiple sea areas, the current network structure needs to retrieve data from multiple data centers, and thus severely affects real-time decision making. In this study, in order to provide a fast data retrieval service for a marine sensor network, we use all the marine sensors as the vertices, establish the edge based on marine events, and abstract the marine sensor network as a graph. Then, we construct a multi-objective balanced partition method to partition the abstract graph into multiple regions and store them in the cloud computing platform. This method effectively increases the correlation of the sensors and decreases the retrieval cost. On this basis, an incremental optimization strategy is designed to dynamically optimize existing partitions when new sensors are added into the network. Experimental results show that the proposed method can achieve the optimal layout for distributed storage in the process of disaster data retrieval in the China Sea area, and effectively optimize the result of partitions when new buoys are deployed, which eventually will provide efficient data access service for marine events.

Improving link prediction in complex networks by adaptively exploiting multiple structural features of networks

NASA Astrophysics Data System (ADS)

Ma, Chuang; Bao, Zhong-Kui; Zhang, Hai-Feng

2017-10-01

So far, many network-structure-based link prediction methods have been proposed. However, these methods only highlight one or two structural features of networks, and then use the methods to predict missing links in different networks. The performances of these existing methods are not always satisfied in all cases since each network has its unique underlying structural features. In this paper, by analyzing different real networks, we find that the structural features of different networks are remarkably different. In particular, even in the same network, their inner structural features are utterly different. Therefore, more structural features should be considered. However, owing to the remarkably different structural features, the contributions of different features are hard to be given in advance. Inspired by these facts, an adaptive fusion model regarding link prediction is proposed to incorporate multiple structural features. In the model, a logistic function combing multiple structural features is defined, then the weight of each feature in the logistic function is adaptively determined by exploiting the known structure information. Last, we use the "learnt" logistic function to predict the connection probabilities of missing links. According to our experimental results, we find that the performance of our adaptive fusion model is better than many similarity indices.

Symmetric caging formation for convex polygonal object transportation by multiple mobile robots based on fuzzy sliding mode control.

PubMed

Dai, Yanyan; Kim, YoonGu; Wee, SungGil; Lee, DongHa; Lee, SukGyu

2016-01-01

In this paper, the problem of object caging and transporting is considered for multiple mobile robots. With the consideration of minimizing the number of robots and decreasing the rotation of the object, the proper points are calculated and assigned to the multiple mobile robots to allow them to form a symmetric caging formation. The caging formation guarantees that all of the Euclidean distances between any two adjacent robots are smaller than the minimal width of the polygonal object so that the object cannot escape. In order to avoid collision among robots, the parameter of the robots radius is utilized to design the caging formation, and the A⁎ algorithm is used so that mobile robots can move to the proper points. In order to avoid obstacles, the robots and the object are regarded as a rigid body to apply artificial potential field method. The fuzzy sliding mode control method is applied for tracking control of the nonholonomic mobile robots. Finally, the simulation and experimental results show that multiple mobile robots are able to cage and transport the polygonal object to the goal position, avoiding obstacles. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Identification and Correction of Additive and Multiplicative Spatial Biases in Experimental High-Throughput Screening.

PubMed

Mazoure, Bogdan; Caraus, Iurie; Nadon, Robert; Makarenkov, Vladimir

2018-06-01

Data generated by high-throughput screening (HTS) technologies are prone to spatial bias. Traditionally, bias correction methods used in HTS assume either a simple additive or, more recently, a simple multiplicative spatial bias model. These models do not, however, always provide an accurate correction of measurements in wells located at the intersection of rows and columns affected by spatial bias. The measurements in these wells depend on the nature of interaction between the involved biases. Here, we propose two novel additive and two novel multiplicative spatial bias models accounting for different types of bias interactions. We describe a statistical procedure that allows for detecting and removing different types of additive and multiplicative spatial biases from multiwell plates. We show how this procedure can be applied by analyzing data generated by the four HTS technologies (homogeneous, microorganism, cell-based, and gene expression HTS), the three high-content screening (HCS) technologies (area, intensity, and cell-count HCS), and the only small-molecule microarray technology available in the ChemBank small-molecule screening database. The proposed methods are included in the AssayCorrector program, implemented in R, and available on CRAN.

Morphology enabled dipole inversion (MEDI) from a single-angle acquisition: comparison with COSMOS in human brain imaging.

PubMed

Liu, Tian; Liu, Jing; de Rochefort, Ludovic; Spincemaille, Pascal; Khalidov, Ildar; Ledoux, James Robert; Wang, Yi

2011-09-01

Magnetic susceptibility varies among brain structures and provides insights into the chemical and molecular composition of brain tissues. However, the determination of an arbitrary susceptibility distribution from the measured MR signal phase is a challenging, ill-conditioned inverse problem. Although a previous method named calculation of susceptibility through multiple orientation sampling (COSMOS) has solved this inverse problem both theoretically and experimentally using multiple angle acquisitions, it is often impractical to carry out on human subjects. Recently, the feasibility of calculating the brain susceptibility distribution from a single-angle acquisition was demonstrated using morphology enabled dipole inversion (MEDI). In this study, we further improved the original MEDI method by sparsifying the edges in the quantitative susceptibility map that do not have a corresponding edge in the magnitude image. Quantitative susceptibility maps generated by the improved MEDI were compared qualitatively and quantitatively with those generated by calculation of susceptibility through multiple orientation sampling. The results show a high degree of agreement between MEDI and calculation of susceptibility through multiple orientation sampling, and the practicality of MEDI allows many potential clinical applications. Copyright © 2011 Wiley-Liss, Inc.

Intelligent query by humming system based on score level fusion of multiple classifiers

NASA Astrophysics Data System (ADS)

Pyo Nam, Gi; Thu Trang Luong, Thi; Ha Nam, Hyun; Ryoung Park, Kang; Park, Sung-Joo

2011-12-01

Recently, the necessity for content-based music retrieval that can return results even if a user does not know information such as the title or singer has increased. Query-by-humming (QBH) systems have been introduced to address this need, as they allow the user to simply hum snatches of the tune to find the right song. Even though there have been many studies on QBH, few have combined multiple classifiers based on various fusion methods. Here we propose a new QBH system based on the score level fusion of multiple classifiers. This research is novel in the following three respects: three local classifiers [quantized binary (QB) code-based linear scaling (LS), pitch-based dynamic time warping (DTW), and LS] are employed; local maximum and minimum point-based LS and pitch distribution feature-based LS are used as global classifiers; and the combination of local and global classifiers based on the score level fusion by the PRODUCT rule is used to achieve enhanced matching accuracy. Experimental results with the 2006 MIREX QBSH and 2009 MIR-QBSH corpus databases show that the performance of the proposed method is better than that of single classifier and other fusion methods.

Accuracy improvement in laser stripe extraction for large-scale triangulation scanning measurement system

NASA Astrophysics Data System (ADS)

Zhang, Yang; Liu, Wei; Li, Xiaodong; Yang, Fan; Gao, Peng; Jia, Zhenyuan

2015-10-01

Large-scale triangulation scanning measurement systems are widely used to measure the three-dimensional profile of large-scale components and parts. The accuracy and speed of the laser stripe center extraction are essential for guaranteeing the accuracy and efficiency of the measuring system. However, in the process of large-scale measurement, multiple factors can cause deviation of the laser stripe center, including the spatial light intensity distribution, material reflectivity characteristics, and spatial transmission characteristics. A center extraction method is proposed for improving the accuracy of the laser stripe center extraction based on image evaluation of Gaussian fitting structural similarity and analysis of the multiple source factors. First, according to the features of the gray distribution of the laser stripe, evaluation of the Gaussian fitting structural similarity is estimated to provide a threshold value for center compensation. Then using the relationships between the gray distribution of the laser stripe and the multiple source factors, a compensation method of center extraction is presented. Finally, measurement experiments for a large-scale aviation composite component are carried out. The experimental results for this specific implementation verify the feasibility of the proposed center extraction method and the improved accuracy for large-scale triangulation scanning measurements.

A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach.

PubMed

Jian, Yulin; Huang, Daoyu; Yan, Jia; Lu, Kun; Huang, Ying; Wen, Tailai; Zeng, Tanyue; Zhong, Shijie; Xie, Qilong

2017-06-19

A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs). The combination coefficients of base kernels, the model parameters of each base kernel, and the regularization parameter are optimized by QPSO simultaneously before implementing the kernel extreme learning machine (KELM) with the composite kernel function. Four types of common single kernel functions (Gaussian kernel, polynomial kernel, sigmoid kernel, and wavelet kernel) are utilized to constitute different composite kernel functions. Moreover, the method is also compared with other existing classification methods: extreme learning machine (ELM), kernel extreme learning machine (KELM), k-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP), radical basis function neural network (RBFNN), and probabilistic neural network (PNN). The results have demonstrated that the proposed QWMK-ELM outperforms the aforementioned methods, not only in precision, but also in efficiency for gas classification.

The "Diagnostic Guideline for Anxiety and Challenging Behaviour" for Persons with Intellectual Disabilities: Preliminary Outcomes on Internalizing Problems, Challenging Behaviours, Quality of Life and Clients' Satisfaction

ERIC Educational Resources Information Center

Pruijssers, Addy; Meijel, Berno; Maaskant, Marian; Teerenstra, Steven; van Achterberg, Theo

2017-01-01

Background: People with intellectual disabilities are vulnerable to develop psychopathology (in particular anxiety) and related challenging behaviour. Method: A comparative multiple case study with an experimental and a control condition. Results: The application of the guideline showed a trend of decreases of internalizing problems (P = 0.07) and…

Implementation of a Culturally Appropriate Positive Behavior Support Plan with a Japanese Mother of a Child with Autism: An Experimental and Qualitative Analysis

ERIC Educational Resources Information Center

Cheremshynski, Christy; Lucyshyn, Joseph M.; Olson, Deborah L.

2013-01-01

The purpose of this study was to empirically investigate a family-centered approach to positive behavior support (PBS) that was designed to be culturally responsive to families of diverse linguistic and cultural backgrounds. A Japanese mother and a child with autism were the primary participants. Multiple research methods were used. A…

Local denoising of digital speckle pattern interferometry fringes by multiplicative correlation and weighted smoothing splines.

PubMed

Federico, Alejandro; Kaufmann, Guillermo H

2005-05-10

We evaluate the use of smoothing splines with a weighted roughness measure for local denoising of the correlation fringes produced in digital speckle pattern interferometry. In particular, we also evaluate the performance of the multiplicative correlation operation between two speckle patterns that is proposed as an alternative procedure to generate the correlation fringes. It is shown that the application of a normalization algorithm to the smoothed correlation fringes reduces the excessive bias generated in the previous filtering stage. The evaluation is carried out by use of computer-simulated fringes that are generated for different average speckle sizes and intensities of the reference beam, including decorrelation effects. A comparison with filtering methods based on the continuous wavelet transform is also presented. Finally, the performance of the smoothing method in processing experimental data is illustrated.

Combining multiple decisions: applications to bioinformatics

NASA Astrophysics Data System (ADS)

Yukinawa, N.; Takenouchi, T.; Oba, S.; Ishii, S.

2008-01-01

Multi-class classification is one of the fundamental tasks in bioinformatics and typically arises in cancer diagnosis studies by gene expression profiling. This article reviews two recent approaches to multi-class classification by combining multiple binary classifiers, which are formulated based on a unified framework of error-correcting output coding (ECOC). The first approach is to construct a multi-class classifier in which each binary classifier to be aggregated has a weight value to be optimally tuned based on the observed data. In the second approach, misclassification of each binary classifier is formulated as a bit inversion error with a probabilistic model by making an analogy to the context of information transmission theory. Experimental studies using various real-world datasets including cancer classification problems reveal that both of the new methods are superior or comparable to other multi-class classification methods.

Nonlinear Semi-Supervised Metric Learning Via Multiple Kernels and Local Topology.

PubMed

Li, Xin; Bai, Yanqin; Peng, Yaxin; Du, Shaoyi; Ying, Shihui

2018-03-01

Changing the metric on the data may change the data distribution, hence a good distance metric can promote the performance of learning algorithm. In this paper, we address the semi-supervised distance metric learning (ML) problem to obtain the best nonlinear metric for the data. First, we describe the nonlinear metric by the multiple kernel representation. By this approach, we project the data into a high dimensional space, where the data can be well represented by linear ML. Then, we reformulate the linear ML by a minimization problem on the positive definite matrix group. Finally, we develop a two-step algorithm for solving this model and design an intrinsic steepest descent algorithm to learn the positive definite metric matrix. Experimental results validate that our proposed method is effective and outperforms several state-of-the-art ML methods.

Statistical reconstruction for cosmic ray muon tomography.

PubMed

Schultz, Larry J; Blanpied, Gary S; Borozdin, Konstantin N; Fraser, Andrew M; Hengartner, Nicolas W; Klimenko, Alexei V; Morris, Christopher L; Orum, Chris; Sossong, Michael J

2007-08-01

Highly penetrating cosmic ray muons constantly shower the earth at a rate of about 1 muon per cm2 per minute. We have developed a technique which exploits the multiple Coulomb scattering of these particles to perform nondestructive inspection without the use of artificial radiation. In prior work [1]-[3], we have described heuristic methods for processing muon data to create reconstructed images. In this paper, we present a maximum likelihood/expectation maximization tomographic reconstruction algorithm designed for the technique. This algorithm borrows much from techniques used in medical imaging, particularly emission tomography, but the statistics of muon scattering dictates differences. We describe the statistical model for multiple scattering, derive the reconstruction algorithm, and present simulated examples. We also propose methods to improve the robustness of the algorithm to experimental errors and events departing from the statistical model.

Static shape control for adaptive wings

NASA Astrophysics Data System (ADS)

Austin, Fred; Rossi, Michael J.; van Nostrand, William; Knowles, Gareth; Jameson, Antony

1994-09-01

A theoretical method was developed and experimentally validated, to control the static shape of flexible structures by employing internal translational actuators. A finite element model of the structure, without the actuators present, is employed to obtain the multiple-input, multiple-output control-system gain matrices for actuator-load control as well as actuator-displacement control. The method is applied to the quasistatic problem of maintaining an optimum-wing cross section during various transonic-cruise flight conditions to obtain significant reductions in the shock-induced drag. Only small, potentially achievable, adaptive modifications to the profile are required. The adaptive-wing concept employs actuators as truss elements of active ribs to reshape the wing cross section by deforming the structure. Finite element analyses of an adaptive-rib model verify the controlled-structure theory. Experiments on the model were conducted, and arbitrarily selected deformed shapes were accurately achieved.

Testing accelerometer rectification error caused by multidimensional composite inputs with double turntable centrifuge.

PubMed

Guan, W; Meng, X F; Dong, X M

2014-12-01

Rectification error is a critical characteristic of inertial accelerometers. Accelerometers working in operational situations are stimulated by composite inputs, including constant acceleration and vibration, from multiple directions. However, traditional methods for evaluating rectification error only use one-dimensional vibration. In this paper, a double turntable centrifuge (DTC) was utilized to produce the constant acceleration and vibration simultaneously and we tested the rectification error due to the composite accelerations. At first, we deduced the expression of the rectification error with the output of the DTC and a static model of the single-axis pendulous accelerometer under test. Theoretical investigation and analysis were carried out in accordance with the rectification error model. Then a detailed experimental procedure and testing results were described. We measured the rectification error with various constant accelerations at different frequencies and amplitudes of the vibration. The experimental results showed the distinguished characteristics of the rectification error caused by the composite accelerations. The linear relation between the constant acceleration and the rectification error was proved. The experimental procedure and results presented in this context can be referenced for the investigation of the characteristics of accelerometer with multiple inputs.

First spatial separation of a heavy ion isomeric beam with a multiple-reflection time-of-flight mass spectrometer

NASA Astrophysics Data System (ADS)

Dickel, T.; Plaß, W. R.; Ayet San Andres, S.; Ebert, J.; Geissel, H.; Haettner, E.; Hornung, C.; Miskun, I.; Pietri, S.; Purushothaman, S.; Reiter, M. P.; Rink, A.-K.; Scheidenberger, C.; Weick, H.; Dendooven, P.; Diwisch, M.; Greiner, F.; Heiße, F.; Knöbel, R.; Lippert, W.; Moore, I. D.; Pohjalainen, I.; Prochazka, A.; Ranjan, M.; Takechi, M.; Winfield, J. S.; Xu, X.

2015-05-01

211Po ions in the ground and isomeric states were produced via 238U projectile fragmentation at 1000 MeV/u. The 211Po ions were spatially separated in flight from the primary beam and other reaction products by the fragment separator FRS. The ions were energy-bunched, slowed-down and thermalized in a gas-filled cryogenic stopping cell (CSC). They were then extracted from the CSC and injected into a high-resolution multiple-reflection time-of-flight mass spectrometer (MR-TOF-MS). The excitation energy of the isomer and, for the first time, the isomeric-to-ground state ratio were determined from the measured mass spectrum. In the subsequent experimental step, the isomers were spatially separated from the ions in the ground state by an ion deflector and finally collected with a silicon detector for decay spectroscopy. This pioneering experimental result opens up unique perspectives for isomer-resolved studies. With this versatile experimental method new isomers with half-lives longer than a few milliseconds can be discovered and their decay properties can be measured with highest sensitivity and selectivity. These experiments can be extended to studies with isomeric beams in nuclear reactions.

[Towards computer-aided catalyst design: Three effective core potential studies of C-H activation]. Final report

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

NONE

1998-12-31

Research in the initial grant period focused on computational studies relevant to the selective activation of methane, the prime component of natural gas. Reaction coordinates for methane activation by experimental models were delineated, as well as the bonding and structure of complexes that effect this important reaction. This research, highlighted in the following sections, also provided the impetus for further development, and application of methods for modeling metal-containing catalysts. Sections of the report describe the following: methane activation by multiple-bonded transition metal complexes; computational lanthanide chemistry; and methane activation by non-imido, multiple-bonded ligands.

Non-linear molecular pattern classification using molecular beacons with multiple targets.

PubMed

Lee, In-Hee; Lee, Seung Hwan; Park, Tai Hyun; Zhang, Byoung-Tak

2013-12-01

In vitro pattern classification has been highlighted as an important future application of DNA computing. Previous work has demonstrated the feasibility of linear classifiers using DNA-based molecular computing. However, complex tasks require non-linear classification capability. Here we design a molecular beacon that can interact with multiple targets and experimentally shows that its fluorescent signals form a complex radial-basis function, enabling it to be used as a building block for non-linear molecular classification in vitro. The proposed method was successfully applied to solving artificial and real-world classification problems: XOR and microRNA expression patterns. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Method for Visually Integrating Multiple Data Acquisition Technologies for Real Time and Retrospective Analysis

NASA Technical Reports Server (NTRS)

Bogart, Edward H. (Inventor); Pope, Alan T. (Inventor)

2000-01-01

A system for display on a single video display terminal of multiple physiological measurements is provided. A subject is monitored by a plurality of instruments which feed data to a computer programmed to receive data, calculate data products such as index of engagement and heart rate, and display the data in a graphical format simultaneously on a single video display terminal. In addition live video representing the view of the subject and the experimental setup may also be integrated into the single data display. The display may be recorded on a standard video tape recorder for retrospective analysis.

Efficient Numerical Methods for Nonlinear-Facilitated Transport and Exchange in a Blood-Tissue Exchange Unit

PubMed Central

Poulain, Christophe A.; Finlayson, Bruce A.; Bassingthwaighte, James B.

2010-01-01

The analysis of experimental data obtained by the multiple-indicator method requires complex mathematical models for which capillary blood-tissue exchange (BTEX) units are the building blocks. This study presents a new, nonlinear, two-region, axially distributed, single capillary, BTEX model. A facilitated transporter model is used to describe mass transfer between plasma and intracellular spaces. To provide fast and accurate solutions, numerical techniques suited to nonlinear convection-dominated problems are implemented. These techniques are the random choice method, an explicit Euler-Lagrange scheme, and the MacCormack method with and without flux correction. The accuracy of the numerical techniques is demonstrated, and their efficiencies are compared. The random choice, Euler-Lagrange and plain MacCormack method are the best numerical techniques for BTEX modeling. However, the random choice and Euler-Lagrange methods are preferred over the MacCormack method because they allow for the derivation of a heuristic criterion that makes the numerical methods stable without degrading their efficiency. Numerical solutions are also used to illustrate some nonlinear behaviors of the model and to show how the new BTEX model can be used to estimate parameters from experimental data. PMID:9146808

Combining multiple positive training sets to generate confidence scores for protein-protein interactions.

PubMed

Yu, Jingkai; Finley, Russell L

2009-01-01

High-throughput experimental and computational methods are generating a wealth of protein-protein interaction data for a variety of organisms. However, data produced by current state-of-the-art methods include many false positives, which can hinder the analyses needed to derive biological insights. One way to address this problem is to assign confidence scores that reflect the reliability and biological significance of each interaction. Most previously described scoring methods use a set of likely true positives to train a model to score all interactions in a dataset. A single positive training set, however, may be biased and not representative of true interaction space. We demonstrate a method to score protein interactions by utilizing multiple independent sets of training positives to reduce the potential bias inherent in using a single training set. We used a set of benchmark yeast protein interactions to show that our approach outperforms other scoring methods. Our approach can also score interactions across data types, which makes it more widely applicable than many previously proposed methods. We applied the method to protein interaction data from both Drosophila melanogaster and Homo sapiens. Independent evaluations show that the resulting confidence scores accurately reflect the biological significance of the interactions.

Multiple-algorithm parallel fusion of infrared polarization and intensity images based on algorithmic complementarity and synergy

NASA Astrophysics Data System (ADS)

Zhang, Lei; Yang, Fengbao; Ji, Linna; Lv, Sheng

2018-01-01

Diverse image fusion methods perform differently. Each method has advantages and disadvantages compared with others. One notion is that the advantages of different image methods can be effectively combined. A multiple-algorithm parallel fusion method based on algorithmic complementarity and synergy is proposed. First, in view of the characteristics of the different algorithms and difference-features among images, an index vector-based feature-similarity is proposed to define the degree of complementarity and synergy. This proposed index vector is a reliable evidence indicator for algorithm selection. Second, the algorithms with a high degree of complementarity and synergy are selected. Then, the different degrees of various features and infrared intensity images are used as the initial weights for the nonnegative matrix factorization (NMF). This avoids randomness of the NMF initialization parameter. Finally, the fused images of different algorithms are integrated using the NMF because of its excellent data fusing performance on independent features. Experimental results demonstrate that the visual effect and objective evaluation index of the fused images obtained using the proposed method are better than those obtained using traditional methods. The proposed method retains all the advantages that individual fusion algorithms have.

Statistical strategies for averaging EC50 from multiple dose-response experiments.

PubMed

Jiang, Xiaoqi; Kopp-Schneider, Annette

2015-11-01

In most dose-response studies, repeated experiments are conducted to determine the EC50 value for a chemical, requiring averaging EC50 estimates from a series of experiments. Two statistical strategies, the mixed-effect modeling and the meta-analysis approach, can be applied to estimate average behavior of EC50 values over all experiments by considering the variabilities within and among experiments. We investigated these two strategies in two common cases of multiple dose-response experiments in (a) complete and explicit dose-response relationships are observed in all experiments and in (b) only in a subset of experiments. In case (a), the meta-analysis strategy is a simple and robust method to average EC50 estimates. In case (b), all experimental data sets can be first screened using the dose-response screening plot, which allows visualization and comparison of multiple dose-response experimental results. As long as more than three experiments provide information about complete dose-response relationships, the experiments that cover incomplete relationships can be excluded from the meta-analysis strategy of averaging EC50 estimates. If there are only two experiments containing complete dose-response information, the mixed-effects model approach is suggested. We subsequently provided a web application for non-statisticians to implement the proposed meta-analysis strategy of averaging EC50 estimates from multiple dose-response experiments.

MRI-based in vivo assessment of early cerebral infarction in a mouse filament perforation model of subarachnoid hemorrhage.

PubMed

Sasaki, Kazumasu; Mutoh, Tatsushi; Nakamura, Kazuhiro; Kojima, Ikuho; Taki, Yasuyuki; Suarez, Jose Ignacio; Ishikawa, Tatsuya

2017-07-13

Experimental subarachnoid hemorrhage (SAH) by endovascular filament perforation method is used widely in mice, but it sometimes present acute cerebral infarctions with varied magnitude and anatomical location. This study aimed to determine the prevalence and location of the acute ischemic injury in this experimental model. Male C57BL/6 mice were subjected to SAH by endovascular perforation. Distribution of SAH was defined by T2*-weighted images within 1h after SAH. Prevalence and location of acute infarction were assessed by diffusion-weighted MR images on day 1 after the induction. Among 72 mice successfully acquired post-SAH MR images, 29 (40%) developed acute infarction. Location of the infarcts was classified into either single infarct (ipsilateral cortex, n=12; caudate putamen, n=3; hippocampus, n=1) or multiple lesions (cortex and caudate putamen, n=6; cortex and hippocampus, n=2; cortex, hippocampus and thalamus/hypothalamus, n=3; bilateral cortex, n=2). The mortality rate within 24h was significantly higher in mice with multiple infarcts than those with single lesion (30% versus 0%; P=0.03). Distribution of the ischemic lesion positively correlated with MRI-evidenced SAH grading (r 2 =0.31, P=0.0002). Experimental SAH immediately after the vessel perforation can induce acute cerebral infarction in varying vascular territories, resulting in increased mortality. The present model may in part, help researchers to interpret the mechanism of clinically-evidenced early multiple combined infarction. Copyright © 2017 Elsevier B.V. All rights reserved.

Pathway Towards Fluency: Using 'disaggregate instruction' to promote science literacy

NASA Astrophysics Data System (ADS)

Brown, Bryan A.; Ryoo, Kihyun; Rodriguez, Jamie

2010-07-01

This study examines the impact of Disaggregate Instruction on students' science learning. Disaggregate Instruction is the idea that science teaching and learning can be separated into conceptual and discursive components. Using randomly assigned experimental and control groups, 49 fifth-grade students received web-based science lessons on photosynthesis using our experimental approach. We supplemented quantitative statistical comparisons of students' performance on pre- and post-test questions (multiple choice and short answer) with a qualitative analysis of students' post-test interviews. The results revealed that students in the experimental group outscored their control group counterparts across all measures. In addition, students taught using the experimental method demonstrated an improved ability to write using scientific language as well as an improved ability to provide oral explanations using scientific language. This study has important implications for how science educators can prepare teachers to teach diverse student populations.

A novel method for the sequential removal and separation of multiple heavy metals from wastewater.

PubMed

Fang, Li; Li, Liang; Qu, Zan; Xu, Haomiao; Xu, Jianfang; Yan, Naiqiang

2018-01-15

A novel method was developed and applied for the treatment of simulated wastewater containing multiple heavy metals. A sorbent of ZnS nanocrystals (NCs) was synthesized and showed extraordinary performance for the removal of Hg 2+ , Cu 2+ , Pb 2+ and Cd 2+ . The removal efficiencies of Hg 2+ , Cu 2+ , Pb 2+ and Cd 2+ were 99.9%, 99.9%, 90.8% and 66.3%, respectively. Meanwhile, it was determined that solubility product (K sp ) of heavy metal sulfides was closely related to adsorption selectivity of various heavy metals on the sorbent. The removal efficiency of Hg 2+ was higher than that of Cd 2+ , while the K sp of HgS was lower than that of CdS. It indicated that preferential adsorption of heavy metals occurred when the K sp of the heavy metal sulfide was lower. In addition, the differences in the K sp of heavy metal sulfides allowed for the exchange of heavy metals, indicating the potential application for the sequential removal and separation of heavy metals from wastewater. According to the cumulative adsorption experimental results, multiple heavy metals were sequentially adsorbed and separated from the simulated wastewater in the order of the K sp of their sulfides. This method holds the promise of sequentially removing and separating multiple heavy metals from wastewater. Copyright © 2017 Elsevier B.V. All rights reserved.

Automated annotation of functional imaging experiments via multi-label classification

PubMed Central

Turner, Matthew D.; Chakrabarti, Chayan; Jones, Thomas B.; Xu, Jiawei F.; Fox, Peter T.; Luger, George F.; Laird, Angela R.; Turner, Jessica A.

2013-01-01

Identifying the experimental methods in human neuroimaging papers is important for grouping meaningfully similar experiments for meta-analyses. Currently, this can only be done by human readers. We present the performance of common machine learning (text mining) methods applied to the problem of automatically classifying or labeling this literature. Labeling terms are from the Cognitive Paradigm Ontology (CogPO), the text corpora are abstracts of published functional neuroimaging papers, and the methods use the performance of a human expert as training data. We aim to replicate the expert's annotation of multiple labels per abstract identifying the experimental stimuli, cognitive paradigms, response types, and other relevant dimensions of the experiments. We use several standard machine learning methods: naive Bayes (NB), k-nearest neighbor, and support vector machines (specifically SMO or sequential minimal optimization). Exact match performance ranged from only 15% in the worst cases to 78% in the best cases. NB methods combined with binary relevance transformations performed strongly and were robust to overfitting. This collection of results demonstrates what can be achieved with off-the-shelf software components and little to no pre-processing of raw text. PMID:24409112

Multiple Kernel Sparse Representation based Orthogonal Discriminative Projection and Its Cost-Sensitive Extension.

PubMed

Zhang, Guoqing; Sun, Huaijiang; Xia, Guiyu; Sun, Quansen

2016-07-07

Sparse representation based classification (SRC) has been developed and shown great potential for real-world application. Based on SRC, Yang et al. [10] devised a SRC steered discriminative projection (SRC-DP) method. However, as a linear algorithm, SRC-DP cannot handle the data with highly nonlinear distribution. Kernel sparse representation-based classifier (KSRC) is a non-linear extension of SRC and can remedy the drawback of SRC. KSRC requires the use of a predetermined kernel function and selection of the kernel function and its parameters is difficult. Recently, multiple kernel learning for SRC (MKL-SRC) [22] has been proposed to learn a kernel from a set of base kernels. However, MKL-SRC only considers the within-class reconstruction residual while ignoring the between-class relationship, when learning the kernel weights. In this paper, we propose a novel multiple kernel sparse representation-based classifier (MKSRC), and then we use it as a criterion to design a multiple kernel sparse representation based orthogonal discriminative projection method (MK-SR-ODP). The proposed algorithm aims at learning a projection matrix and a corresponding kernel from the given base kernels such that in the low dimension subspace the between-class reconstruction residual is maximized and the within-class reconstruction residual is minimized. Furthermore, to achieve a minimum overall loss by performing recognition in the learned low-dimensional subspace, we introduce cost information into the dimensionality reduction method. The solutions for the proposed method can be efficiently found based on trace ratio optimization method [33]. Extensive experimental results demonstrate the superiority of the proposed algorithm when compared with the state-of-the-art methods.

Studies of aerothermal loads generated in regions of shock/shock interaction in hypersonic flow

NASA Technical Reports Server (NTRS)

Holden, Michael S.; Moselle, John R.; Lee, Jinho

1991-01-01

Experimental studies were conducted to examine the aerothermal characteristics of shock/shock/boundary layer interaction regions generated by single and multiple incident shocks. The presented experimental studies were conducted over a Mach number range from 6 to 19 for a range of Reynolds numbers to obtain both laminar and turbulent interaction regions. Detailed heat transfer and pressure measurements were made for a range of interaction types and incident shock strengths over a transverse cylinder, with emphasis on the 3 and 4 type interaction regions. The measurements were compared with the simple Edney, Keyes, and Hains models for a range of interaction configurations and freestream conditions. The complex flowfields and aerothermal loads generated by multiple-shock impingement, while not generating as large peak loads, provide important test cases for code prediction. The detailed heat transfer and pressure measurements proved a good basis for evaluating the accuracy of simple prediction methods and detailed numerical solutions for laminar and transitional regions or shock/shock interactions.

Design and experimental verification for optical module of optical vector-matrix multiplier.

PubMed

Zhu, Weiwei; Zhang, Lei; Lu, Yangyang; Zhou, Ping; Yang, Lin

2013-06-20

Optical computing is a new method to implement signal processing functions. The multiplication between a vector and a matrix is an important arithmetic algorithm in the signal processing domain. The optical vector-matrix multiplier (OVMM) is an optoelectronic system to carry out this operation, which consists of an electronic module and an optical module. In this paper, we propose an optical module for OVMM. To eliminate the cross talk and make full use of the optical elements, an elaborately designed structure that involves spherical lenses and cylindrical lenses is utilized in this optical system. The optical design software package ZEMAX is used to optimize the parameters and simulate the whole system. Finally, experimental data is obtained through experiments to evaluate the overall performance of the system. The results of both simulation and experiment indicate that the system constructed can implement the multiplication between a matrix with dimensions of 16 by 16 and a vector with a dimension of 16 successfully.

Theoretical and Experimental Investigation of Mufflers with Comments on Engine-Exhaust Muffler Design

NASA Technical Reports Server (NTRS)

Davis, Don D , Jr; Stokes, George M; Moore, Dewey; Stevens, George L , Jr

1954-01-01

Equations are presented for the attenuation characteristics of single-chamber and multiple-chamber mufflers of both the expansion-chamber and resonator types, for tuned side-branch tubes, and for the combination of an expansion chamber with a resonator. Experimental curves of attenuation plotted against frequency are presented for 77 different mufflers with a reflection-free tailpipe termination. The experiments were made at room temperature without flow; the sound source was a loud-speaker. A method is given for including the tailpipe reflections in the calculations. Experimental attenuation curves are presented for four different muffler-tailpipe combinations, and the results are compared with the theory. The application of the theory to the design of engine-exhaust mufflers is discussed, and charts are included for the assistance of the designer.

A comparison of experiment and theory for sound propagation in variable area ducts

NASA Technical Reports Server (NTRS)

Nayfeh, A. H.; Kaiser, J. E.; Marshall, R. L.; Hurst, C. J.

1980-01-01

An experimental and analytical program has been carried out to evaluate sound suppression techniques in ducts that produce refraction effects due to axial velocity gradients. The analytical program employs a computer code based on the method of multiple scales to calculate the influence of axial variations due to slow changes in the cross-sectional area as well as transverse gradients due to the wall boundary layers. Detailed comparisons between the analytical predictions and the experimental measurements have been made. The circumferential variations of pressure amplitudes and phases at several axial positions have been examined in straight and variable area ducts, with hard walls and lined sections, and with and without a mean flow. Reasonable agreement between the theoretical and experimental results has been found.

DrugE-Rank: improving drug-target interaction prediction of new candidate drugs or targets by ensemble learning to rank.

PubMed

Yuan, Qingjun; Gao, Junning; Wu, Dongliang; Zhang, Shihua; Mamitsuka, Hiroshi; Zhu, Shanfeng

2016-06-15

Identifying drug-target interactions is an important task in drug discovery. To reduce heavy time and financial cost in experimental way, many computational approaches have been proposed. Although these approaches have used many different principles, their performance is far from satisfactory, especially in predicting drug-target interactions of new candidate drugs or targets. Approaches based on machine learning for this problem can be divided into two types: feature-based and similarity-based methods. Learning to rank is the most powerful technique in the feature-based methods. Similarity-based methods are well accepted, due to their idea of connecting the chemical and genomic spaces, represented by drug and target similarities, respectively. We propose a new method, DrugE-Rank, to improve the prediction performance by nicely combining the advantages of the two different types of methods. That is, DrugE-Rank uses LTR, for which multiple well-known similarity-based methods can be used as components of ensemble learning. The performance of DrugE-Rank is thoroughly examined by three main experiments using data from DrugBank: (i) cross-validation on FDA (US Food and Drug Administration) approved drugs before March 2014; (ii) independent test on FDA approved drugs after March 2014; and (iii) independent test on FDA experimental drugs. Experimental results show that DrugE-Rank outperforms competing methods significantly, especially achieving more than 30% improvement in Area under Prediction Recall curve for FDA approved new drugs and FDA experimental drugs. http://datamining-iip.fudan.edu.cn/service/DrugE-Rank zhusf@fudan.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Multiplicity distributions of shower particles and target fragments in 84 Kr 36-emulsion interactions at 1 GeV per nucleon

NASA Astrophysics Data System (ADS)

Singh, M. K.; Soma, A. K.; Pathak, Ramji; Singh, V.

2014-03-01

This article focuses on multiplicity distributions of shower particles and target fragments for interaction of 84 Kr 36 with NIKFI BR-2 nuclear emulsion target at kinetic energy of 1 GeV per nucleon. Experimental multiplicity distributions of shower particles, grey particles, black particles and heavily ionization particles are well described by multi-component Erlang distribution of multi-source thermal model. We have observed a linear correlation in multiplicities for the above mentioned particles or fragments. Further experimental studies have shown a saturation phenomenon in shower particle multiplicity with the increase of target fragment multiplicity.

Single-molecule techniques in biophysics: a review of the progress in methods and applications.

PubMed

Miller, Helen; Zhou, Zhaokun; Shepherd, Jack; Wollman, Adam J M; Leake, Mark C

2018-02-01

Single-molecule biophysics has transformed our understanding of biology, but also of the physics of life. More exotic than simple soft matter, biomatter lives far from thermal equilibrium, covering multiple lengths from the nanoscale of single molecules to up to several orders of magnitude higher in cells, tissues and organisms. Biomolecules are often characterized by underlying instability: multiple metastable free energy states exist, separated by levels of just a few multiples of the thermal energy scale k B T, where k B is the Boltzmann constant and T absolute temperature, implying complex inter-conversion kinetics in the relatively hot, wet environment of active biological matter. A key benefit of single-molecule biophysics techniques is their ability to probe heterogeneity of free energy states across a molecular population, too challenging in general for conventional ensemble average approaches. Parallel developments in experimental and computational techniques have catalysed the birth of multiplexed, correlative techniques to tackle previously intractable biological questions. Experimentally, progress has been driven by improvements in sensitivity and speed of detectors, and the stability and efficiency of light sources, probes and microfluidics. We discuss the motivation and requirements for these recent experiments, including the underpinning mathematics. These methods are broadly divided into tools which detect molecules and those which manipulate them. For the former we discuss the progress of super-resolution microscopy, transformative for addressing many longstanding questions in the life sciences, and for the latter we include progress in 'force spectroscopy' techniques that mechanically perturb molecules. We also consider in silico progress of single-molecule computational physics, and how simulation and experimentation may be drawn together to give a more complete understanding. Increasingly, combinatorial techniques are now used, including correlative atomic force microscopy and fluorescence imaging, to probe questions closer to native physiological behaviour. We identify the trade-offs, limitations and applications of these techniques, and discuss exciting new directions.

Single-molecule techniques in biophysics: a review of the progress in methods and applications

NASA Astrophysics Data System (ADS)

Miller, Helen; Zhou, Zhaokun; Shepherd, Jack; Wollman, Adam J. M.; Leake, Mark C.

2018-02-01

Single-molecule biophysics has transformed our understanding of biology, but also of the physics of life. More exotic than simple soft matter, biomatter lives far from thermal equilibrium, covering multiple lengths from the nanoscale of single molecules to up to several orders of magnitude higher in cells, tissues and organisms. Biomolecules are often characterized by underlying instability: multiple metastable free energy states exist, separated by levels of just a few multiples of the thermal energy scale k B T, where k B is the Boltzmann constant and T absolute temperature, implying complex inter-conversion kinetics in the relatively hot, wet environment of active biological matter. A key benefit of single-molecule biophysics techniques is their ability to probe heterogeneity of free energy states across a molecular population, too challenging in general for conventional ensemble average approaches. Parallel developments in experimental and computational techniques have catalysed the birth of multiplexed, correlative techniques to tackle previously intractable biological questions. Experimentally, progress has been driven by improvements in sensitivity and speed of detectors, and the stability and efficiency of light sources, probes and microfluidics. We discuss the motivation and requirements for these recent experiments, including the underpinning mathematics. These methods are broadly divided into tools which detect molecules and those which manipulate them. For the former we discuss the progress of super-resolution microscopy, transformative for addressing many longstanding questions in the life sciences, and for the latter we include progress in ‘force spectroscopy’ techniques that mechanically perturb molecules. We also consider in silico progress of single-molecule computational physics, and how simulation and experimentation may be drawn together to give a more complete understanding. Increasingly, combinatorial techniques are now used, including correlative atomic force microscopy and fluorescence imaging, to probe questions closer to native physiological behaviour. We identify the trade-offs, limitations and applications of these techniques, and discuss exciting new directions.

Detection and estimation of defects in a circular plate using operational deflection shapes

NASA Astrophysics Data System (ADS)

Pai, Perngjin F.; Oh, Yunje; Kim, Byeong-Seok

2002-06-01

This paper investigates dynamic characteristics (mode shapes and natural frequencies) and defect detection of circular plates using a scanning laser vibrometer. Exact dynamic characteristics of a circular aluminum plate having a clamped inner rim and a free outer rim are obtained using two methods; one uses Bessel functions and the other uses a multiple shooting method. An in-house finite element code GESA is also used to analyze the circular plate using the DKT plate element. Numerical results show that some reports in the literature are incorrect and that high-frequency Operational Deflection Shapes (ODSs) are needed in order to locate small defects. Detection of two defects in the circular aluminum plate is experimentally studied using the distributions of RMS velocities under broadband periodic chirp excitations. RMS velocities of ODSs, symmetry breaking of ODSs, splitting of natural frequencies and ODSs, and a Boundary Effect Detection (BED) method. The BED method is non-destructive and model-independent; it processes experimental ODSs to reveal extra local boundary effects caused by defects to reveal locations of defects. Experimental results show that small defects in circular plates can be pinpointed by these approaches. Moreover, a new concept of using the balance of elastic and kinetic energies within a mode cell for detecting defects in two- dimensional structures of irregular shapes is proposed.

A comparison of two methods of teaching. Computer managed instruction and keypad questions versus traditional classroom lecture.

PubMed

Halloran, L

1995-01-01

Computers increasingly are being integrated into nursing education. One method of integration is through computer managed instruction (CMI). Recently, technology has become available that allows the integration of keypad questions into CMI. This brings a new type of interactivity between students and teachers into the classroom. The purpose of this study was to evaluate differences in achievement between a control group taught by traditional classroom lecture (TCL) and an experimental group taught using CMI and keypad questions. Both control and experimental groups consisted of convenience samples of junior nursing students in a baccalaureate program taking a medical/surgical nursing course. Achievement was measured by three instructor-developed multiple choice examinations. Findings demonstrated that although the experimental group demonstrated increasingly higher test scores as the semester progressed, no statistical difference was found in achievement between the two groups. One reason for this may be phenomenon of vampire video. Initially, the method of presentation overshadowed the content. As students became desensitized to the method, they were able to focus and absorb more content. This study suggests that CMI and keypads are a viable teaching option for nursing education. It is equal to TCL in student achievement and provides a new level of interaction in the classroom setting.

The role of chemometrics in single and sequential extraction assays: a review. Part II. Cluster analysis, multiple linear regression, mixture resolution, experimental design and other techniques.

PubMed

Giacomino, Agnese; Abollino, Ornella; Malandrino, Mery; Mentasti, Edoardo

2011-03-04

Single and sequential extraction procedures are used for studying element mobility and availability in solid matrices, like soils, sediments, sludge, and airborne particulate matter. In the first part of this review we reported an overview on these procedures and described the applications of chemometric uni- and bivariate techniques and of multivariate pattern recognition techniques based on variable reduction to the experimental results obtained. The second part of the review deals with the use of chemometrics not only for the visualization and interpretation of data, but also for the investigation of the effects of experimental conditions on the response, the optimization of their values and the calculation of element fractionation. We will describe the principles of the multivariate chemometric techniques considered, the aims for which they were applied and the key findings obtained. The following topics will be critically addressed: pattern recognition by cluster analysis (CA), linear discriminant analysis (LDA) and other less common techniques; modelling by multiple linear regression (MLR); investigation of spatial distribution of variables by geostatistics; calculation of fractionation patterns by a mixture resolution method (Chemometric Identification of Substrates and Element Distributions, CISED); optimization and characterization of extraction procedures by experimental design; other multivariate techniques less commonly applied. Copyright © 2010 Elsevier B.V. All rights reserved.

Retrospective estimation of the electric and magnetic field exposure conditions in in vitro experimental reports reveal considerable potential for uncertainty.

PubMed

Portelli, Lucas A; Falldorf, Karsten; Thuróczy, György; Cuppen, Jan

2018-04-01

Experiments on cell cultures exposed to extremely low frequency (ELF, 3-300 Hz) magnetic fields are often subject to multiple sources of uncertainty associated with specific electric and magnetic field exposure conditions. Here we systemically quantify these uncertainties based on exposure conditions described in a group of bioelectromagnetic experimental reports for a representative sampling of the existing literature. The resulting uncertainties, stemming from insufficient, ambiguous, or erroneous description, design, implementation, or validation of the experimental methods and systems, were often substantial enough to potentially make any successful reproduction of the original experimental conditions difficult or impossible. Without making any assumption about the true biological relevance of ELF electric and magnetic fields, these findings suggest another contributing factor which may add to the overall variability and irreproducibility traditionally associated with experimental results of in vitro exposures to low-level ELF magnetic fields. Bioelectromagnetics. 39:231-243, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

The influence of the design matrix on treatment effect estimates in the quantitative analyses of single-subject experimental design research.

PubMed

Moeyaert, Mariola; Ugille, Maaike; Ferron, John M; Beretvas, S Natasha; Van den Noortgate, Wim

2014-09-01

The quantitative methods for analyzing single-subject experimental data have expanded during the last decade, including the use of regression models to statistically analyze the data, but still a lot of questions remain. One question is how to specify predictors in a regression model to account for the specifics of the design and estimate the effect size of interest. These quantitative effect sizes are used in retrospective analyses and allow synthesis of single-subject experimental study results which is informative for evidence-based decision making, research and theory building, and policy discussions. We discuss different design matrices that can be used for the most common single-subject experimental designs (SSEDs), namely, the multiple-baseline designs, reversal designs, and alternating treatment designs, and provide empirical illustrations. The purpose of this article is to guide single-subject experimental data analysts interested in analyzing and meta-analyzing SSED data. © The Author(s) 2014.

Fatigue Life Prediction Based on Crack Closure and Equivalent Initial Flaw Size

PubMed Central

Wang, Qiang; Zhang, Wei; Jiang, Shan

2015-01-01

Failure analysis and fatigue life prediction are necessary and critical for engineering structural materials. In this paper, a general methodology is proposed to predict fatigue life of smooth and circular-hole specimens, in which the crack closure model and equivalent initial flaw size (EIFS) concept are employed. Different effects of crack closure on small crack growth region and long crack growth region are considered in the proposed method. The EIFS is determined by the fatigue limit and fatigue threshold stress intensity factor △Kth. Fatigue limit is directly obtained from experimental data, and △Kth is calculated by using a back-extrapolation method. Experimental data for smooth and circular-hole specimens in three different alloys (Al2024-T3, Al7075-T6 and Ti-6Al-4V) under multiple stress ratios are used to validate the method. In the validation section, Semi-circular surface crack and quarter-circular corner crack are assumed to be the initial crack shapes for the smooth and circular-hole specimens, respectively. A good agreement is observed between model predictions and experimental data. The detailed analysis and discussion are performed on the proposed model. Some conclusions and future work are given. PMID:28793625

Laser-based pedestrian tracking in outdoor environments by multiple mobile robots.

PubMed

Ozaki, Masataka; Kakimuma, Kei; Hashimoto, Masafumi; Takahashi, Kazuhiko

2012-10-29

This paper presents an outdoors laser-based pedestrian tracking system using a group of mobile robots located near each other. Each robot detects pedestrians from its own laser scan image using an occupancy-grid-based method, and the robot tracks the detected pedestrians via Kalman filtering and global-nearest-neighbor (GNN)-based data association. The tracking data is broadcast to multiple robots through intercommunication and is combined using the covariance intersection (CI) method. For pedestrian tracking, each robot identifies its own posture using real-time-kinematic GPS (RTK-GPS) and laser scan matching. Using our cooperative tracking method, all the robots share the tracking data with each other; hence, individual robots can always recognize pedestrians that are invisible to any other robot. The simulation and experimental results show that cooperating tracking provides the tracking performance better than conventional individual tracking does. Our tracking system functions in a decentralized manner without any central server, and therefore, this provides a degree of scalability and robustness that cannot be achieved by conventional centralized architectures.

e-Bitter: Bitterant Prediction by the Consensus Voting From the Machine-Learning Methods

PubMed Central

Zheng, Suqing; Jiang, Mengying; Zhao, Chengwei; Zhu, Rui; Hu, Zhicheng; Xu, Yong; Lin, Fu

2018-01-01

In-silico bitterant prediction received the considerable attention due to the expensive and laborious experimental-screening of the bitterant. In this work, we collect the fully experimental dataset containing 707 bitterants and 592 non-bitterants, which is distinct from the fully or partially hypothetical non-bitterant dataset used in the previous works. Based on this experimental dataset, we harness the consensus votes from the multiple machine-learning methods (e.g., deep learning etc.) combined with the molecular fingerprint to build the bitter/bitterless classification models with five-fold cross-validation, which are further inspected by the Y-randomization test and applicability domain analysis. One of the best consensus models affords the accuracy, precision, specificity, sensitivity, F1-score, and Matthews correlation coefficient (MCC) of 0.929, 0.918, 0.898, 0.954, 0.936, and 0.856 respectively on our test set. For the automatic prediction of bitterant, a graphic program “e-Bitter” is developed for the convenience of users via the simple mouse click. To our best knowledge, it is for the first time to adopt the consensus model for the bitterant prediction and develop the first free stand-alone software for the experimental food scientist. PMID:29651416

e-Bitter: Bitterant Prediction by the Consensus Voting From the Machine-learning Methods

NASA Astrophysics Data System (ADS)

Zheng, Suqing; Jiang, Mengying; Zhao, Chengwei; Zhu, Rui; Hu, Zhicheng; Xu, Yong; Lin, Fu

2018-03-01

In-silico bitterant prediction received the considerable attention due to the expensive and laborious experimental-screening of the bitterant. In this work, we collect the fully experimental dataset containing 707 bitterants and 592 non-bitterants, which is distinct from the fully or partially hypothetical non-bitterant dataset used in the previous works. Based on this experimental dataset, we harness the consensus votes from the multiple machine-learning methods (e.g., deep learning etc.) combined with the molecular fingerprint to build the bitter/bitterless classification models with five-fold cross-validation, which are further inspected by the Y-randomization test and applicability domain analysis. One of the best consensus models affords the accuracy, precision, specificity, sensitivity, F1-score, and Matthews correlation coefficient (MCC) of 0.929, 0.918, 0.898, 0.954, 0.936, and 0.856 respectively on our test set. For the automatic prediction of bitterant, a graphic program “e-Bitter” is developed for the convenience of users via the simple mouse click. To our best knowledge, it is for the first time to adopt the consensus model for the bitterant prediction and develop the first free stand-alone software for the experimental food scientist.

On the Multilevel Solution Algorithm for Markov Chains

NASA Technical Reports Server (NTRS)

Horton, Graham

1997-01-01

We discuss the recently introduced multilevel algorithm for the steady-state solution of Markov chains. The method is based on an aggregation principle which is well established in the literature and features a multiplicative coarse-level correction. Recursive application of the aggregation principle, which uses an operator-dependent coarsening, yields a multi-level method which has been shown experimentally to give results significantly faster than the typical methods currently in use. When cast as a multigrid-like method, the algorithm is seen to be a Galerkin-Full Approximation Scheme with a solution-dependent prolongation operator. Special properties of this prolongation lead to the cancellation of the computationally intensive terms of the coarse-level equations.

Predicting Human Protein Subcellular Locations by the Ensemble of Multiple Predictors via Protein-Protein Interaction Network with Edge Clustering Coefficients

PubMed Central

Du, Pufeng; Wang, Lusheng

2014-01-01

One of the fundamental tasks in biology is to identify the functions of all proteins to reveal the primary machinery of a cell. Knowledge of the subcellular locations of proteins will provide key hints to reveal their functions and to understand the intricate pathways that regulate biological processes at the cellular level. Protein subcellular location prediction has been extensively studied in the past two decades. A lot of methods have been developed based on protein primary sequences as well as protein-protein interaction network. In this paper, we propose to use the protein-protein interaction network as an infrastructure to integrate existing sequence based predictors. When predicting the subcellular locations of a given protein, not only the protein itself, but also all its interacting partners were considered. Unlike existing methods, our method requires neither the comprehensive knowledge of the protein-protein interaction network nor the experimentally annotated subcellular locations of most proteins in the protein-protein interaction network. Besides, our method can be used as a framework to integrate multiple predictors. Our method achieved 56% on human proteome in absolute-true rate, which is higher than the state-of-the-art methods. PMID:24466278

LC-MS determination of steroidal glycosides from Dioscorea deltoidea Wall cell suspension culture: Optimization of pre-LC-MS procedure parameters by Latin Square design.

PubMed

Sarvin, Boris; Fedorova, Elizaveta; Shpigun, Oleg; Titova, Maria; Nikitin, Mikhail; Kochkin, Dmitry; Rodin, Igor; Stavrianidi, Andrey

2018-03-30

In this paper, the ultrasound assisted extraction method for isolation of steroidal glycosides from D. deltoidea plant cell suspension culture with a subsequent HPLC-MS determination was developed. After the organic solvent was selected via a two-factor experiment the optimization via Latin Square 4 × 4 experimental design was carried out for the following parameters: extraction time, organic solvent concentration in extraction solution and the ratio of solvent to sample. It was also shown that the ultrasound assisted extraction method is not suitable for isolation of steroidal glycosides from the D. deltoidea plant material. The results were double-checked using the multiple successive extraction method and refluxing extraction. Optimal conditions for the extraction of steroidal glycosides by the ultrasound assisted extraction method were: extraction time, 60 min; acetonitrile (water) concentration in extraction solution, 50%; the ratio of solvent to sample, 400 mL/g. Also, the developed method was tested on D. deltoidea cell suspension cultures of different terms and conditions of cultivation. The completeness of the extraction was confirmed using the multiple successive extraction method. Copyright © 2018 Elsevier B.V. All rights reserved.

Wavefront reconstruction for multi-lateral shearing interferometry using difference Zernike polynomials fitting

NASA Astrophysics Data System (ADS)

Liu, Ke; Wang, Jiannian; Wang, Hai; Li, Yanqiu

2018-07-01

For the multi-lateral shearing interferometers (multi-LSIs), the measurement accuracy can be enhanced by estimating the wavefront under test with the multidirectional phase information encoded in the shearing interferogram. Usually the multi-LSIs reconstruct the test wavefront from the phase derivatives in multiple directions using the discrete Fourier transforms (DFT) method, which is only suitable to small shear ratios and relatively sensitive to noise. To improve the accuracy of multi-LSIs, wavefront reconstruction from the multidirectional phase differences using the difference Zernike polynomials fitting (DZPF) method is proposed in this paper. For the DZPF method applied in the quadriwave LSI, difference Zernike polynomials in only two orthogonal shear directions are required to represent the phase differences in multiple shear directions. In this way, the test wavefront can be reconstructed from the phase differences in multiple shear directions using a noise-variance weighted least-squares method with almost no extra computational burden, compared with the usual recovery from the phase differences in two orthogonal directions. Numerical simulation results show that the DZPF method can maintain high reconstruction accuracy in a wider range of shear ratios and has much better anti-noise performance than the DFT method. A null test experiment of the quadriwave LSI has been conducted and the experimental results show that the measurement accuracy of the quadriwave LSI can be improved from 0.0054 λ rms to 0.0029 λ rms (λ = 632.8 nm) by substituting the DFT method with the proposed DZPF method in the wavefront reconstruction process.

Noise-free recovery of optodigital encrypted and multiplexed images.

PubMed

Henao, Rodrigo; Rueda, Edgar; Barrera, John F; Torroba, Roberto

2010-02-01

We present a method that allows storing multiple encrypted data using digital holography and a joint transform correlator architecture with a controllable angle reference wave. In this method, the information is multiplexed by using a key and a different reference wave angle for each object. In the recovering process, the use of different reference wave angles prevents noise produced by the nonrecovered objects from being superimposed on the recovered object; moreover, the position of the recovered object in the exit plane can be fully controlled. We present the theoretical analysis and the experimental results that show the potential and applicability of the method.

A new method of measuring gravitational acceleration in an undergraduate laboratory program

NASA Astrophysics Data System (ADS)

Wang, Qiaochu; Wang, Chang; Xiao, Yunhuan; Schulte, Jurgen; Shi, Qingfan

2018-01-01

This paper presents a high accuracy method to measure gravitational acceleration in an undergraduate laboratory program. The experiment is based on water in a cylindrical vessel rotating about its vertical axis at a constant speed. The water surface forms a paraboloid whose focal length is related to rotational period and gravitational acceleration. This experimental setup avoids classical source errors in determining the local value of gravitational acceleration, so prevalent in the common simple pendulum and inclined plane experiments. The presented method combines multiple physics concepts such as kinematics, classical mechanics and geometric optics, offering the opportunity for lateral as well as project-based learning.

A Selfish Constraint Satisfaction Genetic Algorithms for Planning a Long-Distance Transportation Network

NASA Astrophysics Data System (ADS)

Onoyama, Takashi; Maekawa, Takuya; Kubota, Sen; Tsuruta, Setuso; Komoda, Norihisa

To build a cooperative logistics network covering multiple enterprises, a planning method that can build a long-distance transportation network is required. Many strict constraints are imposed on this type of problem. To solve these strict-constraint problems, a selfish constraint satisfaction genetic algorithm (GA) is proposed. In this GA, each gene of an individual satisfies only its constraint selfishly, disregarding the constraints of other genes in the same individuals. Moreover, a constraint pre-checking method is also applied to improve the GA convergence speed. The experimental result shows the proposed method can obtain an accurate solution in a practical response time.

Investigation of condensed matter by means of elastic thermal-neutron scattering

NASA Astrophysics Data System (ADS)

Abov, Yu. G.; Dzheparov, F. S.; Elyutin, N. O.; Lvov, D. V.; Tyulyusov, A. N.

2016-07-01

The application of elastic thermal-neutron scattering in investigations of condensed matter that were performed at the Institute for Theoretical and Experimental Physics is described. An account of diffraction studies with weakly absorbing crystals, including studies of the anomalous-absorption effect and coherent effects in diffuse scattering, is given. Particular attention is given to exposing the method of multiple small-angle neutron scattering (MSANS). It is shown how information about matter inhomogeneities can be obtained by this method on the basis of Molière's theory. Prospects of the development of this method are outlined, and MSANS theory is formulated for a high concentration of matter inhomogeneities.

Discrimination of Medicine Radix Astragali from Different Geographic Origins Using Multiple Spectroscopies Combined with Data Fusion Methods

NASA Astrophysics Data System (ADS)

Wang, Hai-Yan; Song, Chao; Sha, Min; Liu, Jun; Li, Li-Ping; Zhang, Zheng-Yong

2018-05-01

Raman spectra and ultraviolet-visible absorption spectra of four different geographic origins of Radix Astragali were collected. These data were analyzed using kernel principal component analysis combined with sparse representation classification. The results showed that the recognition rate reached 70.44% using Raman spectra for data input and 90.34% using ultraviolet-visible absorption spectra for data input. A new fusion method based on Raman combined with ultraviolet-visible data was investigated and the recognition rate was increased to 96.43%. The experimental results suggested that the proposed data fusion method effectively improved the utilization rate of the original data.

How hot? Systematic convergence of the replica exchange method using multiple reservoirs.

PubMed

Ruscio, Jory Z; Fawzi, Nicolas L; Head-Gordon, Teresa

2010-02-01

We have devised a systematic approach to converge a replica exchange molecular dynamics simulation by dividing the full temperature range into a series of higher temperature reservoirs and a finite number of lower temperature subreplicas. A defined highest temperature reservoir of equilibrium conformations is used to help converge a lower but still hot temperature subreplica, which in turn serves as the high-temperature reservoir for the next set of lower temperature subreplicas. The process is continued until an optimal temperature reservoir is reached to converge the simulation at the target temperature. This gradual convergence of subreplicas allows for better and faster convergence at the temperature of interest and all intermediate temperatures for thermodynamic analysis, as well as optimizing the use of multiple processors. We illustrate the overall effectiveness of our multiple reservoir replica exchange strategy by comparing sampling and computational efficiency with respect to replica exchange, as well as comparing methods when converging the structural ensemble of the disordered Abeta(21-30) peptide simulated with explicit water by comparing calculated Rotating Overhauser Effect Spectroscopy intensities to experimentally measured values. Copyright 2009 Wiley Periodicals, Inc.

Beyond Group: Multiple Person Tracking via Minimal Topology-Energy-Variation.

PubMed

Gao, Shan; Ye, Qixiang; Xing, Junliang; Kuijper, Arjan; Han, Zhenjun; Jiao, Jianbin; Ji, Xiangyang

2017-12-01

Tracking multiple persons is a challenging task when persons move in groups and occlude each other. Existing group-based methods have extensively investigated how to make group division more accurately in a tracking-by-detection framework; however, few of them quantify the group dynamics from the perspective of targets' spatial topology or consider the group in a dynamic view. Inspired by the sociological properties of pedestrians, we propose a novel socio-topology model with a topology-energy function to factor the group dynamics of moving persons and groups. In this model, minimizing the topology-energy-variance in a two-level energy form is expected to produce smooth topology transitions, stable group tracking, and accurate target association. To search for the strong minimum in energy variation, we design the discrete group-tracklet jump moves embedded in the gradient descent method, which ensures that the moves reduce the energy variation of group and trajectory alternately in the varying topology dimension. Experimental results on both RGB and RGB-D data sets show the superiority of our proposed model for multiple person tracking in crowd scenes.

Biomolecular computers with multiple restriction enzymes.

PubMed

Sakowski, Sebastian; Krasinski, Tadeusz; Waldmajer, Jacek; Sarnik, Joanna; Blasiak, Janusz; Poplawski, Tomasz

2017-01-01

The development of conventional, silicon-based computers has several limitations, including some related to the Heisenberg uncertainty principle and the von Neumann "bottleneck". Biomolecular computers based on DNA and proteins are largely free of these disadvantages and, along with quantum computers, are reasonable alternatives to their conventional counterparts in some applications. The idea of a DNA computer proposed by Ehud Shapiro's group at the Weizmann Institute of Science was developed using one restriction enzyme as hardware and DNA fragments (the transition molecules) as software and input/output signals. This computer represented a two-state two-symbol finite automaton that was subsequently extended by using two restriction enzymes. In this paper, we propose the idea of a multistate biomolecular computer with multiple commercially available restriction enzymes as hardware. Additionally, an algorithmic method for the construction of transition molecules in the DNA computer based on the use of multiple restriction enzymes is presented. We use this method to construct multistate, biomolecular, nondeterministic finite automata with four commercially available restriction enzymes as hardware. We also describe an experimental applicaton of this theoretical model to a biomolecular finite automaton made of four endonucleases.

SOAR: An Architecture for General Intelligence

DTIC Science & Technology

1987-12-01

these tasks, and (3) learn about all aspects of the tasks and its performance on them. Soar has existed since mid 1982 as an experimental software system...intelligence. Soar’s behavior has already been studied over a range of tasks and methods (Figure 1), which sample its intended range, though...in multiple small tasks: Generate and test, AND/OR search, hill climbing ( simple and steepest-ascent), means-ends analysis, operator subgoaling

Disease named entity recognition from biomedical literature using a novel convolutional neural network.

PubMed

Zhao, Zhehuan; Yang, Zhihao; Luo, Ling; Wang, Lei; Zhang, Yin; Lin, Hongfei; Wang, Jian

2017-12-28

Automatic disease named entity recognition (DNER) is of utmost importance for development of more sophisticated BioNLP tools. However, most conventional CRF based DNER systems rely on well-designed features whose selection is labor intensive and time-consuming. Though most deep learning methods can solve NER problems with little feature engineering, they employ additional CRF layer to capture the correlation information between labels in neighborhoods which makes them much complicated. In this paper, we propose a novel multiple label convolutional neural network (MCNN) based disease NER approach. In this approach, instead of the CRF layer, a multiple label strategy (MLS) first introduced by us, is employed. First, the character-level embedding, word-level embedding and lexicon feature embedding are concatenated. Then several convolutional layers are stacked over the concatenated embedding. Finally, MLS strategy is applied to the output layer to capture the correlation information between neighboring labels. As shown by the experimental results, MCNN can achieve the state-of-the-art performance on both NCBI and CDR corpora. The proposed MCNN based disease NER method achieves the state-of-the-art performance with little feature engineering. And the experimental results show the MLS strategy's effectiveness of capturing the correlation information between labels in the neighborhood.

Flexibility, Diversity, and Cooperativity: Pillars of Enzyme Catalysis

PubMed Central

Hammes, Gordon G.; Benkovic, Stephen J.; Hammes-Schiffer, Sharon

2011-01-01

This brief review discusses our current understanding of the molecular basis of enzyme catalysis. A historical development is presented, beginning with steady state kinetics and progressing through modern fast reaction methods, NMR, and single molecule fluorescence techniques. Experimental results are summarized for ribonuclease, aspartate aminotransferase, and especially dihydrofolate reductase (DHFR). Multiple intermediates, multiple conformations, and cooperative conformational changes are shown to be an essential part of virtually all enzyme mechanisms. In the case of DHFR, theoretical investigations have provided detailed information about the movement of atoms within the enzyme-substrate complex as the reaction proceeds along the collective reaction coordinate for hydride transfer. A general mechanism is presented for enzyme catalysis that includes multiple intermediates and a complex, multidimensional standard free energy surface. Protein flexibility, diverse protein conformations, and cooperative conformational changes are important features of this model. PMID:22029278

Uncertainty assessment of PM2.5 contamination mapping using spatiotemporal sequential indicator simulations and multi-temporal monitoring data.

PubMed

Yang, Yong; Christakos, George; Huang, Wei; Lin, Chengda; Fu, Peihong; Mei, Yang

2016-04-12

Because of the rapid economic growth in China, many regions are subjected to severe particulate matter pollution. Thus, improving the methods of determining the spatiotemporal distribution and uncertainty of air pollution can provide considerable benefits when developing risk assessments and environmental policies. The uncertainty assessment methods currently in use include the sequential indicator simulation (SIS) and indicator kriging techniques. However, these methods cannot be employed to assess multi-temporal data. In this work, a spatiotemporal sequential indicator simulation (STSIS) based on a non-separable spatiotemporal semivariogram model was used to assimilate multi-temporal data in the mapping and uncertainty assessment of PM2.5 distributions in a contaminated atmosphere. PM2.5 concentrations recorded throughout 2014 in Shandong Province, China were used as the experimental dataset. Based on the number of STSIS procedures, we assessed various types of mapping uncertainties, including single-location uncertainties over one day and multiple days and multi-location uncertainties over one day and multiple days. A comparison of the STSIS technique with the SIS technique indicate that a better performance was obtained with the STSIS method.

A Novel Method for Reconstructing Broken Contour Lines Extracted from Scanned Topographic Maps

NASA Astrophysics Data System (ADS)

Wang, Feng; Liu, Pingzhi; Yang, Yun; Wei, Haiping; An, Xiaoya

2018-05-01

It is known that after segmentation and morphological operations on scanned topographic maps, gaps occur in contour lines. It is also well known that filling these gaps and reconstruction of contour lines with high accuracy and completeness is not an easy problem. In this paper, a novel method is proposed dedicated in automatic or semiautomatic filling up caps and reconstructing broken contour lines in binary images. The key part of end points' auto-matching and reconnecting is deeply discussed after introducing the procedure of reconstruction, in which some key algorithms and mechanisms are presented and realized, including multiple incremental backing trace to get weighted average direction angle of end points, the max constraint angle control mechanism based on the multiple gradient ranks, combination of weighted Euclidean distance and deviation angle to determine the optimum matching end point, bidirectional parabola control, etc. Lastly, experimental comparisons based on typically samples are complemented between proposed method and the other representative method, the results indicate that the former holds higher accuracy and completeness, better stability and applicability.

Uncertainty assessment of PM2.5 contamination mapping using spatiotemporal sequential indicator simulations and multi-temporal monitoring data

NASA Astrophysics Data System (ADS)

Yang, Yong; Christakos, George; Huang, Wei; Lin, Chengda; Fu, Peihong; Mei, Yang

2016-04-01

Because of the rapid economic growth in China, many regions are subjected to severe particulate matter pollution. Thus, improving the methods of determining the spatiotemporal distribution and uncertainty of air pollution can provide considerable benefits when developing risk assessments and environmental policies. The uncertainty assessment methods currently in use include the sequential indicator simulation (SIS) and indicator kriging techniques. However, these methods cannot be employed to assess multi-temporal data. In this work, a spatiotemporal sequential indicator simulation (STSIS) based on a non-separable spatiotemporal semivariogram model was used to assimilate multi-temporal data in the mapping and uncertainty assessment of PM2.5 distributions in a contaminated atmosphere. PM2.5 concentrations recorded throughout 2014 in Shandong Province, China were used as the experimental dataset. Based on the number of STSIS procedures, we assessed various types of mapping uncertainties, including single-location uncertainties over one day and multiple days and multi-location uncertainties over one day and multiple days. A comparison of the STSIS technique with the SIS technique indicate that a better performance was obtained with the STSIS method.

Advanced analysis techniques for uranium assay

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

Geist, W. H.; Ensslin, Norbert; Carrillo, L. A.

2001-01-01

Uranium has a negligible passive neutron emission rate making its assay practicable only with an active interrogation method. The active interrogation uses external neutron sources to induce fission events in the uranium in order to determine the mass. This technique requires careful calibration with standards that are representative of the items to be assayed. The samples to be measured are not always well represented by the available standards which often leads to large biases. A technique of active multiplicity counting is being developed to reduce some of these assay difficulties. Active multiplicity counting uses the measured doubles and triples countmore » rates to determine the neutron multiplication (f4) and the product of the source-sample coupling ( C ) and the 235U mass (m). Since the 35U mass always appears in the multiplicity equations as the product of Cm, the coupling needs to be determined before the mass can be known. A relationship has been developed that relates the coupling to the neutron multiplication. The relationship is based on both an analytical derivation and also on empirical observations. To determine a scaling constant present in this relationship, known standards must be used. Evaluation of experimental data revealed an improvement over the traditional calibration curve analysis method of fitting the doubles count rate to the 235Um ass. Active multiplicity assay appears to relax the requirement that the calibration standards and unknown items have the same chemical form and geometry.« less

A comparison of methods for teaching receptive labeling to children with autism spectrum disorders: a systematic replication.

PubMed

Grow, Laura L; Kodak, Tiffany; Carr, James E

2014-01-01

Previous research has demonstrated that the conditional-only method (starting with a multiple-stimulus array) is more efficient than the simple-conditional method (progressive incorporation of more stimuli into the array) for teaching receptive labeling to children with autism spectrum disorders (Grow, Carr, Kodak, Jostad, & Kisamore,). The current study systematically replicated the earlier study by comparing the 2 approaches using progressive prompting with 2 boys with autism. The results showed that the conditional-only method was a more efficient and reliable teaching procedure than the simple-conditional method. The results further call into question the practice of teaching simple discriminations to facilitate acquisition of conditional discriminations. © Society for the Experimental Analysis of Behavior.

Peptide-membrane Interactions by Spin-labeling EPR

PubMed Central

Smirnova, Tatyana I.; Smirnov, Alex I.

2016-01-01

Site-directed spin labeling (SDSL) in combination with Electron Paramagnetic Resonance (EPR) spectroscopy is a well-established method that has recently grown in popularity as an experimental technique, with multiple applications in protein and peptide science. The growth is driven by development of labeling strategies, as well as by considerable technical advances in the field, that are paralleled by an increased availability of EPR instrumentation. While the method requires an introduction of a paramagnetic probe at a well-defined position in a peptide sequence, it has been shown to be minimally destructive to the peptide structure and energetics of the peptide-membrane interactions. In this chapter, we describe basic approaches for using SDSL EPR spectroscopy to study interactions between small peptides and biological membranes or membrane mimetic systems. We focus on experimental approaches to quantify peptide-membrane binding, topology of bound peptides, and characterize peptide aggregation. Sample preparation protocols including spin-labeling methods and preparation of membrane mimetic systems are also described. PMID:26477253

Experimental validation of spatial Fourier transform-based multiple sound zone generation with a linear loudspeaker array.

PubMed

Okamoto, Takuma; Sakaguchi, Atsushi

2017-03-01

Generating acoustically bright and dark zones using loudspeakers is gaining attention as one of the most important acoustic communication techniques for such uses as personal sound systems and multilingual guide services. Although most conventional methods are based on numerical solutions, an analytical approach based on the spatial Fourier transform with a linear loudspeaker array has been proposed, and its effectiveness has been compared with conventional acoustic energy difference maximization and presented by computer simulations. To describe the effectiveness of the proposal in actual environments, this paper investigates the experimental validation of the proposed approach with rectangular and Hann windows and compared it with three conventional methods: simple delay-and-sum beamforming, contrast maximization, and least squares-based pressure matching using an actually implemented linear array of 64 loudspeakers in an anechoic chamber. The results of both the computer simulations and the actual experiments show that the proposed approach with a Hann window more accurately controlled the bright and dark zones than the conventional methods.

Optimization of Compton-suppression and summing schemes for the TIGRESS HPGe detector array

NASA Astrophysics Data System (ADS)

Schumaker, M. A.; Svensson, C. E.; Andreoiu, C.; Andreyev, A.; Austin, R. A. E.; Ball, G. C.; Bandyopadhyay, D.; Boston, A. J.; Chakrawarthy, R. S.; Churchman, R.; Drake, T. E.; Finlay, P.; Garrett, P. E.; Grinyer, G. F.; Hackman, G.; Hyland, B.; Jones, B.; Maharaj, R.; Morton, A. C.; Pearson, C. J.; Phillips, A. A.; Sarazin, F.; Scraggs, H. C.; Smith, M. B.; Valiente-Dobón, J. J.; Waddington, J. C.; Watters, L. M.

2007-04-01

Methods of optimizing the performance of an array of Compton-suppressed, segmented HPGe clover detectors have been developed which rely on the physical position sensitivity of both the HPGe crystals and the Compton-suppression shields. These relatively simple analysis procedures promise to improve the precision of experiments with the TRIUMF-ISAC Gamma-Ray Escape-Suppressed Spectrometer (TIGRESS). Suppression schemes will improve the efficiency and peak-to-total ratio of TIGRESS for high γ-ray multiplicity events by taking advantage of the 20-fold segmentation of the Compton-suppression shields, while the use of different summing schemes will improve results for a wide range of experimental conditions. The benefits of these methods are compared for many γ-ray energies and multiplicities using a GEANT4 simulation, and the optimal physical configuration of the TIGRESS array under each set of conditions is determined.

A weighted multiple-relaxation-time lattice Boltzmann method for multiphase flows and its application to partial coalescence cascades

NASA Astrophysics Data System (ADS)

Fakhari, Abbas; Bolster, Diogo; Luo, Li-Shi

2017-07-01

We present a lattice Boltzmann method (LBM) with a weighted multiple-relaxation-time (WMRT) collision model and an adaptive mesh refinement (AMR) algorithm for direct numerical simulation of two-phase flows in three dimensions. The proposed WMRT model enhances the numerical stability of the LBM for immiscible fluids at high density ratios, particularly on the D3Q27 lattice. The effectiveness and efficiency of the proposed WMRT-LBM-AMR is validated through simulations of (a) buoyancy-driven motion and deformation of a gas bubble rising in a viscous liquid; (b) the bag-breakup mechanism of a falling drop; (c) crown splashing of a droplet on a wet surface; and (d) the partial coalescence mechanism of a liquid drop at a liquid-liquid interface. The numerical simulations agree well with available experimental data and theoretical approximations where applicable.

Robust lane detection and tracking using multiple visual cues under stochastic lane shape conditions

NASA Astrophysics Data System (ADS)

Huang, Zhi; Fan, Baozheng; Song, Xiaolin

2018-03-01

As one of the essential components of environment perception techniques for an intelligent vehicle, lane detection is confronted with challenges including robustness against the complicated disturbance and illumination, also adaptability to stochastic lane shapes. To overcome these issues, we proposed a robust lane detection method named classification-generation-growth-based (CGG) operator to the detected lines, whereby the linear lane markings are identified by synergizing multiple visual cues with the a priori knowledge and spatial-temporal information. According to the quality of linear lane fitting, the linear and linear-parabolic models are dynamically switched to describe the actual lane. The Kalman filter with adaptive noise covariance and the region of interests (ROI) tracking are applied to improve the robustness and efficiency. Experiments were conducted with images covering various challenging scenarios. The experimental results evaluate the effectiveness of the presented method for complicated disturbances, illumination, and stochastic lane shapes.

FlyCap: Markerless Motion Capture Using Multiple Autonomous Flying Cameras.

PubMed

Xu, Lan; Liu, Yebin; Cheng, Wei; Guo, Kaiwen; Zhou, Guyue; Dai, Qionghai; Fang, Lu

2017-07-18

Aiming at automatic, convenient and non-instrusive motion capture, this paper presents a new generation markerless motion capture technique, the FlyCap system, to capture surface motions of moving characters using multiple autonomous flying cameras (autonomous unmanned aerial vehicles(UAVs) each integrated with an RGBD video camera). During data capture, three cooperative flying cameras automatically track and follow the moving target who performs large-scale motions in a wide space. We propose a novel non-rigid surface registration method to track and fuse the depth of the three flying cameras for surface motion tracking of the moving target, and simultaneously calculate the pose of each flying camera. We leverage the using of visual-odometry information provided by the UAV platform, and formulate the surface tracking problem in a non-linear objective function that can be linearized and effectively minimized through a Gaussian-Newton method. Quantitative and qualitative experimental results demonstrate the plausible surface and motion reconstruction results.

Multiple Spectral-Spatial Classification Approach for Hyperspectral Data

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Benediktsson, Jon Atli; Chanussot, Jocelyn; Tilton, James C.

2010-01-01

A .new multiple classifier approach for spectral-spatial classification of hyperspectral images is proposed. Several classifiers are used independently to classify an image. For every pixel, if all the classifiers have assigned this pixel to the same class, the pixel is kept as a marker, i.e., a seed of the spatial region, with the corresponding class label. We propose to use spectral-spatial classifiers at the preliminary step of the marker selection procedure, each of them combining the results of a pixel-wise classification and a segmentation map. Different segmentation methods based on dissimilar principles lead to different classification results. Furthermore, a minimum spanning forest is built, where each tree is rooted on a classification -driven marker and forms a region in the spectral -spatial classification: map. Experimental results are presented for two hyperspectral airborne images. The proposed method significantly improves classification accuracies, when compared to previously proposed classification techniques.

Behavior identification based on geotagged photo data set.

PubMed

Liu, Guo-qi; Zhang, Yi-jia; Fu, Ying-mao; Liu, Ying

2014-01-01

The popularity of mobile devices has produced a set of image data with geographic information, time information, and text description information, which is called geotagged photo data set. The division of this kind of data by its behavior and the location not only can identify the user's important location and daily behavior, but also helps users to sort the huge image data. This paper proposes a method to build an index based on multiple classification result, which can divide the data set multiple times and distribute labels to the data to build index according to the estimated probability of classification results in order to accomplish the identification of users' important location and daily behaviors. This paper collects 1400 discrete sets of data as experimental data to verify the method proposed in this paper. The result of the experiment shows that the index and actual tagging results have a high inosculation.

Three-dimensional imaging and photostimulation by remote-focusing and holographic light patterning

PubMed Central

Anselmi, Francesca; Ventalon, Cathie; Bègue, Aurélien; Ogden, David; Emiliani, Valentina

2011-01-01

Access to three-dimensional structures in the brain is fundamental to probe signal processing at multiple levels, from integration of synaptic inputs to network activity mapping. Here, we present an optical method for independent three-dimensional photoactivation and imaging by combination of digital holography with remote-focusing. We experimentally demonstrate compensation of spherical aberration for out-of-focus imaging in a range of at least 300 μm, as well as scanless imaging along oblique planes. We apply this method to perform functional imaging along tilted dendrites of hippocampal pyramidal neurons in brain slices, after photostimulation by multiple spots glutamate uncaging. By bringing extended portions of tilted dendrites simultaneously in-focus, we monitor the spatial extent of dendritic calcium signals, showing a shift from a widespread to a spatially confined response upon blockage of voltage-gated Na+ channels. PMID:22074779

Matching multiple rigid domain decompositions of proteins

PubMed Central

Flynn, Emily; Streinu, Ileana

2017-01-01

We describe efficient methods for consistently coloring and visualizing collections of rigid cluster decompositions obtained from variations of a protein structure, and lay the foundation for more complex setups that may involve different computational and experimental methods. The focus here is on three biological applications: the conceptually simpler problems of visualizing results of dilution and mutation analyses, and the more complex task of matching decompositions of multiple NMR models of the same protein. Implemented into the KINARI web server application, the improved visualization techniques give useful information about protein folding cores, help examining the effect of mutations on protein flexibility and function, and provide insights into the structural motions of PDB proteins solved with solution NMR. These tools have been developed with the goal of improving and validating rigidity analysis as a credible coarse-grained model capturing essential information about a protein’s slow motions near the native state. PMID:28141528

Evaluation of Fear Using Nonintrusive Measurement of Multimodal Sensors

PubMed Central

Choi, Jong-Suk; Bang, Jae Won; Heo, Hwan; Park, Kang Ryoung

2015-01-01

Most previous research into emotion recognition used either a single modality or multiple modalities of physiological signal. However, the former method allows for limited enhancement of accuracy, and the latter has the disadvantages that its performance can be affected by head or body movements. Further, the latter causes inconvenience to the user due to the sensors attached to the body. Among various emotions, the accurate evaluation of fear is crucial in many applications, such as criminal psychology, intelligent surveillance systems and the objective evaluation of horror movies. Therefore, we propose a new method for evaluating fear based on nonintrusive measurements obtained using multiple sensors. Experimental results based on the t-test, the effect size and the sum of all of the correlation values with other modalities showed that facial temperature and subjective evaluation are more reliable than electroencephalogram (EEG) and eye blinking rate for the evaluation of fear. PMID:26205268

On the nonlinear dynamics of trolling-mode AFM: Analytical solution using multiple time scales method

NASA Astrophysics Data System (ADS)

Sajjadi, Mohammadreza; Pishkenari, Hossein Nejat; Vossoughi, Gholamreza

2018-06-01

Trolling mode atomic force microscopy (TR-AFM) has resolved many imaging problems by a considerable reduction of the liquid-resonator interaction forces in liquid environments. The present study develops a nonlinear model of the meniscus force exerted to the nanoneedle of TR-AFM and presents an analytical solution to the distributed-parameter model of TR-AFM resonator utilizing multiple time scales (MTS) method. Based on the developed analytical solution, the frequency-response curves of the resonator operation in air and liquid (for different penetration length of the nanoneedle) are obtained. The closed-form analytical solution and the frequency-response curves are validated by the comparison with both the finite element solution of the main partial differential equations and the experimental observations. The effect of excitation angle of the resonator on horizontal oscillation of the probe tip and the effect of different parameters on the frequency-response of the system are investigated.

Game theoretic wireless resource allocation for H.264 MGS video transmission over cognitive radio networks

NASA Astrophysics Data System (ADS)

Fragkoulis, Alexandros; Kondi, Lisimachos P.; Parsopoulos, Konstantinos E.

2015-03-01

We propose a method for the fair and efficient allocation of wireless resources over a cognitive radio system network to transmit multiple scalable video streams to multiple users. The method exploits the dynamic architecture of the Scalable Video Coding extension of the H.264 standard, along with the diversity that OFDMA networks provide. We use a game-theoretic Nash Bargaining Solution (NBS) framework to ensure that each user receives the minimum video quality requirements, while maintaining fairness over the cognitive radio system. An optimization problem is formulated, where the objective is the maximization of the Nash product while minimizing the waste of resources. The problem is solved by using a Swarm Intelligence optimizer, namely Particle Swarm Optimization. Due to the high dimensionality of the problem, we also introduce a dimension-reduction technique. Our experimental results demonstrate the fairness imposed by the employed NBS framework.

Development of a chromatographic method with multi-criteria decision making design for simultaneous determination of nifedipine and atenolol in content uniformity testing.

PubMed

Ahmed, Sameh; Alqurshi, Abdulmalik; Mohamed, Abdel-Maaboud Ismail

2018-07-01

A new robust and reliable high-performance liquid chromatography (HPLC) method with multi-criteria decision making (MCDM) approach was developed to allow simultaneous quantification of atenolol (ATN) and nifedipine (NFD) in content uniformity testing. Felodipine (FLD) was used as an internal standard (I.S.) in this study. A novel marriage between a new interactive response optimizer and a HPLC method was suggested for multiple response optimizations of target responses. An interactive response optimizer was used as a decision and prediction tool for the optimal settings of target responses, according to specified criteria, based on Derringer's desirability. Four independent variables were considered in this study: Acetonitrile%, buffer pH and concentration along with column temperature. Eight responses were optimized: retention times of ATN, NFD, and FLD, resolutions between ATN/NFD and NFD/FLD, and plate numbers for ATN, NFD, and FLD. Multiple regression analysis was applied in order to scan the influences of the most significant variables for the regression models. The experimental design was set to give minimum retention times, maximum resolution and plate numbers. The interactive response optimizer allowed prediction of optimum conditions according to these criteria with a good composite desirability value of 0.98156. The developed method was validated according to the International Conference on Harmonization (ICH) guidelines with the aid of the experimental design. The developed MCDM-HPLC method showed superior robustness and resolution in short analysis time allowing successful simultaneous content uniformity testing of ATN and NFD in marketed capsules. The current work presents an interactive response optimizer as an efficient platform to optimize, predict responses, and validate HPLC methodology with tolerable design space for assay in quality control laboratories. Copyright © 2018 Elsevier B.V. All rights reserved.

A global parallel model based design of experiments method to minimize model output uncertainty.

PubMed

Bazil, Jason N; Buzzard, Gregory T; Rundell, Ann E

2012-03-01

Model-based experiment design specifies the data to be collected that will most effectively characterize the biological system under study. Existing model-based design of experiment algorithms have primarily relied on Fisher Information Matrix-based methods to choose the best experiment in a sequential manner. However, these are largely local methods that require an initial estimate of the parameter values, which are often highly uncertain, particularly when data is limited. In this paper, we provide an approach to specify an informative sequence of multiple design points (parallel design) that will constrain the dynamical uncertainty of the biological system responses to within experimentally detectable limits as specified by the estimated experimental noise. The method is based upon computationally efficient sparse grids and requires only a bounded uncertain parameter space; it does not rely upon initial parameter estimates. The design sequence emerges through the use of scenario trees with experimental design points chosen to minimize the uncertainty in the predicted dynamics of the measurable responses of the system. The algorithm was illustrated herein using a T cell activation model for three problems that ranged in dimension from 2D to 19D. The results demonstrate that it is possible to extract useful information from a mathematical model where traditional model-based design of experiments approaches most certainly fail. The experiments designed via this method fully constrain the model output dynamics to within experimentally resolvable limits. The method is effective for highly uncertain biological systems characterized by deterministic mathematical models with limited data sets. Also, it is highly modular and can be modified to include a variety of methodologies such as input design and model discrimination.

Impact of a multiple-micronutrient food supplement on the nutritional status of schoolchildren.

PubMed

Vinod Kumar, Malavika; Rajagopalan, S

2006-09-01

. Multiple-micronutrient deficiencies exist in many developing nations. A system to deliver multiple micronutrients effectively would be of value in these countries. . To evaluate the delivery of multiple micronutrients through the food route. The goal was to test the stability of the supplement during cooking and storage and then to test its bioefficacy and bioavailability in residential schoolchildren 5 to 15 years of age. A pre- and post-test design was used to study children 5 to 15 years of age, with an experimental and a control group. The experimental group (n=211) consisted of children from two residential schools, and the control group (n=202) consisted of children from three residential schools. The experimental group received a micronutrient supplement containing vitamin A, vitamin B2, vitamin B6 vitamin B12, folic acid, niacin, calcium pantothenate, vitamin C, vitamin E, iron, lysine, and calcium daily for 9 months. There was no nutritional intervention in the control group. Children in the experimental and control groups were matched by socioeconomic status, age, and eating habits at baseline. All of the children in the experimental and control schools were dewormed at baseline, after 4 months, and at the endpoint. Biochemical measurements (hemoglobin, serum vitamin A, serum vitamin E, serum vitamin B12, and serum folic acid) were measured at baseline, after 4 months, and at the endpoint (after 9 months). The heights and weights of the children were also measured at baseline and endpoint. Serum vitamins A and E were measured in a subsample of 50% and vitamin B12 and serum folic acid measured in a subsample of 25% of the children. In the experimental group, the mean gains in hemoglobin, serum vitamin A, serum vitamin E, serum vitamin B12, and serum folic acid over 9 months were 0.393 g/dL, 6.0375 microg/dL, 1037.45 microg/dL, 687.604 pg/mL, and 1.864 ng/mL, respectively. In the control group, the mean losses in hemoglobin and serum vitamin A over 9 months were 0.9556 g/dL and 10.0641 microg/dL, respectively, and the mean gains in serum vitamin E, vitamin B12, and folic acid were 903.52 microg/dL, 233.283 pg/mL, and 0.0279 ng/mL. The mean gain in all biochemical measurements was significantly higher (p < .05) in the experimental group than in the control group. Vitamin A, vitamin E, vitamin B12, folic acid, and iron are bioavailable from the multiple-micronutrient food supplement used in this study. This method of micronutrient delivery has been beneficial. We believe the study intervention was beneficial because of small doses of the micronutrients added but delivered many times through meals throughout the day, over a period of 9 months.

A Compound Fault Diagnosis for Rolling Bearings Method Based on Blind Source Separation and Ensemble Empirical Mode Decomposition

PubMed Central

Wang, Huaqing; Li, Ruitong; Tang, Gang; Yuan, Hongfang; Zhao, Qingliang; Cao, Xi

2014-01-01

A Compound fault signal usually contains multiple characteristic signals and strong confusion noise, which makes it difficult to separate week fault signals from them through conventional ways, such as FFT-based envelope detection, wavelet transform or empirical mode decomposition individually. In order to improve the compound faults diagnose of rolling bearings via signals’ separation, the present paper proposes a new method to identify compound faults from measured mixed-signals, which is based on ensemble empirical mode decomposition (EEMD) method and independent component analysis (ICA) technique. With the approach, a vibration signal is firstly decomposed into intrinsic mode functions (IMF) by EEMD method to obtain multichannel signals. Then, according to a cross correlation criterion, the corresponding IMF is selected as the input matrix of ICA. Finally, the compound faults can be separated effectively by executing ICA method, which makes the fault features more easily extracted and more clearly identified. Experimental results validate the effectiveness of the proposed method in compound fault separating, which works not only for the outer race defect, but also for the rollers defect and the unbalance fault of the experimental system. PMID:25289644

Evaluating Composite Sampling Methods of Bacillus Spores at Low Concentrations

PubMed Central

Hess, Becky M.; Amidan, Brett G.; Anderson, Kevin K.; Hutchison, Janine R.

2016-01-01

Restoring all facility operations after the 2001 Amerithrax attacks took years to complete, highlighting the need to reduce remediation time. Some of the most time intensive tasks were environmental sampling and sample analyses. Composite sampling allows disparate samples to be combined, with only a single analysis needed, making it a promising method to reduce response times. We developed a statistical experimental design to test three different composite sampling methods: 1) single medium single pass composite (SM-SPC): a single cellulose sponge samples multiple coupons with a single pass across each coupon; 2) single medium multi-pass composite: a single cellulose sponge samples multiple coupons with multiple passes across each coupon (SM-MPC); and 3) multi-medium post-sample composite (MM-MPC): a single cellulose sponge samples a single surface, and then multiple sponges are combined during sample extraction. Five spore concentrations of Bacillus atrophaeus Nakamura spores were tested; concentrations ranged from 5 to 100 CFU/coupon (0.00775 to 0.155 CFU/cm2). Study variables included four clean surface materials (stainless steel, vinyl tile, ceramic tile, and painted dry wallboard) and three grime coated/dirty materials (stainless steel, vinyl tile, and ceramic tile). Analysis of variance for the clean study showed two significant factors: composite method (p< 0.0001) and coupon material (p = 0.0006). Recovery efficiency (RE) was higher overall using the MM-MPC method compared to the SM-SPC and SM-MPC methods. RE with the MM-MPC method for concentrations tested (10 to 100 CFU/coupon) was similar for ceramic tile, dry wall, and stainless steel for clean materials. RE was lowest for vinyl tile with both composite methods. Statistical tests for the dirty study showed RE was significantly higher for vinyl and stainless steel materials, but lower for ceramic tile. These results suggest post-sample compositing can be used to reduce sample analysis time when responding to a Bacillus anthracis contamination event of clean or dirty surfaces. PMID:27736999

Evaluating Composite Sampling Methods of Bacillus Spores at Low Concentrations.

PubMed

Hess, Becky M; Amidan, Brett G; Anderson, Kevin K; Hutchison, Janine R

2016-01-01

Restoring all facility operations after the 2001 Amerithrax attacks took years to complete, highlighting the need to reduce remediation time. Some of the most time intensive tasks were environmental sampling and sample analyses. Composite sampling allows disparate samples to be combined, with only a single analysis needed, making it a promising method to reduce response times. We developed a statistical experimental design to test three different composite sampling methods: 1) single medium single pass composite (SM-SPC): a single cellulose sponge samples multiple coupons with a single pass across each coupon; 2) single medium multi-pass composite: a single cellulose sponge samples multiple coupons with multiple passes across each coupon (SM-MPC); and 3) multi-medium post-sample composite (MM-MPC): a single cellulose sponge samples a single surface, and then multiple sponges are combined during sample extraction. Five spore concentrations of Bacillus atrophaeus Nakamura spores were tested; concentrations ranged from 5 to 100 CFU/coupon (0.00775 to 0.155 CFU/cm2). Study variables included four clean surface materials (stainless steel, vinyl tile, ceramic tile, and painted dry wallboard) and three grime coated/dirty materials (stainless steel, vinyl tile, and ceramic tile). Analysis of variance for the clean study showed two significant factors: composite method (p< 0.0001) and coupon material (p = 0.0006). Recovery efficiency (RE) was higher overall using the MM-MPC method compared to the SM-SPC and SM-MPC methods. RE with the MM-MPC method for concentrations tested (10 to 100 CFU/coupon) was similar for ceramic tile, dry wall, and stainless steel for clean materials. RE was lowest for vinyl tile with both composite methods. Statistical tests for the dirty study showed RE was significantly higher for vinyl and stainless steel materials, but lower for ceramic tile. These results suggest post-sample compositing can be used to reduce sample analysis time when responding to a Bacillus anthracis contamination event of clean or dirty surfaces.

Layered clustering multi-fault diagnosis for hydraulic piston pump

NASA Astrophysics Data System (ADS)

Du, Jun; Wang, Shaoping; Zhang, Haiyan

2013-04-01

Efficient diagnosis is very important for improving reliability and performance of aircraft hydraulic piston pump, and it is one of the key technologies in prognostic and health management system. In practice, due to harsh working environment and heavy working loads, multiple faults of an aircraft hydraulic pump may occur simultaneously after long time operations. However, most existing diagnosis methods can only distinguish pump faults that occur individually. Therefore, new method needs to be developed to realize effective diagnosis of simultaneous multiple faults on aircraft hydraulic pump. In this paper, a new method based on the layered clustering algorithm is proposed to diagnose multiple faults of an aircraft hydraulic pump that occur simultaneously. The intensive failure mechanism analyses of the five main types of faults are carried out, and based on these analyses the optimal combination and layout of diagnostic sensors is attained. The three layered diagnosis reasoning engine is designed according to the faults' risk priority number and the characteristics of different fault feature extraction methods. The most serious failures are first distinguished with the individual signal processing. To the desultory faults, i.e., swash plate eccentricity and incremental clearance increases between piston and slipper, the clustering diagnosis algorithm based on the statistical average relative power difference (ARPD) is proposed. By effectively enhancing the fault features of these two faults, the ARPDs calculated from vibration signals are employed to complete the hypothesis testing. The ARPDs of the different faults follow different probability distributions. Compared with the classical fast Fourier transform-based spectrum diagnosis method, the experimental results demonstrate that the proposed algorithm can diagnose the multiple faults, which occur synchronously, with higher precision and reliability.

A facility for investigation of multiple hadrons at cosmic-ray energies

NASA Technical Reports Server (NTRS)

Valtonen, E.; Torsti, J. J.; Arvela, H.; Lumme, M.; Nieminen, M.; Peltonen, J.; Vainikka, E.

1985-01-01

An experimental arrangement for studying multiple hadrons produced in high-energy hadron-nucleus interactions is under construction at the university of Turku. The method of investigation is based on the detection of hadrons arriving simultaneously at sea level over an area of a few square meters. The apparatus consists of a hadron spectrometer with position-sensitive detectors in connection with a small air shower array. The position resolution using streamer tube detectors will be about 10 mm. Energy spectra of hadrons or groups of simultaneous hadrons produced at primary energies below 10 to the 16th power eV can be measured in the energy range 1 to 2000 GeV.

An efficient method to transcription factor binding sites imputation via simultaneous completion of multiple matrices with positional consistency.

PubMed

Guo, Wei-Li; Huang, De-Shuang

2017-08-22

Transcription factors (TFs) are DNA-binding proteins that have a central role in regulating gene expression. Identification of DNA-binding sites of TFs is a key task in understanding transcriptional regulation, cellular processes and disease. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) enables genome-wide identification of in vivo TF binding sites. However, it is still difficult to map every TF in every cell line owing to cost and biological material availability, which poses an enormous obstacle for integrated analysis of gene regulation. To address this problem, we propose a novel computational approach, TFBSImpute, for predicting additional TF binding profiles by leveraging information from available ChIP-seq TF binding data. TFBSImpute fuses the dataset to a 3-mode tensor and imputes missing TF binding signals via simultaneous completion of multiple TF binding matrices with positional consistency. We show that signals predicted by our method achieve overall similarity with experimental data and that TFBSImpute significantly outperforms baseline approaches, by assessing the performance of imputation methods against observed ChIP-seq TF binding profiles. Besides, motif analysis shows that TFBSImpute preforms better in capturing binding motifs enriched in observed data compared with baselines, indicating that the higher performance of TFBSImpute is not simply due to averaging related samples. We anticipate that our approach will constitute a useful complement to experimental mapping of TF binding, which is beneficial for further study of regulation mechanisms and disease.

Using "Omics" and Integrated Multi-Omics Approaches to Guide Probiotic Selection to Mitigate Chytridiomycosis and Other Emerging Infectious Diseases.

PubMed

Rebollar, Eria A; Antwis, Rachael E; Becker, Matthew H; Belden, Lisa K; Bletz, Molly C; Brucker, Robert M; Harrison, Xavier A; Hughey, Myra C; Kueneman, Jordan G; Loudon, Andrew H; McKenzie, Valerie; Medina, Daniel; Minbiole, Kevin P C; Rollins-Smith, Louise A; Walke, Jenifer B; Weiss, Sophie; Woodhams, Douglas C; Harris, Reid N

2016-01-01

Emerging infectious diseases in wildlife are responsible for massive population declines. In amphibians, chytridiomycosis caused by Batrachochytrium dendrobatidis, Bd, has severely affected many amphibian populations and species around the world. One promising management strategy is probiotic bioaugmentation of antifungal bacteria on amphibian skin. In vivo experimental trials using bioaugmentation strategies have had mixed results, and therefore a more informed strategy is needed to select successful probiotic candidates. Metagenomic, transcriptomic, and metabolomic methods, colloquially called "omics," are approaches that can better inform probiotic selection and optimize selection protocols. The integration of multiple omic data using bioinformatic and statistical tools and in silico models that link bacterial community structure with bacterial defensive function can allow the identification of species involved in pathogen inhibition. We recommend using 16S rRNA gene amplicon sequencing and methods such as indicator species analysis, the Kolmogorov-Smirnov Measure, and co-occurrence networks to identify bacteria that are associated with pathogen resistance in field surveys and experimental trials. In addition to 16S amplicon sequencing, we recommend approaches that give insight into symbiont function such as shotgun metagenomics, metatranscriptomics, or metabolomics to maximize the probability of finding effective probiotic candidates, which can then be isolated in culture and tested in persistence and clinical trials. An effective mitigation strategy to ameliorate chytridiomycosis and other emerging infectious diseases is necessary; the advancement of omic methods and the integration of multiple omic data provide a promising avenue toward conservation of imperiled species.

Simulation studies of the fidelity of biomolecular structure ensemble recreation

NASA Astrophysics Data System (ADS)

Lätzer, Joachim; Eastwood, Michael P.; Wolynes, Peter G.

2006-12-01

We examine the ability of Bayesian methods to recreate structural ensembles for partially folded molecules from averaged data. Specifically we test the ability of various algorithms to recreate different transition state ensembles for folding proteins using a multiple replica simulation algorithm using input from "gold standard" reference ensembles that were first generated with a Gō-like Hamiltonian having nonpairwise additive terms. A set of low resolution data, which function as the "experimental" ϕ values, were first constructed from this reference ensemble. The resulting ϕ values were then treated as one would treat laboratory experimental data and were used as input in the replica reconstruction algorithm. The resulting ensembles of structures obtained by the replica algorithm were compared to the gold standard reference ensemble, from which those "data" were, in fact, obtained. It is found that for a unimodal transition state ensemble with a low barrier, the multiple replica algorithm does recreate the reference ensemble fairly successfully when no experimental error is assumed. The Kolmogorov-Smirnov test as well as principal component analysis show that the overlap of the recovered and reference ensembles is significantly enhanced when multiple replicas are used. Reduction of the multiple replica ensembles by clustering successfully yields subensembles with close similarity to the reference ensembles. On the other hand, for a high barrier transition state with two distinct transition state ensembles, the single replica algorithm only samples a few structures of one of the reference ensemble basins. This is due to the fact that the ϕ values are intrinsically ensemble averaged quantities. The replica algorithm with multiple copies does sample both reference ensemble basins. In contrast to the single replica case, the multiple replicas are constrained to reproduce the average ϕ values, but allow fluctuations in ϕ for each individual copy. These fluctuations facilitate a more faithful sampling of the reference ensemble basins. Finally, we test how robustly the reconstruction algorithm can function by introducing errors in ϕ comparable in magnitude to those suggested by some authors. In this circumstance we observe that the chances of ensemble recovery with the replica algorithm are poor using a single replica, but are improved when multiple copies are used. A multimodal transition state ensemble, however, turns out to be more sensitive to large errors in ϕ (if appropriately gauged) and attempts at successful recreation of the reference ensemble with simple replica algorithms can fall short.

Experimental Design for Stochastic Models of Nonlinear Signaling Pathways Using an Interval-Wise Linear Noise Approximation and State Estimation

PubMed Central

Zimmer, Christoph

2016-01-01

Background Computational modeling is a key technique for analyzing models in systems biology. There are well established methods for the estimation of the kinetic parameters in models of ordinary differential equations (ODE). Experimental design techniques aim at devising experiments that maximize the information encoded in the data. For ODE models there are well established approaches for experimental design and even software tools. However, data from single cell experiments on signaling pathways in systems biology often shows intrinsic stochastic effects prompting the development of specialized methods. While simulation methods have been developed for decades and parameter estimation has been targeted for the last years, only very few articles focus on experimental design for stochastic models. Methods The Fisher information matrix is the central measure for experimental design as it evaluates the information an experiment provides for parameter estimation. This article suggest an approach to calculate a Fisher information matrix for models containing intrinsic stochasticity and high nonlinearity. The approach makes use of a recently suggested multiple shooting for stochastic systems (MSS) objective function. The Fisher information matrix is calculated by evaluating pseudo data with the MSS technique. Results The performance of the approach is evaluated with simulation studies on an Immigration-Death, a Lotka-Volterra, and a Calcium oscillation model. The Calcium oscillation model is a particularly appropriate case study as it contains the challenges inherent to signaling pathways: high nonlinearity, intrinsic stochasticity, a qualitatively different behavior from an ODE solution, and partial observability. The computational speed of the MSS approach for the Fisher information matrix allows for an application in realistic size models. PMID:27583802

Construction of multi-scale consistent brain networks: methods and applications.

PubMed

Ge, Bao; Tian, Yin; Hu, Xintao; Chen, Hanbo; Zhu, Dajiang; Zhang, Tuo; Han, Junwei; Guo, Lei; Liu, Tianming

2015-01-01

Mapping human brain networks provides a basis for studying brain function and dysfunction, and thus has gained significant interest in recent years. However, modeling human brain networks still faces several challenges including constructing networks at multiple spatial scales and finding common corresponding networks across individuals. As a consequence, many previous methods were designed for a single resolution or scale of brain network, though the brain networks are multi-scale in nature. To address this problem, this paper presents a novel approach to constructing multi-scale common structural brain networks from DTI data via an improved multi-scale spectral clustering applied on our recently developed and validated DICCCOLs (Dense Individualized and Common Connectivity-based Cortical Landmarks). Since the DICCCOL landmarks possess intrinsic structural correspondences across individuals and populations, we employed the multi-scale spectral clustering algorithm to group the DICCCOL landmarks and their connections into sub-networks, meanwhile preserving the intrinsically-established correspondences across multiple scales. Experimental results demonstrated that the proposed method can generate multi-scale consistent and common structural brain networks across subjects, and its reproducibility has been verified by multiple independent datasets. As an application, these multi-scale networks were used to guide the clustering of multi-scale fiber bundles and to compare the fiber integrity in schizophrenia and healthy controls. In general, our methods offer a novel and effective framework for brain network modeling and tract-based analysis of DTI data.

PPII propensity of multiple-guest amino acids in a proline-rich environment.

PubMed

Moradi, Mahmoud; Babin, Volodymyr; Sagui, Celeste; Roland, Christopher

2011-07-07

There has been considerable debate about the intrinsic PPII propensity of amino acid residues in denatured polypeptides. Experimentally, this scale is based on the behavior of guest amino acid residues placed in the middle of proline-based hosts. We have used classical molecular dynamics simulations combined with replica-exchange methods to carry out a comprehensive analysis of the conformational equilibria of proline-based host oligopeptides with multiple guest amino acids including alanine, glutamine, valine, and asparagine. The tracked structural characteristics include the secondary structural motifs based on the Ramachandran angles and the cis/trans isomerization of the prolyl bonds. In agreement with our recent study of single amino acid guests, we did not observe an intrinsic PPII propensity in any of the guest amino acids in a multiple-guest setting. Instead, the experimental results can be explained in terms of (i) the steric restrictions imposed on the C-terminal guest amino acid that is immediately followed by a proline residue and (ii) an increase in the trans content of the prolyl bonds due to the presence of guest residues. In terms of the latter, we found that the more guests added to the system, the larger the increase in the trans content of the prolyl bonds, which results in an effective increase in the PPII content of the peptide.

A Quantitative Review of Ethnic Group Differences in Experimental Pain Response: Do Biology, Psychology and Culture Matter?

PubMed Central

Riley, Joseph L.; Williams, Ameenah K.K.; Fillingim, Roger B.

2012-01-01

Objective Pain is a subjectively complex and universal experience. We examine research investigating ethnic group differences in experimental pain response, and factors contributing to group differences. Method We conducted a systematic literature review and analysis of studies using experimental pain stimuli to assess pain sensitivity across multiple ethnic groups. Our search covered the period from 1944-2011, and utilized the PUBMED bibliographic database; a reference source containing over 17 million citations. We calculated effect sizes, identified ethnic/racial group categories, pain stimuli and measures, and examined findings regarding biopsychosociocultural factors contributing to ethnic/racial group differences. Results We found 472 studies investigating ethnic group differences and pain. Twenty-six of these met our review inclusion criteria of investigating ethnic group differences in experimental pain. The majority of studies included comparisons between African Americans (AA) and non-Hispanic Whites (NHW). There were consistently moderate to large effect sizes for pain tolerance across multiple stimulus modalities; African Americans demonstrated lower pain tolerance. For pain threshold, findings were generally in the same direction, but effect sizes were small to moderate across ethnic groups. Limited data were available for suprathreshold pain ratings. A subset of studies comparing NHW and other ethnic groups showed a variable range of effect sizes for pain threshold and tolerance. Conclusion There are potentially important ethnic/racial group differences in experimental pain perception. Elucidating ethnic group differences, has translational merit for culturally-competent clinical care and for addressing and reducing pain treatment disparities among ethnically/racially diverse groups. PMID:22390201

Neural data science: accelerating the experiment-analysis-theory cycle in large-scale neuroscience.

PubMed

Paninski, L; Cunningham, J P

2018-06-01

Modern large-scale multineuronal recording methodologies, including multielectrode arrays, calcium imaging, and optogenetic techniques, produce single-neuron resolution data of a magnitude and precision that were the realm of science fiction twenty years ago. The major bottlenecks in systems and circuit neuroscience no longer lie in simply collecting data from large neural populations, but also in understanding this data: developing novel scientific questions, with corresponding analysis techniques and experimental designs to fully harness these new capabilities and meaningfully interrogate these questions. Advances in methods for signal processing, network analysis, dimensionality reduction, and optimal control-developed in lockstep with advances in experimental neurotechnology-promise major breakthroughs in multiple fundamental neuroscience problems. These trends are clear in a broad array of subfields of modern neuroscience; this review focuses on recent advances in methods for analyzing neural time-series data with single-neuronal precision. Copyright © 2018 Elsevier Ltd. All rights reserved.

Vibrational Spectroscopy of Fluoroformate, FCO2-, Trapped in Helium Nanodroplets.

PubMed

Thomas, Daniel A; Mucha, Eike; Gewinner, Sandy; Schöllkopf, Wieland; Meijer, Gerard; von Helden, Gert

2018-05-03

Fluoroformate, also known as carbonofluoridate, is an intriguing molecule readily formed by the reductive derivatization of carbon dioxide. In spite of its well-known stability, a detailed structural characterization of the isolated anion has yet to be reported. Presented in this work is the vibrational spectrum of fluoroformate obtained by infrared action spectroscopy of ions trapped in helium nanodroplets, the first application of this technique to a molecular anion. The experimental method yields narrow spectral lines, providing experimental constraints on the structure that can be accurately reproduced using high-level ab initio methods. In addition, two notable Fermi resonances between a fundamental and combination band are observed. The electrostatic potential map of fluoroformate reveals substantial charge density on fluorine as well as on the oxygen atoms, suggesting multiple sites for interaction with hydrogen bond donors and electrophiles, which may in turn lead to intriguing solvation structures and reaction pathways.

Enhanced ICP for the Registration of Large-Scale 3D Environment Models: An Experimental Study

PubMed Central

Han, Jianda; Yin, Peng; He, Yuqing; Gu, Feng

2016-01-01

One of the main applications of mobile robots is the large-scale perception of the outdoor environment. One of the main challenges of this application is fusing environmental data obtained by multiple robots, especially heterogeneous robots. This paper proposes an enhanced iterative closest point (ICP) method for the fast and accurate registration of 3D environmental models. First, a hierarchical searching scheme is combined with the octree-based ICP algorithm. Second, an early-warning mechanism is used to perceive the local minimum problem. Third, a heuristic escape scheme based on sampled potential transformation vectors is used to avoid local minima and achieve optimal registration. Experiments involving one unmanned aerial vehicle and one unmanned surface vehicle were conducted to verify the proposed technique. The experimental results were compared with those of normal ICP registration algorithms to demonstrate the superior performance of the proposed method. PMID:26891298

Solid, liquid, and interfacial properties of TiAl alloys: parameterization of a new modified embedded atom method model

NASA Astrophysics Data System (ADS)

Sun, Shoutian; Ramu Ramachandran, Bala; Wick, Collin D.

2018-02-01

New interatomic potentials for pure Ti and Al, and binary TiAl were developed utilizing the second nearest neighbour modified embedded-atom method (MEAM) formalism. The potentials were parameterized to reproduce multiple properties spanning bulk solids, solid surfaces, solid/liquid phase changes, and liquid interfacial properties. This was carried out using a newly developed optimization procedure that combined the simple minimization of a fitness function with a genetic algorithm to efficiently span the parameter space. The resulting MEAM potentials gave good agreement with experimental and DFT solid and liquid properties, and reproduced the melting points for Ti, Al, and TiAl. However, the surface tensions from the model consistently underestimated experimental values. Liquid TiAl’s surface was found to be mostly covered with Al atoms, showing that Al has a significant propensity for the liquid/air interface.

Solid, liquid, and interfacial properties of TiAl alloys: parameterization of a new modified embedded atom method model.

PubMed

Sun, Shoutian; Ramachandran, Bala Ramu; Wick, Collin D

2018-02-21

New interatomic potentials for pure Ti and Al, and binary TiAl were developed utilizing the second nearest neighbour modified embedded-atom method (MEAM) formalism. The potentials were parameterized to reproduce multiple properties spanning bulk solids, solid surfaces, solid/liquid phase changes, and liquid interfacial properties. This was carried out using a newly developed optimization procedure that combined the simple minimization of a fitness function with a genetic algorithm to efficiently span the parameter space. The resulting MEAM potentials gave good agreement with experimental and DFT solid and liquid properties, and reproduced the melting points for Ti, Al, and TiAl. However, the surface tensions from the model consistently underestimated experimental values. Liquid TiAl's surface was found to be mostly covered with Al atoms, showing that Al has a significant propensity for the liquid/air interface.

Protein Sectors: Statistical Coupling Analysis versus Conservation

PubMed Central

Teşileanu, Tiberiu; Colwell, Lucy J.; Leibler, Stanislas

2015-01-01

Statistical coupling analysis (SCA) is a method for analyzing multiple sequence alignments that was used to identify groups of coevolving residues termed “sectors”. The method applies spectral analysis to a matrix obtained by combining correlation information with sequence conservation. It has been asserted that the protein sectors identified by SCA are functionally significant, with different sectors controlling different biochemical properties of the protein. Here we reconsider the available experimental data and note that it involves almost exclusively proteins with a single sector. We show that in this case sequence conservation is the dominating factor in SCA, and can alone be used to make statistically equivalent functional predictions. Therefore, we suggest shifting the experimental focus to proteins for which SCA identifies several sectors. Correlations in protein alignments, which have been shown to be informative in a number of independent studies, would then be less dominated by sequence conservation. PMID:25723535

Learning-based meta-algorithm for MRI brain extraction.

PubMed

Shi, Feng; Wang, Li; Gilmore, John H; Lin, Weili; Shen, Dinggang

2011-01-01

Multiple-segmentation-and-fusion method has been widely used for brain extraction, tissue segmentation, and region of interest (ROI) localization. However, such studies are hindered in practice by their computational complexity, mainly coming from the steps of template selection and template-to-subject nonlinear registration. In this study, we address these two issues and propose a novel learning-based meta-algorithm for MRI brain extraction. Specifically, we first use exemplars to represent the entire template library, and assign the most similar exemplar to the test subject. Second, a meta-algorithm combining two existing brain extraction algorithms (BET and BSE) is proposed to conduct multiple extractions directly on test subject. Effective parameter settings for the meta-algorithm are learned from the training data and propagated to subject through exemplars. We further develop a level-set based fusion method to combine multiple candidate extractions together with a closed smooth surface, for obtaining the final result. Experimental results show that, with only a small portion of subjects for training, the proposed method is able to produce more accurate and robust brain extraction results, at Jaccard Index of 0.956 +/- 0.010 on total 340 subjects under 6-fold cross validation, compared to those by the BET and BSE even using their best parameter combinations.

A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach

PubMed Central

Jian, Yulin; Huang, Daoyu; Yan, Jia; Lu, Kun; Huang, Ying; Wen, Tailai; Zeng, Tanyue; Zhong, Shijie; Xie, Qilong

2017-01-01

A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs). The combination coefficients of base kernels, the model parameters of each base kernel, and the regularization parameter are optimized by QPSO simultaneously before implementing the kernel extreme learning machine (KELM) with the composite kernel function. Four types of common single kernel functions (Gaussian kernel, polynomial kernel, sigmoid kernel, and wavelet kernel) are utilized to constitute different composite kernel functions. Moreover, the method is also compared with other existing classification methods: extreme learning machine (ELM), kernel extreme learning machine (KELM), k-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP), radical basis function neural network (RBFNN), and probabilistic neural network (PNN). The results have demonstrated that the proposed QWMK-ELM outperforms the aforementioned methods, not only in precision, but also in efficiency for gas classification. PMID:28629202

Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis

PubMed Central

2013-01-01

Background Protein-protein interactions (PPIs) play crucial roles in the execution of various cellular processes and form the basis of biological mechanisms. Although large amount of PPIs data for different species has been generated by high-throughput experimental techniques, current PPI pairs obtained with experimental methods cover only a fraction of the complete PPI networks, and further, the experimental methods for identifying PPIs are both time-consuming and expensive. Hence, it is urgent and challenging to develop automated computational methods to efficiently and accurately predict PPIs. Results We present here a novel hierarchical PCA-EELM (principal component analysis-ensemble extreme learning machine) model to predict protein-protein interactions only using the information of protein sequences. In the proposed method, 11188 protein pairs retrieved from the DIP database were encoded into feature vectors by using four kinds of protein sequences information. Focusing on dimension reduction, an effective feature extraction method PCA was then employed to construct the most discriminative new feature set. Finally, multiple extreme learning machines were trained and then aggregated into a consensus classifier by majority voting. The ensembling of extreme learning machine removes the dependence of results on initial random weights and improves the prediction performance. Conclusions When performed on the PPI data of Saccharomyces cerevisiae, the proposed method achieved 87.00% prediction accuracy with 86.15% sensitivity at the precision of 87.59%. Extensive experiments are performed to compare our method with state-of-the-art techniques Support Vector Machine (SVM). Experimental results demonstrate that proposed PCA-EELM outperforms the SVM method by 5-fold cross-validation. Besides, PCA-EELM performs faster than PCA-SVM based method. Consequently, the proposed approach can be considered as a new promising and powerful tools for predicting PPI with excellent performance and less time. PMID:23815620

Experimental Validation of the Dynamic Inertia Measurement Method to Find the Mass Properties of an Iron Bird Test Article

NASA Technical Reports Server (NTRS)

Chin, Alexander W.; Herrera, Claudia Y.; Spivey, Natalie D.; Fladung, William A.; Cloutier, David

2015-01-01

The mass properties of an aerospace vehicle are required by multiple disciplines in the analysis and prediction of flight behavior. Pendulum oscillation methods have been developed and employed for almost a century as a means to measure mass properties. However, these oscillation methods are costly, time consuming, and risky. The NASA Armstrong Flight Research Center has been investigating the Dynamic Inertia Measurement, or DIM method as a possible alternative to oscillation methods. The DIM method uses ground test techniques that are already applied to aerospace vehicles when conducting modal surveys. Ground vibration tests would require minimal additional instrumentation and time to apply the DIM method. The DIM method has been validated on smaller test articles, but has not yet been fully proven on large aerospace vehicles.

Can you sequence ecology? Metagenomics of adaptive diversification.

PubMed

Marx, Christopher J

2013-01-01

Few areas of science have benefited more from the expansion in sequencing capability than the study of microbial communities. Can sequence data, besides providing hypotheses of the functions the members possess, detect the evolutionary and ecological processes that are occurring? For example, can we determine if a species is adapting to one niche, or if it is diversifying into multiple specialists that inhabit distinct niches? Fortunately, adaptation of populations in the laboratory can serve as a model to test our ability to make such inferences about evolution and ecology from sequencing. Even adaptation to a single niche can give rise to complex temporal dynamics due to the transient presence of multiple competing lineages. If there are multiple niches, this complexity is augmented by segmentation of the population into multiple specialists that can each continue to evolve within their own niche. For a known example of parallel diversification that occurred in the laboratory, sequencing data gave surprisingly few obvious, unambiguous signs of the ecological complexity present. Whereas experimental systems are open to direct experimentation to test hypotheses of selection or ecological interaction, the difficulty in "seeing ecology" from sequencing for even such a simple system suggests translation to communities like the human microbiome will be quite challenging. This will require both improved empirical methods to enhance the depth and time resolution for the relevant polymorphisms and novel statistical approaches to rigorously examine time-series data for signs of various evolutionary and ecological phenomena within and between species.

Hydrotherapy for the treatment of pain in people with multiple sclerosis: a randomized controlled trial.

PubMed

Castro-Sánchez, Adelaida María; Matarán-Peñarrocha, Guillermo A; Lara-Palomo, Inmaculada; Saavedra-Hernández, Manuel; Arroyo-Morales, Manuel; Moreno-Lorenzo, Carmen

2012-01-01

Background. Multiple sclerosis (MS) is a chronic demyelinating neurological disease. Several studies have reported that complementary and alternative therapies can have positive effects against pain in these patients. Objective. The objective was to investigate the effectiveness of an Ai-Chi aquatic exercise program against pain and other symptoms in MS patients. Methods. In this randomized controlled trial, 73 MS patients were randomly assigned to an experimental or control group for a 20-week treatment program. The experimental group underwent 40 sessions of Ai-Chi exercise in swimming pool and the control group 40 sessions of abdominal breathing and contraction-relaxation exercises in therapy room. Outcome variables were pain, disability, spasm, depression, fatigue, and autonomy, which were assessed before the intervention and immediately and at 4 and 10 weeks after the last treatment session. Results. The experimental group showed a significant (P < 0.028) and clinically relevant decrease in pain intensity versus baseline, with an immediate posttreatment reduction in median visual analogue scale scores of 50% that was maintained for up to 10 weeks. Significant improvements were also observed in spasm, fatigue, disability, and autonomy. Conclusion. According to these findings, an Ai-Chi aquatic exercise program improves pain, spasms, disability, fatigue, depression, and autonomy in MS patients.

Hydrotherapy for the Treatment of Pain in People with Multiple Sclerosis: A Randomized Controlled Trial

PubMed Central

Castro-Sánchez, Adelaida María; Matarán-Peñarrocha, Guillermo A.; Lara-Palomo, Inmaculada; Saavedra-Hernández, Manuel; Arroyo-Morales, Manuel; Moreno-Lorenzo, Carmen

2012-01-01

Background. Multiple sclerosis (MS) is a chronic demyelinating neurological disease. Several studies have reported that complementary and alternative therapies can have positive effects against pain in these patients. Objective. The objective was to investigate the effectiveness of an Ai-Chi aquatic exercise program against pain and other symptoms in MS patients. Methods. In this randomized controlled trial, 73 MS patients were randomly assigned to an experimental or control group for a 20-week treatment program. The experimental group underwent 40 sessions of Ai-Chi exercise in swimming pool and the control group 40 sessions of abdominal breathing and contraction-relaxation exercises in therapy room. Outcome variables were pain, disability, spasm, depression, fatigue, and autonomy, which were assessed before the intervention and immediately and at 4 and 10 weeks after the last treatment session. Results. The experimental group showed a significant (P < 0.028) and clinically relevant decrease in pain intensity versus baseline, with an immediate posttreatment reduction in median visual analogue scale scores of 50% that was maintained for up to 10 weeks. Significant improvements were also observed in spasm, fatigue, disability, and autonomy. Conclusion. According to these findings, an Ai-Chi aquatic exercise program improves pain, spasms, disability, fatigue, depression, and autonomy in MS patients. PMID:21785645

Experimental task-based optimization of a four-camera variable-pinhole small-animal SPECT system

NASA Astrophysics Data System (ADS)

Hesterman, Jacob Y.; Kupinski, Matthew A.; Furenlid, Lars R.; Wilson, Donald W.

2005-04-01

We have previously utilized lumpy object models and simulated imaging systems in conjunction with the ideal observer to compute figures of merit for hardware optimization. In this paper, we describe the development of methods and phantoms necessary to validate or experimentally carry out these optimizations. Our study was conducted on a four-camera small-animal SPECT system that employs interchangeable pinhole plates to operate under a variety of pinhole configurations and magnifications (representing optimizable system parameters). We developed a small-animal phantom capable of producing random backgrounds for each image sequence. The task chosen for the study was the detection of a 2mm diameter sphere within the phantom-generated random background. A total of 138 projection images were used, half of which included the signal. As our observer, we employed the channelized Hotelling observer (CHO) with Laguerre-Gauss channels. The signal-to-noise (SNR) of this observer was used to compare different system configurations. Results indicate agreement between experimental and simulated data with higher detectability rates found for multiple-camera, multiple-pinhole, and high-magnification systems, although it was found that mixtures of magnifications often outperform systems employing a single magnification. This work will serve as a basis for future studies pertaining to system hardware optimization.

Optical Theory Improvements to Space Domain Awareness

DTIC Science & Technology

2016-09-15

to other portions of system design. These design components include the Field of View (FoV) of the telescope and the physical dimensions of the system...trying to capture physical characteristics of the object being imaged, and the blurring caused by the atmosphere degrades and limits this capability...experimentally verified in multiple physical experiments [53, 54]. The drawback to these methods is that they assume that the noise caused by the atmosphere is

An Experimental Study of Large Compressive Loads Upon Residual Strain Fields and the Interaction Between Surface Strain Fields Created by Coldworking Fastener Holes.

DTIC Science & Technology

1981-02-01

Strains" (J. of Basic Eng., Vol. 82, Series D, June 1960), pp, 426-434. 10. Morse, S., A.J. Durelli, and C.A. Sciammarella , "Geo- metry of Moire...grid Method, a Practical Moire Stress-analysis Tool" (Exp. Mech., Vol. 7, July 1967), pp. 19A-22A. 20. Sciammarella , C., "Moire-fringe Multiplication

Cyclotron resonance spectroscopy in a high mobility two dimensional electron gas using characteristic matrix methods.

PubMed

Hilton, David J

2012-12-31

We develop a new characteristic matrix-based method to analyze cyclotron resonance experiments in high mobility two-dimensional electron gas samples where direct interference between primary and satellite reflections has previously limited the frequency resolution. This model is used to simulate experimental data taken using terahertz time-domain spectroscopy that show multiple pulses from the substrate with a separation of 15 ps that directly interfere in the time-domain. We determine a cyclotron dephasing lifetime of 15.1 ± 0.5 ps at 1.5 K and 5.0 ± 0.5 ps at 75 K.

The Research on Linux Memory Forensics

NASA Astrophysics Data System (ADS)

Zhang, Jun; Che, ShengBing

2018-03-01

Memory forensics is a branch of computer forensics. It does not depend on the operating system API, and analyzes operating system information from binary memory data. Based on the 64-bit Linux operating system, it analyzes system process and thread information from physical memory data. Using ELF file debugging information and propose a method for locating kernel structure member variable, it can be applied to different versions of the Linux operating system. The experimental results show that the method can successfully obtain the sytem process information from physical memory data, and can be compatible with multiple versions of the Linux kernel.

USSAERO computer program development, versions B and C

NASA Technical Reports Server (NTRS)

Woodward, F. A.

1980-01-01

Versions B and C of the unified subsonic and supersonic aerodynamic analysis program, USSAERO, are described. Version B incorporates a new symmetrical singularity method to provide improved surface pressure distributions on wings in subsonic flow. Version C extends the range of application of the program to include the analysis of multiple engine nacelles or finned external stores. In addition, nonlinear compressibility effects in high subsonic and supersonic flows are approximated using a correction based on the local Mach number at panel control points. Several examples are presented comparing the results of these programs with other panel methods and experimental data.

Speckle noise reduction in digital holography by slightly rotating the object

NASA Astrophysics Data System (ADS)

Herrera-Ramirez, Jorge; Hincapie-Zuluaga, Diego Andrés; Garcia-Sucerquia, Jorge

2016-12-01

This work shows the realization of speckle reduction in the numerical reconstruction of digitally recorded holograms by the superposition of multiple slightly rotated digital holographic images of the object. The superposition of T uncorrelated holographic images reduces the contrast of the speckle noise of the image following the expected 1/√{T} law. The effect of the method on the borders of the resulting image is evaluated by quantifying the utilization of the dynamic range or the contrast between the white and black areas of a regular die. Experimental results validate the feasibility of the proposed method.

Phase retrieval without unwrapping by single-shot dual-wavelength digital holography

NASA Astrophysics Data System (ADS)

Min, Junwei; Yao, Baoli; Zhou, Meiling; Guo, Rongli; Lei, Ming; Yang, Yanlong; Dan, Dan; Yan, Shaohui; Peng, Tong

2014-12-01

A phase retrieval method by using single-shot dual-wavelength digital holography is proposed. Each single wavelength hologram is extracted from the color CCD recorded hologram at one exposure, and the unwrapped phase image of object can be reconstructed directly. Different from the traditional multiple wavelength phase unwrapping techniques, any single complex wave-fronts at different wavelengths have no need to be calculated any more. Thus, the phase retrieval is computationally fast and straightforward, and the limitations on the total optical path difference are significantly relaxed. The practicability of the proposed method is demonstrated by both simulated and experimental results.

Interferograms, schlieren, and shadowgraphs constructed from real- and ideal-gas, two- and three-dimensional computed flowfields

NASA Technical Reports Server (NTRS)

Yates, Leslie A.

1993-01-01

The construction of interferograms, schlieren, and shadowgraphs from computed flowfield solutions permits one-to-one comparisons of computed and experimental results. A method of constructing these images from both ideal- and real-gas, two and three-dimensional computed flowfields is described. The computational grids can be structured or unstructured, and multiple grids are an option. Constructed images are shown for several types of computed flows including nozzle, wake, and reacting flows; comparisons to experimental images are also shown. In addition, th sensitivity of these images to errors in the flowfield solution is demonstrated, and the constructed images can be used to identify problem areas in the computations.

Interferograms, Schlieren, and Shadowgraphs Constructed from Real- and Ideal-Gas, Two- and Three-Dimensional Computed Flowfields

NASA Technical Reports Server (NTRS)

Yates, Leslie A.

1992-01-01

The construction of interferograms, schlieren, and shadowgraphs from computed flowfield solutions permits one-to-one comparisons of computed and experimental results. A method for constructing these images from both ideal- and real-gas, two- and three-dimensional computed flowfields is described. The computational grids can be structured or unstructured, and multiple grids are an option. Constructed images are shown for several types of computed flows including nozzle, wake, and reacting flows; comparisons to experimental images are also shown. In addition, the sensitivity of these images to errors in the flowfield solution is demonstrated, and the constructed images can be used to identify problem areas in the computations.

On an image reconstruction method for ECT

NASA Astrophysics Data System (ADS)

Sasamoto, Akira; Suzuki, Takayuki; Nishimura, Yoshihiro

2007-04-01

An image by Eddy Current Testing(ECT) is a blurred image to original flaw shape. In order to reconstruct fine flaw image, a new image reconstruction method has been proposed. This method is based on an assumption that a very simple relationship between measured data and source were described by a convolution of response function and flaw shape. This assumption leads to a simple inverse analysis method with deconvolution.In this method, Point Spread Function (PSF) and Line Spread Function(LSF) play a key role in deconvolution processing. This study proposes a simple data processing to determine PSF and LSF from ECT data of machined hole and line flaw. In order to verify its validity, ECT data for SUS316 plate(200x200x10mm) with artificial machined hole and notch flaw had been acquired by differential coil type sensors(produced by ZETEC Inc). Those data were analyzed by the proposed method. The proposed method restored sharp discrete multiple hole image from interfered data by multiple holes. Also the estimated width of line flaw has been much improved compared with original experimental data. Although proposed inverse analysis strategy is simple and easy to implement, its validity to holes and line flaw have been shown by many results that much finer image than original image have been reconstructed.

Observing system simulation experiments with multiple methods

NASA Astrophysics Data System (ADS)

Ishibashi, Toshiyuki

2014-11-01

An observing System Simulation Experiment (OSSE) is a method to evaluate impacts of hypothetical observing systems on analysis and forecast accuracy in numerical weather prediction (NWP) systems. Since OSSE requires simulations of hypothetical observations, uncertainty of OSSE results is generally larger than that of observing system experiments (OSEs). To reduce such uncertainty, OSSEs for existing observing systems are often carried out as calibration of the OSSE system. The purpose of this study is to achieve reliable OSSE results based on results of OSSEs with multiple methods. There are three types of OSSE methods. The first one is the sensitivity observing system experiment (SOSE) based OSSE (SOSEOSSE). The second one is the ensemble of data assimilation cycles (ENDA) based OSSE (ENDA-OSSE). The third one is the nature-run (NR) based OSSE (NR-OSSE). These three OSSE methods have very different properties. The NROSSE evaluates hypothetical observations in a virtual (hypothetical) world, NR. The ENDA-OSSE is very simple method but has a sampling error problem due to a small size ensemble. The SOSE-OSSE requires a very highly accurate analysis field as a pseudo truth of the real atmosphere. We construct these three types of OSSE methods in the Japan meteorological Agency (JMA) global 4D-Var experimental system. In the conference, we will present initial results of these OSSE systems and their comparisons.

Metabolic pathways as possible therapeutic targets for progressive multiple sclerosis.

PubMed

Heidker, Rebecca M; Emerson, Mitchell R; LeVine, Steven M

2017-08-01

Unlike relapsing remitting multiple sclerosis, there are very few therapeutic options for patients with progressive forms of multiple sclerosis. While immune mechanisms are key participants in the pathogenesis of relapsing remitting multiple sclerosis, the mechanisms underlying the development of progressive multiple sclerosis are less well understood. Putative mechanisms behind progressive multiple sclerosis have been put forth: insufficient energy production via mitochondrial dysfunction, activated microglia, iron accumulation, oxidative stress, activated astrocytes, Wallerian degeneration, apoptosis, etc . Furthermore, repair processes such as remyelination are incomplete. Experimental therapies that strive to improve metabolism within neurons and glia, e.g. , oligodendrocytes, could act to counter inadequate energy supplies and/or support remyelination. Most experimental approaches have been examined as standalone interventions; however, it is apparent that the biochemical steps being targeted are part of larger pathways, which are further intertwined with other metabolic pathways. Thus, the potential benefits of a tested intervention, or of an established therapy, e.g. , ocrelizumab, could be undermined by constraints on upstream and/or downstream steps. If correct, then this argues for a more comprehensive, multifaceted approach to therapy. Here we review experimental approaches to support neuronal and glial metabolism, and/or promote remyelination, which may have potential to lessen or delay progressive multiple sclerosis.

Impaired neurosteroid synthesis in multiple sclerosis

PubMed Central

Noorbakhsh, Farshid; Ellestad, Kristofor K.; Maingat, Ferdinand; Warren, Kenneth G.; Han, May H.; Steinman, Lawrence; Baker, Glen B.

2011-01-01

High-throughput technologies have led to advances in the recognition of disease pathways and their underlying mechanisms. To investigate the impact of micro-RNAs on the disease process in multiple sclerosis, a prototypic inflammatory neurological disorder, we examined cerebral white matter from patients with or without the disease by micro-RNA profiling, together with confirmatory reverse transcription–polymerase chain reaction analysis, immunoblotting and gas chromatography-mass spectrometry. These observations were verified using the in vivo multiple sclerosis model, experimental autoimmune encephalomyelitis. Brains of patients with or without multiple sclerosis demonstrated differential expression of multiple micro-RNAs, but expression of three neurosteroid synthesis enzyme-specific micro-RNAs (miR-338, miR-155 and miR-491) showed a bias towards induction in patients with multiple sclerosis (P < 0.05). Analysis of the neurosteroidogenic pathways targeted by micro-RNAs revealed suppression of enzyme transcript and protein levels in the white matter of patients with multiple sclerosis (P < 0.05). This was confirmed by firefly/Renilla luciferase micro-RNA target knockdown experiments (P < 0.05) and detection of specific micro-RNAs by in situ hybridization in the brains of patients with or without multiple sclerosis. Levels of important neurosteroids, including allopregnanolone, were suppressed in the white matter of patients with multiple sclerosis (P < 0.05). Induction of the murine micro-RNAs, miR-338 and miR-155, accompanied by diminished expression of neurosteroidogenic enzymes and allopregnanolone, was also observed in the brains of mice with experimental autoimmune encephalomyelitis (P < 0.05). Allopregnanolone treatment of the experimental autoimmune encephalomyelitis mouse model limited the associated neuropathology, including neuroinflammation, myelin and axonal injury and reduced neurobehavioral deficits (P < 0.05). These multi-platform studies point to impaired neurosteroidogenesis in both multiple sclerosis and experimental autoimmune encephalomyelitis. The findings also indicate that allopregnanolone and perhaps other neurosteroid-like compounds might represent potential biomarkers or therapies for multiple sclerosis. PMID:21908875

Single-Image Distance Measurement by a Smart Mobile Device.

PubMed

Chen, Shangwen; Fang, Xianyong; Shen, Jianbing; Wang, Linbo; Shao, Ling

2017-12-01

Existing distance measurement methods either require multiple images and special photographing poses or only measure the height with a special view configuration. We propose a novel image-based method that can measure various types of distance from single image captured by a smart mobile device. The embedded accelerometer is used to determine the view orientation of the device. Consequently, pixels can be back-projected to the ground, thanks to the efficient calibration method using two known distances. Then the distance in pixel is transformed to a real distance in centimeter with a linear model parameterized by the magnification ratio. Various types of distance specified in the image can be computed accordingly. Experimental results demonstrate the effectiveness of the proposed method.

Investigation to realize a computationally efficient implementation of the high-order instantaneous-moments-based fringe analysis method

NASA Astrophysics Data System (ADS)

Gorthi, Sai Siva; Rajshekhar, Gannavarpu; Rastogi, Pramod

2010-06-01

Recently, a high-order instantaneous moments (HIM)-operator-based method was proposed for accurate phase estimation in digital holographic interferometry. The method relies on piece-wise polynomial approximation of phase and subsequent evaluation of the polynomial coefficients from the HIM operator using single-tone frequency estimation. The work presents a comparative analysis of the performance of different single-tone frequency estimation techniques, like Fourier transform followed by optimization, estimation of signal parameters by rotational invariance technique (ESPRIT), multiple signal classification (MUSIC), and iterative frequency estimation by interpolation on Fourier coefficients (IFEIF) in HIM-operator-based methods for phase estimation. Simulation and experimental results demonstrate the potential of the IFEIF technique with respect to computational efficiency and estimation accuracy.

On dealing with multiple correlation peaks in PIV

NASA Astrophysics Data System (ADS)

Masullo, A.; Theunissen, R.

2018-05-01

A novel algorithm to analyse PIV images in the presence of strong in-plane displacement gradients and reduce sub-grid filtering is proposed in this paper. Interrogation windows subjected to strong in-plane displacement gradients often produce correlation maps presenting multiple peaks. Standard multi-grid procedures discard such ambiguous correlation windows using a signal to noise (SNR) filter. The proposed algorithm improves the standard multi-grid algorithm allowing the detection of splintered peaks in a correlation map through an automatic threshold, producing multiple displacement vectors for each correlation area. Vector locations are chosen by translating images according to the peak displacements and by selecting the areas with the strongest match. The method is assessed on synthetic images of a boundary layer of varying intensity and a sinusoidal displacement field of changing wavelength. An experimental case of a flow exhibiting strong velocity gradients is also provided to show the improvements brought by this technique.

Crack Damage Detection Method via Multiple Visual Features and Efficient Multi-Task Learning Model.

PubMed

Wang, Baoxian; Zhao, Weigang; Gao, Po; Zhang, Yufeng; Wang, Zhe

2018-06-02

This paper proposes an effective and efficient model for concrete crack detection. The presented work consists of two modules: multi-view image feature extraction and multi-task crack region detection. Specifically, multiple visual features (such as texture, edge, etc.) of image regions are calculated, which can suppress various background noises (such as illumination, pockmark, stripe, blurring, etc.). With the computed multiple visual features, a novel crack region detector is advocated using a multi-task learning framework, which involves restraining the variability for different crack region features and emphasizing the separability between crack region features and complex background ones. Furthermore, the extreme learning machine is utilized to construct this multi-task learning model, thereby leading to high computing efficiency and good generalization. Experimental results of the practical concrete images demonstrate that the developed algorithm can achieve favorable crack detection performance compared with traditional crack detectors.

Experimental Design for Stochastic Models of Nonlinear Signaling Pathways Using an Interval-Wise Linear Noise Approximation and State Estimation.

PubMed

Zimmer, Christoph

2016-01-01

Computational modeling is a key technique for analyzing models in systems biology. There are well established methods for the estimation of the kinetic parameters in models of ordinary differential equations (ODE). Experimental design techniques aim at devising experiments that maximize the information encoded in the data. For ODE models there are well established approaches for experimental design and even software tools. However, data from single cell experiments on signaling pathways in systems biology often shows intrinsic stochastic effects prompting the development of specialized methods. While simulation methods have been developed for decades and parameter estimation has been targeted for the last years, only very few articles focus on experimental design for stochastic models. The Fisher information matrix is the central measure for experimental design as it evaluates the information an experiment provides for parameter estimation. This article suggest an approach to calculate a Fisher information matrix for models containing intrinsic stochasticity and high nonlinearity. The approach makes use of a recently suggested multiple shooting for stochastic systems (MSS) objective function. The Fisher information matrix is calculated by evaluating pseudo data with the MSS technique. The performance of the approach is evaluated with simulation studies on an Immigration-Death, a Lotka-Volterra, and a Calcium oscillation model. The Calcium oscillation model is a particularly appropriate case study as it contains the challenges inherent to signaling pathways: high nonlinearity, intrinsic stochasticity, a qualitatively different behavior from an ODE solution, and partial observability. The computational speed of the MSS approach for the Fisher information matrix allows for an application in realistic size models.

PrimerDesign-M: A multiple-alignment based multiple-primer design tool for walking across variable genomes

DOE PAGES

Yoon, Hyejin; Leitner, Thomas

2014-12-17

Analyses of entire viral genomes or mtDNA requires comprehensive design of many primers across their genomes. In addition, simultaneous optimization of several DNA primer design criteria may improve overall experimental efficiency and downstream bioinformatic processing. To achieve these goals, we developed PrimerDesign-M. It includes several options for multiple-primer design, allowing researchers to efficiently design walking primers that cover long DNA targets, such as entire HIV-1 genomes, and that optimizes primers simultaneously informed by genetic diversity in multiple alignments and experimental design constraints given by the user. PrimerDesign-M can also design primers that include DNA barcodes and minimize primer dimerization. PrimerDesign-Mmore » finds optimal primers for highly variable DNA targets and facilitates design flexibility by suggesting alternative designs to adapt to experimental conditions.« less

Epizootic pneumonia of bighorn sheep following experimental exposure to Mycoplasma ovipneumoniae.

PubMed

Besser, Thomas E; Cassirer, E Frances; Potter, Kathleen A; Lahmers, Kevin; Oaks, J Lindsay; Shanthalingam, Sudarvili; Srikumaran, Subramaniam; Foreyt, William J

2014-01-01

Bronchopneumonia is a population limiting disease of bighorn sheep (Ovis canadensis). The cause of this disease has been a subject of debate. Leukotoxin expressing Mannheimia haemolytica and Bibersteinia trehalosi produce acute pneumonia after experimental challenge but are infrequently isolated from animals in natural outbreaks. Mycoplasma ovipneumoniae, epidemiologically implicated in naturally occurring outbreaks, has received little experimental evaluation as a primary agent of bighorn sheep pneumonia. In two experiments, bighorn sheep housed in multiple pens 7.6 to 12 m apart were exposed to M. ovipneumoniae by introduction of a single infected or challenged animal to a single pen. Respiratory disease was monitored by observation of clinical signs and confirmed by necropsy. Bacterial involvement in the pneumonic lungs was evaluated by conventional aerobic bacteriology and by culture-independent methods. In both experiments the challenge strain of M. ovipneumoniae was transmitted to all animals both within and between pens and all infected bighorn sheep developed bronchopneumonia. In six bighorn sheep in which the disease was allowed to run its course, three died with bronchopneumonia 34, 65, and 109 days after M. ovipneumoniae introduction. Diverse bacterial populations, predominantly including multiple obligate anaerobic species, were present in pneumonic lung tissues at necropsy. Exposure to a single M. ovipneumoniae infected animal resulted in transmission of infection to all bighorn sheep both within the pen and in adjacent pens, and all infected sheep developed bronchopneumonia. The epidemiologic, pathologic and microbiologic findings in these experimental animals resembled those seen in naturally occurring pneumonia outbreaks in free ranging bighorn sheep.

High-resolution whole-brain DCE-MRI using constrained reconstruction: Prospective clinical evaluation in brain tumor patients

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

Guo, Yi, E-mail: yiguo@usc.edu; Zhu, Yinghua; Lingala, Sajan Goud

Purpose: To clinically evaluate a highly accelerated T1-weighted dynamic contrast-enhanced (DCE) MRI technique that provides high spatial resolution and whole-brain coverage via undersampling and constrained reconstruction with multiple sparsity constraints. Methods: Conventional (rate-2 SENSE) and experimental DCE-MRI (rate-30) scans were performed 20 minutes apart in 15 brain tumor patients. The conventional clinical DCE-MRI had voxel dimensions 0.9 × 1.3 × 7.0 mm{sup 3}, FOV 22 × 22 × 4.2 cm{sup 3}, and the experimental DCE-MRI had voxel dimensions 0.9 × 0.9 × 1.9 mm{sup 3}, and broader coverage 22 × 22 × 19 cm{sup 3}. Temporal resolution was 5 smore » for both protocols. Time-resolved images and blood–brain barrier permeability maps were qualitatively evaluated by two radiologists. Results: The experimental DCE-MRI scans showed no loss of qualitative information in any of the cases, while achieving substantially higher spatial resolution and whole-brain spatial coverage. Average qualitative scores (from 0 to 3) were 2.1 for the experimental scans and 1.1 for the conventional clinical scans. Conclusions: The proposed DCE-MRI approach provides clinically superior image quality with higher spatial resolution and coverage than currently available approaches. These advantages may allow comprehensive permeability mapping in the brain, which is especially valuable in the setting of large lesions or multiple lesions spread throughout the brain.« less

Bag-of-features based medical image retrieval via multiple assignment and visual words weighting.

PubMed

Wang, Jingyan; Li, Yongping; Zhang, Ying; Wang, Chao; Xie, Honglan; Chen, Guoling; Gao, Xin

2011-11-01

Bag-of-features based approaches have become prominent for image retrieval and image classification tasks in the past decade. Such methods represent an image as a collection of local features, such as image patches and key points with scale invariant feature transform (SIFT) descriptors. To improve the bag-of-features methods, we first model the assignments of local descriptors as contribution functions, and then propose a novel multiple assignment strategy. Assuming the local features can be reconstructed by their neighboring visual words in a vocabulary, reconstruction weights can be solved by quadratic programming. The weights are then used to build contribution functions, resulting in a novel assignment method, called quadratic programming (QP) assignment. We further propose a novel visual word weighting method. The discriminative power of each visual word is analyzed by the sub-similarity function in the bin that corresponds to the visual word. Each sub-similarity function is then treated as a weak classifier. A strong classifier is learned by boosting methods that combine those weak classifiers. The weighting factors of the visual words are learned accordingly. We evaluate the proposed methods on medical image retrieval tasks. The methods are tested on three well-known data sets, i.e., the ImageCLEFmed data set, the 304 CT Set, and the basal-cell carcinoma image set. Experimental results demonstrate that the proposed QP assignment outperforms the traditional nearest neighbor assignment, the multiple assignment, and the soft assignment, whereas the proposed boosting based weighting strategy outperforms the state-of-the-art weighting methods, such as the term frequency weights and the term frequency-inverse document frequency weights.

A novel framework of tissue membrane systems for image fusion.

PubMed

Zhang, Zulin; Yi, Xinzhong; Peng, Hong

2014-01-01

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

Acoustic processing method for MS/MS experiments

NASA Technical Reports Server (NTRS)

Whymark, R. R.

1973-01-01

Acoustical methods in which intense sound beams can be used to control the position of objects are considered. The position control arises from the radiation force experienced when a body is placed in a sound field. A description of the special properties of intense sound fields useful for position control is followed by a discussion of the more obvious methods of position, namely the use of multiple sound beams. A new type of acoustic position control device is reported that has advantages of simplicity and reliability and utilizes only a single sound beam. Finally a description is given of an experimental single beam levitator, and the results obtained in a number of key levitation experiments.

Micro–Single-Photon Emission Computed Tomography Image Acquisition and Quantification of Sodium-Iodide Symporter–Mediated Radionuclide Accumulation in Mouse Thyroid and Salivary Glands

PubMed Central

Brandt, Michael P.; Kloos, Richard T.; Shen, Daniel H.; Zhang, Xiaoli; Liu, Yu-Yu

2012-01-01

Background Micro–single-photon emission computed tomography (SPECT) provides a noninvasive way to evaluate the effects of genetic and/or pharmacological modulation on sodium-iodide symporter (NIS)–mediated radionuclide accumulation in mouse thyroid and salivary glands. However, parameters affecting image acquisition and analysis of mouse thyroids and salivary glands have not been thoroughly investigated. In this study, we investigated the effects of region-of-interest (ROI) selection, collimation, scan time, and imaging orbit on image acquisition and quantification of thyroidal and salivary radionuclide accumulation in mice. Methods The effects of data window minima and maxima on thyroidal and salivary ROI selection using a visual boundary method were examined in SPECT images acquired from mice injected with 123I NaI. The effects of collimation, scan time, and imaging orbit on counting linearity and signal intensity were investigated using phantoms filled with various activities of 123I NaI or Tc-99m pertechnetate. Spatial resolution of target organs in whole-animal images was compared between circular orbit with parallel-hole collimation and spiral orbit with five-pinhole collimation. Lastly, the inter-experimental variability of the same mouse scanned multiple times was compared with the intra-experimental variability among different mice scanned at the same time. Results Thyroid ROI was separated from salivary glands by empirically increasing the data window maxima. Counting linearity within the range of 0.5–14.2 μCi was validated by phantom imaging using single- or multiple-pinhole collimators with circular or spiral imaging orbit. Scanning time could be shortened to 15 minutes per mouse without compromising counting linearity despite proportionally decreased signal intensity. Whole-animal imaging using a spiral orbit with five-pinhole collimators achieved a high spatial resolution and counting linearity. Finally, the extent of inter-experimental variability of NIS-mediated radionuclide accumulation in the thyroid and salivary glands by SPECT imaging in the same mouse was less than the magnitude of variability among the littermates. Conclusions The impacts of multiple variables and experimental designs on micro-SPECT imaging and quantification of radionuclide accumulation in mouse thyroid and salivary glands can be minimized. This platform will serve as an invaluable tool to screen for pharmacologic reagents that differentially modulate thyroidal and salivary radioiodine accumulation in preclinical mouse models. PMID:22540327

An analytical and experimental study of sound propagation and attenuation in variable-area ducts. [reducing aircraft engine noise

NASA Technical Reports Server (NTRS)

Nayfeh, A. H.; Kaiser, J. E.; Marshall, R. L.; Hurst, L. J.

1978-01-01

The performance of sound suppression techniques in ducts that produce refraction effects due to axial velocity gradients was evaluated. A computer code based on the method of multiple scales was used to calculate the influence of axial variations due to slow changes in the cross-sectional area as well as transverse gradients due to the wall boundary layers. An attempt was made to verify the analytical model through direct comparison of experimental and computational results and the analytical determination of the influence of axial gradients on optimum liner properties. However, the analytical studies were unable to examine the influence of non-parallel ducts on the optimum linear conditions. For liner properties not close to optimum, the analytical predictions and the experimental measurements were compared. The circumferential variations of pressure amplitudes and phases at several axial positions were examined in straight and variable-area ducts, hard-wall and lined sections with and without a mean flow. Reasonable agreement between the theoretical and experimental results was obtained.

Research designs for studies evaluating the effectiveness of change and improvement strategies.

PubMed

Eccles, M; Grimshaw, J; Campbell, M; Ramsay, C

2003-02-01

The methods of evaluating change and improvement strategies are not well described. The design and conduct of a range of experimental and non-experimental quantitative designs are considered. Such study designs should usually be used in a context where they build on appropriate theoretical, qualitative and modelling work, particularly in the development of appropriate interventions. A range of experimental designs are discussed including single and multiple arm randomised controlled trials and the use of more complex factorial and block designs. The impact of randomisation at both group and individual levels and three non-experimental designs (uncontrolled before and after, controlled before and after, and time series analysis) are also considered. The design chosen will reflect both the needs (and resources) in any particular circumstances and also the purpose of the evaluation. The general principle underlying the choice of evaluative design is, however, simple-those conducting such evaluations should use the most robust design possible to minimise bias and maximise generalisability.

Modeling and experimental parametric study of a tri-leg compliant orthoplanar spring based multi-mode piezoelectric energy harvester

NASA Astrophysics Data System (ADS)

Dhote, Sharvari; Yang, Zhengbao; Zu, Jean

2018-01-01

This paper presents the modeling and experimental parametric study of a nonlinear multi-frequency broad bandwidth piezoelectric vibration-based energy harvester. The proposed harvester consists of a tri-leg compliant orthoplanar spring (COPS) and multiple masses with piezoelectric plates attached at three different locations. The vibration modes, resonant frequencies, and strain distributions are studied using the finite element analysis. The prototype is manufactured and experimentally investigated to study the effect of single as well as multiple light-weight masses on the bandwidth. The dynamic behavior of the harvester with a mass at the center is modeled numerically and characterized experimentally. The simulation and experimental results are in good agreement. A wide bandwidth with three close nonlinear vibration modes is observed during the experiments when four masses are added to the proposed harvester. The current generator with four masses shows a significant performance improvement with multiple nonlinear peaks under both forward and reverse frequency sweeps.

A Method for Improving the Pose Accuracy of a Robot Manipulator Based on Multi-Sensor Combined Measurement and Data Fusion

PubMed Central

Liu, Bailing; Zhang, Fumin; Qu, Xinghua

2015-01-01

An improvement method for the pose accuracy of a robot manipulator by using a multiple-sensor combination measuring system (MCMS) is presented. It is composed of a visual sensor, an angle sensor and a series robot. The visual sensor is utilized to measure the position of the manipulator in real time, and the angle sensor is rigidly attached to the manipulator to obtain its orientation. Due to the higher accuracy of the multi-sensor, two efficient data fusion approaches, the Kalman filter (KF) and multi-sensor optimal information fusion algorithm (MOIFA), are used to fuse the position and orientation of the manipulator. The simulation and experimental results show that the pose accuracy of the robot manipulator is improved dramatically by 38%∼78% with the multi-sensor data fusion. Comparing with reported pose accuracy improvement methods, the primary advantage of this method is that it does not require the complex solution of the kinematics parameter equations, increase of the motion constraints and the complicated procedures of the traditional vision-based methods. It makes the robot processing more autonomous and accurate. To improve the reliability and accuracy of the pose measurements of MCMS, the visual sensor repeatability is experimentally studied. An optimal range of 1 × 0.8 × 1 ∼ 2 × 0.8 × 1 m in the field of view (FOV) is indicated by the experimental results. PMID:25850067

Comparison of Geant4 multiple Coulomb scattering models with theory for radiotherapy protons

NASA Astrophysics Data System (ADS)

Makarova, Anastasia; Gottschalk, Bernard; Sauerwein, Wolfgang

2017-08-01

Usually, Monte Carlo models are validated against experimental data. However, models of multiple Coulomb scattering (MCS) in the Gaussian approximation are exceptional in that we have theories which are probably more accurate than the experiments which have, so far, been done to test them. In problems directly sensitive to the distribution of angles leaving the target, the relevant theory is the Molière/Fano/Hanson variant of Molière theory (Gottschalk et al 1993 Nucl. Instrum. Methods Phys. Res. B 74 467-90). For transverse spreading of the beam in the target itself, the theory of Preston and Koehler (Gottschalk (2012 arXiv:1204.4470)) holds. Therefore, in this paper we compare Geant4 simulations, using the Urban and Wentzel models of MCS, with theory rather than experiment, revealing trends which would otherwise be obscured by experimental scatter. For medium-energy (radiotherapy) protons, and low-Z (water-like) target materials, Wentzel appears to be better than Urban in simulating the distribution of outgoing angles. For beam spreading in the target itself, the two models are essentially equal.

Model predictive control of the solid oxide fuel cell stack temperature with models based on experimental data

NASA Astrophysics Data System (ADS)

Pohjoranta, Antti; Halinen, Matias; Pennanen, Jari; Kiviaho, Jari

2015-03-01

Generalized predictive control (GPC) is applied to control the maximum temperature in a solid oxide fuel cell (SOFC) stack and the temperature difference over the stack. GPC is a model predictive control method and the models utilized in this work are ARX-type (autoregressive with extra input), multiple input-multiple output, polynomial models that were identified from experimental data obtained from experiments with a complete SOFC system. The proposed control is evaluated by simulation with various input-output combinations, with and without constraints. A comparison with conventional proportional-integral-derivative (PID) control is also made. It is shown that if only the stack maximum temperature is controlled, a standard PID controller can be used to obtain output performance comparable to that obtained with the significantly more complex model predictive controller. However, in order to control the temperature difference over the stack, both the stack minimum and the maximum temperature need to be controlled and this cannot be done with a single PID controller. In such a case the model predictive controller provides a feasible and effective solution.

Comparison of Geant4 multiple Coulomb scattering models with theory for radiotherapy protons.

PubMed

Makarova, Anastasia; Gottschalk, Bernard; Sauerwein, Wolfgang

2017-07-06

Usually, Monte Carlo models are validated against experimental data. However, models of multiple Coulomb scattering (MCS) in the Gaussian approximation are exceptional in that we have theories which are probably more accurate than the experiments which have, so far, been done to test them. In problems directly sensitive to the distribution of angles leaving the target, the relevant theory is the Molière/Fano/Hanson variant of Molière theory (Gottschalk et al 1993 Nucl. Instrum. Methods Phys. Res. B 74 467-90). For transverse spreading of the beam in the target itself, the theory of Preston and Koehler (Gottschalk (2012 arXiv:1204.4470)) holds. Therefore, in this paper we compare Geant4 simulations, using the Urban and Wentzel models of MCS, with theory rather than experiment, revealing trends which would otherwise be obscured by experimental scatter. For medium-energy (radiotherapy) protons, and low-Z (water-like) target materials, Wentzel appears to be better than Urban in simulating the distribution of outgoing angles. For beam spreading in the target itself, the two models are essentially equal.

Bayesian Dose-Response Modeling in Sparse Data

NASA Astrophysics Data System (ADS)

Kim, Steven B.

This book discusses Bayesian dose-response modeling in small samples applied to two different settings. The first setting is early phase clinical trials, and the second setting is toxicology studies in cancer risk assessment. In early phase clinical trials, experimental units are humans who are actual patients. Prior to a clinical trial, opinions from multiple subject area experts are generally more informative than the opinion of a single expert, but we may face a dilemma when they have disagreeing prior opinions. In this regard, we consider compromising the disagreement and compare two different approaches for making a decision. In addition to combining multiple opinions, we also address balancing two levels of ethics in early phase clinical trials. The first level is individual-level ethics which reflects the perspective of trial participants. The second level is population-level ethics which reflects the perspective of future patients. We extensively compare two existing statistical methods which focus on each perspective and propose a new method which balances the two conflicting perspectives. In toxicology studies, experimental units are living animals. Here we focus on a potential non-monotonic dose-response relationship which is known as hormesis. Briefly, hormesis is a phenomenon which can be characterized by a beneficial effect at low doses and a harmful effect at high doses. In cancer risk assessments, the estimation of a parameter, which is known as a benchmark dose, can be highly sensitive to a class of assumptions, monotonicity or hormesis. In this regard, we propose a robust approach which considers both monotonicity and hormesis as a possibility. In addition, We discuss statistical hypothesis testing for hormesis and consider various experimental designs for detecting hormesis based on Bayesian decision theory. Past experiments have not been optimally designed for testing for hormesis, and some Bayesian optimal designs may not be optimal under a wrong parametric assumption. In this regard, we consider a robust experimental design which does not require any parametric assumption.

A kinetic Monte Carlo simulation method of van der Waals epitaxy for atomistic nucleation-growth processes of transition metal dichalcogenides.

PubMed

Nie, Yifan; Liang, Chaoping; Cha, Pil-Ryung; Colombo, Luigi; Wallace, Robert M; Cho, Kyeongjae

2017-06-07

Controlled growth of crystalline solids is critical for device applications, and atomistic modeling methods have been developed for bulk crystalline solids. Kinetic Monte Carlo (KMC) simulation method provides detailed atomic scale processes during a solid growth over realistic time scales, but its application to the growth modeling of van der Waals (vdW) heterostructures has not yet been developed. Specifically, the growth of single-layered transition metal dichalcogenides (TMDs) is currently facing tremendous challenges, and a detailed understanding based on KMC simulations would provide critical guidance to enable controlled growth of vdW heterostructures. In this work, a KMC simulation method is developed for the growth modeling on the vdW epitaxy of TMDs. The KMC method has introduced full material parameters for TMDs in bottom-up synthesis: metal and chalcogen adsorption/desorption/diffusion on substrate and grown TMD surface, TMD stacking sequence, chalcogen/metal ratio, flake edge diffusion and vacancy diffusion. The KMC processes result in multiple kinetic behaviors associated with various growth behaviors observed in experiments. Different phenomena observed during vdW epitaxy process are analysed in terms of complex competitions among multiple kinetic processes. The KMC method is used in the investigation and prediction of growth mechanisms, which provide qualitative suggestions to guide experimental study.

Optimizing the Calculation of DM,CO and VC via the Single Breath Single Oxygen Tension DLCO/NO Method

PubMed Central

Coffman, Kirsten E.; Taylor, Bryan J.; Carlson, Alex R.; Wentz, Robert J.; Johnson, Bruce D.

2015-01-01

Alveolar-capillary membrane conductance (DM,CO) and pulmonary-capillary blood volume (VC) are calculated via lung diffusing capacity for carbon monoxide (DLCO) and nitric oxide (DLNO) using the single breath, single oxygen tension (single-FiO2) method. However, two calculation parameters, the reaction rate of carbon monoxide with blood (θCO) and the DM,NO/DM,CO ratio (α-ratio), are controversial. This study systematically determined optimal θCO and α-ratio values to be used in the single-FiO2 method that yielded the most similar DM,CO and VC values compared to the ‘gold-standard’ multiple-FiO2 method. Eleven healthy subjects performed single breath DLCO/DLNO maneuvers at rest and during exercise. DM,CO and VC were calculated via the single-FiO2 and multiple-FiO2 methods by implementing seven θCO equations and a range of previously reported α-ratios. The RP θCO equation (Reeves and Park, Respiration physiology 88:1–21, 1992.) and an α-ratio of 4.0–4.4 yielded DM,CO and VC values that were most similar between methods. The RP θCO equation and an experimental α-ratio should be used in future studies. PMID:26521031

Nonadiabatic dynamics of electron transfer in solution: Explicit and implicit solvent treatments that include multiple relaxation time scales

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

Schwerdtfeger, Christine A.; Soudackov, Alexander V.; Hammes-Schiffer, Sharon, E-mail: shs3@illinois.edu

2014-01-21

The development of efficient theoretical methods for describing electron transfer (ET) reactions in condensed phases is important for a variety of chemical and biological applications. Previously, dynamical dielectric continuum theory was used to derive Langevin equations for a single collective solvent coordinate describing ET in a polar solvent. In this theory, the parameters are directly related to the physical properties of the system and can be determined from experimental data or explicit molecular dynamics simulations. Herein, we combine these Langevin equations with surface hopping nonadiabatic dynamics methods to calculate the rate constants for thermal ET reactions in polar solvents formore » a wide range of electronic couplings and reaction free energies. Comparison of explicit and implicit solvent calculations illustrates that the mapping from explicit to implicit solvent models is valid even for solvents exhibiting complex relaxation behavior with multiple relaxation time scales and a short-time inertial response. The rate constants calculated for implicit solvent models with a single solvent relaxation time scale corresponding to water, acetonitrile, and methanol agree well with analytical theories in the Golden rule and solvent-controlled regimes, as well as in the intermediate regime. The implicit solvent models with two relaxation time scales are in qualitative agreement with the analytical theories but quantitatively overestimate the rate constants compared to these theories. Analysis of these simulations elucidates the importance of multiple relaxation time scales and the inertial component of the solvent response, as well as potential shortcomings of the analytical theories based on single time scale solvent relaxation models. This implicit solvent approach will enable the simulation of a wide range of ET reactions via the stochastic dynamics of a single collective solvent coordinate with parameters that are relevant to experimentally accessible systems.« less

Multiscale Simulation and Modeling of Multilayer Heteroepitactic Growth of C60 on Pentacene.

PubMed

Acevedo, Yaset M; Cantrell, Rebecca A; Berard, Philip G; Koch, Donald L; Clancy, Paulette

2016-03-29

We apply multiscale methods to describe the strained growth of multiple layers of C60 on a thin film of pentacene. We study this growth in the presence of a monolayer pentacene step to compare our simulations to recent experimental studies by Breuer and Witte of submonolayer growth in the presence of monolayer steps. The molecular-level details of this organic semiconductor interface have ramifications on the macroscale structural and electronic behavior of this system and allow us to describe several unexplained experimental observations for this system. The growth of a C60 thin film on a pentacene surface is complicated by the differing crystal habits of the two component species, leading to heteroepitactical growth. In order to probe this growth, we use three computational methods that offer different approaches to coarse-graining the system and differing degrees of computational efficiency. We present a new, efficient reaction-diffusion continuum model for 2D systems whose results compare well with mesoscale kinetic Monte Carlo (KMC) results for submonolayer growth. KMC extends our ability to simulate multiple layers but requires a library of predefined rates for event transitions. Coarse-grained molecular dynamics (CGMD) circumvents KMC's need for predefined lattices, allowing defects and grain boundaries to provide a more realistic thin film morphology. For multilayer growth, in this particularly suitable candidate for coarse-graining, CGMD is a preferable approach to KMC. Combining the results from these three methods, we show that the lattice strain induced by heteroepitactical growth promotes 3D growth and the creation of defects in the first monolayer. The CGMD results are consistent with experimental results on the same system by Conrad et al. and by Breuer and Witte in which C60 aggregates change from a 2D structure at low temperature to 3D clusters along the pentacene step edges at higher temperatures.

[Experimental research of turbidity influence on water quality monitoring of COD in UV-visible spectroscopy].

PubMed

Tang, Bin; Wei, Biao; Wu, De-Cao; Mi, De-Ling; Zhao, Jing-Xiao; Feng, Peng; Jiang, Shang-Hai; Mao, Ben-Jiang

2014-11-01

Eliminating turbidity is a direct effect spectroscopy detection of COD key technical problems. This stems from the UV-visible spectroscopy detected key quality parameters depend on an accurate and effective analysis of water quality parameters analytical model, and turbidity is an important parameter that affects the modeling. In this paper, we selected formazine turbidity solution and standard solution of potassium hydrogen phthalate to study the turbidity affect of UV--visible absorption spectroscopy detection of COD, at the characteristics wavelength of 245, 300, 360 and 560 nm wavelength point several characteristics with the turbidity change in absorbance method of least squares curve fitting, thus analyzes the variation of absorbance with turbidity. The results show, In the ultraviolet range of 240 to 380 nm, as the turbidity caused by particle produces compounds to the organics, it is relatively complicated to test the turbidity affections on the water Ultraviolet spectra; in the visible region of 380 to 780 nm, the turbidity of the spectrum weakens with wavelength increases. Based on this, this paper we study the multiplicative scatter correction method affected by the turbidity of the water sample spectra calibration test, this method can correct water samples spectral affected by turbidity. After treatment, by comparing the spectra before, the results showed that the turbidity caused by wavelength baseline shift points have been effectively corrected, and features in the ultraviolet region has not diminished. Then we make multiplicative scatter correction for the three selected UV liquid-visible absorption spectroscopy, experimental results shows that on the premise of saving the characteristic of the Ultraviolet-Visible absorption spectrum of water samples, which not only improve the quality of COD spectroscopy detection SNR, but also for providing an efficient data conditioning regimen for establishing an accurate of the chemical measurement methods.

PIV measurements of airflow past multiple cylinders

NASA Astrophysics Data System (ADS)

Wodziak, Waldemar; Sobczyk, Jacek

2018-06-01

Flow characteristics in vicinity of six circular cylinders aligned inline was investigated experimentally by means of PIV method. Experiments were conducted in a low speed closed circuit wind tunnel. Inflow velocity was 1.2 m/s which corresponds to Re=1600 based on the cylinder diameter. Spacing ratio between cylinders L/D was 1.5. Instantaneous and averaged velocity fields were presented. Experiments were designed in order to use their results as a test case for future numerical calculations.

Statistical characteristics of excess fiber length in loose tubes of optical cable

NASA Astrophysics Data System (ADS)

Andreev, Vladimir A.; Gavryushin, Sergey A.; Popov, Boris V.; Popov, Victor B.; Vazhdaev, Michael A.

2017-04-01

This paper presents an analysis of the data measurements of excess fiber length in the loose tubes of optical cable during the post-process quality control of ready-made products. At determining estimates of numerical characteristics of excess fiber length method of results processing of direct multiple equally accurate measurements has been used. The results of experimental research of the excess length value at the manufacturing technology of loose tube remains constant.

Thermal Modeling of the Injection of Standard and Thermally Insulated Cored Wire

NASA Astrophysics Data System (ADS)

Castro-Cedeno, E.-I.; Jardy, A.; Carré, A.; Gerardin, S.; Bellot, J. P.

2017-12-01

Cored wire injection is a widespread method used to perform alloying additions during ferrous and non-ferrous liquid metal treatment. The wire consists of a metal casing that is tightly wrapped around a core of material; the casing delays the release of the material as the wire is immersed into the melt. This method of addition presents advantages such as higher repeatability and yield of cored material with respect to bulk additions. Experimental and numerical work has been performed by several authors on the subject of alloy additions, spherical and cylindrical geometries being mainly considered. Surprisingly this has not been the case for cored wire, where the reported experimental or numerical studies are scarce. This work presents a 1-D finite volume numerical model aimed for the simulation of the thermal phenomena which occurs when the wire is injected into a liquid metal bath. It is currently being used as a design tool for the conception of new types of cored wire. A parametric study on the effect of injection velocity and steel casing thickness for an Al cored wire immersed into a steel melt at 1863 K (1590 °C) is presented. The standard single casing wire is further compared against a wire with multiple casings. Numerical results show that over a certain range of injection velocities, the core contents' release is delayed in the multiple casing when compared to a single casing wire.

An R package for the integrated analysis of metabolomics and spectral data.

PubMed

Costa, Christopher; Maraschin, Marcelo; Rocha, Miguel

2016-06-01

Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as nuclear magnetic resonance, gas or liquid chromatography, mass spectrometry, infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Measurement of the Infinite Multiplication Constant of Natural Uranium--Graphite Lattices in the RB-1 Critical Assembly by Means of the Zero Reactivity Method. MISURA DELLA COSTANTE DI MOLTIPLICAZIONE INFINITA DI RETICOLI A URANIO NATURALE E GRAFITE NELL'INSIEME CRITICO RB-1 CON IL METODO DELLA REATTIVITA' NULLA (in Italian)

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

Ghillardotti, G.

1966-07-01

To reduce uncertainties to the minimum, measurements in the RB-1 were conducted on the same materials and with the same instrumentation as those used previously in MARIUS. The values measured in the RB-1, compared with the already known substitution data, are as follows: (a) the difference between the multiplication and the absorption intensity; (b) the fine structure of the flux in the cell; (c) the Pu/U index. The infinite mutiplication factor K{sub infinity} is obtained by combining measurements (a) and (b). The results of this research can be summed up as follows: 1. A consistent and complete experimental procedure hasmore » been devised for measuring the K{sub infinity} of natural uranium/graphite lattices by means of the zero reactivity method. The same applies to the procedure for analysis of the experimental data. 2. The error in (K{sub infinity} -- 1) inherent in the measurement can in our opinion be reduced to 2%. This limit was reached in the last experiment on lattices consisting of tubular elements. 3. Agreement proved to be good with the results obtained by the CEA in the critical assembly MARIUS. (auth)« less

Beamspace fast fully adaptive brain source localization for limited data sequences

NASA Astrophysics Data System (ADS)

Ravan, Maryam

2017-05-01

In the electroencephalogram (EEG) or magnetoencephalogram (MEG) context, brain source localization methods that rely on estimating second order statistics often fail when the observations are taken over a short time interval, especially when the number of electrodes is large. To address this issue, in previous study, we developed a multistage adaptive processing called fast fully adaptive (FFA) approach that can significantly reduce the required sample support while still processing all available degrees of freedom (DOFs). This approach processes the observed data in stages through a decimation procedure. In this study, we introduce a new form of FFA approach called beamspace FFA. We first divide the brain into smaller regions and transform the measured data from the source space to the beamspace in each region. The FFA approach is then applied to the beamspaced data of each region. The goal of this modification is to benefit the correlation sensitivity reduction between sources in different brain regions. To demonstrate the performance of the beamspace FFA approach in the limited data scenario, simulation results with multiple deep and cortical sources as well as experimental results are compared with regular FFA and widely used FINE approaches. Both simulation and experimental results demonstrate that the beamspace FFA method can localize different types of multiple correlated brain sources in low signal to noise ratios more accurately with limited data.

Interval sampling methods and measurement error: a computer simulation.

PubMed

Wirth, Oliver; Slaven, James; Taylor, Matthew A

2014-01-01

A simulation study was conducted to provide a more thorough account of measurement error associated with interval sampling methods. A computer program simulated the application of momentary time sampling, partial-interval recording, and whole-interval recording methods on target events randomly distributed across an observation period. The simulation yielded measures of error for multiple combinations of observation period, interval duration, event duration, and cumulative event duration. The simulations were conducted up to 100 times to yield measures of error variability. Although the present simulation confirmed some previously reported characteristics of interval sampling methods, it also revealed many new findings that pertain to each method's inherent strengths and weaknesses. The analysis and resulting error tables can help guide the selection of the most appropriate sampling method for observation-based behavioral assessments. © Society for the Experimental Analysis of Behavior.

Simple and inexpensive microfluidic devices for the generation of monodisperse multiple emulsions

NASA Astrophysics Data System (ADS)

Li, Er Qiang; Zhang, Jia Ming; Thoroddsen, Sigurdur T.

2014-01-01

Droplet-based microfluidic devices have become a preferred versatile platform for various fields in physics, chemistry and biology. Polydimethylsiloxane soft lithography, the mainstay for fabricating microfluidic devices, usually requires the usage of expensive apparatus and a complex manufacturing procedure. Here, we report the design and fabrication of simple and inexpensive microfluidic devices based on microscope glass slides and pulled glass capillaries, for generating monodisperse multiple emulsions. The advantages of our method lie in a simple manufacturing procedure, inexpensive processing equipment and flexibility in the surface modification of the designed microfluidic devices. Different types of devices have been designed and tested and the experimental results demonstrated their robustness for preparing monodisperse single, double, triple and multi-component emulsions.

Tracking and recognition of multiple human targets moving in a wireless pyroelectric infrared sensor network.

PubMed

Xiong, Ji; Li, Fangmin; Zhao, Ning; Jiang, Na

2014-04-22

With characteristics of low-cost and easy deployment, the distributed wireless pyroelectric infrared sensor network has attracted extensive interest, which aims to make it an alternate infrared video sensor in thermal biometric applications for tracking and identifying human targets. In these applications, effectively processing signals collected from sensors and extracting the features of different human targets has become crucial. This paper proposes the application of empirical mode decomposition and the Hilbert-Huang transform to extract features of moving human targets both in the time domain and the frequency domain. Moreover, the support vector machine is selected as the classifier. The experimental results demonstrate that by using this method the identification rates of multiple moving human targets are around 90%.

Prediction of Ionizing Radiation Resistance in Bacteria Using a Multiple Instance Learning Model.

PubMed

Aridhi, Sabeur; Sghaier, Haïtham; Zoghlami, Manel; Maddouri, Mondher; Nguifo, Engelbert Mephu

2016-01-01

Ionizing-radiation-resistant bacteria (IRRB) are important in biotechnology. In this context, in silico methods of phenotypic prediction and genotype-phenotype relationship discovery are limited. In this work, we analyzed basal DNA repair proteins of most known proteome sequences of IRRB and ionizing-radiation-sensitive bacteria (IRSB) in order to learn a classifier that correctly predicts this bacterial phenotype. We formulated the problem of predicting bacterial ionizing radiation resistance (IRR) as a multiple-instance learning (MIL) problem, and we proposed a novel approach for this purpose. We provide a MIL-based prediction system that classifies a bacterium to either IRRB or IRSB. The experimental results of the proposed system are satisfactory with 91.5% of successful predictions.

Using input command pre-shaping to suppress multiple mode vibration

NASA Technical Reports Server (NTRS)

Hyde, James M.; Seering, Warren P.

1990-01-01

Spacecraft, space-borne robotic systems, and manufacturing equipment often utilize lightweight materials and configurations that give rise to vibration problems. Prior research has led to the development of input command pre-shapers that can significantly reduce residual vibration. These shapers exhibit marked insensitivity to errors in natural frequency estimates and can be combined to minimize vibration at more than one frequency. This paper presents a method for the development of multiple mode input shapers which are simpler to implement than previous designs and produce smaller system response delays. The new technique involves the solution of a group of simultaneous non-linear impulse constraint equations. The resulting shapers were tested on a model of MACE, an MIT/NASA experimental flexible structure.

Cultural psychiatry: research strategies and future directions.

PubMed

Kirmayer, Laurence J; Ban, Lauren

2013-01-01

This chapter reviews some key aspects of current research in cultural psychiatry and explores future prospects. The first section discusses the multiple meanings of culture in the contemporary world and their relevance for understanding mental health and illness. The next section considers methodological strategies for unpacking the concept of culture and studying the impact of cultural variables, processes and contexts. Multiple methods are needed to address the many different components or dimensions of cultural identity and experience that constitute local worlds, ways of life or systems of knowledge. Quantitative and observational methods of clinical epidemiology and experimental science as well as qualitative ethnographic methods are needed to capture crucial aspects of culture as systems of meaning and practice. Emerging issues in cultural psychiatric research include: cultural variations in illness experience and expression; the situated nature of cognition and emotion; cultural configurations of self and personhood; concepts of mental disorder and mental health literacy; and the prospect of ecosocial models of health and culturally based interventions. The conclusion considers the implications of the emerging perspectives from cultural neuroscience for psychiatric theory and practice. Copyright © 2013 S. Karger AG, Basel.

Resolving occlusion and segmentation errors in multiple video object tracking

NASA Astrophysics Data System (ADS)

Cheng, Hsu-Yung; Hwang, Jenq-Neng

2009-02-01

In this work, we propose a method to integrate the Kalman filter and adaptive particle sampling for multiple video object tracking. The proposed framework is able to detect occlusion and segmentation error cases and perform adaptive particle sampling for accurate measurement selection. Compared with traditional particle filter based tracking methods, the proposed method generates particles only when necessary. With the concept of adaptive particle sampling, we can avoid degeneracy problem because the sampling position and range are dynamically determined by parameters that are updated by Kalman filters. There is no need to spend time on processing particles with very small weights. The adaptive appearance for the occluded object refers to the prediction results of Kalman filters to determine the region that should be updated and avoids the problem of using inadequate information to update the appearance under occlusion cases. The experimental results have shown that a small number of particles are sufficient to achieve high positioning and scaling accuracy. Also, the employment of adaptive appearance substantially improves the positioning and scaling accuracy on the tracking results.

Laser-Based Pedestrian Tracking in Outdoor Environments by Multiple Mobile Robots

PubMed Central

Ozaki, Masataka; Kakimuma, Kei; Hashimoto, Masafumi; Takahashi, Kazuhiko

2012-01-01

This paper presents an outdoors laser-based pedestrian tracking system using a group of mobile robots located near each other. Each robot detects pedestrians from its own laser scan image using an occupancy-grid-based method, and the robot tracks the detected pedestrians via Kalman filtering and global-nearest-neighbor (GNN)-based data association. The tracking data is broadcast to multiple robots through intercommunication and is combined using the covariance intersection (CI) method. For pedestrian tracking, each robot identifies its own posture using real-time-kinematic GPS (RTK-GPS) and laser scan matching. Using our cooperative tracking method, all the robots share the tracking data with each other; hence, individual robots can always recognize pedestrians that are invisible to any other robot. The simulation and experimental results show that cooperating tracking provides the tracking performance better than conventional individual tracking does. Our tracking system functions in a decentralized manner without any central server, and therefore, this provides a degree of scalability and robustness that cannot be achieved by conventional centralized architectures. PMID:23202171

Technical Note: Harmonic analysis applied to MR image distortion fields specific to arbitrarily shaped volumes.

PubMed

Stanescu, T; Jaffray, D

2018-05-25

Magnetic resonance imaging is expected to play a more important role in radiation therapy given the recent developments in MR-guided technologies. MR images need to consistently show high spatial accuracy to facilitate RT specific tasks such as treatment planning and in-room guidance. The present study investigates a new harmonic analysis method for the characterization of complex 3D fields derived from MR images affected by system-related distortions. An interior Dirichlet problem based on solving the Laplace equation with boundary conditions (BCs) was formulated for the case of a 3D distortion field. The second-order boundary value problem (BVP) was solved using a finite elements method (FEM) for several quadratic geometries - i.e., sphere, cylinder, cuboid, D-shaped, and ellipsoid. To stress-test the method and generalize it, the BVP was also solved for more complex surfaces such as a Reuleaux 9-gon and the MR imaging volume of a scanner featuring a high degree of surface irregularities. The BCs were formatted from reference experimental data collected with a linearity phantom featuring a volumetric grid structure. The method was validated by comparing the harmonic analysis results with the corresponding experimental reference fields. The harmonic fields were found to be in good agreement with the baseline experimental data for all geometries investigated. In the case of quadratic domains, the percentage of sampling points with residual values larger than 1 mm were 0.5% and 0.2% for the axial components and vector magnitude, respectively. For the general case of a domain defined by the available MR imaging field of view, the reference data showed a peak distortion of about 12 mm and 79% of the sampling points carried a distortion magnitude larger than 1 mm (tolerance intrinsic to the experimental data). The upper limits of the residual values after comparison with the harmonic fields showed max and mean of 1.4 mm and 0.25 mm, respectively, with only 1.5% of sampling points exceeding 1 mm. A novel harmonic analysis approach relying on finite element methods was introduced and validated for multiple volumes with surface shape functions ranging from simple to highly complex. Since a boundary value problem is solved the method requires input data from only the surface of the desired domain of interest. It is believed that the harmonic method will facilitate (a) the design of new phantoms dedicated for the quantification of MR image distortions in large volumes and (b) an integrative approach of combining multiple imaging tests specific to radiotherapy into a single test object for routine imaging quality control. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Multiple-path model of spectral reflectance of a dyed fabric.

PubMed

Rogers, Geoffrey; Dalloz, Nicolas; Fournel, Thierry; Hebert, Mathieu

2017-05-01

Experimental results are presented of the spectral reflectance of a dyed fabric as analyzed by a multiple-path model of reflection. The multiple-path model provides simple analytic expressions for reflection and transmission of turbid media by applying the Beer-Lambert law to each path through the medium and summing over all paths, each path weighted by its probability. The path-length probability is determined by a random-walk analysis. The experimental results presented here show excellent agreement with predictions made by the model.

Robust decentralized controller for minimizing coupling effect in single inductor multiple output DC-DC converter operating in continuous conduction mode.

PubMed

Medeiros, Renan Landau Paiva de; Barra, Walter; Bessa, Iury Valente de; Chaves Filho, João Edgar; Ayres, Florindo Antonio de Cavalho; Neves, Cleonor Crescêncio das

2018-02-01

This paper describes a novel robust decentralized control design methodology for a single inductor multiple output (SIMO) DC-DC converter. Based on a nominal multiple input multiple output (MIMO) plant model and performance requirements, a pairing input-output analysis is performed to select the suitable input to control each output aiming to attenuate the loop coupling. Thus, the plant uncertainty limits are selected and expressed in interval form with parameter values of the plant model. A single inductor dual output (SIDO) DC-DC buck converter board is developed for experimental tests. The experimental results show that the proposed methodology can maintain a desirable performance even in the presence of parametric uncertainties. Furthermore, the performance indexes calculated from experimental data show that the proposed methodology outperforms classical MIMO control techniques. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Experimental evidence of quantum radiation reaction in aligned crystals.

PubMed

Wistisen, Tobias N; Di Piazza, Antonino; Knudsen, Helge V; Uggerhøj, Ulrik I

2018-02-23

Quantum radiation reaction is the influence of multiple photon emissions from a charged particle on the particle's dynamics, characterized by a significant energy-momentum loss per emission. Here we report experimental radiation emission spectra from ultrarelativistic positrons in silicon in a regime where quantum radiation reaction effects dominate the positron's dynamics. Our analysis shows that while the widely used quantum approach is overall the best model, it does not completely describe all the data in this regime. Thus, these experimental findings may prompt seeking more generally valid methods to describe quantum radiation reaction. This experiment is a fundamental test of quantum electrodynamics in a regime where the dynamics of charged particles is strongly influenced not only by the external electromagnetic fields but also by the radiation field generated by the charges themselves and where each photon emission may significantly reduce the energy of the charge.

Experimental and theoretical studies of near-ground acoustic radiation propagation in the atmosphere

NASA Astrophysics Data System (ADS)

Belov, Vladimir V.; Burkatovskaya, Yuliya B.; Krasnenko, Nikolai P.; Rakov, Aleksandr S.; Rakov, Denis S.; Shamanaeva, Liudmila G.

2017-11-01

Results of experimental and theoretical studies of the process of near-ground propagation of monochromatic acoustic radiation on atmospheric paths from a source to a receiver taking into account the contribution of multiple scattering on fluctuations of atmospheric temperature and wind velocity, refraction of sound on the wind velocity and temperature gradients, and its reflection by the underlying surface for different models of the atmosphere depending the sound frequency, coefficient of reflection from the underlying surface, propagation distance, and source and receiver altitudes are presented. Calculations were performed by the Monte Carlo method using the local estimation algorithm by the computer program developed by the authors. Results of experimental investigations under controllable conditions are compared with theoretical estimates and results of analytical calculations for the Delany-Bazley impedance model. Satisfactory agreement of the data obtained confirms the correctness of the suggested computer program.

A comparison of between- and within-subjects imitation designs.

PubMed

Kressley, Regina A; Knopf, Monika

2006-12-01

Two experimental methods, which have dominated the study of declarative memory in preverbal children with imitation tasks, namely the deferred imitation and elicited imitation paradigm, differ in the amount of physical contact with test stimuli afforded infants prior to a test for long-term recall. The current study assessed effects of pre- and post-demonstration contact with test stimuli on deferred imitation of novel, single-step unrelated actions with multiple objects by 8(1/2)- and 10(1/2)-month-old infants (N=50). The rate of target action completion after a delay remained consistent at both ages across different conditions of prior contact with test stimuli. This study shows that a within-subjects baseline appraisal is valid within certain experimental parameters and offers a more economical alternative. The results show furthermore that different experimental designs utilized to assess deferred imitation are highly comparable for the first year despite differences in determining baseline.

Tuning Nb–Pt Interactions To Facilitate Fuel Cell Electrocatalysis

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

Ghoshal, Shraboni; Jia, Qingying; Bates, Michael K.

High stability, availability of multiple oxidation states, and accessibility within a wide electrochemical window are the prime features of Nb that make it a favorable candidate for electrocatalysis, especially when it is combined with Pt. However, Nb has been used as a support in the form of oxides in all previously reported Pt–Nb electrocatalysts, and no Pt–Nb alloying phase has been demonstrated hitherto. Herein, we report a multifunctional Pt–Nb composite (PtNb/NbOx-C) where Nb exists both as an alloying component with Pt and as an oxide support and is synthesized by means of a simple wet chemical method. In this work,more » the Pt–Nb alloy phase has been firmly verified with the help of multiple spectroscopic methods. This allows for the experimental evidence of the theoretical prediction that Pt–Nb alloy interactions improve the oxygen reduction reaction (ORR) activity of Pt. In addition, such a combination of multiphase Nb brings up myriad features encompassing increased ORR durability, immunity to phosphate anion poisoning, enhanced hydrogen oxidation reaction (HOR) activity, and oxidative carbon monoxide (CO) stripping, making this electrocatalyst useful in multiple fuel cell systems.« less

Multiple disturbances classifier for electric signals using adaptive structuring neural networks

NASA Astrophysics Data System (ADS)

Lu, Yen-Ling; Chuang, Cheng-Long; Fahn, Chin-Shyurng; Jiang, Joe-Air

2008-07-01

This work proposes a novel classifier to recognize multiple disturbances for electric signals of power systems. The proposed classifier consists of a series of pipeline-based processing components, including amplitude estimator, transient disturbance detector, transient impulsive detector, wavelet transform and a brand-new neural network for recognizing multiple disturbances in a power quality (PQ) event. Most of the previously proposed methods usually treated a PQ event as a single disturbance at a time. In practice, however, a PQ event often consists of various types of disturbances at the same time. Therefore, the performances of those methods might be limited in real power systems. This work considers the PQ event as a combination of several disturbances, including steady-state and transient disturbances, which is more analogous to the real status of a power system. Six types of commonly encountered power quality disturbances are considered for training and testing the proposed classifier. The proposed classifier has been tested on electric signals that contain single disturbance or several disturbances at a time. Experimental results indicate that the proposed PQ disturbance classification algorithm can achieve a high accuracy of more than 97% in various complex testing cases.

Biomolecular computers with multiple restriction enzymes

PubMed Central

Sakowski, Sebastian; Krasinski, Tadeusz; Waldmajer, Jacek; Sarnik, Joanna; Blasiak, Janusz; Poplawski, Tomasz

2017-01-01

Abstract The development of conventional, silicon-based computers has several limitations, including some related to the Heisenberg uncertainty principle and the von Neumann “bottleneck”. Biomolecular computers based on DNA and proteins are largely free of these disadvantages and, along with quantum computers, are reasonable alternatives to their conventional counterparts in some applications. The idea of a DNA computer proposed by Ehud Shapiro’s group at the Weizmann Institute of Science was developed using one restriction enzyme as hardware and DNA fragments (the transition molecules) as software and input/output signals. This computer represented a two-state two-symbol finite automaton that was subsequently extended by using two restriction enzymes. In this paper, we propose the idea of a multistate biomolecular computer with multiple commercially available restriction enzymes as hardware. Additionally, an algorithmic method for the construction of transition molecules in the DNA computer based on the use of multiple restriction enzymes is presented. We use this method to construct multistate, biomolecular, nondeterministic finite automata with four commercially available restriction enzymes as hardware. We also describe an experimental applicaton of this theoretical model to a biomolecular finite automaton made of four endonucleases. PMID:29064510

Decomposition and extraction: a new framework for visual classification.

PubMed

Fang, Yuqiang; Chen, Qiang; Sun, Lin; Dai, Bin; Yan, Shuicheng

2014-08-01

In this paper, we present a novel framework for visual classification based on hierarchical image decomposition and hybrid midlevel feature extraction. Unlike most midlevel feature learning methods, which focus on the process of coding or pooling, we emphasize that the mechanism of image composition also strongly influences the feature extraction. To effectively explore the image content for the feature extraction, we model a multiplicity feature representation mechanism through meaningful hierarchical image decomposition followed by a fusion step. In particularly, we first propose a new hierarchical image decomposition approach in which each image is decomposed into a series of hierarchical semantical components, i.e, the structure and texture images. Then, different feature extraction schemes can be adopted to match the decomposed structure and texture processes in a dissociative manner. Here, two schemes are explored to produce property related feature representations. One is based on a single-stage network over hand-crafted features and the other is based on a multistage network, which can learn features from raw pixels automatically. Finally, those multiple midlevel features are incorporated by solving a multiple kernel learning task. Extensive experiments are conducted on several challenging data sets for visual classification, and experimental results demonstrate the effectiveness of the proposed method.

Fast and robust brain tumor segmentation using level set method with multiple image information.

PubMed

Lok, Ka Hei; Shi, Lin; Zhu, Xianlun; Wang, Defeng

2017-01-01

Brain tumor segmentation is a challenging task for its variation in intensity. The phenomenon is caused by the inhomogeneous content of tumor tissue and the choice of imaging modality. In 2010 Zhang developed the Selective Binary Gaussian Filtering Regularizing Level Set (SBGFRLS) model that combined the merits of edge-based and region-based segmentation. To improve the SBGFRLS method by modifying the singed pressure force (SPF) term with multiple image information and demonstrate effectiveness of proposed method on clinical images. In original SBGFRLS model, the contour evolution direction mainly depends on the SPF. By introducing a directional term in SPF, the metric could control the evolution direction. The SPF is altered by statistic values enclosed by the contour. This concept can be extended to jointly incorporate multiple image information. The new SPF term is expected to bring a solution for blur edge problem in brain tumor segmentation. The proposed method is validated with clinical images including pre- and post-contrast magnetic resonance images. The accuracy and robustness is compared with sensitivity, specificity, DICE similarity coefficient and Jaccard similarity index. Experimental results show improvement, in particular the increase of sensitivity at the same specificity, in segmenting all types of tumors except for the diffused tumor. The novel brain tumor segmentation method is clinical-oriented with fast, robust and accurate implementation and a minimal user interaction. The method effectively segmented homogeneously enhanced, non-enhanced, heterogeneously-enhanced, and ring-enhanced tumor under MR imaging. Though the method is limited by identifying edema and diffuse tumor, several possible solutions are suggested to turn the curve evolution into a fully functional clinical diagnosis tool.

Development and Validation of a Statistical Shape Modeling-Based Finite Element Model of the Cervical Spine Under Low-Level Multiple Direction Loading Conditions

PubMed Central

Bredbenner, Todd L.; Eliason, Travis D.; Francis, W. Loren; McFarland, John M.; Merkle, Andrew C.; Nicolella, Daniel P.

2014-01-01

Cervical spinal injuries are a significant concern in all trauma injuries. Recent military conflicts have demonstrated the substantial risk of spinal injury for the modern warfighter. Finite element models used to investigate injury mechanisms often fail to examine the effects of variation in geometry or material properties on mechanical behavior. The goals of this study were to model geometric variation for a set of cervical spines, to extend this model to a parametric finite element model, and, as a first step, to validate the parametric model against experimental data for low-loading conditions. Individual finite element models were created using cervical spine (C3–T1) computed tomography data for five male cadavers. Statistical shape modeling (SSM) was used to generate a parametric finite element model incorporating variability of spine geometry, and soft-tissue material property variation was also included. The probabilistic loading response of the parametric model was determined under flexion-extension, axial rotation, and lateral bending and validated by comparison to experimental data. Based on qualitative and quantitative comparison of the experimental loading response and model simulations, we suggest that the model performs adequately under relatively low-level loading conditions in multiple loading directions. In conclusion, SSM methods coupled with finite element analyses within a probabilistic framework, along with the ability to statistically validate the overall model performance, provide innovative and important steps toward describing the differences in vertebral morphology, spinal curvature, and variation in material properties. We suggest that these methods, with additional investigation and validation under injurious loading conditions, will lead to understanding and mitigating the risks of injury in the spine and other musculoskeletal structures. PMID:25506051