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Sample records for hybrid homology modeling

  1. Modeling Non-homologous End Joining

    Science.gov (United States)

    Li, Yongfeng

    2013-01-01

    Non-homologous end joining (NHEJ) is the dominant DNA double strand break (DSB) repair pathway and involves several NHEJ proteins such as Ku, DNA-PKcs, XRCC4, Ligase IV and so on. Once DSBs are generated, Ku is first recruited to the DNA end, followed by other NHEJ proteins for DNA end processing and ligation. Because of the direct ligation of break ends without the need for a homologous template, NHEJ turns out to be an error-prone but efficient repair pathway. Some mechanisms have been proposed of how the efficiency of NHEJ repair is affected. The type of DNA damage is an important factor of NHEJ repair. For instance, the length of DNA fragment may determine the recruitment efficiency of NHEJ protein such as Ku [1], or the complexity of the DNA breaks [2] is accounted for the choice of NHEJ proteins and subpathway of NHEJ repair. On the other hand, the chromatin structure also plays a role of the accessibility of NHEJ protein to the DNA damage site. In this talk, some mathematical models of NHEJ, that consist of series of biochemical reactions complying with the laws of chemical reaction (e.g. mass action, etc.), will be introduced. By mathematical and numerical analysis and parameter estimation, the models are able to capture the qualitative biological features and show good agreement with experimental data. As conclusions, from the viewpoint of modeling, how the NHEJ proteins are recruited will be first discussed for connection between the classical sequential model [4] and recently proposed two-phase model [5]. Then how the NHEJ repair pathway is affected, by the length of DNA fragment [6], the complexity of DNA damage [7] and the chromatin structure [8], will be addressed

  2. CPHmodels-3.0--remote homology modeling using structure-guided sequence profiles

    DEFF Research Database (Denmark)

    Nielsen, Morten; Lundegaard, Claus; Lund, Ole

    2010-01-01

    CPHmodels-3.0 is a web server predicting protein 3D structure by use of single template homology modeling. The server employs a hybrid of the scoring functions of CPHmodels-2.0 and a novel remote homology-modeling algorithm. A query sequence is first attempted modeled using the fast CPHmodels-2.......0 profile-profile scoring function suitable for close homology modeling. The new computational costly remote homology-modeling algorithm is only engaged provided that no suitable PDB template is identified in the initial search. CPHmodels-3.0 was benchmarked in the CASP8 competition and produced models.......3 A. These performance values place the CPHmodels-3.0 method in the group of high performing 3D prediction tools. Beside its accuracy, one of the important features of the method is its speed. For most queries, the response time of the server is...

  3. A geometric model for Hochschild homology of Soergel bimodules

    DEFF Research Database (Denmark)

    Webster, Ben; Williamson, Geordie

    2008-01-01

    An important step in the calculation of the triply graded link homology of Khovanov and Rozansky is the determination of the Hochschild homology of Soergel bimodules for SL(n). We present a geometric model for this Hochschild homology for any simple group G, as B–equivariant intersection cohomology...... on generators whose degree is explicitly determined by the geometry of the orbit closure, and to describe its Hilbert series, proving a conjecture of Jacob Rasmussen....

  4. Low-Threshold Lasing from 2D Homologous Organic-Inorganic Hybrid Ruddlesden-Popper Perovskite Single Crystals.

    Science.gov (United States)

    Raghavan, Chinnambedu Murugesan; Chen, Tzu-Pei; Li, Shao-Sian; Chen, Wei-Liang; Lo, Chao-Yuan; Liao, Yu-Ming; Haider, Golam; Lin, Cheng-Chieh; Chen, Chia-Chun; Sankar, Raman; Chang, Yu-Ming; Chou, Fang-Cheng; Chen, Chun-Wei

    2018-05-09

    Organic-inorganic hybrid two-dimensional (2D) perovskites have recently attracted great attention in optical and optoelectronic applications due to their inherent natural quantum-well structure. We report the growth of high-quality millimeter-sized single crystals belonging to homologous two-dimensional (2D) hybrid organic-inorganic Ruddelsden-Popper perovskites (RPPs) of (BA) 2 (MA) n-1 Pb n I 3 n+1 ( n = 1, 2, and 3) by a slow evaporation at a constant-temperature (SECT) solution-growth strategy. The as-grown 2D hybrid perovskite single crystals exhibit excellent crystallinity, phase purity, and spectral uniformity. Low-threshold lasing behaviors with different emission wavelengths at room temperature have been observed from the homologous 2D hybrid RPP single crystals. Our result demonstrates that solution-growth homologous organic-inorganic hybrid 2D perovskite single crystals open up a new window as a promising candidate for optical gain media.

  5. Homology of polytene elements between Drosophila and Zaprionus determined by in situ hybridization in Zaprionus indianus.

    Science.gov (United States)

    Campos, S R C; Rieger, T T; Santos, J F

    2007-05-09

    The drosophilid Zaprionus indianus due to its economical importance as an insect pest in Brazil deserves more investigation into its genetics. Its mitotic karyotype and a line-drawing map of its polytene chromosomes are already available. This paper presents a photomap of Z. indianus polytene chromosomes, which was used as the reference map for identification of sections marked by in situ hybridization with gene probes. Hybridization signals for Hsp70 and Hsr-omega were detected, respectively, in sections 34B and 32C of chromosome V of Z. indianus, which indicates its homology to the chromosomal arm 3R of Drosophila melanogaster and, therefore, to Muller's element E. The main signal for Hsp83 gene probe hybridization was in section 17C of Z. indianus chromosome III, suggesting its homology to arm 3L of D. melanogaster and to element D of Muller. The Ubi probe hybridized in sections 10C of chromosome II and 17A of chromosome III. Probably the 17A is the polyubiquitin locus, with homology to arm 3L of D. melanogaster and to the mullerian D element, as suggested also by Hsp83 gene location. The Br-C gene was mapped in section 1D, near the tip of the X chromosome, indicating its homology to the X chromosome of D. melanogaster and to mullerian element A. The Dpp gene probe hybridized mainly in the section 32A of chromosome V and, at lower frequencies to other sections, although no signal was observed as expected in the correspondent mullerian B element. This result led to the suggestion of a rearrangement including the Dpp locus in Z. indianus, the secondary signals possibly pointing to related genes of the TGF-beta family. In conclusion, the results indicate that chromosomes X, III, V of Z. indianus are respectively correspondents to elements A, D, and E of Muller. At least chromosome V of Z. indianus seems to share synteny with the 3R arm of D. melanogaster, as indicated by the relative positions of Hsp70 and Hsr-omega, although the Dpp gene indicates a disruption of

  6. CPHmodels-3.0--remote homology modeling using structure-guided sequence profiles.

    Science.gov (United States)

    Nielsen, Morten; Lundegaard, Claus; Lund, Ole; Petersen, Thomas Nordahl

    2010-07-01

    CPHmodels-3.0 is a web server predicting protein 3D structure by use of single template homology modeling. The server employs a hybrid of the scoring functions of CPHmodels-2.0 and a novel remote homology-modeling algorithm. A query sequence is first attempted modeled using the fast CPHmodels-2.0 profile-profile scoring function suitable for close homology modeling. The new computational costly remote homology-modeling algorithm is only engaged provided that no suitable PDB template is identified in the initial search. CPHmodels-3.0 was benchmarked in the CASP8 competition and produced models for 94% of the targets (117 out of 128), 74% were predicted as high reliability models (87 out of 117). These achieved an average RMSD of 4.6 A when superimposed to the 3D structure. The remaining 26% low reliably models (30 out of 117) could superimpose to the true 3D structure with an average RMSD of 9.3 A. These performance values place the CPHmodels-3.0 method in the group of high performing 3D prediction tools. Beside its accuracy, one of the important features of the method is its speed. For most queries, the response time of the server is web server is available at http://www.cbs.dtu.dk/services/CPHmodels/.

  7. Prefiltering Model for Homology Detection Algorithms on GPU.

    Science.gov (United States)

    Retamosa, Germán; de Pedro, Luis; González, Ivan; Tamames, Javier

    2016-01-01

    Homology detection has evolved over the time from heavy algorithms based on dynamic programming approaches to lightweight alternatives based on different heuristic models. However, the main problem with these algorithms is that they use complex statistical models, which makes it difficult to achieve a relevant speedup and find exact matches with the original results. Thus, their acceleration is essential. The aim of this article was to prefilter a sequence database. To make this work, we have implemented a groundbreaking heuristic model based on NVIDIA's graphics processing units (GPUs) and multicore processors. Depending on the sensitivity settings, this makes it possible to quickly reduce the sequence database by factors between 50% and 95%, while rejecting no significant sequences. Furthermore, this prefiltering application can be used together with multiple homology detection algorithms as a part of a next-generation sequencing system. Extensive performance and accuracy tests have been carried out in the Spanish National Centre for Biotechnology (NCB). The results show that GPU hardware can accelerate the execution times of former homology detection applications, such as National Centre for Biotechnology Information (NCBI), Basic Local Alignment Search Tool for Proteins (BLASTP), up to a factor of 4.

  8. HOMOLOGY MODELING AND MOLECULAR DYNAMICS STUDY OF MYCOBACTERIUM TUBERCULOSIS UREASE

    Directory of Open Access Journals (Sweden)

    Lisnyak Yu. V.

    2017-10-01

    Full Text Available Introduction. M. tuberculosis urease (MTU is an attractive target for chemotherapeutic intervention in tuberculosis by designing new safe and efficient enzyme inhibitors. A prerequisite for designing such inhibitors is an understanding of urease's three-dimensional (3D structure organization. 3D structure of M. tuberculosis urease is unknown. When experimental three-dimensional structure of a protein is not known, homology modeling, the most commonly used computational structure prediction method, is the technique of choice. This paper aimed to build a 3D-structure of M. tuberculosis urease by homology modeling and to study its stability by molecular dynamics simulations. Materials and methods. To build MTU model, five high-resolution X-ray structures of bacterial ureases with three-subunit composition (2KAU, 5G4H, 4UBP, 4СEU, and 4EPB have been selected as templates. For each template five stochastic alignments were created and for each alignment, a three-dimensional model was built. Then, each model was energy minimized and the models were ranked by quality Z-score. The MTU model with highest quality estimation amongst 25 potential models was selected. To further improve structure quality the model was refined by short molecular dynamics simulation that resulted in 20 snapshots which were rated according to their energy and the quality Z-score. The best scoring model having minimum energy was chosen as a final homology model of 3D structure for M. tuberculosis. The final model of MTU was also validated by using PDBsum and QMEAN servers. These checks confirmed good quality of MTU homology model. Results and discussion. Homology model of MTU is a nonamer (homotrimer of heterotrimers, (αβγ3 consisting of 2349 residues. In MTU heterotrimer, sub-units α, β, and γ tightly interact with each other at a surface of approximately 3000 Å2. Sub-unit α contains the enzyme active site with two Ni atoms coordinated by amino acid residues His347, His

  9. Protein homology model refinement by large-scale energy optimization.

    Science.gov (United States)

    Park, Hahnbeom; Ovchinnikov, Sergey; Kim, David E; DiMaio, Frank; Baker, David

    2018-03-20

    Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.

  10. Homologous Basal Ganglia Network Models in Physiological and Parkinsonian Conditions

    Directory of Open Access Journals (Sweden)

    Jyotika Bahuguna

    2017-08-01

    Full Text Available The classical model of basal ganglia has been refined in recent years with discoveries of subpopulations within a nucleus and previously unknown projections. One such discovery is the presence of subpopulations of arkypallidal and prototypical neurons in external globus pallidus, which was previously considered to be a primarily homogeneous nucleus. Developing a computational model of these multiple interconnected nuclei is challenging, because the strengths of the connections are largely unknown. We therefore use a genetic algorithm to search for the unknown connectivity parameters in a firing rate model. We apply a binary cost function derived from empirical firing rate and phase relationship data for the physiological and Parkinsonian conditions. Our approach generates ensembles of over 1,000 configurations, or homologies, for each condition, with broad distributions for many of the parameter values and overlap between the two conditions. However, the resulting effective weights of connections from or to prototypical and arkypallidal neurons are consistent with the experimental data. We investigate the significance of the weight variability by manipulating the parameters individually and cumulatively, and conclude that the correlation observed between the parameters is necessary for generating the dynamics of the two conditions. We then investigate the response of the networks to a transient cortical stimulus, and demonstrate that networks classified as physiological effectively suppress activity in the internal globus pallidus, and are not susceptible to oscillations, whereas parkinsonian networks show the opposite tendency. Thus, we conclude that the rates and phase relationships observed in the globus pallidus are predictive of experimentally observed higher level dynamical features of the physiological and parkinsonian basal ganglia, and that the multiplicity of solutions generated by our method may well be indicative of a natural

  11. Compositional Modelling of Stochastic Hybrid Systems

    NARCIS (Netherlands)

    Strubbe, S.N.

    2005-01-01

    In this thesis we present a modelling framework for compositional modelling of stochastic hybrid systems. Hybrid systems consist of a combination of continuous and discrete dynamics. The state space of a hybrid system is hybrid in the sense that it consists of a continuous component and a discrete

  12. Hybrid pseudomonads engineered by two-step homologous recombination acquire novel degradation abilities toward aromatics and polychlorinated biphenyls

    Energy Technology Data Exchange (ETDEWEB)

    Suenaga, Hikaru [National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba (Japan). Bioproduction Research Inst.; Nonaka, Kazuhiko; Goto, Masatoshi [Kyushu Univ., Fukuoka (Japan). Dept. of Bioscience and Biotechnology; Fujihara, Hidehiko; Furukawa, Kensuke [Beppu Univ. (Japan). Dept. of Fermentation and Food Science

    2010-10-15

    Pseudomonas pseudoalcaligenes KF707 possesses a chromosomally encoded bph gene cluster responsible for the catabolism of biphenyl and polychlorinated biphenyls. Previously, we constructed chimeric versions of the bphA1 gene, which encodes a large subunit of biphenyl dioxygenase, by using DNA shuffling between bphA1 genes from P. pseudoalcaligenes KF707 and Burkholderia xenovorans LB400. In this study, we demonstrate replacement of the bphA1 gene with chimeric bphA1 sequence within the chromosomal bph gene cluster by two-step homologous recombination. Notably, some of the hybrid strains acquired enhanced and/or expanded degradation capabilities for specific aromatic compounds, including single aromatic hydrocarbons and polychlorinated biphenyls. (orig.)

  13. Hybrid dynamics for currency modeling

    OpenAIRE

    Theodosopoulos, Ted; Trifunovic, Alex

    2006-01-01

    We present a simple hybrid dynamical model as a tool to investigate behavioral strategies based on trend following. The multiplicative symbolic dynamics are generated using a lognormal diffusion model for the at-the-money implied volatility term structure. Thus, are model exploits information from derivative markets to obtain qualititative properties of the return distribution for the underlier. We apply our model to the JPY-USD exchange rate and the corresponding 1mo., 3mo., 6mo. and 1yr. im...

  14. Modeling Human Serum Albumin Tertiary Structure to Teach Upper-Division Chemistry Students Bioinformatics and Homology Modeling Basics

    Science.gov (United States)

    Petrovic, Dus?an; Zlatovic´, Mario

    2015-01-01

    A homology modeling laboratory experiment has been developed for an introductory molecular modeling course for upper-division undergraduate chemistry students. With this experiment, students gain practical experience in homology model preparation and assessment as well as in protein visualization using the educational version of PyMOL…

  15. Osmoregulatory effects of hypophysectomy and homologous prolactin replacement in hybrid striped bass

    DEFF Research Database (Denmark)

    Jackson, Leslie F; McCormick, Stephen D; Madsen, Steffen S

    2005-01-01

    The effects of ovine prolactin (oPRL) and striped bass prolactin (sbPRL; Morone saxatilis) on plasma osmolality, electrolyte balance, and gill Na+,K+-ATPase activity were investigated in hypophysectomized (Hx), freshwater (FW)-acclimated, hybrid striped bass (M. saxatilis x Morone chrysops...... or 100 ng/g), or hormone vehicle (0.9% NaCl) at 48-h intervals (days 0, 2, 4, and 6) in FW and then sampled for blood plasma 24 h after the fourth injection (day 7). In Hx fish, oPRL (5 and 20 microg/g) and sbPRL (10 and 100 ng/g) were effective in maintaining plasma osmolality and levels of Na+, Cl...... balance in FW-adapted hybrid striped bass, and that this may involve downregulation of branchial Na+,K+-ATPase activity....

  16. Hybrid2 - The hybrid power system simulation model

    Energy Technology Data Exchange (ETDEWEB)

    Baring-Gould, E.I.; Green, H.J.; Dijk, V.A.P. van [National Renewable Energy Lab., Golden, CO (United States); Manwell, J.F. [Univ. of Massachusetts, Amherst, MA (United States)

    1996-12-31

    There is a large-scale need and desire for energy in remote communities, especially in the developing world; however the lack of a user friendly, flexible performance prediction model for hybrid power systems incorporating renewables hindered the analysis of hybrids as options to conventional solutions. A user friendly model was needed with the versatility to simulate the many system locations, widely varying hardware configurations, and differing control options for potential hybrid power systems. To meet these ends, researchers from the National Renewable Energy Laboratory (NREL) and the University of Massachusetts (UMass) developed the Hybrid2 software. This paper provides an overview of the capabilities, features, and functionality of the Hybrid2 code, discusses its validation and future plans. Model availability and technical support provided to Hybrid2 users are also discussed. 12 refs., 3 figs., 4 tabs.

  17. Model Reduction of Hybrid Systems

    DEFF Research Database (Denmark)

    Shaker, Hamid Reza

    gramians. Generalized gramians are the solutions to the observability and controllability Lyapunov inequalities. In the first framework the projection matrices are found based on the common generalized gramians. This framework preserves the stability of the original switched system for all switching...... is guaranteed to be preserved for arbitrary switching signal. To compute the common generalized gramians linear matrix inequalities (LMI’s) need to be solved. These LMI’s are not always feasible. In order to solve the problem of conservatism, the second framework is presented. In this method the projection......High-Technological solutions of today are characterized by complex dynamical models. A lot of these models have inherent hybrid/switching structure. Hybrid/switched systems are powerful models for distributed embedded systems design where discrete controls are applied to continuous processes...

  18. Hybrid Model of Content Extraction

    DEFF Research Database (Denmark)

    Qureshi, Pir Abdul Rasool; Memon, Nasrullah

    2012-01-01

    We present a hybrid model for content extraction from HTML documents. The model operates on Document Object Model (DOM) tree of the corresponding HTML document. It evaluates each tree node and associated statistical features like link density and text distribution across the node to predict...... significance of the node towards overall content provided by the document. Once significance of the nodes is determined, the formatting characteristics like fonts, styles and the position of the nodes are evaluated to identify the nodes with similar formatting as compared to the significant nodes. The proposed...

  19. Evaporator modeling - A hybrid approach

    International Nuclear Information System (INIS)

    Ding Xudong; Cai Wenjian; Jia Lei; Wen Changyun

    2009-01-01

    In this paper, a hybrid modeling approach is proposed to model two-phase flow evaporators. The main procedures for hybrid modeling includes: (1) Based on the energy and material balance, and thermodynamic principles to formulate the process fundamental governing equations; (2) Select input/output (I/O) variables responsible to the system performance which can be measured and controlled; (3) Represent those variables existing in the original equations but are not measurable as simple functions of selected I/Os or constants; (4) Obtaining a single equation which can correlate system inputs and outputs; and (5) Identify unknown parameters by linear or nonlinear least-squares methods. The method takes advantages of both physical and empirical modeling approaches and can accurately predict performance in wide operating range and in real-time, which can significantly reduce the computational burden and increase the prediction accuracy. The model is verified with the experimental data taken from a testing system. The testing results show that the proposed model can predict accurately the performance of the real-time operating evaporator with the maximum error of ±8%. The developed models will have wide applications in operational optimization, performance assessment, fault detection and diagnosis

  20. Novel protein interactions with an actin homolog (MreB) of Helicobacter pylori determined by bacterial two-hybrid system.

    Science.gov (United States)

    Zepeda Gurrola, Reyna Cristina; Fu, Yajuan; Rodríguez Luna, Isabel Cristina; Benítez Cardoza, Claudia Guadalupe; López López, María de Jesús; López Vidal, Yolanda; Gutíerrez, Germán Rubén Aguilar; Rodríguez Pérez, Mario A; Guo, Xianwu

    2017-08-01

    The bacterium Helicobacter pylori infects more than 50% of the world population and causes several gastroduodenal diseases, including gastric cancer. Nevertheless, we still need to explore some protein interactions that may be involved in pathogenesis. MreB, an actin homolog, showed some special characteristics in previous studies, indicating that it could have different functions. Protein functions could be realized via protein-protein interactions. In the present study, the MreB protein from H. pylori 26695 fused with two tags 10×His and GST in tandem was overexpressed and purified from Escherchia coli. The purified recombinant protein was used to perform a pull-down assay with H. pylori 26695 cell lysate. The pulled-down proteins were identified by mass spectrometry (MALDI-TOF), in which the known important proteins related to morphogenesis were absent but several proteins related to pathogenesis process were observed. The bacterial two-hybrid system was further used to evaluate the protein interactions and showed that new interactions of MreB respectively with VacA, UreB, HydB, HylB and AddA were confirmed but the interaction MreB-MreC was not validated. These results indicated that the protein MreB in H. pylori has a distinct interactome, does not participate in cell morphogenesis via MreB-MreC but could be related to pathogenesis. Copyright © 2017 Elsevier GmbH. All rights reserved.

  1. Hybrid model of steam boiler

    International Nuclear Information System (INIS)

    Rusinowski, Henryk; Stanek, Wojciech

    2010-01-01

    In the case of big energy boilers energy efficiency is usually determined with the application of the indirect method. Flue gas losses and unburnt combustible losses have a significant influence on the boiler's efficiency. To estimate these losses the knowledge of the operating parameters influence on the flue gases temperature and the content of combustible particles in the solid combustion products is necessary. A hybrid model of a boiler developed with the application of both analytical modelling and artificial intelligence is described. The analytical part of the model includes the balance equations. The empirical models express the dependence of the flue gas temperature and the mass fraction of the unburnt combustibles in solid combustion products on the operating parameters of a boiler. The empirical models have been worked out by means of neural and regression modelling.

  2. Homology modeling of the serotonin transporter: Insights into the primary escitalopram-binding Site

    DEFF Research Database (Denmark)

    Jørgensen, Anne Marie; Tagmose, L.; Jørgensen, A.M.M.

    2007-01-01

    -ray structure of the closely related amino acid transporter, Aquifex aeolicus leucine transporter (LeuT), provides an opportunity to develop a three-dimensional model of the structure of SERT. We present herein a homology model of SERT using LeuT as the template and containing escitalopram as a bound ligand...

  3. Deriving simulators for hybrid Chi models

    NARCIS (Netherlands)

    Beek, van D.A.; Man, K.L.; Reniers, M.A.; Rooda, J.E.; Schiffelers, R.R.H.

    2006-01-01

    The hybrid Chi language is formalism for modeling, simulation and verification of hybrid systems. The formal semantics of hybrid Chi allows the definition of provably correct implementations for simulation, verification and realtime control. This paper discusses the principles of deriving an

  4. Cellulase enzyme: Homology modeling, binding site identification and molecular docking

    Science.gov (United States)

    Selvam, K.; Senbagam, D.; Selvankumar, T.; Sudhakar, C.; Kamala-Kannan, S.; Senthilkumar, B.; Govarthanan, M.

    2017-12-01

    Cellulase is an enzyme that degrades the linear polysaccharide like cellulose into glucose by breaking the β-1,4- glycosidic bonds. These enzymes are the third largest enzymes with a great potential towards the ethanol production and play a vital role in degrading the biomass. The production of ethanol depends upon the ability of the cellulose to utilize the wide range of substrates. In this study, the 3D structure of cellulase from Acinetobacter sp. was modeled by using Modeler 9v9 and validated by Ramachandran plot. The accuracy of the predicted 3D structure was checked using Ramachandran plot analysis showed that 81.1% in the favored region, compatibility of an atomic model (3D) with amino acid sequence (1D) for the model was observed as 78.21% and 49.395% for Verify 3D and ERRAT at SAVES server. As the binding efficacy with the substrate might suggests the choice of the substrate as carbon and nitrogen sources, the cellobiose, cellotetraose, cellotetriose and laminaribiose were employed in the docking studies. The docking of cellobiose, cellotetraose, cellotetriose and laminaribiose with cellulase exhibited the binding energy of -6.1523 kJ/mol, -7.8759 kJ/mol,-6.1590 kJ/mol and -6.7185 kJ/mol, respectively. These docking studies revealed that cellulase has the greater potential towards the cellotetraose as a substrate for the high yield of ethanol.

  5. Illustrating and homology modeling the proteins of the Zika virus [version 2; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Sean Ekins

    2016-09-01

    Full Text Available The Zika virus (ZIKV is a flavivirus of the family Flaviviridae, which is similar to dengue virus, yellow fever and West Nile virus. Recent outbreaks in South America, Latin America, the Caribbean and in particular Brazil have led to concern for the spread of the disease and potential to cause Guillain-Barré syndrome and microcephaly. Although ZIKV has been known of for over 60 years there is very little in the way of knowledge of the virus with few publications and no crystal structures. No antivirals have been tested against it either in vitro or in vivo. ZIKV therefore epitomizes a neglected disease. Several suggested steps have been proposed which could be taken to initiate ZIKV antiviral drug discovery using both high throughput screens as well as structure-based design based on homology models for the key proteins. We now describe preliminary homology models created for NS5, FtsJ, NS4B, NS4A, HELICc, DEXDc, peptidase S7, NS2B, NS2A, NS1, E stem, glycoprotein M, propeptide, capsid and glycoprotein E using SWISS-MODEL. Eleven out of 15 models pass our model quality criteria for their further use. While a ZIKV glycoprotein E homology model was initially described in the immature conformation as a trimer, we now describe the mature dimer conformer which allowed the construction of an illustration of the complete virion. By comparing illustrations of ZIKV based on this new homology model and the dengue virus crystal structure we propose potential differences that could be exploited for antiviral and vaccine design. The prediction of sites for glycosylation on this protein may also be useful in this regard. While we await a cryo-EM structure of ZIKV and eventual crystal structures of the individual proteins, these homology models provide the community with a starting point for structure-based design of drugs and vaccines as well as a for computational virtual screening.

  6. [Preparation of monoclonal antibody against 4-amylphenol and homology modeling of its Fv fragment].

    Science.gov (United States)

    Cheng, Lei; Wu, Haizhen; Fei, Jing; Zhang, Lujia; Ye, Jiang; Zhang, Huizhan

    2017-03-01

    Objective To prepare and characterize a monoclonal antibody (mAb) against 4-amylphenol (4-AP), clone its cDNA sequence and make homology modeling for its Fv fragment. Methods A high-affinity anti-4-AP mAb was generated from a hybridoma cell line F10 using electrofusion between splenocytes from APA-BSA-immunized mouse and Sp2/0 myeloma cells. Then we extracted the mRNA of F10 cells and cloned the cDNA of mAb. The homology modeling and molecular docking of its Fv fragment was conducted with biological software. Results Under the optimum conditions, the ic-ELISA equation was y=A 2 +(A 1 -A 2 )/(1+(x/x 0 ) p ) (A 1 =1.28; A 2 =-0.066; x 0 =12560.75; p=0.74) with a correlation coefficient (R 2 ) of 0.997. The lowest detectable limit was 0.65 μg/mL. The heavy and light chains of mAb respectively belonged to IgG1 and Kappa. The homology modeling and molecular docking studies revealed that the binding of 4-Ap and mAb was attributed to the hydrogen bond and hydrophobic interactions. Conclusion The study successfully established a stable 4-AP mAb-secreting hybridoma cell line. The study on spatial structure of Fv fragment using homology modeling provided a reference for the development and design of single chain variable fragments.

  7. Binding modes of dihydroquinoxalinones in a homology model of bradykinin receptor 1.

    Science.gov (United States)

    Ha, Sookhee N; Hey, Pat J; Ransom, Rick W; Harrell, C Meacham; Murphy, Kathryn L; Chang, Ray; Chen, Tsing-Bau; Su, Dai-Shi; Markowitz, M Kristine; Bock, Mark G; Freidinger, Roger M; Hess, Fred J

    2005-05-27

    We report the first homology model of human bradykinin receptor B1 generated from the crystal structure of bovine rhodopsin as a template. Using an automated docking procedure, two B1 receptor antagonists of the dihydroquinoxalinone structural class were docked into the receptor model. Site-directed mutagenesis data of the amino acid residues in TM1, TM3, TM6, and TM7 were incorporated to place the compounds in the binding site of the homology model of the human B1 bradykinin receptor. The best pose in agreement with the mutation data was selected for detailed study of the receptor-antagonist interaction. To test the model, the calculated antagonist-receptor binding energy was correlated with the experimentally measured binding affinity (K(i)) for nine dihydroquinoxalinone analogs. The model was used to gain insight into the molecular mechanism for receptor function and to optimize the dihydroquinoxalinone analogs.

  8. Accurate protein structure modeling using sparse NMR data and homologous structure information.

    Science.gov (United States)

    Thompson, James M; Sgourakis, Nikolaos G; Liu, Gaohua; Rossi, Paolo; Tang, Yuefeng; Mills, Jeffrey L; Szyperski, Thomas; Montelione, Gaetano T; Baker, David

    2012-06-19

    While information from homologous structures plays a central role in X-ray structure determination by molecular replacement, such information is rarely used in NMR structure determination because it can be incorrect, both locally and globally, when evolutionary relationships are inferred incorrectly or there has been considerable evolutionary structural divergence. Here we describe a method that allows robust modeling of protein structures of up to 225 residues by combining (1)H(N), (13)C, and (15)N backbone and (13)Cβ chemical shift data, distance restraints derived from homologous structures, and a physically realistic all-atom energy function. Accurate models are distinguished from inaccurate models generated using incorrect sequence alignments by requiring that (i) the all-atom energies of models generated using the restraints are lower than models generated in unrestrained calculations and (ii) the low-energy structures converge to within 2.0 Å backbone rmsd over 75% of the protein. Benchmark calculations on known structures and blind targets show that the method can accurately model protein structures, even with very remote homology information, to a backbone rmsd of 1.2-1.9 Å relative to the conventional determined NMR ensembles and of 0.9-1.6 Å relative to X-ray structures for well-defined regions of the protein structures. This approach facilitates the accurate modeling of protein structures using backbone chemical shift data without need for side-chain resonance assignments and extensive analysis of NOESY cross-peak assignments.

  9. Homology modelling of Drosophila cytochrome P450 enzymes associated with insecticide resistance.

    Science.gov (United States)

    Jones, Robert T; Bakker, Saskia E; Stone, Deborah; Shuttleworth, Sally N; Boundy, Sam; McCart, Caroline; Daborn, Phillip J; ffrench-Constant, Richard H; van den Elsen, Jean M H

    2010-10-01

    Overexpression of the cytochrome P450 gene Cyp6g1 confers resistance against DDT and a broad range of other insecticides in Drosophila melanogaster Meig. In the absence of crystal structures of CYP6G1 or complexes with its substrates, structural studies rely on homology modelling and ligand docking to understand P450-substrate interactions. Homology models are presented for CYP6G1, a P450 associated with resistance to DDT and neonicotinoids, and two other enzymes associated with insecticide resistance in D. melanogaster, CYP12D1 and CYP6A2. The models are based on a template of the X-ray structure of the phylogenetically related human CYP3A4, which is known for its broad substrate specificity. The model of CYP6G1 has a much smaller active site cavity than the template. The cavity is also 'V'-shaped and is lined with hydrophobic residues, showing high shape and chemical complementarity with the molecular characteristics of DDT. Comparison of the DDT-CYP6G1 complex and a non-resistant CYP6A2 homology model implies that tight-fit recognition of this insecticide is important in CYP6G1. The active site can accommodate differently shaped substrates ranging from imidacloprid to malathion but not the pyrethroids permethrin and cyfluthrin. The CYP6G1, CYP12D1 and CYP6A2 homology models can provide a structural insight into insecticide resistance in flies overexpressing P450 enzymes with broad substrate specificities.

  10. GPCRM: a homology modeling web service with triple membrane-fitted quality assessment of GPCR models.

    Science.gov (United States)

    Miszta, Przemyslaw; Pasznik, Pawel; Jakowiecki, Jakub; Sztyler, Agnieszka; Latek, Dorota; Filipek, Slawomir

    2018-05-21

    Due to the involvement of G protein-coupled receptors (GPCRs) in most of the physiological and pathological processes in humans they have been attracting a lot of attention from pharmaceutical industry as well as from scientific community. Therefore, the need for new, high quality structures of GPCRs is enormous. The updated homology modeling service GPCRM (http://gpcrm.biomodellab.eu/) meets those expectations by greatly reducing the execution time of submissions (from days to hours/minutes) with nearly the same average quality of obtained models. Additionally, due to three different scoring functions (Rosetta, Rosetta-MP, BCL::Score) it is possible to select accurate models for the required purposes: the structure of the binding site, the transmembrane domain or the overall shape of the receptor. Currently, no other web service for GPCR modeling provides this possibility. GPCRM is continually upgraded in a semi-automatic way and the number of template structures has increased from 20 in 2013 to over 90 including structures the same receptor with different ligands which can influence the structure not only in the on/off manner. Two types of protein viewers can be used for visual inspection of obtained models. The extended sortable tables with available templates provide links to external databases and display ligand-receptor interactions in visual form.

  11. Sequence-structure relationships in RNA loops: establishing the basis for loop homology modeling.

    Science.gov (United States)

    Schudoma, Christian; May, Patrick; Nikiforova, Viktoria; Walther, Dirk

    2010-01-01

    The specific function of RNA molecules frequently resides in their seemingly unstructured loop regions. We performed a systematic analysis of RNA loops extracted from experimentally determined three-dimensional structures of RNA molecules. A comprehensive loop-structure data set was created and organized into distinct clusters based on structural and sequence similarity. We detected clear evidence of the hallmark of homology present in the sequence-structure relationships in loops. Loops differing by structures. Thus, our results support the application of homology modeling for RNA loop model building. We established a threshold that may guide the sequence divergence-based selection of template structures for RNA loop homology modeling. Of all possible sequences that are, under the assumption of isosteric relationships, theoretically compatible with actual sequences observed in RNA structures, only a small fraction is contained in the Rfam database of RNA sequences and classes implying that the actual RNA loop space may consist of a limited number of unique loop structures and conserved sequences. The loop-structure data sets are made available via an online database, RLooM. RLooM also offers functionalities for the modeling of RNA loop structures in support of RNA engineering and design efforts.

  12. Homology modelling and docking analysis of L-lactate dehydrogenase from Streptococcus thermopilus

    Directory of Open Access Journals (Sweden)

    Vukić Vladimir R.

    2016-01-01

    Full Text Available The aim of this research was to create a three-dimensional model of L-lactate dehydrogenase from the main yoghurt starter culture - Streptococcus thermopilus, to analyse its structural features and investigate substrate binding in the active site. NCBI BlastP was used against the Protein Data Bank database in order to identify the template for construction of homology models. Multiple sequence alignment was performed using the program MUSCULE within the UGENE 1.11.3 program. Homology models were constructed using the program Modeller v. 9.17. The obtained 3D model was verified by Ramachandran plots. Molecular docking simulations were performed using the program Surflex-Dock. The highest sequence similarity was observed with L-lactate dehydrogenase from Lactobacillus casei subsp. casei, with 69% identity. Therefore, its structure (PDB ID: 2ZQY:A was selected as a modelling template for homology modelling. Active residues are by sequence similarity predicted: S. thermophilus - HIS181 and S. aureus - HIS179. Binding energy of pyruvate to L-lactate dehydrogenase of S. thermopilus was - 7.874 kcal/mol. Pyruvate in L-lactate dehydrogenase of S. thermopilus makes H bonds with catalytic HIS181 (1.9 Å, as well as with THR235 (3.6 Å. Although our results indicate similar position of substrates between L-lactate dehydrogenase of S. thermopilus and S. aureus, differences in substrate distances and binding energy values could influence the reaction rate. Based on these results, the L-lactate dehydrogenase model proposed here could be used as a guide for further research, such as transition states of the reaction through molecular dynamics. [Projekat Ministarstva nauke Republike Srbije, br. III 46009

  13. Determination and validation of mTOR kinase-domain 3D structure by homology modeling

    Directory of Open Access Journals (Sweden)

    Lakhlili W

    2015-07-01

    Full Text Available Wiame Lakhlili,1 Gwénaël Chevé,2 Abdelaziz Yasri,2 Azeddine Ibrahimi1 1Laboratoire de Biotechnologie (MedBiotech, Faculté de Médecine et de Pharmacie de Rabat, Université Mohammed V de Rabat, Rabat, Morroco; 2OriBase Pharma, Cap Gamma, Parc Euromédecine, Montpellier, France Abstract: The AKT/mammalian target of rapamycin (mTOR pathway is considered as one of the commonly activated and deregulated signaling pathways in human cancer. mTOR is associated with other proteins in two molecular complexes: mTOR complex 1/Raptor and the mTOR complex 2/Rictor. Using the crystal structure of the related lipid kinase PI3Kγ, we built a model of the catalytic region of mTOR. The modeling of the three-dimensional (3D structure of the mTOR was performed by homology modeling program SWISS-MODEL. The quality and validation of the obtained model were performed using PROCHECK and PROVE softwares. The overall stereochemical property of the protein was assessed by the Ramachandran plot. The model validation was also done by docking of known inhibitors. In this paper, we describe and validate a 3D model for the mTOR catalytic site.Keywords: mTOR, homology modeling, mTOR kinase-domain, docking

  14. HYbrid Coordinate Ocean Model (HYCOM): Global

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Global HYbrid Coordinate Ocean Model (HYCOM) and U.S. Navy Coupled Ocean Data Assimilation (NCODA) 3-day, daily forecast at approximately 9-km (1/12-degree)...

  15. Travelling Waves in Hybrid Chemotaxis Models

    KAUST Repository

    Franz, Benjamin

    2013-12-18

    Hybrid models of chemotaxis combine agent-based models of cells with partial differential equation models of extracellular chemical signals. In this paper, travelling wave properties of hybrid models of bacterial chemotaxis are investigated. Bacteria are modelled using an agent-based (individual-based) approach with internal dynamics describing signal transduction. In addition to the chemotactic behaviour of the bacteria, the individual-based model also includes cell proliferation and death. Cells consume the extracellular nutrient field (chemoattractant), which is modelled using a partial differential equation. Mesoscopic and macroscopic equations representing the behaviour of the hybrid model are derived and the existence of travelling wave solutions for these models is established. It is shown that cell proliferation is necessary for the existence of non-transient (stationary) travelling waves in hybrid models. Additionally, a numerical comparison between the wave speeds of the continuum models and the hybrid models shows good agreement in the case of weak chemotaxis and qualitative agreement for the strong chemotaxis case. In the case of slow cell adaptation, we detect oscillating behaviour of the wave, which cannot be explained by mean-field approximations. © 2013 Society for Mathematical Biology.

  16. Polyglutamine Disease Modeling: Epitope Based Screen for Homologous Recombination using CRISPR/Cas9 System.

    Science.gov (United States)

    An, Mahru C; O'Brien, Robert N; Zhang, Ningzhe; Patra, Biranchi N; De La Cruz, Michael; Ray, Animesh; Ellerby, Lisa M

    2014-04-15

    We have previously reported the genetic correction of Huntington's disease (HD) patient-derived induced pluripotent stem cells using traditional homologous recombination (HR) approaches. To extend this work, we have adopted a CRISPR-based genome editing approach to improve the efficiency of recombination in order to generate allelic isogenic HD models in human cells. Incorporation of a rapid antibody-based screening approach to measure recombination provides a powerful method to determine relative efficiency of genome editing for modeling polyglutamine diseases or understanding factors that modulate CRISPR/Cas9 HR.

  17. Hybrid rocket engine, theoretical model and experiment

    Science.gov (United States)

    Chelaru, Teodor-Viorel; Mingireanu, Florin

    2011-06-01

    The purpose of this paper is to build a theoretical model for the hybrid rocket engine/motor and to validate it using experimental results. The work approaches the main problems of the hybrid motor: the scalability, the stability/controllability of the operating parameters and the increasing of the solid fuel regression rate. At first, we focus on theoretical models for hybrid rocket motor and compare the results with already available experimental data from various research groups. A primary computation model is presented together with results from a numerical algorithm based on a computational model. We present theoretical predictions for several commercial hybrid rocket motors, having different scales and compare them with experimental measurements of those hybrid rocket motors. Next the paper focuses on tribrid rocket motor concept, which by supplementary liquid fuel injection can improve the thrust controllability. A complementary computation model is also presented to estimate regression rate increase of solid fuel doped with oxidizer. Finally, the stability of the hybrid rocket motor is investigated using Liapunov theory. Stability coefficients obtained are dependent on burning parameters while the stability and command matrixes are identified. The paper presents thoroughly the input data of the model, which ensures the reproducibility of the numerical results by independent researchers.

  18. DockoMatic 2.0: high throughput inverse virtual screening and homology modeling.

    Science.gov (United States)

    Bullock, Casey; Cornia, Nic; Jacob, Reed; Remm, Andrew; Peavey, Thomas; Weekes, Ken; Mallory, Chris; Oxford, Julia T; McDougal, Owen M; Andersen, Timothy L

    2013-08-26

    DockoMatic is a free and open source application that unifies a suite of software programs within a user-friendly graphical user interface (GUI) to facilitate molecular docking experiments. Here we describe the release of DockoMatic 2.0; significant software advances include the ability to (1) conduct high throughput inverse virtual screening (IVS); (2) construct 3D homology models; and (3) customize the user interface. Users can now efficiently setup, start, and manage IVS experiments through the DockoMatic GUI by specifying receptor(s), ligand(s), grid parameter file(s), and docking engine (either AutoDock or AutoDock Vina). DockoMatic automatically generates the needed experiment input files and output directories and allows the user to manage and monitor job progress. Upon job completion, a summary of results is generated by Dockomatic to facilitate interpretation by the user. DockoMatic functionality has also been expanded to facilitate the construction of 3D protein homology models using the Timely Integrated Modeler (TIM) wizard. The wizard TIM provides an interface that accesses the basic local alignment search tool (BLAST) and MODELER programs and guides the user through the necessary steps to easily and efficiently create 3D homology models for biomacromolecular structures. The DockoMatic GUI can be customized by the user, and the software design makes it relatively easy to integrate additional docking engines, scoring functions, or third party programs. DockoMatic is a free comprehensive molecular docking software program for all levels of scientists in both research and education.

  19. Towards Modelling of Hybrid Systems

    DEFF Research Database (Denmark)

    Wisniewski, Rafal

    2006-01-01

    system consists of a number of dynamical systems that are glued together according to information encoded in the discrete part of the system. We develop a definition of a hybrid system as a functor from the category generated by a transition system to the category of directed topological spaces. Its...

  20. MollDE: a homology modeling framework you can click with.

    Science.gov (United States)

    Canutescu, Adrian A; Dunbrack, Roland L

    2005-06-15

    Molecular Integrated Development Environment (MolIDE) is an integrated application designed to provide homology modeling tools and protocols under a uniform, user-friendly graphical interface. Its main purpose is to combine the most frequent modeling steps in a semi-automatic, interactive way, guiding the user from the target protein sequence to the final three-dimensional protein structure. The typical basic homology modeling process is composed of building sequence profiles of the target sequence family, secondary structure prediction, sequence alignment with PDB structures, assisted alignment editing, side-chain prediction and loop building. All of these steps are available through a graphical user interface. MolIDE's user-friendly and streamlined interactive modeling protocol allows the user to focus on the important modeling questions, hiding from the user the raw data generation and conversion steps. MolIDE was designed from the ground up as an open-source, cross-platform, extensible framework. This allows developers to integrate additional third-party programs to MolIDE. http://dunbrack.fccc.edu/molide/molide.php rl_dunbrack@fccc.edu.

  1. Hybrid computer modelling in plasma physics

    International Nuclear Information System (INIS)

    Hromadka, J; Ibehej, T; Hrach, R

    2016-01-01

    Our contribution is devoted to development of hybrid modelling techniques. We investigate sheath structures in the vicinity of solids immersed in low temperature argon plasma of different pressures by means of particle and fluid computer models. We discuss the differences in results obtained by these methods and try to propose a way to improve the results of fluid models in the low pressure area. There is a possibility to employ Chapman-Enskog method to find appropriate closure relations of fluid equations in a case when particle distribution function is not Maxwellian. We try to follow this way to enhance fluid model and to use it in hybrid plasma model further. (paper)

  2. Structural insights into a high affinity nanobody:antigen complex by homology modelling

    DEFF Research Database (Denmark)

    Skottrup, Peter Durand

    2017-01-01

    Porphyromonas gingivalis is a major periodontitis-causing pathogens. P. gingivalis secrete a cysteine protease termed RgpB, which is specific for Arg-Xaa bonds in substrates. Recently, a nanobody-based assay was used to demonstrate that RgpB could represent a novel diagnostic target, thereby...... simplifying. P. gingivalis detection. The nanobody, VHH7, had a high binding affinity and was specific for RgpB, when tested towards the highly identical RgpA. In this study a homology model of VHH7 was build. The complementarity determining regions (CDR) comprising the paratope residues responsible for Rgp...

  3. Reactor systems modeling for ICF hybrids

    International Nuclear Information System (INIS)

    Berwald, D.H.; Meier, W.R.

    1980-10-01

    The computational models of ICF reactor subsystems developed by LLNL and TRW are described and a computer program was incorporated for use in the EPRI-sponsored Feasibility Assessment of Fusion-Fission Hybrids. Representative parametric variations have been examined. Many of the ICF subsystem models are very preliminary and more quantitative models need to be developed and included in the code

  4. Functional Coverage of the Human Genome by Existing Structures, Structural Genomics Targets, and Homology Models.

    Directory of Open Access Journals (Sweden)

    2005-08-01

    Full Text Available The bias in protein structure and function space resulting from experimental limitations and targeting of particular functional classes of proteins by structural biologists has long been recognized, but never continuously quantified. Using the Enzyme Commission and the Gene Ontology classifications as a reference frame, and integrating structure data from the Protein Data Bank (PDB, target sequences from the structural genomics projects, structure homology derived from the SUPERFAMILY database, and genome annotations from Ensembl and NCBI, we provide a quantified view, both at the domain and whole-protein levels, of the current and projected coverage of protein structure and function space relative to the human genome. Protein structures currently provide at least one domain that covers 37% of the functional classes identified in the genome; whole structure coverage exists for 25% of the genome. If all the structural genomics targets were solved (twice the current number of structures in the PDB, it is estimated that structures of one domain would cover 69% of the functional classes identified and complete structure coverage would be 44%. Homology models from existing experimental structures extend the 37% coverage to 56% of the genome as single domains and 25% to 31% for complete structures. Coverage from homology models is not evenly distributed by protein family, reflecting differing degrees of sequence and structure divergence within families. While these data provide coverage, conversely, they also systematically highlight functional classes of proteins for which structures should be determined. Current key functional families without structure representation are highlighted here; updated information on the "most wanted list" that should be solved is available on a weekly basis from http://function.rcsb.org:8080/pdb/function_distribution/index.html.

  5. Structural insights into a high affinity nanobody:antigen complex by homology modelling.

    Science.gov (United States)

    Skottrup, Peter Durand

    2017-09-01

    Porphyromonas gingivalis is a major periodontitis-causing pathogens. P. gingivalis secrete a cysteine protease termed RgpB, which is specific for Arg-Xaa bonds in substrates. Recently, a nanobody-based assay was used to demonstrate that RgpB could represent a novel diagnostic target, thereby simplifying. P. gingivalis detection. The nanobody, VHH7, had a high binding affinity and was specific for RgpB, when tested towards the highly identical RgpA. In this study a homology model of VHH7 was build. The complementarity determining regions (CDR) comprising the paratope residues responsible for RgpB binding were identified and used as input to the docking. Furthermore, residues likely involved in the RgpB epitope was identified based upon RgpB:RgpA alignment and analysis of residue surface accessibility. CDR residues and putitative RgpB epitope residues were used as input to an information-driven flexible docking approach using the HADDOCK server. Analysis of the VHH7:RgpB model demonstrated that the epitope was found in the immunoglobulin-like domain and residue pairs located at the molecular paratope:epitope interface important for complex stability was identified. Collectively, the VHH7 homology model and VHH7:RgpB docking supplies knowledge of the residues involved in the high affinity interaction. This information could prove valuable in the design of an antibody-drug conjugate for specific RgpB targeting. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. Variable selection in near infrared spectroscopy for quantitative models of homologous analogs of cephalosporins

    Directory of Open Access Journals (Sweden)

    Yan-Chun Feng

    2014-07-01

    Full Text Available Two universal spectral ranges (4550–4100 cm-1 and 6190–5510 cm-1 for construction of quantitative models of homologous analogs of cephalosporins were proposed by evaluating the performance of five spectral ranges and their combinations, using three data sets of cephalosporins for injection, i.e., cefuroxime sodium, ceftriaxone sodium and cefoperazone sodium. Subsequently, the proposed ranges were validated by using eight calibration sets of other homologous analogs of cephalosporins for injection, namely cefmenoxime hydrochloride, ceftezole sodium, cefmetazole, cefoxitin sodium, cefotaxime sodium, cefradine, cephazolin sodium and ceftizoxime sodium. All the constructed quantitative models for the eight kinds of cephalosporins using these universal ranges could fulfill the requirements for quick quantification. After that, competitive adaptive reweighted sampling (CARS algorithm and infrared (IR–near infrared (NIR two-dimensional (2D correlation spectral analysis were used to determine the scientific basis of these two spectral ranges as the universal regions for the construction of quantitative models of cephalosporins. The CARS algorithm demonstrated that the ranges of 4550–4100 cm-1 and 6190–5510 cm-1 included some key wavenumbers which could be attributed to content changes of cephalosporins. The IR–NIR 2D spectral analysis showed that certain wavenumbers in these two regions have strong correlations to the structures of those cephalosporins that were easy to degrade.

  7. A hybrid mammalian cell cycle model

    Directory of Open Access Journals (Sweden)

    Vincent Noël

    2013-08-01

    Full Text Available Hybrid modeling provides an effective solution to cope with multiple time scales dynamics in systems biology. Among the applications of this method, one of the most important is the cell cycle regulation. The machinery of the cell cycle, leading to cell division and proliferation, combines slow growth, spatio-temporal re-organisation of the cell, and rapid changes of regulatory proteins concentrations induced by post-translational modifications. The advancement through the cell cycle comprises a well defined sequence of stages, separated by checkpoint transitions. The combination of continuous and discrete changes justifies hybrid modelling approaches to cell cycle dynamics. We present a piecewise-smooth version of a mammalian cell cycle model, obtained by hybridization from a smooth biochemical model. The approximate hybridization scheme, leading to simplified reaction rates and binary event location functions, is based on learning from a training set of trajectories of the smooth model. We discuss several learning strategies for the parameters of the hybrid model.

  8. A Hybrid 3D Indoor Space Model

    Directory of Open Access Journals (Sweden)

    A. Jamali

    2016-10-01

    Full Text Available GIS integrates spatial information and spatial analysis. An important example of such integration is for emergency response which requires route planning inside and outside of a building. Route planning requires detailed information related to indoor and outdoor environment. Indoor navigation network models including Geometric Network Model (GNM, Navigable Space Model, sub-division model and regular-grid model lack indoor data sources and abstraction methods. In this paper, a hybrid indoor space model is proposed. In the proposed method, 3D modeling of indoor navigation network is based on surveying control points and it is less dependent on the 3D geometrical building model. This research proposes a method of indoor space modeling for the buildings which do not have proper 2D/3D geometrical models or they lack semantic or topological information. The proposed hybrid model consists of topological, geometrical and semantical space.

  9. Hybrid simulation models of production networks

    CERN Document Server

    Kouikoglou, Vassilis S

    2001-01-01

    This book is concerned with a most important area of industrial production, that of analysis and optimization of production lines and networks using discrete-event models and simulation. The book introduces a novel approach that combines analytic models and discrete-event simulation. Unlike conventional piece-by-piece simulation, this method observes a reduced number of events between which the evolution of the system is tracked analytically. Using this hybrid approach, several models are developed for the analysis of production lines and networks. The hybrid approach combines speed and accuracy for exceptional analysis of most practical situations. A number of optimization problems, involving buffer design, workforce planning, and production control, are solved through the use of hybrid models.

  10. Modelling dependable systems using hybrid Bayesian networks

    International Nuclear Information System (INIS)

    Neil, Martin; Tailor, Manesh; Marquez, David; Fenton, Norman; Hearty, Peter

    2008-01-01

    A hybrid Bayesian network (BN) is one that incorporates both discrete and continuous nodes. In our extensive applications of BNs for system dependability assessment, the models are invariably hybrid and the need for efficient and accurate computation is paramount. We apply a new iterative algorithm that efficiently combines dynamic discretisation with robust propagation algorithms on junction tree structures to perform inference in hybrid BNs. We illustrate its use in the field of dependability with two example of reliability estimation. Firstly we estimate the reliability of a simple single system and next we implement a hierarchical Bayesian model. In the hierarchical model we compute the reliability of two unknown subsystems from data collected on historically similar subsystems and then input the result into a reliability block model to compute system level reliability. We conclude that dynamic discretisation can be used as an alternative to analytical or Monte Carlo methods with high precision and can be applied to a wide range of dependability problems

  11. Homology modeling of Homo sapiens lipoic acid synthase: Substrate docking and insights on its binding mode.

    Science.gov (United States)

    Krishnamoorthy, Ezhilarasi; Hassan, Sameer; Hanna, Luke Elizabeth; Padmalayam, Indira; Rajaram, Rama; Viswanathan, Vijay

    2017-05-07

    Lipoic acid synthase (LIAS) is an iron-sulfur cluster mitochondrial enzyme which catalyzes the final step in the de novo pathway for the biosynthesis of lipoic acid, a potent antioxidant. Recently there has been significant interest in its role in metabolic diseases and its deficiency in LIAS expression has been linked to conditions such as diabetes, atherosclerosis and neonatal-onset epilepsy, suggesting a strong inverse correlation between LIAS reduction and disease status. In this study we use a bioinformatics approach to predict its structure, which would be helpful to understanding its role. A homology model for LIAS protein was generated using X-ray crystallographic structure of Thermosynechococcus elongatus BP-1 (PDB ID: 4U0P). The predicted structure has 93% of the residues in the most favour region of Ramachandran plot. The active site of LIAS protein was mapped and docked with S-Adenosyl Methionine (SAM) using GOLD software. The LIAS-SAM complex was further refined using molecular dynamics simulation within the subsite 1 and subsite 3 of the active site. To the best of our knowledge, this is the first study to report a reliable homology model of LIAS protein. This study will facilitate a better understanding mode of action of the enzyme-substrate complex for future studies in designing drugs that can target LIAS protein. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Equipment for fully homologous bulb turbine model testing in Laval University

    International Nuclear Information System (INIS)

    Fraser R; Vallée D; Jean Y; Deschênes C

    2014-01-01

    Within the context of liberalisation of the energy market, hydroelectricity remains a first class source of clean and renewable energy. Combining the growing demand of energy, its increasing value and the appreciation associated to the sustainable development, low head sites formerly considered as non-profitable are now exploitable. Bulb turbines likely to equip such sites are traditionally developed on model using right angle transmission leading to piers enlargement for power take off shaft passage, thus restricting possibilities to have fully homologous hydraulic passages. Aiming to sustain good quality development on fully homologous scale model of bulb turbines, the Hydraulic Machines Laboratory (LAMH) of Laval University has developed a brake with an enhanced power to weight ratio. This powerful brake is small enough to be located in the bulb shell while dissipating power without mandatory test head reduction. This paper first presents the basic technology of this brake and its application. Then both its main performance capabilities and dimensional characteristics will be detailed. The instrumentation used to perform accurate measurements will be finally presented

  13. Discovery of a Dipeptide Epimerase Enzymatic Function Guided by Homology Modeling and Virtual Screening

    Energy Technology Data Exchange (ETDEWEB)

    Kalyanaraman, C.; Imker, H; Fedorov, A; Fedorov, E; Glasner, M; Babbitt, P; Almo, S; Gerlt, J; Jacobson, M

    2008-01-01

    We have developed a computational approach to aid the assignment of enzymatic function for uncharacterized proteins that uses homology modeling to predict the structure of the binding site and in silico docking to identify potential substrates. We apply this method to proteins in the functionally diverse enolase superfamily that are homologous to the characterized L-Ala-D/L-Glu epimerase from Bacillus subtilis. In particular, a protein from Thermotoga martima was predicted to have different substrate specificity, which suggests that it has a different, but as yet unknown, biological function. This prediction was experimentally confirmed, resulting in the assignment of epimerase activity for L-Ala-D/L-Phe, L-Ala-D/L-Tyr, and L-Ala-D/L-His, whereas the enzyme is annotated incorrectly in GenBank as muconate cycloisomerase. Subsequently, crystal structures of the enzyme were determined in complex with three substrates, showing close agreement with the computational models and revealing the structural basis for the observed substrate selectivity.

  14. A restraint molecular dynamics and simulated annealing approach for protein homology modeling utilizing mean angles

    Directory of Open Access Journals (Sweden)

    Maurer Till

    2005-04-01

    Full Text Available Abstract Background We have developed the program PERMOL for semi-automated homology modeling of proteins. It is based on restrained molecular dynamics using a simulated annealing protocol in torsion angle space. As main restraints defining the optimal local geometry of the structure weighted mean dihedral angles and their standard deviations are used which are calculated with an algorithm described earlier by Döker et al. (1999, BBRC, 257, 348–350. The overall long-range contacts are established via a small number of distance restraints between atoms involved in hydrogen bonds and backbone atoms of conserved residues. Employing the restraints generated by PERMOL three-dimensional structures are obtained using standard molecular dynamics programs such as DYANA or CNS. Results To test this modeling approach it has been used for predicting the structure of the histidine-containing phosphocarrier protein HPr from E. coli and the structure of the human peroxisome proliferator activated receptor γ (Ppar γ. The divergence between the modeled HPr and the previously determined X-ray structure was comparable to the divergence between the X-ray structure and the published NMR structure. The modeled structure of Ppar γ was also very close to the previously solved X-ray structure with an RMSD of 0.262 nm for the backbone atoms. Conclusion In summary, we present a new method for homology modeling capable of producing high-quality structure models. An advantage of the method is that it can be used in combination with incomplete NMR data to obtain reasonable structure models in accordance with the experimental data.

  15. Structural differences of matrix metalloproteinases. Homology modeling and energy minimization of enzyme-substrate complexes

    DEFF Research Database (Denmark)

    Terp, G E; Christensen, I T; Jørgensen, Flemming Steen

    2000-01-01

    Matrix metalloproteinases are extracellular enzymes taking part in the remodeling of extracellular matrix. The structures of the catalytic domain of MMP1, MMP3, MMP7 and MMP8 are known, but structures of enzymes belonging to this family still remain to be determined. A general approach...... to the homology modeling of matrix metalloproteinases, exemplified by the modeling of MMP2, MMP9, MMP12 and MMP14 is described. The models were refined using an energy minimization procedure developed for matrix metalloproteinases. This procedure includes incorporation of parameters for zinc and calcium ions...... in the AMBER 4.1 force field, applying a non-bonded approach and a full ion charge representation. Energy minimization of the apoenzymes yielded structures with distorted active sites, while reliable three-dimensional structures of the enzymes containing a substrate in active site were obtained. The structural...

  16. Weather forecasting based on hybrid neural model

    Science.gov (United States)

    Saba, Tanzila; Rehman, Amjad; AlGhamdi, Jarallah S.

    2017-11-01

    Making deductions and expectations about climate has been a challenge all through mankind's history. Challenges with exact meteorological directions assist to foresee and handle problems well in time. Different strategies have been investigated using various machine learning techniques in reported forecasting systems. Current research investigates climate as a major challenge for machine information mining and deduction. Accordingly, this paper presents a hybrid neural model (MLP and RBF) to enhance the accuracy of weather forecasting. Proposed hybrid model ensure precise forecasting due to the specialty of climate anticipating frameworks. The study concentrates on the data representing Saudi Arabia weather forecasting. The main input features employed to train individual and hybrid neural networks that include average dew point, minimum temperature, maximum temperature, mean temperature, average relative moistness, precipitation, normal wind speed, high wind speed and average cloudiness. The output layer composed of two neurons to represent rainy and dry weathers. Moreover, trial and error approach is adopted to select an appropriate number of inputs to the hybrid neural network. Correlation coefficient, RMSE and scatter index are the standard yard sticks adopted for forecast accuracy measurement. On individual standing MLP forecasting results are better than RBF, however, the proposed simplified hybrid neural model comes out with better forecasting accuracy as compared to both individual networks. Additionally, results are better than reported in the state of art, using a simple neural structure that reduces training time and complexity.

  17. Improving model construction of profile HMMs for remote homology detection through structural alignment

    Directory of Open Access Journals (Sweden)

    Zaverucha Gerson

    2007-11-01

    Full Text Available Abstract Background Remote homology detection is a challenging problem in Bioinformatics. Arguably, profile Hidden Markov Models (pHMMs are one of the most successful approaches in addressing this important problem. pHMM packages present a relatively small computational cost, and perform particularly well at recognizing remote homologies. This raises the question of whether structural alignments could impact the performance of pHMMs trained from proteins in the Twilight Zone, as structural alignments are often more accurate than sequence alignments at identifying motifs and functional residues. Next, we assess the impact of using structural alignments in pHMM performance. Results We used the SCOP database to perform our experiments. Structural alignments were obtained using the 3DCOFFEE and MAMMOTH-mult tools; sequence alignments were obtained using CLUSTALW, TCOFFEE, MAFFT and PROBCONS. We performed leave-one-family-out cross-validation over super-families. Performance was evaluated through ROC curves and paired two tailed t-test. Conclusion We observed that pHMMs derived from structural alignments performed significantly better than pHMMs derived from sequence alignment in low-identity regions, mainly below 20%. We believe this is because structural alignment tools are better at focusing on the important patterns that are more often conserved through evolution, resulting in higher quality pHMMs. On the other hand, sensitivity of these tools is still quite low for these low-identity regions. Our results suggest a number of possible directions for improvements in this area.

  18. Improving model construction of profile HMMs for remote homology detection through structural alignment.

    Science.gov (United States)

    Bernardes, Juliana S; Dávila, Alberto M R; Costa, Vítor S; Zaverucha, Gerson

    2007-11-09

    Remote homology detection is a challenging problem in Bioinformatics. Arguably, profile Hidden Markov Models (pHMMs) are one of the most successful approaches in addressing this important problem. pHMM packages present a relatively small computational cost, and perform particularly well at recognizing remote homologies. This raises the question of whether structural alignments could impact the performance of pHMMs trained from proteins in the Twilight Zone, as structural alignments are often more accurate than sequence alignments at identifying motifs and functional residues. Next, we assess the impact of using structural alignments in pHMM performance. We used the SCOP database to perform our experiments. Structural alignments were obtained using the 3DCOFFEE and MAMMOTH-mult tools; sequence alignments were obtained using CLUSTALW, TCOFFEE, MAFFT and PROBCONS. We performed leave-one-family-out cross-validation over super-families. Performance was evaluated through ROC curves and paired two tailed t-test. We observed that pHMMs derived from structural alignments performed significantly better than pHMMs derived from sequence alignment in low-identity regions, mainly below 20%. We believe this is because structural alignment tools are better at focusing on the important patterns that are more often conserved through evolution, resulting in higher quality pHMMs. On the other hand, sensitivity of these tools is still quite low for these low-identity regions. Our results suggest a number of possible directions for improvements in this area.

  19. Homology modeling of parasite histone deacetylases to guide the structure-based design of selective inhibitors.

    Science.gov (United States)

    Melesina, Jelena; Robaa, Dina; Pierce, Raymond J; Romier, Christophe; Sippl, Wolfgang

    2015-11-01

    Histone deacetylases (HDACs) are promising epigenetic targets for the treatment of various diseases, including cancer and neurodegenerative disorders. There is evidence that they can also be addressed to treat parasitic infections. Recently, the first X-ray structure of a parasite HDAC was published, Schistosoma mansoni HDAC8, giving structural insights into its inhibition. However, most of the targets from parasites of interest still lack this structural information. Therefore, we prepared homology models of relevant parasitic HDACs and compared them to human and S. mansoni HDACs. The information about known S. mansoni HDAC8 inhibitors and compounds that affect the growth of Trypanosoma, Leishmania and Plasmodium species was used to validate the models by docking and molecular dynamics studies. Our results provide analysis of structural features of parasitic HDACs and should be helpful for selecting promising candidates for biological testing and for structure-based optimisation of parasite-specific inhibitors. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. In silico predictive studies of mAHR congener binding using homology modelling and molecular docking.

    Science.gov (United States)

    Panda, Roshni; Cleave, A Suneetha Susan; Suresh, P K

    2014-09-01

    The aryl hydrocarbon receptor (AHR) is one of the principal xenobiotic, nuclear receptor that is responsible for the early events involved in the transcription of a complex set of genes comprising the CYP450 gene family. In the present computational study, homology modelling and molecular docking were carried out with the objective of predicting the relationship between the binding efficiency and the lipophilicity of different polychlorinated biphenyl (PCB) congeners and the AHR in silico. Homology model of the murine AHR was constructed by several automated servers and assessed by PROCHECK, ERRAT, VERIFY3D and WHAT IF. The resulting model of the AHR by MODWEB was used to carry out molecular docking of 36 PCB congeners using PatchDock server. The lipophilicity of the congeners was predicted using the XLOGP3 tool. The results suggest that the lipophilicity influences binding energy scores and is positively correlated with the same. Score and Log P were correlated with r = +0.506 at p = 0.01 level. In addition, the number of chlorine (Cl) atoms and Log P were highly correlated with r = +0.900 at p = 0.01 level. The number of Cl atoms and scores also showed a moderate positive correlation of r = +0.481 at p = 0.01 level. To the best of our knowledge, this is the first study employing PatchDock in the docking of AHR to the environmentally deleterious congeners and attempting to correlate structural features of the AHR with its biochemical properties with regards to PCBs. The result of this study are consistent with those of other computational studies reported in the previous literature that suggests that a combination of docking, scoring and ranking organic pollutants could be a possible predictive tool for investigating ligand-mediated toxicity, for their subsequent validation using wet lab-based studies. © The Author(s) 2012.

  1. Hybrid quantum teleportation: A theoretical model

    Energy Technology Data Exchange (ETDEWEB)

    Takeda, Shuntaro; Mizuta, Takahiro; Fuwa, Maria; Yoshikawa, Jun-ichi; Yonezawa, Hidehiro; Furusawa, Akira [Department of Applied Physics, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan)

    2014-12-04

    Hybrid quantum teleportation – continuous-variable teleportation of qubits – is a promising approach for deterministically teleporting photonic qubits. We propose how to implement it with current technology. Our theoretical model shows that faithful qubit transfer can be achieved for this teleportation by choosing an optimal gain for the teleporter’s classical channel.

  2. A Novel Hybrid Similarity Calculation Model

    Directory of Open Access Journals (Sweden)

    Xiaoping Fan

    2017-01-01

    Full Text Available This paper addresses the problems of similarity calculation in the traditional recommendation algorithms of nearest neighbor collaborative filtering, especially the failure in describing dynamic user preference. Proceeding from the perspective of solving the problem of user interest drift, a new hybrid similarity calculation model is proposed in this paper. This model consists of two parts, on the one hand the model uses the function fitting to describe users’ rating behaviors and their rating preferences, and on the other hand it employs the Random Forest algorithm to take user attribute features into account. Furthermore, the paper combines the two parts to build a new hybrid similarity calculation model for user recommendation. Experimental results show that, for data sets of different size, the model’s prediction precision is higher than the traditional recommendation algorithms.

  3. Divergent Roles of RPA Homologs of the Model Archaeon Halobacterium salinarum in Survival of DNA Damage.

    Science.gov (United States)

    Evans, Jessica J; Gygli, Patrick E; McCaskill, Julienne; DeVeaux, Linda C

    2018-04-20

    The haloarchaea are unusual in possessing genes for multiple homologs to the ubiquitous single-stranded DNA binding protein (SSB or replication protein A, RPA) found in all three domains of life. Halobacterium salinarum contains five homologs: two are eukaryotic in organization, two are prokaryotic and are encoded on the minichromosomes, and one is uniquely euryarchaeal. Radiation-resistant mutants previously isolated show upregulation of one of the eukaryotic-type RPA genes. Here, we have created deletions in the five RPA operons. These deletion mutants were exposed to DNA-damaging conditions: ionizing radiation, UV radiation, and mitomycin C. Deletion of the euryarchaeal homolog, although not lethal as in Haloferax volcanii , causes severe sensitivity to all of these agents. Deletion of the other RPA/SSB homologs imparts a variable sensitivity to these DNA-damaging agents, suggesting that the different RPA homologs have specialized roles depending on the type of genomic insult encountered.

  4. Hybrid Energy System Modeling in Modelica

    Energy Technology Data Exchange (ETDEWEB)

    William R. Binder; Christiaan J. J. Paredis; Humberto E. Garcia

    2014-03-01

    In this paper, a Hybrid Energy System (HES) configuration is modeled in Modelica. Hybrid Energy Systems (HES) have as their defining characteristic the use of one or more energy inputs, combined with the potential for multiple energy outputs. Compared to traditional energy systems, HES provide additional operational flexibility so that high variability in both energy production and consumption levels can be absorbed more effectively. This is particularly important when including renewable energy sources, whose output levels are inherently variable, determined by nature. The specific HES configuration modeled in this paper include two energy inputs: a nuclear plant, and a series of wind turbines. In addition, the system produces two energy outputs: electricity and synthetic fuel. The models are verified through simulations of the individual components, and the system as a whole. The simulations are performed for a range of component sizes, operating conditions, and control schemes.

  5. Mathematical Modeling of Hybrid Electrical Engineering Systems

    Directory of Open Access Journals (Sweden)

    A. A. Lobaty

    2016-01-01

    Full Text Available A large class of systems that have found application in various industries and households, electrified transportation facilities and energy sector has been classified as electrical engineering systems. Their characteristic feature is a combination of continuous and discontinuous modes of operation, which is reflected in the appearance of a relatively new term “hybrid systems”. A wide class of hybrid systems is pulsed DC converters operating in a pulse width modulation, which are non-linear systems with variable structure. Using various methods for linearization it is possible to obtain linear mathematical models that rather accurately simulate behavior of such systems. However, the presence in the mathematical models of exponential nonlinearities creates considerable difficulties in the implementation of digital hardware. The solution can be found while using an approximation of exponential functions by polynomials of the first order, that, however, violates the rigor accordance of the analytical model with characteristics of a real object. There are two practical approaches to synthesize algorithms for control of hybrid systems. The first approach is based on the representation of the whole system by a discrete model which is described by difference equations that makes it possible to synthesize discrete algorithms. The second approach is based on description of the system by differential equations. The equations describe synthesis of continuous algorithms and their further implementation in a digital computer included in the control loop system. The paper considers modeling of a hybrid electrical engineering system using differential equations. Neglecting the pulse duration, it has been proposed to describe behavior of vector components in phase coordinates of the hybrid system by stochastic differential equations containing generally non-linear differentiable random functions. A stochastic vector-matrix equation describing dynamics of the

  6. HOMOLOGY MODELING AND FUNCTIONAL CHARACTERIZATION OF THREE-DIMENSIONAL STRUCTURE OF DAHP SYNTHASE FROM BRACHYPODIUM DISTACHYON

    Directory of Open Access Journals (Sweden)

    Aditya Dev

    2013-06-01

    Full Text Available The Shikimate pathway is an attractive target for herbicides and antimicrobial agents because it is essential in microbes and plants but absent in animals. The 3-deoxy-D-arabino-heptulosonate 7-phosphate synthase (DAHPS is the first enzyme of this pathway, which is involved in the condensation of phosphoenolpyruvate (PEP and D-erythrose 4-phosphate (E4P to produce 3-deoxy-D-arabino-heptulosonate 7-phosphate (DAHP. DAHPS enzymes have been divided into two types, class I and class II, based on their primary amino acid sequence and three dimensional structures. The plant DAHPS belongs to class II and is regulated differently than DAHPS from microorganisms. To understand the structural basis of such differences in DAHPS from plants and its catalytic mechanism, we have used sequence analysis, homology modeling and docking approach to generate the three dimensional models of DAHP synthase from Brachypodium distachyon (Bd-DAHPS complexed with substrate PEP for the first time. The three dimensional models of Bd-DAHPS provides a detailed knowledge of the active site and the important secondary structural regions that play significant roles in the regulatory mechanism and further may be helpful for design of specific inhibitors towards herbicide development.

  7. Structural insights into transient receptor potential vanilloid type 1 (TRPV1) from homology modeling, flexible docking, and mutational studies.

    Science.gov (United States)

    Lee, Jin Hee; Lee, Yoonji; Ryu, HyungChul; Kang, Dong Wook; Lee, Jeewoo; Lazar, Jozsef; Pearce, Larry V; Pavlyukovets, Vladimir A; Blumberg, Peter M; Choi, Sun

    2011-04-01

    The transient receptor potential vanilloid subtype 1 (TRPV1) is a non-selective cation channel composed of four monomers with six transmembrane helices (TM1-TM6). TRPV1 is found in the central and peripheral nervous system, and it is an important therapeutic target for pain relief. We describe here the construction of a tetrameric homology model of rat TRPV1 (rTRPV1). We experimentally evaluated by mutational analysis the contribution of residues of rTRPV1 contributing to ligand binding by the prototypical TRPV1 agonists, capsaicin and resiniferatoxin (RTX). We then performed docking analysis using our homology model. The docking results with capsaicin and RTX showed that our homology model was reliable, affording good agreement with our mutation data. Additionally, the binding mode of a simplified RTX (sRTX) ligand as predicted by the modeling agreed well with those of capsaicin and RTX, accounting for the high binding affinity of the sRTX ligand for TRPV1. Through the homology modeling, docking and mutational studies, we obtained important insights into the ligand-receptor interactions at the molecular level which should prove of value in the design of novel TRPV1 ligands.

  8. Optimization of hybrid model on hajj travel

    Science.gov (United States)

    Cahyandari, R.; Ariany, R. L.; Sukono

    2018-03-01

    Hajj travel insurance is an insurance product offered by the insurance company in preparing funds to perform the pilgrimage. This insurance product helps would-be pilgrims to set aside a fund of saving hajj with regularly, but also provides funds of profit sharing (mudharabah) and insurance protection. Scheme of insurance product fund management is largely using the hybrid model, which is the fund from would-be pilgrims will be divided into three account management, that is personal account, tabarru’, and ujrah. Scheme of hybrid model on hajj travel insurance was already discussed at the earlier paper with titled “The Hybrid Model Algorithm on Sharia Insurance”, taking the example case of Mitra Mabrur Plus product from Bumiputera company. On these advanced paper, will be made the previous optimization model design, with partition of benefit the tabarru’ account. Benefits such as compensation for 40 critical illness which initially only for participants of insurance only, on optimization is intended for participants of the insurance and his heir, also to benefit the hospital bills. Meanwhile, the benefits of death benefit is given if the participant is fixed die.

  9. GPCR-SSFE: A comprehensive database of G-protein-coupled receptor template predictions and homology models

    Directory of Open Access Journals (Sweden)

    Kreuchwig Annika

    2011-05-01

    Full Text Available Abstract Background G protein-coupled receptors (GPCRs transduce a wide variety of extracellular signals to within the cell and therefore have a key role in regulating cell activity and physiological function. GPCR malfunction is responsible for a wide range of diseases including cancer, diabetes and hyperthyroidism and a large proportion of drugs on the market target these receptors. The three dimensional structure of GPCRs is important for elucidating the molecular mechanisms underlying these diseases and for performing structure-based drug design. Although structural data are restricted to only a handful of GPCRs, homology models can be used as a proxy for those receptors not having crystal structures. However, many researchers working on GPCRs are not experienced homology modellers and are therefore unable to benefit from the information that can be gleaned from such three-dimensional models. Here, we present a comprehensive database called the GPCR-SSFE, which provides initial homology models of the transmembrane helices for a large variety of family A GPCRs. Description Extending on our previous theoretical work, we have developed an automated pipeline for GPCR homology modelling and applied it to a large set of family A GPCR sequences. Our pipeline is a fragment-based approach that exploits available family A crystal structures. The GPCR-SSFE database stores the template predictions, sequence alignments, identified sequence and structure motifs and homology models for 5025 family A GPCRs. Users are able to browse the GPCR dataset according to their pharmacological classification or search for results using a UniProt entry name. It is also possible for a user to submit a GPCR sequence that is not contained in the database for analysis and homology model building. The models can be viewed using a Jmol applet and are also available for download along with the alignments. Conclusions The data provided by GPCR-SSFE are useful for investigating

  10. GPCR-SSFE: a comprehensive database of G-protein-coupled receptor template predictions and homology models.

    Science.gov (United States)

    Worth, Catherine L; Kreuchwig, Annika; Kleinau, Gunnar; Krause, Gerd

    2011-05-23

    G protein-coupled receptors (GPCRs) transduce a wide variety of extracellular signals to within the cell and therefore have a key role in regulating cell activity and physiological function. GPCR malfunction is responsible for a wide range of diseases including cancer, diabetes and hyperthyroidism and a large proportion of drugs on the market target these receptors. The three dimensional structure of GPCRs is important for elucidating the molecular mechanisms underlying these diseases and for performing structure-based drug design. Although structural data are restricted to only a handful of GPCRs, homology models can be used as a proxy for those receptors not having crystal structures. However, many researchers working on GPCRs are not experienced homology modellers and are therefore unable to benefit from the information that can be gleaned from such three-dimensional models. Here, we present a comprehensive database called the GPCR-SSFE, which provides initial homology models of the transmembrane helices for a large variety of family A GPCRs. Extending on our previous theoretical work, we have developed an automated pipeline for GPCR homology modelling and applied it to a large set of family A GPCR sequences. Our pipeline is a fragment-based approach that exploits available family A crystal structures. The GPCR-SSFE database stores the template predictions, sequence alignments, identified sequence and structure motifs and homology models for 5025 family A GPCRs. Users are able to browse the GPCR dataset according to their pharmacological classification or search for results using a UniProt entry name. It is also possible for a user to submit a GPCR sequence that is not contained in the database for analysis and homology model building. The models can be viewed using a Jmol applet and are also available for download along with the alignments. The data provided by GPCR-SSFE are useful for investigating general and detailed sequence-structure-function relationships

  11. Diverse binding site structures revealed in homology models of polyreactive immunoglobulins

    Science.gov (United States)

    Ramsland, Paul A.; Guddat, Luke W.; Edmundson, Allen B.; Raison, Robert L.

    1997-09-01

    We describe here computer-assisted homology models of the combiningsite structure of three polyreactive immunoglobulins. Template-based modelsof Fv (VL-VH) fragments were derived forthe surface IgM expressed by the malignant CD5 positive B cells from threepatients with chronic lymphocytic leukaemia (CLL). The conserved frameworkregions were constructed using crystal coordinates taken from highlyhomologous human variable domain structures (Pot and Hil). Complementaritydetermining regions (CDRs) were predicted by grafting loops, taken fromknown immunoglobulin structures, onto the Fv framework models. The CDRtemplates were chosen, where possible, to be of the same length and of highresidue identity or similarity. LCDR1, 2 and 3 as well as HCDR1 and 2 forthe Fv were constructed using this strategy. For HCDR3 prediction, adatabase containing the Cartesian coordinates of 30 of these loops wascompiled from unliganded antibody X-ray crystallographic structures and anHCDR3 of the same length as that of the B CLL Fv was selected as a template.In one case (Yar), the resulting HCDR3 model gave unfavourable interactionswhen incorporated into the Fv model. This HCDR3 was therefore modelled usingan alternative strategy of construction of the loop stems, using apreviously described HCDR3 conformation (Pot), followed by chain closurewith a β-turn. The template models were subjected to positionalrefinement using energy minimisation and molecular dynamics simulations(X-PLOR). An electrostatic surface description (GRASP) did not reveal acommon structural feature within the binding sites of the three polyreactiveFv. Thus, polyreactive immunoglobulins may recognise similar and multipleantigens through a diverse array of binding site structures.

  12. Gravitational waves in hybrid quintessential inflationary models

    Energy Technology Data Exchange (ETDEWEB)

    Sa, Paulo M [Departamento de Fisica, Faculdade de Ciencias e Tecnologia, Universidade do Algarve, Campus de Gambelas, 8005-139 Faro (Portugal); Henriques, Alfredo B, E-mail: pmsa@ualg.pt, E-mail: alfredo.henriques@ist.utl.pt [Centro Multidisciplinar de Astrofisica - CENTRA and Departamento de Fisica, Instituto Superior Tecnico, UTL, Av. Rovisco Pais, 1049-001 Lisboa (Portugal)

    2011-09-22

    The generation of primordial gravitational waves is investigated within the hybrid quintessential inflationary model. Using the method of continuous Bogoliubov coefficients, we calculate the full gravitational-wave energy spectrum. The post-inflationary kination period, characteristic of quintessential inflationary models, leaves a clear signature on the spectrum, namely, a sharp rise of the gravitational-wave spectral energy density {Omega}{sub GW} at high frequencies. For appropriate values of the parameters of the model, {Omega}{sub GW} can be as high as 10{sup -12} in the MHz-GHz range of frequencies.

  13. Gravitational waves in hybrid quintessential inflationary models

    International Nuclear Information System (INIS)

    Sa, Paulo M; Henriques, Alfredo B

    2011-01-01

    The generation of primordial gravitational waves is investigated within the hybrid quintessential inflationary model. Using the method of continuous Bogoliubov coefficients, we calculate the full gravitational-wave energy spectrum. The post-inflationary kination period, characteristic of quintessential inflationary models, leaves a clear signature on the spectrum, namely, a sharp rise of the gravitational-wave spectral energy density Ω GW at high frequencies. For appropriate values of the parameters of the model, Ω GW can be as high as 10 -12 in the MHz-GHz range of frequencies.

  14. Modelling Chemical Preservation of Plantain Hybrid Fruits

    Directory of Open Access Journals (Sweden)

    Ogueri Nwaiwu

    2017-08-01

    Full Text Available New plantain hybrids plants have been developed but not much has been done on the post-harvest keeping quality of the fruits and how they are affected by microbial colonization. Hence fruits from a tetraploid hybrid PITA 2 (TMPx 548-9 obtained by crossing plantain varieties Obino l’Ewai and Calcutta 4 (AA and two local triploid (AAB plantain landraces Agbagba and Obino l’Ewai were subjected to various concentrations of acetic, sorbic and propionic acid to determine the impact of chemical concentration, chemical type and plantain variety on ripening and weight loss of plantain fruits. Analysis of titratable acidity, moisture content and total soluble solids showed that there were no significant differences between fruits of hybrid and local varieties. The longest time to ripening from harvest (24 days was achieved with fruits of Agbagba treated with 3% propionic acid. However, fruits of PITA 2 hybrid treated with propionic and sorbic acid at 3% showed the longest green life which indicated that the chemicals may work better at higher concentrations. The Obino l’Ewai cultivar had the highest weight loss for all chemical types used. Modelling data obtained showed that plantain variety had the most significant effect on ripening and indicates that ripening of the fruits may depend on the plantain variety. It appears that weight loss of fruits from the plantain hybrid and local cultivars was not affected by the plantain variety, chemical type. The chemicals at higher concentrations may have an effect on ripening of the fruits and will need further investigation.

  15. A theoretical model of the tridimensional structure of Bacillus thuringiensis subsp. medellin Cry 11Bb toxin deduced by homology modelling

    Directory of Open Access Journals (Sweden)

    Gutierrez Pablo

    2001-01-01

    Full Text Available Cry11Bb is an insecticidal crystal protein produced by Bacillus thuringiensis subsp. medellin during its stationary phase; this ¶-endotoxin is active against dipteran insects and has great potential for mosquito borne disease control. Here, we report the first theoretical model of the tridimensional structure of a Cry11 toxin. The tridimensional structure of the Cry11Bb toxin was obtained by homology modelling on the structures of the Cry1Aa and Cry3Aa toxins. In this work we give a brief description of our model and hypothesize the residues of the Cry11Bb toxin that could be important in receptor recognition and pore formation. This model will serve as a starting point for the design of mutagenesis experiments aimed to the improvement of toxicity, and to provide a new tool for the elucidation of the mechanism of action of these mosquitocidal proteins.

  16. Reaction mechanism of sterol hydroxylation by steroid C25 dehydrogenase - Homology model, reactivity and isoenzymatic diversity.

    Science.gov (United States)

    Rugor, Agnieszka; Wójcik-Augustyn, Anna; Niedzialkowska, Ewa; Mordalski, Stefan; Staroń, Jakub; Bojarski, Andrzej; Szaleniec, Maciej

    2017-08-01

    Steroid C25 dehydrogenase (S25DH) is a molybdenum-containing oxidoreductase isolated from the anaerobic Sterolibacterium denitrificans Chol-1S. S25DH is classified as 'EBDH-like' enzyme (EBDH, ethylbenzene dehydrogenase) and catalyzes the introduction of an OH group to the C25 atom of a sterol aliphatic side-chain. Due to its regioselectivity, S25DH is proposed as a catalyst in production of pharmaceuticals: calcifediol or 25-hydroxycholesterol. The aim of presented research was to obtain structural model of catalytic subunit α and investigate the reaction mechanism of the O 2 -independent tertiary carbon atom activation. Based on homology modeling and theoretical calculations, a S25DH α subunit model was for the first time characterized and compared to other S25DH-like isoforms. The molecular dynamics simulations of the enzyme-substrate complexes revealed two stable binding modes of a substrate, which are stabilized predominantly by van der Waals forces in the hydrophobic substrate channel. However, H-bond interactions involving polar residues with C3=O/C3-OH in the steroid ring appear to be responsible for positioning the substrate. These results may explain the experimental kinetic results which showed that 3-ketosterols are hydroxylated 5-10-fold faster than 3-hydroxysterols. The reaction mechanism was studied using QM:MM and QM-only cluster models. The postulated mechanism involves homolytic CH cleavage by the MoO ligand, giving rise to a radical intermediate with product obtained in an OH rebound process. The hypothesis was supported by kinetic isotopic effect (KIE) experiments involving 25,26,26,26-[ 2 H]-cholesterol (4.5) and the theoretically predicted intrinsic KIE (7.0-7.2). Finally, we have demonstrated that the recombinant S25DH-like isoform catalyzes the same reaction as S25DH. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. Comments On Clock Models In Hybrid Automata And Hybrid Control Systems

    Directory of Open Access Journals (Sweden)

    Virginia Ecaterina OLTEAN

    2001-12-01

    Full Text Available Hybrid systems have received a lot of attention in the past decade and a number of different models have been proposed in order to establish mathematical framework that is able to handle both continuous and discrete aspects. This contribution is focused on two models: hybrid automata and hybrid control systems with continuous-discrete interface and the importance of clock models is emphasized. Simple and relevant examples, some taken from the literature, accompany the presentation.

  18. Homology models guide discovery of diverse enzyme specificities among dipeptide epimerases in the enolase superfamily

    Science.gov (United States)

    Lukk, Tiit; Sakai, Ayano; Kalyanaraman, Chakrapani; Brown, Shoshana D.; Imker, Heidi J.; Song, Ling; Fedorov, Alexander A.; Fedorov, Elena V.; Toro, Rafael; Hillerich, Brandan; Seidel, Ronald; Patskovsky, Yury; Vetting, Matthew W.; Nair, Satish K.; Babbitt, Patricia C.; Almo, Steven C.; Gerlt, John A.; Jacobson, Matthew P.

    2012-01-01

    The rapid advance in genome sequencing presents substantial challenges for protein functional assignment, with half or more of new protein sequences inferred from these genomes having uncertain assignments. The assignment of enzyme function in functionally diverse superfamilies represents a particular challenge, which we address through a combination of computational predictions, enzymology, and structural biology. Here we describe the results of a focused investigation of a group of enzymes in the enolase superfamily that are involved in epimerizing dipeptides. The first members of this group to be functionally characterized were Ala-Glu epimerases in Eschericiha coli and Bacillus subtilis, based on the operon context and enzymological studies; these enzymes are presumed to be involved in peptidoglycan recycling. We have subsequently studied more than 65 related enzymes by computational methods, including homology modeling and metabolite docking, which suggested that many would have divergent specificities;, i.e., they are likely to have different (unknown) biological roles. In addition to the Ala-Phe epimerase specificity reported previously, we describe the prediction and experimental verification of: (i) a new group of presumed Ala-Glu epimerases; (ii) several enzymes with specificity for hydrophobic dipeptides, including one from Cytophaga hutchinsonii that epimerizes D-Ala-D-Ala; and (iii) a small group of enzymes that epimerize cationic dipeptides. Crystal structures for certain of these enzymes further elucidate the structural basis of the specificities. The results highlight the potential of computational methods to guide experimental characterization of enzymes in an automated, large-scale fashion. PMID:22392983

  19. Homology modeling, molecular dynamics and inhibitor binding study on MurD ligase of Mycobacterium tuberculosis.

    Science.gov (United States)

    Arvind, Akanksha; Kumar, Vivek; Saravanan, Parameswaran; Mohan, C Gopi

    2012-09-01

    The cell wall of mycobacterium offers well validated targets which can be exploited for discovery of new lead compounds. MurC-MurF ligases catalyze a series of irreversible steps in the biosynthesis of peptidoglycan precursor, i.e. MurD catalyzes the ligation of D-glutamate to the nucleotide precursor UMA. The three dimensional structure of Mtb-MurD is not known and was predicted by us for the first time using comparative homology modeling technique. The accuracy and stability of the predicted Mtb-MurD structure was validated using Procheck and molecular dynamics simulation. Key interactions in Mtb-MurD were studied using docking analysis of available transition state inhibitors of E.coli-MurD. The docking analysis revealed that analogues of both L and D forms of glutamic acid have similar interaction profiles with Mtb-MurD. Further, residues His192, Arg382, Ser463, and Tyr470 are proposed to be important for inhibitor-(Mtb-MurD) interactions. We also identified few pharmacophoric features essential for Mtb-MurD ligase inhibitory activity and which can further been utilized for the discovery of putative antitubercular chemotherapy.

  20. Conserved Functional Motifs and Homology Modeling to Predict Hidden Moonlighting Functional Sites

    KAUST Repository

    Wong, Aloysius Tze; Gehring, Christoph A; Irving, Helen R.

    2015-01-01

    Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here, we review how hidden moonlighting functional centers, which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico, which, in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.

  1. Conserved Functional Motifs and Homology Modeling to Predict Hidden Moonlighting Functional Sites

    KAUST Repository

    Wong, Aloysius Tze

    2015-06-09

    Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here, we review how hidden moonlighting functional centers, which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico, which, in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.

  2. Design of Xen Hybrid Multiple Police Model

    Science.gov (United States)

    Sun, Lei; Lin, Renhao; Zhu, Xianwei

    2017-10-01

    Virtualization Technology has attracted more and more attention. As a popular open-source virtualization tools, XEN is used more and more frequently. Xsm, XEN security model, has also been widespread concern. The safety status classification has not been established in the XSM, and it uses the virtual machine as a managed object to make Dom0 a unique administrative domain that does not meet the minimum privilege. According to these questions, we design a Hybrid multiple police model named SV_HMPMD that organically integrates multiple single security policy models include DTE,RBAC,BLP. It can fullfill the requirement of confidentiality and integrity for security model and use different particle size to different domain. In order to improve BLP’s practicability, the model introduce multi-level security labels. In order to divide the privilege in detail, we combine DTE with RBAC. In order to oversize privilege, we limit the privilege of domain0.

  3. Homology modeling and protein engineering of alkane monooxygenase in Burkholderia thailandensis MSMB121: in silico insights.

    Science.gov (United States)

    Jain, Chakresh Kumar; Gupta, Money; Prasad, Yamuna; Wadhwa, Gulshan; Sharma, Sanjeev Kumar

    2014-07-01

    The degradation of hydrocarbons plays an important role in the eco-balancing of petroleum products, pesticides and other toxic products in the environment. The degradation of hydrocarbons by microbes such as Geobacillus thermodenitrificans, Burkhulderia, Gordonia sp. and Acinetobacter sp. has been studied intensively in the literature. The present study focused on the in silico protein engineering of alkane monooxygenase (ladA)-a protein involved in the alkane degradation pathway. We demonstrated the improvement in substrate binding energy with engineered ladA in Burkholderia thailandensis MSMB121. We identified an ortholog of ladA monooxygenase found in B. thailandensis MSMB121, and showed it to be an enzyme involved in an alkane degradation pathway studied extensively in Geobacillus thermodenitrificans. Homology modeling of the three-dimensional structure of ladA was performed with a crystal structure (protein databank ID: 3B9N) as a template in MODELLER 9v11, and further validated using PROCHECK, VERIFY-3D and WHATIF tools. Specific amino acids were substituted in the region corresponding to amino acids 305-370 of ladA protein, resulting in an enhancement of binding energy in different alkane chain molecules as compared to wild protein structures in the docking experiments. The substrate binding energy with the protein was calculated using Vina (Implemented in VEGAZZ). Molecular dynamics simulations were performed to study the dynamics of different alkane chain molecules inside the binding pockets of wild and mutated ladA. Here, we hypothesize an improvement in binding energies and accessibility of substrates towards engineered ladA enzyme, which could be further facilitated for wet laboratory-based experiments for validation of the alkane degradation pathway in this organism.

  4. Cloning, Expression, Sequence Analysis and Homology Modeling of the Prolyl Endoprotease from Eurygaster integriceps Puton

    Directory of Open Access Journals (Sweden)

    Ravi Chandra Yandamuri

    2014-10-01

    Full Text Available eurygaster integriceps Puton, commonly known as sunn pest, is a major pest of wheat in Northern Africa, the Middle East and Eastern Europe. This insect injects a prolyl endoprotease into the wheat, destroying the gluten. The purpose of this study was to clone the full length cDNA of the sunn pest prolyl endoprotease (spPEP for expression in E. coli and to compare the amino acid sequence of the enzyme to other known PEPs in both phylogeny and potential tertiary structure. Sequence analysis shows that the 5ꞌ UTR contains several putative transcription factor binding sites for transcription factors known to be expressed in Drosophila that might be useful targets for inhibition of the enzyme. The spPEP was first identified as a prolyl endoprotease by Darkoh et al., 2010. The enzyme is a unique serine protease of the S9A family by way of its substrate recognition of the gluten proteins, which are greater than 30 kD in size. At 51% maximum identity to known PEPs, homology modeling using SWISS-MODEL, the porcine brain PEP (PDB: 2XWD was selected in the database of known PEP structures, resulting in a predicted tertiary structure 99% identical to the porcine brain PEP structure. A Km for the recombinant spPEP was determined to be 210 ± 53 µM for the zGly-Pro-pNA substrate in 0.025 M ethanolamine, pH 8.5, containing 0.1 M NaCl at 37 °C with a turnover rate of 172 ± 47 µM Gly-Pro-pNA/s/µM of enzyme.

  5. Infectious disease modeling a hybrid system approach

    CERN Document Server

    Liu, Xinzhi

    2017-01-01

    This volume presents infectious diseases modeled mathematically, taking seasonality and changes in population behavior into account, using a switched and hybrid systems framework. The scope of coverage includes background on mathematical epidemiology, including classical formulations and results; a motivation for seasonal effects and changes in population behavior, an investigation into term-time forced epidemic models with switching parameters, and a detailed account of several different control strategies. The main goal is to study these models theoretically and to establish conditions under which eradication or persistence of the disease is guaranteed. In doing so, the long-term behavior of the models is determined through mathematical techniques from switched systems theory. Numerical simulations are also given to augment and illustrate the theoretical results and to help study the efficacy of the control schemes.

  6. Craniomandibular form and body size variation of first generation mouse hybrids: A model for hominin hybridization.

    Science.gov (United States)

    Warren, Kerryn A; Ritzman, Terrence B; Humphreys, Robyn A; Percival, Christopher J; Hallgrímsson, Benedikt; Ackermann, Rebecca Rogers

    2018-03-01

    Hybridization occurs in a number of mammalian lineages, including among primate taxa. Analyses of ancient genomes have shown that hybridization between our lineage and other archaic hominins in Eurasia occurred numerous times in the past. However, we still have limited empirical data on what a hybrid skeleton looks like, or how to spot patterns of hybridization among fossils for which there are no genetic data. Here we use experimental mouse models to supplement previous studies of primates. We characterize size and shape variation in the cranium and mandible of three wild-derived inbred mouse strains and their first generation (F 1 ) hybrids. The three parent taxa in our analysis represent lineages that diverged over approximately the same period as the human/Neanderthal/Denisovan lineages and their hybrids are variably successful in the wild. Comparisons of body size, as quantified by long bone measurements, are also presented to determine whether the identified phenotypic effects of hybridization are localized to the cranium or represent overall body size changes. The results indicate that hybrid cranial and mandibular sizes, as well as limb length, exceed that of the parent taxa in all cases. All three F 1 hybrid crosses display similar patterns of size and form variation. These results are generally consistent with earlier studies on primates and other mammals, suggesting that the effects of hybridization may be similar across very different scenarios of hybridization, including different levels of hybrid fitness. This paper serves to supplement previous studies aimed at identifying F 1 hybrids in the fossil record and to introduce further research that will explore hybrid morphologies using mice as a proxy for better understanding hybridization in the hominin fossil record. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Discovery of a Manduca sexta Allatotropin Antagonist from a Manduca sexta Allatotropin Receptor Homology Model.

    Science.gov (United States)

    Kai, Zhen-Peng; Zhu, Jing-Jing; Deng, Xi-Le; Yang, Xin-Ling; Chen, Shan-Shan

    2018-04-03

    Insect G protein coupled receptors (GPCRs) have important roles in modulating biology, physiology and behavior. They have been identified as candidate targets for next-generation insecticides, yet these targets have been relatively poorly exploited for insect control. In this study, we present a pipeline of novel Manduca sexta allatotropin (Manse-AT) antagonist discovery with homology modeling, docking, molecular dynamics simulation and structure-activity relationship. A series of truncated and alanine-replacement analogs of Manse-AT were assayed for the stimulation of juvenile hormone biosynthesis. The minimum sequence required to retain potent biological activity is the C -terminal amidated octapeptide Manse-AT (6-13). We identified three residues essential for bioactivity (Thr⁴, Arg6 and Phe⁸) by assaying alanine-replacement analogs of Manse-AT (6-13). Alanine replacement of other residues resulted in reduced potency but bioactivity was retained. The 3D structure of the receptor (Manse-ATR) was built and the binding pocket was identified. The binding affinities of all the analogs were estimated by calculating the free energy of binding. The calculated binding affinities corresponded to the biological activities of the analogs, which supporting our localization of the binding pocket. Then, based on the docking and molecular dynamics studies of Manse-AT (10-13), we described it can act as a potent Manse-AT antagonist. The antagonistic effect on JH biosynthesis of Manse-AT (10-13) validated our hypothesis. The IC 50 value of antagonist Manse-AT (10-13) is 0.9 nM. The structure-activity relationship of antagonist Manse-AT (10-13) was also studied for the further purpose of investigating theoretically the structure factors influencing activity. These data will be useful for the design of new Manse-AT agonist and antagonist as potential pest control agents.

  8. Discovery of a Manduca sexta Allatotropin Antagonist from a Manduca sexta Allatotropin Receptor Homology Model

    Directory of Open Access Journals (Sweden)

    Zhen-Peng Kai

    2018-04-01

    Full Text Available Insect G protein coupled receptors (GPCRs have important roles in modulating biology, physiology and behavior. They have been identified as candidate targets for next-generation insecticides, yet these targets have been relatively poorly exploited for insect control. In this study, we present a pipeline of novel Manduca sexta allatotropin (Manse-AT antagonist discovery with homology modeling, docking, molecular dynamics simulation and structure-activity relationship. A series of truncated and alanine-replacement analogs of Manse-AT were assayed for the stimulation of juvenile hormone biosynthesis. The minimum sequence required to retain potent biological activity is the C-terminal amidated octapeptide Manse-AT (6–13. We identified three residues essential for bioactivity (Thr4, Arg6 and Phe8 by assaying alanine-replacement analogs of Manse-AT (6–13. Alanine replacement of other residues resulted in reduced potency but bioactivity was retained. The 3D structure of the receptor (Manse-ATR was built and the binding pocket was identified. The binding affinities of all the analogs were estimated by calculating the free energy of binding. The calculated binding affinities corresponded to the biological activities of the analogs, which supporting our localization of the binding pocket. Then, based on the docking and molecular dynamics studies of Manse-AT (10–13, we described it can act as a potent Manse-AT antagonist. The antagonistic effect on JH biosynthesis of Manse-AT (10–13 validated our hypothesis. The IC50 value of antagonist Manse-AT (10–13 is 0.9 nM. The structure-activity relationship of antagonist Manse-AT (10–13 was also studied for the further purpose of investigating theoretically the structure factors influencing activity. These data will be useful for the design of new Manse-AT agonist and antagonist as potential pest control agents.

  9. Homology modeling and in silico prediction of Ulcerative colitis associated polymorphisms of NOD1.

    Science.gov (United States)

    Majumdar, Ishani; Nagpal, Isha; Paul, Jaishree

    2017-10-01

    Cytosolic pattern recognition receptors play key roles in innate immune response. Nucleotide binding and oligomerisation domain containing protein 1 (NOD1) belonging to the Nod-like receptor C (NLRC) sub-family of Nod-like receptors (NLRs) is important for detection and clearance of intra-cellular Gram negative bacteria. NOD1 is involved in activation of pro-inflammatory pathways. Limited structural data is available for NOD1. Using different templates for each domain of NOD1, we determined the full-length homology model of NOD1. ADP binding amino acids within the nucleotide binding domain (NBD) of NOD1 were also predicted. Key residues in inter-domain interaction were identified by sequence comparison with Oryctolagus cuniculus NOD2, a related protein. Interactions between NBD and winged helix domain (WHD) were found to be conserved in NOD1. Functional and structural effect of single nucleotide polymorphisms within the NOD1 NBD domain associated with susceptibility risk to Ulcerative colitis (UC), an inflammatory disorder of the colon was evaluated by in silico studies. Mutations W219R and L349P were predicted to be damaging and disease associated by prediction programs SIFT, PolyPhen2, PANTHER, SNP&GO, PhD SNP and SNAP2. We further validated the effect of W219R and L349P mutation on NOD1 function in vitro. Elevated mRNA expression of pro-inflammatory cytokines IL8 and IL-1β was seen as compared to the wild type NOD1 in intestinal epithelial cell line HT29 when stimulated with NOD1 ligand. Thus, these mutations may indeed have a bearing on pathogenesis of inflammation during UC. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. A hybrid modeling approach for option pricing

    Science.gov (United States)

    Hajizadeh, Ehsan; Seifi, Abbas

    2011-11-01

    The complexity of option pricing has led many researchers to develop sophisticated models for such purposes. The commonly used Black-Scholes model suffers from a number of limitations. One of these limitations is the assumption that the underlying probability distribution is lognormal and this is so controversial. We propose a couple of hybrid models to reduce these limitations and enhance the ability of option pricing. The key input to option pricing model is volatility. In this paper, we use three popular GARCH type model for estimating volatility. Then, we develop two non-parametric models based on neural networks and neuro-fuzzy networks to price call options for S&P 500 index. We compare the results with those of Black-Scholes model and show that both neural network and neuro-fuzzy network models outperform Black-Scholes model. Furthermore, comparing the neural network and neuro-fuzzy approaches, we observe that for at-the-money options, neural network model performs better and for both in-the-money and an out-of-the money option, neuro-fuzzy model provides better results.

  11. Binding Mode Prediction of 5-Hydroxytryptamine 2C Receptor Ligands by Homology Modeling and Molecular Docking Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Ahmed, Asif; Nagarajan, Shanthi; Doddareddy, Munikumar Reddy; Cho, Yong Seo; Pae, Ae Nim [Korea Institute of Science and Technology, Seoul (Korea, Republic of)

    2011-06-15

    Serotonin or 5-hydroxytryptamine subtype 2C (5-HT{sub 2C}) receptor belongs to class A amine subfamily of Gprotein- coupled receptor (GPCR) super family and its ligands has therapeutic promise as anti-depressant and -obesity agents. So far, bovine rhodopsin from class A opsin subfamily was the mostly used X-ray crystal template to model this receptor. Here, we explained homology model using beta 2 adrenergic receptor (β2AR), the model was energetically minimized and validated by flexible ligand docking with known agonists and antagonists. In the active site Asp134, Ser138 of transmembrane 3 (TM3), Arg195 of extracellular loop 2 (ECL2) and Tyr358 of TM7 were found as important residues to interact with agonists. In addition to these, V208 of ECL2 and N351 of TM7 was found to interact with antagonists. Several conserved residues including Trp324, Phe327 and Phe328 were also found to contribute hydrophobic interaction. The predicted ligand binding mode is in good agreement with published mutagenesis and homology model data. This new template derived homology model can be useful for further virtual screening based lead identification.

  12. Fluid and hybrid models for streamers

    Science.gov (United States)

    Bonaventura, Zdeněk

    2016-09-01

    Streamers are contracted ionizing waves with self-generated field enhancement that propagate into a low-ionized medium exposed to high electric field leaving filamentary trails of plasma behind. The widely used model to study streamer dynamics is based on drift-diffusion equations for electrons and ions, assuming local field approximation, coupled with Poisson's equation. For problems where presence of energetic electrons become important a fluid approach needs to be extended by a particle model, accompanied also with Monte Carlo Collision technique, that takes care of motion of these electrons. A combined fluid-particle approach is used to study an influence of surface emission processes on a fast-pulsed dielectric barrier discharge in air at atmospheric pressure. It is found that fluid-only model predicts substantially faster reignition dynamics compared to coupled fluid-particle model. Furthermore, a hybrid model can be created in which the population of electrons is divided in the energy space into two distinct groups: (1) low energy `bulk' electrons that are treated with fluid model, and (2) high energy `beam' electrons, followed as particles. The hybrid model is then capable not only to deal with streamer discharges in laboratory conditions, but also allows us to study electron acceleration in streamer zone of lighting leaders. There, the production of fast electrons from streamers is investigated, since these (runaway) electrons act as seeds for the relativistic runaway electron avalanche (RREA) mechanism, important for high-energy atmospheric physics phenomena. Results suggest that high energy electrons effect the streamer propagation, namely the velocity, the peak electric field, and thus also the production rate of runaway electrons. This work has been supported by the Czech Science Foundation research project 15-04023S.

  13. Modeling of renewable hybrid energy sources

    Directory of Open Access Journals (Sweden)

    Dumitru Cristian Dragos

    2009-12-01

    Full Text Available Recent developments and trends in the electric power consumption indicate an increasing use of renewable energy. Renewable energy technologies offer the promise of clean, abundant energy gathered from self-renewing resources such as the sun, wind, earth and plants. Virtually all regions of the world have renewable resources of one type or another. By this point of view studies on renewable energies focuses more and more attention. The present paper intends to present different mathematical models related to different types of renewable energy sources such as: solar energy and wind energy. It is also presented the validation and adaptation of such models to hybrid systems working in geographical and meteorological conditions specific to central part of Transylvania region. The conclusions based on validation of such models are also shown.

  14. Relative orientation of collagen molecules within a fibril: a homology model for homo sapiens type I collagen.

    Science.gov (United States)

    Collier, Thomas A; Nash, Anthony; Birch, Helen L; de Leeuw, Nora H

    2018-02-15

    Type I collagen is an essential extracellular protein that plays an important structural role in tissues that require high tensile strength. However, owing to the molecule's size, to date no experimental structural data are available for the Homo sapiens species. Therefore, there is a real need to develop a reliable homology model and a method to study the packing of the collagen molecules within the fibril. Through the use of the homology model and implementation of a novel simulation technique, we have ascertained the orientations of the collagen molecules within a fibril, which is currently below the resolution limit of experimental techniques. The longitudinal orientation of collagen molecules within a fibril has a significant effect on the mechanical and biological properties of the fibril, owing to the different amino acid side chains available at the interface between the molecules.

  15. Hybrid Models of Alternative Current Filter for Hvdc

    Directory of Open Access Journals (Sweden)

    Ufa Ruslan A.

    2017-01-01

    Full Text Available Based on a hybrid simulation concept of HVDC, the developed hybrid AC filter models, providing the sufficiently full and adequate modeling of all single continuous spectrum of quasi-steady-state and transient processes in the filter, are presented. The obtained results suggest that usage of the hybrid simulation approach is carried out a methodically accurate with guaranteed instrumental error solution of differential equation systems of mathematical models of HVDC.

  16. Hybrid Modeling Improves Health and Performance Monitoring

    Science.gov (United States)

    2007-01-01

    Scientific Monitoring Inc. was awarded a Phase I Small Business Innovation Research (SBIR) project by NASA's Dryden Flight Research Center to create a new, simplified health-monitoring approach for flight vehicles and flight equipment. The project developed a hybrid physical model concept that provided a structured approach to simplifying complex design models for use in health monitoring, allowing the output or performance of the equipment to be compared to what the design models predicted, so that deterioration or impending failure could be detected before there would be an impact on the equipment's operational capability. Based on the original modeling technology, Scientific Monitoring released I-Trend, a commercial health- and performance-monitoring software product named for its intelligent trending, diagnostics, and prognostics capabilities, as part of the company's complete ICEMS (Intelligent Condition-based Equipment Management System) suite of monitoring and advanced alerting software. I-Trend uses the hybrid physical model to better characterize the nature of health or performance alarms that result in "no fault found" false alarms. Additionally, the use of physical principles helps I-Trend identify problems sooner. I-Trend technology is currently in use in several commercial aviation programs, and the U.S. Air Force recently tapped Scientific Monitoring to develop next-generation engine health-management software for monitoring its fleet of jet engines. Scientific Monitoring has continued the original NASA work, this time under a Phase III SBIR contract with a joint NASA-Pratt & Whitney aviation security program on propulsion-controlled aircraft under missile-damaged aircraft conditions.

  17. Analysis of chromosome aberration data by hybrid-scale models

    International Nuclear Information System (INIS)

    Indrawati, Iwiq; Kumazawa, Shigeru

    2000-02-01

    This paper presents a new methodology for analyzing data of chromosome aberrations, which is useful to understand the characteristics of dose-response relationships and to construct the calibration curves for the biological dosimetry. The hybrid scale of linear and logarithmic scales brings a particular plotting paper, where the normal section paper, two types of semi-log papers and the log-log paper are continuously connected. The hybrid-hybrid plotting paper may contain nine kinds of linear relationships, and these are conveniently called hybrid scale models. One can systematically select the best-fit model among the nine models by among the conditions for a straight line of data points. A biological interpretation is possible with some hybrid-scale models. In this report, the hybrid scale models were applied to separately reported data on chromosome aberrations in human lymphocytes as well as on chromosome breaks in Tradescantia. The results proved that the proposed models fit the data better than the linear-quadratic model, despite the demerit of the increased number of model parameters. We showed that the hybrid-hybrid model (both variables of dose and response using the hybrid scale) provides the best-fit straight lines to be used as the reliable and readable calibration curves of chromosome aberrations. (author)

  18. Molecular cloning, sequence analysis and homology modeling of the first caudata amphibian antifreeze-like protein in axolotl (Ambystoma mexicanum).

    Science.gov (United States)

    Zhang, Songyan; Gao, Jiuxiang; Lu, Yiling; Cai, Shasha; Qiao, Xue; Wang, Yipeng; Yu, Haining

    2013-08-01

    Antifreeze proteins (AFPs) refer to a class of polypeptides that are produced by certain vertebrates, plants, fungi, and bacteria and which permit their survival in subzero environments. In this study, we report the molecular cloning, sequence analysis and three-dimensional structure of the axolotl antifreeze-like protein (AFLP) by homology modeling of the first caudate amphibian AFLP. We constructed a full-length spleen cDNA library of axolotl (Ambystoma mexicanum). An EST having highest similarity (∼42%) with freeze-responsive liver protein Li16 from Rana sylvatica was identified, and the full-length cDNA was subsequently obtained by RACE-PCR. The axolotl antifreeze-like protein sequence represents an open reading frame for a putative signal peptide and the mature protein composed of 93 amino acids. The calculated molecular mass and the theoretical isoelectric point (pl) of this mature protein were 10128.6 Da and 8.97, respectively. The molecular characterization of this gene and its deduced protein were further performed by detailed bioinformatics analysis. The three-dimensional structure of current AFLP was predicted by homology modeling, and the conserved residues required for functionality were identified. The homology model constructed could be of use for effective drug design. This is the first report of an antifreeze-like protein identified from a caudate amphibian.

  19. A hybrid model for electricity spot prices

    International Nuclear Information System (INIS)

    Anderson, C.L.D.

    2004-01-01

    Electricity prices were highly regulated prior to the deregulation of the electric power industry. Prices were predictable, allowing generators and wholesalers to calculate their production costs and revenues. With deregulation, electricity has become the most volatile of all commodities. Electricity must be consumed as soon as it is generated due to the inability to store it in any sufficient quantity. Economic uncertainty exists because the supply of electricity cannot shift as quickly as the demand, which is highly variable. When demand increases quickly, the price must respond. Therefore, price spikes occur that are orders of magnitude higher than the base electricity price. This paper presents a robust and realistic model for spot market electricity prices used to manage risk in volatile markets. The model is a hybrid of a top down data driven method commonly used for financial applications, and a bottom up system driven method commonly used in regulated electricity markets. The advantage of the model is that it incorporates primary system drivers and demonstrates their effects on final prices. The 4 primary modules of the model are: (1) a model for forced outages, (2) a model for maintenance outages, (3) an electrical load model, and (4) a price model which combines the results of the previous 3 models. The performance of each model was tested. The forced outage model is the first of its kind to simulate the system on an aggregate basis using Weibull distributions. The overall spot price model was calibrated to, and tested with, data from the electricity market in Pennsylvania, New Jersey and Maryland. The model performed well in simulated market prices and adapted readily to changing system conditions and new electricity markets. This study examined the pricing of derivative contracts on electrical power. It also compared a range of portfolio scenarios using a Cash Flow at Risk approach

  20. A hybrid model for electricity spot prices

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, C.L.D.

    2004-07-01

    Electricity prices were highly regulated prior to the deregulation of the electric power industry. Prices were predictable, allowing generators and wholesalers to calculate their production costs and revenues. With deregulation, electricity has become the most volatile of all commodities. Electricity must be consumed as soon as it is generated due to the inability to store it in any sufficient quantity. Economic uncertainty exists because the supply of electricity cannot shift as quickly as the demand, which is highly variable. When demand increases quickly, the price must respond. Therefore, price spikes occur that are orders of magnitude higher than the base electricity price. This paper presents a robust and realistic model for spot market electricity prices used to manage risk in volatile markets. The model is a hybrid of a top down data driven method commonly used for financial applications, and a bottom up system driven method commonly used in regulated electricity markets. The advantage of the model is that it incorporates primary system drivers and demonstrates their effects on final prices. The 4 primary modules of the model are: (1) a model for forced outages, (2) a model for maintenance outages, (3) an electrical load model, and (4) a price model which combines the results of the previous 3 models. The performance of each model was tested. The forced outage model is the first of its kind to simulate the system on an aggregate basis using Weibull distributions. The overall spot price model was calibrated to, and tested with, data from the electricity market in Pennsylvania, New Jersey and Maryland. The model performed well in simulated market prices and adapted readily to changing system conditions and new electricity markets. This study examined the pricing of derivative contracts on electrical power. It also compared a range of portfolio scenarios using a Cash Flow at Risk approach.

  1. A Hybrid Teaching and Learning Model

    Science.gov (United States)

    Juhary, Jowati Binti

    This paper aims at analysing the needs for a specific teaching and learning model for the National Defence University of Malaysia (NDUM). The main argument is that whether there are differences between teaching and learning for academic component versus military component at the university. It is further argued that in order to achieve excellence, there should be one teaching and learning culture. Data were collected through interviews with military cadets. It is found that there are variations of teaching and learning strategies for academic courses, in comparison to a dominant teaching and learning style for military courses. Thus, in the interest of delivering quality education and training for students at the university, the paper argues that possibly a hybrid model for teaching and learning is fundamental in order to generate a one culture of academic and military excellence for the NDUM.

  2. Modelling supervisory controller for hybrid power systems

    Energy Technology Data Exchange (ETDEWEB)

    Pereira, A; Bindner, H; Lundsager, P [Risoe National Lab., Roskilde (Denmark); Jannerup, O [Technical Univ. of Denmark, Dept. of Automation, Lyngby (Denmark)

    1999-03-01

    Supervisory controllers are important to achieve optimal operation of hybrid power systems. The performance and economics of such systems depend mainly on the control strategy for switching on/off components. The modular concept described in this paper is an attempt to design standard supervisory controllers that could be used in different applications, such as village power and telecommunication applications. This paper presents some basic aspects of modelling and design of modular supervisory controllers using the object-oriented modelling technique. The functional abstraction hierarchy technique is used to formulate the control requirements and identify the functions of the control system. The modular algorithm is generic and flexible enough to be used with any system configuration and several goals (different applications). The modularity includes accepting modification of system configuration and goals during operation with minor or no changes in the supervisory controller. (au)

  3. A discriminative method for family-based protein remote homology detection that combines inductive logic programming and propositional models.

    Science.gov (United States)

    Bernardes, Juliana S; Carbone, Alessandra; Zaverucha, Gerson

    2011-03-23

    Remote homology detection is a hard computational problem. Most approaches have trained computational models by using either full protein sequences or multiple sequence alignments (MSA), including all positions. However, when we deal with proteins in the "twilight zone" we can observe that only some segments of sequences (motifs) are conserved. We introduce a novel logical representation that allows us to represent physico-chemical properties of sequences, conserved amino acid positions and conserved physico-chemical positions in the MSA. From this, Inductive Logic Programming (ILP) finds the most frequent patterns (motifs) and uses them to train propositional models, such as decision trees and support vector machines (SVM). We use the SCOP database to perform our experiments by evaluating protein recognition within the same superfamily. Our results show that our methodology when using SVM performs significantly better than some of the state of the art methods, and comparable to other. However, our method provides a comprehensible set of logical rules that can help to understand what determines a protein function. The strategy of selecting only the most frequent patterns is effective for the remote homology detection. This is possible through a suitable first-order logical representation of homologous properties, and through a set of frequent patterns, found by an ILP system, that summarizes essential features of protein functions.

  4. A Hybrid Tsunami Risk Model for Japan

    Science.gov (United States)

    Haseemkunju, A. V.; Smith, D. F.; Khater, M.; Khemici, O.; Betov, B.; Scott, J.

    2014-12-01

    Around the margins of the Pacific Ocean, denser oceanic plates slipping under continental plates cause subduction earthquakes generating large tsunami waves. The subducting Pacific and Philippine Sea plates create damaging interplate earthquakes followed by huge tsunami waves. It was a rupture of the Japan Trench subduction zone (JTSZ) and the resultant M9.0 Tohoku-Oki earthquake that caused the unprecedented tsunami along the Pacific coast of Japan on March 11, 2011. EQECAT's Japan Earthquake model is a fully probabilistic model which includes a seismo-tectonic model describing the geometries, magnitudes, and frequencies of all potential earthquake events; a ground motion model; and a tsunami model. Within the much larger set of all modeled earthquake events, fault rupture parameters for about 24000 stochastic and 25 historical tsunamigenic earthquake events are defined to simulate tsunami footprints using the numerical tsunami model COMCOT. A hybrid approach using COMCOT simulated tsunami waves is used to generate inundation footprints, including the impact of tides and flood defenses. Modeled tsunami waves of major historical events are validated against observed data. Modeled tsunami flood depths on 30 m grids together with tsunami vulnerability and financial models are then used to estimate insured loss in Japan from the 2011 tsunami. The primary direct report of damage from the 2011 tsunami is in terms of the number of buildings damaged by municipality in the tsunami affected area. Modeled loss in Japan from the 2011 tsunami is proportional to the number of buildings damaged. A 1000-year return period map of tsunami waves shows high hazard along the west coast of southern Honshu, on the Pacific coast of Shikoku, and on the east coast of Kyushu, primarily associated with major earthquake events on the Nankai Trough subduction zone (NTSZ). The highest tsunami hazard of more than 20m is seen on the Sanriku coast in northern Honshu, associated with the JTSZ.

  5. A muscle model for hybrid muscle activation

    Directory of Open Access Journals (Sweden)

    Klauer Christian

    2015-09-01

    Full Text Available To develop model-based control strategies for Functional Electrical Stimulation (FES in order to support weak voluntary muscle contractions, a hybrid model for describing joint motions induced by concurrent voluntary-and FES induced muscle activation is proposed. It is based on a Hammerstein model – as commonly used in feedback controlled FES – and exemplarily applied to describe the shoulder abduction joint angle. Main component of a Hammerstein muscle model is usually a static input nonlinearity depending on the stimulation intensity. To additionally incorporate voluntary contributions, we extended the static non-linearity by a second input describing the intensity of the voluntary contribution that is estimated by electromyography (EMG measurements – even during active FES. An Artificial Neural Network (ANN is used to describe the static input non-linearity. The output of the ANN drives a second-order linear dynamical system that describes the combined muscle activation and joint angle dynamics. The tunable parameters are adapted to the individual subject by a system identification approach using previously recorded I/O-data. The model has been validated in two healthy subjects yielding RMS values for the joint angle error of 3.56° and 3.44°, respectively.

  6. Hybrid discrete choice models: Gained insights versus increasing effort

    International Nuclear Information System (INIS)

    Mariel, Petr; Meyerhoff, Jürgen

    2016-01-01

    Hybrid choice models expand the standard models in discrete choice modelling by incorporating psychological factors as latent variables. They could therefore provide further insights into choice processes and underlying taste heterogeneity but the costs of estimating these models often significantly increase. This paper aims at comparing the results from a hybrid choice model and a classical random parameter logit. Point of departure for this analysis is whether researchers and practitioners should add hybrid choice models to their suite of models routinely estimated. Our comparison reveals, in line with the few prior studies, that hybrid models gain in efficiency by the inclusion of additional information. The use of one of the two proposed approaches, however, depends on the objective of the analysis. If disentangling preference heterogeneity is most important, hybrid model seems to be preferable. If the focus is on predictive power, a standard random parameter logit model might be the better choice. Finally, we give recommendations for an adequate use of hybrid choice models based on known principles of elementary scientific inference. - Highlights: • The paper compares performance of a Hybrid Choice Model (HCM) and a classical Random Parameter Logit (RPL) model. • The HCM indeed provides insights regarding preference heterogeneity not gained from the RPL. • The RPL has similar predictive power as the HCM in our data. • The costs of estimating HCM seem to be justified when learning more on taste heterogeneity is a major study objective.

  7. Hybrid discrete choice models: Gained insights versus increasing effort

    Energy Technology Data Exchange (ETDEWEB)

    Mariel, Petr, E-mail: petr.mariel@ehu.es [UPV/EHU, Economía Aplicada III, Avda. Lehendakari Aguire, 83, 48015 Bilbao (Spain); Meyerhoff, Jürgen [Institute for Landscape Architecture and Environmental Planning, Technical University of Berlin, D-10623 Berlin, Germany and The Kiel Institute for the World Economy, Duesternbrooker Weg 120, 24105 Kiel (Germany)

    2016-10-15

    Hybrid choice models expand the standard models in discrete choice modelling by incorporating psychological factors as latent variables. They could therefore provide further insights into choice processes and underlying taste heterogeneity but the costs of estimating these models often significantly increase. This paper aims at comparing the results from a hybrid choice model and a classical random parameter logit. Point of departure for this analysis is whether researchers and practitioners should add hybrid choice models to their suite of models routinely estimated. Our comparison reveals, in line with the few prior studies, that hybrid models gain in efficiency by the inclusion of additional information. The use of one of the two proposed approaches, however, depends on the objective of the analysis. If disentangling preference heterogeneity is most important, hybrid model seems to be preferable. If the focus is on predictive power, a standard random parameter logit model might be the better choice. Finally, we give recommendations for an adequate use of hybrid choice models based on known principles of elementary scientific inference. - Highlights: • The paper compares performance of a Hybrid Choice Model (HCM) and a classical Random Parameter Logit (RPL) model. • The HCM indeed provides insights regarding preference heterogeneity not gained from the RPL. • The RPL has similar predictive power as the HCM in our data. • The costs of estimating HCM seem to be justified when learning more on taste heterogeneity is a major study objective.

  8. Combined HQSAR, topomer CoMFA, homology modeling and docking studies on triazole derivatives as SGLT2 inhibitors.

    Science.gov (United States)

    Yu, Shuling; Yuan, Jintao; Zhang, Yi; Gao, Shufang; Gan, Ying; Han, Meng; Chen, Yuewen; Zhou, Qiaoqiao; Shi, Jiahua

    2017-06-01

    Sodium-glucose cotransporter 2 (SGLT2) is a promising target for diabetes therapy. We aimed to develop computational approaches to identify structural features for more potential SGLT2 inhibitors. In this work, 46 triazole derivatives as SGLT2 inhibitors were studied using a combination of several approaches, including hologram quantitative structure-activity relationships (HQSAR), topomer comparative molecular field analysis (CoMFA), homology modeling, and molecular docking. HQSAR and topomer CoMFA were used to construct models. Molecular docking was conducted to investigate the interaction of triazole derivatives and homology modeling of SGLT2, as well as to validate the results of the HQSAR and topomer CoMFA models. The most effective HQSAR and topomer CoMFA models exhibited noncross-validated correlation coefficients of 0.928 and 0.891 for the training set, respectively. External predictions were made successfully on a test set and then compared with previously reported models. The graphical results of HQSAR and topomer CoMFA were proven to be consistent with the binding mode of the inhibitors and SGLT2 from molecular docking. The models and docking provided important insights into the design of potent inhibitors for SGLT2.

  9. Exploratory Topology Modelling of Form-Active Hybrid Structures

    DEFF Research Database (Denmark)

    Holden Deleuran, Anders; Pauly, Mark; Tamke, Martin

    2016-01-01

    The development of novel form-active hybrid structures (FAHS) is impeded by a lack of modelling tools that allow for exploratory topology modelling of shaped assemblies. We present a flexible and real-time computational design modelling pipeline developed for the exploratory modelling of FAHS...... that enables designers and engineers to iteratively construct and manipulate form-active hybrid assembly topology on the fly. The pipeline implements Kangaroo2's projection-based methods for modelling hybrid structures consisting of slender beams and cable networks. A selection of design modelling sketches...

  10. Molecular modeling used to evaluate CYP2C9-dependent metabolism: homology modeling, molecular dynamics and docking simulations.

    Science.gov (United States)

    Mendieta-Wejebe, Jessica E; Correa-Basurto, José; García-Segovia, Erika M; Ceballos-Cancino, Gisela; Rosales-Hernández, Martha C

    2011-07-01

    Cytochrome P450 (CYP) 2C9 is the principal isoform of the CYP2C subfamily in the human liver and is involved in the oxidation of several endogenous and xenobiotic compounds, including many therapeutic drugs. The metabolism of drugs by CYP2C9 can yield either safe or toxic products, which may be related to the recognition and binding modes of the substrates to this isoform. These interactions can be studied using in silico methods such as quantum chemistry, molecular dynamics and docking simulations, which can also be useful for predicting the structure of metabolites. In these types of studies, the ligand and the protein must be tridimensional models; thus, the protein can be built by homology modeling or retrieved from the Protein Data Bank. Therefore, the current review emphasizes the importance of using in silico methods to predict the metabolism of CYP2C9 because these computational tools have allowed the description of the principal characteristics of the active site of this isoform at the molecular level and the chemical properties of its ligands.

  11. Repeat-swap homology modeling of secondary active transporters: updated protocol and prediction of elevator-type mechanisms.

    Science.gov (United States)

    Vergara-Jaque, Ariela; Fenollar-Ferrer, Cristina; Kaufmann, Desirée; Forrest, Lucy R

    2015-01-01

    Secondary active transporters are critical for neurotransmitter clearance and recycling during synaptic transmission and uptake of nutrients. These proteins mediate the movement of solutes against their concentration gradients, by using the energy released in the movement of ions down pre-existing concentration gradients. To achieve this, transporters conform to the so-called alternating-access hypothesis, whereby the protein adopts at least two conformations in which the substrate binding sites are exposed to one or other side of the membrane, but not both simultaneously. Structures of a bacterial homolog of neuronal glutamate transporters, GltPh, in several different conformational states have revealed that the protein structure is asymmetric in the outward- and inward-open states, and that the conformational change connecting them involves a elevator-like movement of a substrate binding domain across the membrane. The structural asymmetry is created by inverted-topology repeats, i.e., structural repeats with similar overall folds whose transmembrane topologies are related to each other by two-fold pseudo-symmetry around an axis parallel to the membrane plane. Inverted repeats have been found in around three-quarters of secondary transporter folds. Moreover, the (a)symmetry of these systems has been successfully used as a bioinformatic tool, called "repeat-swap modeling" to predict structural models of a transporter in one conformation using the known structure of the transporter in the complementary conformation as a template. Here, we describe an updated repeat-swap homology modeling protocol, and calibrate the accuracy of the method using GltPh, for which both inward- and outward-facing conformations are known. We then apply this repeat-swap homology modeling procedure to a concentrative nucleoside transporter, VcCNT, which has a three-dimensional arrangement related to that of GltPh. The repeat-swapped model of VcCNT predicts that nucleoside transport also

  12. Repeat-swap homology modeling of secondary active transporters: updated protocol and prediction of elevator-type mechanisms

    Directory of Open Access Journals (Sweden)

    Cristina eFenollar Ferrer

    2015-09-01

    Full Text Available Secondary active transporters are critical for neurotransmitter clearance and recycling during synaptic transmission and uptake of nutrients. These proteins mediate the movement of solutes against their concentration gradients, by using the energy released in the movement of ions down pre-existing concentration gradients. To achieve this, transporters conform to the so-called alternating-access hypothesis, whereby the protein adopts at least two conformations in which the substrate binding sites are exposed to either the outside or inside of the membrane, but not both simultaneously. Structures of a bacterial homolog of neuronal glutamate transporters, GltPh, in several different conformational states have revealed that the protein structure is asymmetric in the outward- and inward-open states, and that the conformational change connecting them involves a elevator-like movement of a substrate binding domain across the membrane. The structural asymmetry is created by inverted-topology repeats, i.e., structural repeats with similar overall folds whose transmembrane topologies are related to each other by two-fold pseudo-symmetry around an axis parallel to the membrane plane. Inverted repeats have been found in around three-quarters of secondary transporter folds. Moreover, the (asymmetry of these systems has been successfully used as a bioinformatic tool, called repeat-swap modeling to predict structural models of a transporter in one conformation using the known structure of the transporter in the complementary conformation as a template. Here, we describe an updated repeat-swap homology modeling protocol, and calibrate the accuracy of the method using GltPh, for which both inward- and outward-facing conformations are known. We then apply this repeat-swap homology modeling procedure to a concentrative nucleoside transporter, VcCNT, which has a three-dimensional arrangement related to that of GltPh. The repeat-swapped model of VcCNT predicts that

  13. Construction and validation of a homology model of the human voltage-gated proton channel hHV1.

    Science.gov (United States)

    Kulleperuma, Kethika; Smith, Susan M E; Morgan, Deri; Musset, Boris; Holyoake, John; Chakrabarti, Nilmadhab; Cherny, Vladimir V; DeCoursey, Thomas E; Pomès, Régis

    2013-04-01

    The topological similarity of voltage-gated proton channels (H(V)1s) to the voltage-sensing domain (VSD) of other voltage-gated ion channels raises the central question of whether H(V)1s have a similar structure. We present the construction and validation of a homology model of the human H(V)1 (hH(V)1). Multiple structural alignment was used to construct structural models of the open (proton-conducting) state of hH(V)1 by exploiting the homology of hH(V)1 with VSDs of K(+) and Na(+) channels of known three-dimensional structure. The comparative assessment of structural stability of the homology models and their VSD templates was performed using massively repeated molecular dynamics simulations in which the proteins were allowed to relax from their initial conformation in an explicit membrane mimetic. The analysis of structural deviations from the initial conformation based on up to 125 repeats of 100-ns simulations for each system reveals structural features consistently retained in the homology models and leads to a consensus structural model for hH(V)1 in which well-defined external and internal salt-bridge networks stabilize the open state. The structural and electrostatic properties of this open-state model are compatible with proton translocation and offer an explanation for the reversal of charge selectivity in neutral mutants of Asp(112). Furthermore, these structural properties are consistent with experimental accessibility data, providing a valuable basis for further structural and functional studies of hH(V)1. Each Arg residue in the S4 helix of hH(V)1 was replaced by His to test accessibility using Zn(2+) as a probe. The two outermost Arg residues in S4 were accessible to external solution, whereas the innermost one was accessible only to the internal solution. Both modeling and experimental data indicate that in the open state, Arg(211), the third Arg residue in the S4 helix in hH(V)1, remains accessible to the internal solution and is located near the

  14. Comments on the Updated Tetrapartite Pallium Model in the Mouse and Chick, Featuring a Homologous Claustro-Insular Complex.

    Science.gov (United States)

    Puelles, Luis

    2017-01-01

    This essay reviews step by step the conceptual changes of the updated tetrapartite pallium model from its tripartite and early tetrapartite antecedents. The crucial observations in mouse material are explained first in the context of assumptions, tentative interpretations, and literature data. Errors and the solutions offered to resolve them are made explicit. Next, attention is centered on the lateral pallium sector of the updated model, whose definition is novel in incorporating a claustro-insular complex distinct from both olfactory centers (ventral pallium) and the isocortex (dorsal pallium). The general validity of the model is postulated at least for tetrapods. Genoarchitectonic studies performed to check the presence of a claustro-insular field homolog in the avian brain are reviewed next. These studies have indeed revealed the existence of such a complex in the avian mesopallium (though stratified outside-in rather than inside-out as in mammals), and there are indications that the same pattern may be found in reptiles as well. Peculiar pallio-pallial tangential migratory phenomena are apparently shared as well between mice and chicks. The issue of whether the avian mesopallium has connections that are similar to the known connections of the mammalian claustro-insular complex is considered next. Accrued data are consistent with similar connections for the avian insula homolog, but they are judged to be insufficient to reach definitive conclusions about the avian claustrum. An aside discusses that conserved connections are not a necessary feature of field-homologous neural centers. Finally, the present scenario on the evolution of the pallium of sauropsids and mammals is briefly visited, as highlighted by the updated tetrapartite model and present results. © 2017 S. Karger AG, Basel.

  15. Synthesis, Biological Evaluation, and Molecular Modeling Studies of New Oxadiazole-Stilbene Hybrids against Phytopathogenic Fungi

    Science.gov (United States)

    Jian, Weilin; He, Daohang; Song, Shaoyun

    2016-08-01

    Natural stilbenes (especially resveratrol) play important roles in plant protection by acting as both constitutive and inducible defenses. However, their exogenous applications on crops as fungicidal agents are challenged by their oxidative degradation and limited availability. In this study, a new class of resveratrol-inspired oxadiazole-stilbene hybrids was synthesized via Wittig-Horner reaction. Bioassay results indicated that some of the compounds exhibited potent fungicidal activity against Botrytis cinerea in vitro. Among these stilbene hybrids, compounds 11 showed promising inhibitory activity with the EC50 value of 144.6 μg/mL, which was superior to that of resveratrol (315.6 μg/mL). Remarkably, the considerably abnormal mycelial morphology was observed in the presence of compound 11. The inhibitory profile was further proposed by homology modeling and molecular docking studies, which showed the possible interaction of resveratrol and oxadiazole-stilbene hybrids with the cytochrome P450-dependent sterol 14α-demethylase from B. cinerea (BcCYP51) for the first time. Taken together, these results would provide new insights into the fungicidal mechanism of stilbenes, as well as an important clue for biology-oriented synthesis of stilbene hybrids with improved bioactivity against plant pathogenic fungi in crop protection.

  16. Homology modeling, molecular docking and DNA binding studies of nucleotide excision repair UvrC protein from M. tuberculosis.

    Science.gov (United States)

    Parulekar, Rishikesh S; Barage, Sagar H; Jalkute, Chidambar B; Dhanavade, Maruti J; Fandilolu, Prayagraj M; Sonawane, Kailas D

    2013-08-01

    Mycobacterium tuberculosis is a Gram positive, acid-fast bacteria belonging to genus Mycobacterium, is the leading causative agent of most cases of tuberculosis. The pathogenicity of the bacteria is enhanced by its developed DNA repair mechanism which consists of machineries such as nucleotide excision repair. Nucleotide excision repair consists of excinuclease protein UvrABC endonuclease, multi-enzymatic complex which carries out repair of damaged DNA in sequential manner. UvrC protein is a part of this complex and thus helps to repair the damaged DNA of M. tuberculosis. Hence, structural bioinformatics study of UvrC protein from M. tuberculosis was carried out using homology modeling and molecular docking techniques. Assessment of the reliability of the homology model was carried out by predicting its secondary structure along with its model validation. The predicted structure was docked with the ATP and the interacting amino acid residues of UvrC protein with the ATP were found to be TRP539, PHE89, GLU536, ILE402 and ARG575. The binding of UvrC protein with the DNA showed two different domains. The residues from domain I of the protein VAL526, THR524 and LEU521 interact with the DNA whereas, amino acids interacting from the domain II of the UvrC protein included ARG597, GLU595, GLY594 and GLY592 residues. This predicted model could be useful to design new inhibitors of UvrC enzyme to prevent pathogenesis of Mycobacterium and so the tuberculosis.

  17. Modelling of data uncertainties on hybrid computers

    Energy Technology Data Exchange (ETDEWEB)

    Schneider, Anke (ed.)

    2016-06-15

    The codes d{sup 3}f and r{sup 3}t are well established for modelling density-driven flow and nuclide transport in the far field of repositories for hazardous material in deep geological formations. They are applicable in porous media as well as in fractured rock or mudstone, for modelling salt- and heat transport as well as a free groundwater surface. Development of the basic framework of d{sup 3}f and r{sup 3}t had begun more than 20 years ago. Since that time significant advancements took place in the requirements for safety assessment as well as for computer hardware development. The period of safety assessment for a repository of high-level radioactive waste was extended to 1 million years, and the complexity of the models is steadily growing. Concurrently, the demands on accuracy increase. Additionally, model and parameter uncertainties become more and more important for an increased understanding of prediction reliability. All this leads to a growing demand for computational power that requires a considerable software speed-up. An effective way to achieve this is the use of modern, hybrid computer architectures which requires basically the set-up of new data structures and a corresponding code revision but offers a potential speed-up by several orders of magnitude. The original codes d{sup 3}f and r{sup 3}t were applications of the software platform UG /BAS 94/ whose development had begun in the early nineteennineties. However, UG had recently been advanced to the C++ based, substantially revised version UG4 /VOG 13/. To benefit also in the future from state-of-the-art numerical algorithms and to use hybrid computer architectures, the codes d{sup 3}f and r{sup 3}t were transferred to this new code platform. Making use of the fact that coupling between different sets of equations is natively supported in UG4, d{sup 3}f and r{sup 3}t were combined to one conjoint code d{sup 3}f++. A direct estimation of uncertainties for complex groundwater flow models with the

  18. Model predictive control of hybrid systems : stability and robustness

    NARCIS (Netherlands)

    Lazar, M.

    2006-01-01

    This thesis considers the stabilization and the robust stabilization of certain classes of hybrid systems using model predictive control. Hybrid systems represent a broad class of dynamical systems in which discrete behavior (usually described by a finite state machine) and continuous behavior

  19. Transient Model of Hybrid Concentrated Photovoltaic with Thermoelectric Generator

    DEFF Research Database (Denmark)

    Mahmoudi Nezhad, Sajjad; Qing, Shaowei; Rezaniakolaei, Alireza

    2017-01-01

    Transient performance of a concentrated photovoltaic thermoelectric (CPV-TEG) hybrid system is modeled and investigated. A heat sink with water, as the working fluid has been implemented as the cold reservoir of the hybrid system to harvest the heat loss from CPV cell and to increase the efficiency...

  20. How to Choose the Suitable Template for Homology Modelling of GPCRs: 5-HT7 Receptor as a Test Case.

    Science.gov (United States)

    Shahaf, Nir; Pappalardo, Matteo; Basile, Livia; Guccione, Salvatore; Rayan, Anwar

    2016-09-01

    G protein-coupled receptors (GPCRs) are a super-family of membrane proteins that attract great pharmaceutical interest due to their involvement in almost every physiological activity, including extracellular stimuli, neurotransmission, and hormone regulation. Currently, structural information on many GPCRs is mainly obtained by the techniques of computer modelling in general and by homology modelling in particular. Based on a quantitative analysis of eighteen antagonist-bound, resolved structures of rhodopsin family "A" receptors - also used as templates to build 153 homology models - it was concluded that a higher sequence identity between two receptors does not guarantee a lower RMSD between their structures, especially when their pair-wise sequence identity (within trans-membrane domain and/or in binding pocket) lies between 25 % and 40 %. This study suggests that we should consider all template receptors having a sequence identity ≤50 % with the query receptor. In fact, most of the GPCRs, compared to the currently available resolved structures of GPCRs, fall within this range and lack a correlation between structure and sequence. When testing suitability for structure-based drug design, it was found that choosing as a template the most similar resolved protein, based on sequence resemblance only, led to unsound results in many cases. Molecular docking analyses were carried out, and enrichment factors as well as attrition rates were utilized as criteria for assessing suitability for structure-based drug design. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Design, analysis and modeling of a novel hybrid powertrain system based on hybridized automated manual transmission

    Science.gov (United States)

    Wu, Guang; Dong, Zuomin

    2017-09-01

    Hybrid electric vehicles are widely accepted as a promising short to mid-term technical solution due to noticeably improved efficiency and lower emissions at competitive costs. In recent years, various hybrid powertrain systems were proposed and implemented based on different types of conventional transmission. Power-split system, including Toyota Hybrid System and Ford Hybrid System, are well-known examples. However, their relatively low torque capacity, and the drive of alternative and more advanced designs encouraged other innovative hybrid system designs. In this work, a new type of hybrid powertrain system based hybridized automated manual transmission (HAMT) is proposed. By using the concept of torque gap filler (TGF), this new hybrid powertrain type has the potential to overcome issue of torque gap during gearshift. The HAMT design (patent pending) is described in details, from gear layout and design of gear ratios (EV mode and HEV mode) to torque paths at different gears. As an analytical tool, mutli-body model of vehicle equipped with this HAMT was built to analyze powertrain dynamics at various steady and transient modes. A gearshift was decomposed and analyzed based basic modes. Furthermore, a Simulink-SimDriveline hybrid vehicle model was built for the new transmission, driveline and vehicle modular. Control strategy has also been built to harmonically coordinate different powertrain components to realize TGF function. A vehicle launch simulation test has been completed under 30% of accelerator pedal position to reveal details during gearshift. Simulation results showed that this HAMT can eliminate most torque gap that has been persistent issue of traditional AMT, improving both drivability and performance. This work demonstrated a new type of transmission that features high torque capacity, high efficiency and improved drivability.

  2. Expression of venom gene homologs in diverse python tissues suggests a new model for the evolution of snake venom.

    Science.gov (United States)

    Reyes-Velasco, Jacobo; Card, Daren C; Andrew, Audra L; Shaney, Kyle J; Adams, Richard H; Schield, Drew R; Casewell, Nicholas R; Mackessy, Stephen P; Castoe, Todd A

    2015-01-01

    Snake venom gene evolution has been studied intensively over the past several decades, yet most previous studies have lacked the context of complete snake genomes and the full context of gene expression across diverse snake tissues. We took a novel approach to studying snake venom evolution by leveraging the complete genome of the Burmese python, including information from tissue-specific patterns of gene expression. We identified the orthologs of snake venom genes in the python genome, and conducted detailed analysis of gene expression of these venom homologs to identify patterns that differ between snake venom gene families and all other genes. We found that venom gene homologs in the python are expressed in many different tissues outside of oral glands, which illustrates the pitfalls of using transcriptomic data alone to define "venom toxins." We hypothesize that the python may represent an ancestral state prior to major venom development, which is supported by our finding that the expansion of venom gene families is largely restricted to highly venomous caenophidian snakes. Therefore, the python provides insight into biases in which genes were recruited for snake venom systems. Python venom homologs are generally expressed at lower levels, have higher variance among tissues, and are expressed in fewer organs compared with all other python genes. We propose a model for the evolution of snake venoms in which venom genes are recruited preferentially from genes with particular expression profile characteristics, which facilitate a nearly neutral transition toward specialized venom system expression. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  3. Bond graph model-based fault diagnosis of hybrid systems

    CERN Document Server

    Borutzky, Wolfgang

    2015-01-01

    This book presents a bond graph model-based approach to fault diagnosis in mechatronic systems appropriately represented by a hybrid model. The book begins by giving a survey of the fundamentals of fault diagnosis and failure prognosis, then recalls state-of-art developments referring to latest publications, and goes on to discuss various bond graph representations of hybrid system models, equations formulation for switched systems, and simulation of their dynamic behavior. The structured text: • focuses on bond graph model-based fault detection and isolation in hybrid systems; • addresses isolation of multiple parametric faults in hybrid systems; • considers system mode identification; • provides a number of elaborated case studies that consider fault scenarios for switched power electronic systems commonly used in a variety of applications; and • indicates that bond graph modelling can also be used for failure prognosis. In order to facilitate the understanding of fault diagnosis and the presented...

  4. Hybrid model for simulation of plasma jet injection in tokamak

    Science.gov (United States)

    Galkin, Sergei A.; Bogatu, I. N.

    2016-10-01

    Hybrid kinetic model of plasma treats the ions as kinetic particles and the electrons as charge neutralizing massless fluid. The model is essentially applicable when most of the energy is concentrated in the ions rather than in the electrons, i.e. it is well suited for the high-density hyper-velocity C60 plasma jet. The hybrid model separates the slower ion time scale from the faster electron time scale, which becomes disregardable. That is why hybrid codes consistently outperform the traditional PIC codes in computational efficiency, still resolving kinetic ions effects. We discuss 2D hybrid model and code with exact energy conservation numerical algorithm and present some results of its application to simulation of C60 plasma jet penetration through tokamak-like magnetic barrier. We also examine the 3D model/code extension and its possible applications to tokamak and ionospheric plasmas. The work is supported in part by US DOE DE-SC0015776 Grant.

  5. A Structural Model Decomposition Framework for Hybrid Systems Diagnosis

    Science.gov (United States)

    Daigle, Matthew; Bregon, Anibal; Roychoudhury, Indranil

    2015-01-01

    Nowadays, a large number of practical systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete modes of behavior, each defined by a set of continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task very challenging. In this work, we present a new modeling and diagnosis framework for hybrid systems. Models are composed from sets of user-defined components using a compositional modeling approach. Submodels for residual generation are then generated for a given mode, and reconfigured efficiently when the mode changes. Efficient reconfiguration is established by exploiting causality information within the hybrid system models. The submodels can then be used for fault diagnosis based on residual generation and analysis. We demonstrate the efficient causality reassignment, submodel reconfiguration, and residual generation for fault diagnosis using an electrical circuit case study.

  6. Model for optimum design of standalone hybrid renewable energy ...

    African Journals Online (AJOL)

    An optimization model for the design of a hybrid renewable energy microgrid ... and increasing the rated power of the wind energy conversion system (WECS) or solar ... a 70% reduction in gas emissions and an 80% reduction in energy costs.

  7. Hybrid Modelling of Individual Movement and Collective Behaviour

    KAUST Repository

    Franz, Benjamin

    2013-01-01

    Mathematical models of dispersal in biological systems are often written in terms of partial differential equations (PDEs) which describe the time evolution of population-level variables (concentrations, densities). A more detailed modelling approach is given by individual-based (agent-based) models which describe the behaviour of each organism. In recent years, an intermediate modelling methodology - hybrid modelling - has been applied to a number of biological systems. These hybrid models couple an individual-based description of cells/animals with a PDE-model of their environment. In this chapter, we overview hybrid models in the literature with the focus on the mathematical challenges of this modelling approach. The detailed analysis is presented using the example of chemotaxis, where cells move according to extracellular chemicals that can be altered by the cells themselves. In this case, individual-based models of cells are coupled with PDEs for extracellular chemical signals. Travelling waves in these hybrid models are investigated. In particular, we show that in contrary to the PDEs, hybrid chemotaxis models only develop a transient travelling wave. © 2013 Springer-Verlag Berlin Heidelberg.

  8. Nuclear Hybrid Energy System Modeling: RELAP5 Dynamic Coupling Capabilities

    Energy Technology Data Exchange (ETDEWEB)

    Piyush Sabharwall; Nolan Anderson; Haihua Zhao; Shannon Bragg-Sitton; George Mesina

    2012-09-01

    The nuclear hybrid energy systems (NHES) research team is currently developing a dynamic simulation of an integrated hybrid energy system. A detailed simulation of proposed NHES architectures will allow initial computational demonstration of a tightly coupled NHES to identify key reactor subsystem requirements, identify candidate reactor technologies for a hybrid system, and identify key challenges to operation of the coupled system. This work will provide a baseline for later coupling of design-specific reactor models through industry collaboration. The modeling capability addressed in this report focuses on the reactor subsystem simulation.

  9. Toward the virtual screening of potential drugs in the homology modeled NAD+ dependent DNA ligase from Mycobacterium tuberculosis.

    Science.gov (United States)

    Singh, Vijai; Somvanshi, Pallavi

    2010-02-01

    DNA ligase is an important enzyme and it plays vital role in the replication and repair; also catalyzes nick joining between adjacent bases of DNA. The NAD(+) dependent DNA ligase is selectively present in eubacteria and few viruses; but missing in humans. Homology modeling was used to generate 3-D structure of NAD(+) dependent DNA ligase (LigA) of Mycobacterium tuberculosis using the known template (PDB: 2OWO). Furthermore, the stereochemical quality and torsion angle of 3-D structure was validated. Numerous effective drugs were selected and the active amino acid residue in LigA was targeted and virtual screening through molecular docking was done. In this analysis, four drugs Chloroquine, Hydroxychloroquine, Putrienscine and Adriamycin were found more potent in inhibition of M. tuberculosis through the robust binding affinity between protein-drug interactions in comparison with the other studied drugs. A phylogenetic tree was constructed and it was observed that homology of LigA in M. tuberculosis resembled with other Mycobacterium species. The conserved active amino acids of LigA may be useful to target these drugs. These findings could be used as the starting point of a rational design of novel antibacterial drugs and its analogs.

  10. Binding site analysis of full-length α1a adrenergic receptor using homology modeling and molecular docking

    International Nuclear Information System (INIS)

    Pedretti, Alessandro; Elena Silva, Maria; Villa, Luigi; Vistoli, Giulio

    2004-01-01

    The recent availability of crystal structure of bovine rhodopsin offers new opportunities in order to approach the construction of G protein coupled receptors. This study focuses the attention on the modeling of full-length α 1a adrenergic receptor (α 1a -AR) due to its biological role and significant implications in pharmacological treatment of benign prostate hyperplasia. This work could be considered made up by two main steps: (a) the construction of full structure of α 1a -AR, through homology modeling methods; (b) the automated docking of an endogenous agonist, norepinephrine, and of an antagonist, WB-4101, using BioDock program. The obtained results highlight the key residues involved in binding sites of both agonists and antagonists, confirming the mutagenesis data and giving new suggestions for the rational design of selective ligands

  11. VITAL NMR: using chemical shift derived secondary structure information for a limited set of amino acids to assess homology model accuracy

    Energy Technology Data Exchange (ETDEWEB)

    Brothers, Michael C.; Nesbitt, Anna E.; Hallock, Michael J. [University of Illinois at Urbana-Champaign, Department of Chemistry (United States); Rupasinghe, Sanjeewa G. [University of Illinois at Urbana-Champaign, Department of Cell and Developmental Biology (United States); Tang Ming [University of Illinois at Urbana-Champaign, Department of Chemistry (United States); Harris, Jason; Baudry, Jerome [University of Tennessee, Department of Biochemistry, Cellular and Molecular Biology (United States); Schuler, Mary A. [University of Illinois at Urbana-Champaign, Department of Cell and Developmental Biology (United States); Rienstra, Chad M., E-mail: rienstra@illinois.edu [University of Illinois at Urbana-Champaign, Department of Chemistry (United States)

    2012-01-15

    Homology modeling is a powerful tool for predicting protein structures, whose success depends on obtaining a reasonable alignment between a given structural template and the protein sequence being analyzed. In order to leverage greater predictive power for proteins with few structural templates, we have developed a method to rank homology models based upon their compliance to secondary structure derived from experimental solid-state NMR (SSNMR) data. Such data is obtainable in a rapid manner by simple SSNMR experiments (e.g., {sup 13}C-{sup 13}C 2D correlation spectra). To test our homology model scoring procedure for various amino acid labeling schemes, we generated a library of 7,474 homology models for 22 protein targets culled from the TALOS+/SPARTA+ training set of protein structures. Using subsets of amino acids that are plausibly assigned by SSNMR, we discovered that pairs of the residues Val, Ile, Thr, Ala and Leu (VITAL) emulate an ideal dataset where all residues are site specifically assigned. Scoring the models with a predicted VITAL site-specific dataset and calculating secondary structure with the Chemical Shift Index resulted in a Pearson correlation coefficient (-0.75) commensurate to the control (-0.77), where secondary structure was scored site specifically for all amino acids (ALL 20) using STRIDE. This method promises to accelerate structure procurement by SSNMR for proteins with unknown folds through guiding the selection of remotely homologous protein templates and assessing model quality.

  12. VITAL NMR: Using Chemical Shift Derived Secondary Structure Information for a Limited Set of Amino Acids to Assess Homology Model Accuracy

    Energy Technology Data Exchange (ETDEWEB)

    Brothers, Michael C [University of Illinois, Urbana-Champaign; Nesbitt, Anna E [University of Illinois, Urbana-Champaign; Hallock, Michael J [University of Illinois, Urbana-Champaign; Rupasinghe, Sanjeewa [University of Illinois, Urbana-Champaign; Tang, Ming [University of Illinois, Urbana-Champaign; Harris, Jason B [ORNL; Baudry, Jerome Y [ORNL; Schuler, Mary A [University of Illinois, Urbana-Champaign; Rienstra, Chad M [University of Illinois, Urbana-Champaign

    2011-01-01

    Homology modeling is a powerful tool for predicting protein structures, whose success depends on obtaining a reasonable alignment between a given structural template and the protein sequence being analyzed. In order to leverage greater predictive power for proteins with few structural templates, we have developed a method to rank homology models based upon their compliance to secondary structure derived from experimental solid-state NMR (SSNMR) data. Such data is obtainable in a rapid manner by simple SSNMR experiments (e.g., (13)C-(13)C 2D correlation spectra). To test our homology model scoring procedure for various amino acid labeling schemes, we generated a library of 7,474 homology models for 22 protein targets culled from the TALOS+/SPARTA+ training set of protein structures. Using subsets of amino acids that are plausibly assigned by SSNMR, we discovered that pairs of the residues Val, Ile, Thr, Ala and Leu (VITAL) emulate an ideal dataset where all residues are site specifically assigned. Scoring the models with a predicted VITAL site-specific dataset and calculating secondary structure with the Chemical Shift Index resulted in a Pearson correlation coefficient (-0.75) commensurate to the control (-0.77), where secondary structure was scored site specifically for all amino acids (ALL 20) using STRIDE. This method promises to accelerate structure procurement by SSNMR for proteins with unknown folds through guiding the selection of remotely homologous protein templates and assessing model quality.

  13. A hybrid Scatter/Transform cloaking model

    Directory of Open Access Journals (Sweden)

    Gad Licht

    2015-01-01

    Full Text Available A new Scatter/Transform cloak is developed that combines the light bending of refraction characteristic of a Transform cloak with the scatter cancellation characteristic of a Scatter cloak. The hybrid cloak incorporates both Transform’s variable index of refraction with modified linear intrusions to maximize the Scatter cloak effect. Scatter/Transform improved the scattering cross-section of cloaking in a 2-dimensional space to 51.7% compared to only 39.6% or 45.1% respectively with either Scatter or Transform alone. Metamaterials developed with characteristics based on the new ST hybrid cloak will exhibit superior cloaking capabilities.

  14. Hybrid approach to structure modeling of the histamine H3 receptor: Multi-level assessment as a tool for model verification.

    Directory of Open Access Journals (Sweden)

    Jakub Jończyk

    Full Text Available The crucial role of G-protein coupled receptors and the significant achievements associated with a better understanding of the spatial structure of known receptors in this family encouraged us to undertake a study on the histamine H3 receptor, whose crystal structure is still unresolved. The latest literature data and availability of different software enabled us to build homology models of higher accuracy than previously published ones. The new models are expected to be closer to crystal structures; and therefore, they are much more helpful in the design of potential ligands. In this article, we describe the generation of homology models with the use of diverse tools and a hybrid assessment. Our study incorporates a hybrid assessment connecting knowledge-based scoring algorithms with a two-step ligand-based docking procedure. Knowledge-based scoring employs probability theory for global energy minimum determination based on information about native amino acid conformation from a dataset of experimentally determined protein structures. For a two-step docking procedure two programs were applied: GOLD was used in the first step and Glide in the second. Hybrid approaches offer advantages by combining various theoretical methods in one modeling algorithm. The biggest advantage of hybrid methods is their intrinsic ability to self-update and self-refine when additional structural data are acquired. Moreover, the diversity of computational methods and structural data used in hybrid approaches for structure prediction limit inaccuracies resulting from theoretical approximations or fuzziness of experimental data. The results of docking to the new H3 receptor model allowed us to analyze ligand-receptor interactions for reference compounds.

  15. Superconductivity in the periodic Anderson model with anisotropic hybridization

    International Nuclear Information System (INIS)

    Sarasua, L.G.; Continentino, Mucio A.

    2003-01-01

    In this work we study superconductivity in the periodic Anderson model with both on-site and intersite hybridization, including the interband Coulomb repulsion. We show that the presence of the intersite hybridization together with the on-site hybridization significantly affects the superconducting properties of the system. The symmetry of the hybridization has a strong influence in the symmetry of the superconducting order parameter of the ground state. The interband Coulomb repulsion may increase or decrease the superconducting critical temperature at small values of this interaction, while is detrimental to superconductivity for strong values. We show that the present model can give rise to positive or negative values of dT c /dP, depending on the values of the system parameters

  16. Modelling and Verifying Communication Failure of Hybrid Systems in HCSP

    DEFF Research Database (Denmark)

    Wang, Shuling; Nielson, Flemming; Nielson, Hanne Riis

    2016-01-01

    Hybrid systems are dynamic systems with interacting discrete computation and continuous physical processes. They have become ubiquitous in our daily life, e.g. automotive, aerospace and medical systems, and in particular, many of them are safety-critical. For a safety-critical hybrid system......, in the presence of communication failure, the expected control from the controller will get lost and as a consequence the physical process cannot behave as expected. In this paper, we mainly consider the communication failure caused by the non-engagement of one party in communication action, i.......e. the communication itself fails to occur. To address this issue, this paper proposes a formal framework by extending HCSP, a formal modeling language for hybrid systems, for modeling and verifying hybrid systems in the absence of receiving messages due to communication failure. We present two inference systems...

  17. Fluid Survival Tool: A Model Checker for Hybrid Petri Nets

    NARCIS (Netherlands)

    Postema, Björn Frits; Remke, Anne Katharina Ingrid; Haverkort, Boudewijn R.H.M.; Ghasemieh, Hamed

    2014-01-01

    Recently, algorithms for model checking Stochastic Time Logic (STL) on Hybrid Petri nets with a single general one-shot transition (HPNG) have been introduced. This paper presents a tool for model checking HPNG models against STL formulas. A graphical user interface (GUI) not only helps to

  18. Nuclear Hybrid Energy System Model Stability Testing

    Energy Technology Data Exchange (ETDEWEB)

    Greenwood, Michael Scott [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Cetiner, Sacit M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Fugate, David W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2017-04-01

    A Nuclear Hybrid Energy System (NHES) uses a nuclear reactor as the basic power generation unit, and the power generated is used by multiple customers as combinations of thermal power or electrical power. The definition and architecture of a particular NHES can be adapted based on the needs and opportunities of different localities and markets. For example, locations in need of potable water may be best served by coupling a desalination plant to the NHES. Similarly, a location near oil refineries may have a need for emission-free hydrogen production. Using the flexible, multi-domain capabilities of Modelica, Argonne National Laboratory, Idaho National Laboratory, and Oak Ridge National Laboratory are investigating the dynamics (e.g., thermal hydraulics and electrical generation/consumption) and cost of a hybrid system. This paper examines the NHES work underway, emphasizing the control system developed for individual subsystems and the overall supervisory control system.

  19. Hybrid Modeling and Optimization of Yogurt Starter Culture Continuous Fermentation

    Directory of Open Access Journals (Sweden)

    Silviya Popova

    2009-10-01

    Full Text Available The present paper presents a hybrid model of yogurt starter mixed culture fermentation. The main nonlinearities within a classical structure of continuous process model are replaced by neural networks. The new hybrid model accounts for the dependence of the two microorganisms' kinetics from the on-line measured characteristics of the culture medium - pH. Then the model was used further for calculation of the optimal time profile of pH. The obtained results are with agreement with the experimental once.

  20. Mechanisms Underlying Mammalian Hybrid Sterility in Two Feline Interspecies Models.

    Science.gov (United States)

    Davis, Brian W; Seabury, Christopher M; Brashear, Wesley A; Li, Gang; Roelke-Parker, Melody; Murphy, William J

    2015-10-01

    The phenomenon of male sterility in interspecies hybrids has been observed for over a century, however, few genes influencing this recurrent phenotype have been identified. Genetic investigations have been primarily limited to a small number of model organisms, thus limiting our understanding of the underlying molecular basis of this well-documented "rule of speciation." We utilized two interspecies hybrid cat breeds in a genome-wide association study employing the Illumina 63 K single-nucleotide polymorphism array. Collectively, we identified eight autosomal genes/gene regions underlying associations with hybrid male sterility (HMS) involved in the function of the blood-testis barrier, gamete structural development, and transcriptional regulation. We also identified several candidate hybrid sterility regions on the X chromosome, with most residing in close proximity to complex duplicated regions. Differential gene expression analyses revealed significant chromosome-wide upregulation of X chromosome transcripts in testes of sterile hybrids, which were enriched for genes involved in chromatin regulation of gene expression. Our expression results parallel those reported in Mus hybrids, supporting the "Large X-Effect" in mammalian HMS and the potential epigenetic basis for this phenomenon. These results support the value of the interspecies feline model as a powerful tool for comparison to rodent models of HMS, demonstrating unique aspects and potential commonalities that underpin mammalian reproductive isolation. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  1. Biochemical Kinetics Model of DSB Repair and GammaH2AX FOCI by Non-homologous End Joining

    Science.gov (United States)

    Cucinotta, Francis, A.; Pluth, Janice M.; Anderson, Jennifer A.; Harper, Jane V.; O'Neill, Peter

    2007-01-01

    We developed a biochemical kinetics approach to describe the repair of double strand breaks (DSB) produced by low LET radiation by modeling molecular events associated with the mechanisms of non-homologous end-joining (NHEJ). A system of coupled non-linear ordinary differential equations describes the induction of DSB and activation pathways for major NHEJ components including Ku(sub 70/80), DNA-PK(sub cs), and the Ligase IV-XRCC4 hetero-dimer. The autophosphorylation of DNA-PK(sub cs and subsequent induction of gamma-H2AX foci observed after ionizing radiation exposure were modeled. A two-step model of DNA-PK(sub cs) regulation of repair was developed with the initial step allowing access of other NHEJ components to breaks, and a second step limiting access to Ligase IV-XRCC4. Our model assumes that the transition from the first to second-step depends on DSB complexity, with a much slower-rate for complex DSB. The model faithfully reproduced several experimental data sets, including DSB rejoining as measured by pulsed-field electrophoresis (PFGE), quantification of the induction of gamma-H2AX foci, and live cell imaging of the induction of Ku(sub 70/80). Predictions are made for the behaviors of NHEJ components at low doses and dose-rates, where a steady-state is found at dose-rates of 0.1 Gy/hr or lower.

  2. Discovery of Novel Inhibitors for Nek6 Protein through Homology Model Assisted Structure Based Virtual Screening and Molecular Docking Approaches

    Directory of Open Access Journals (Sweden)

    P. Srinivasan

    2014-01-01

    Full Text Available Nek6 is a member of the NIMA (never in mitosis, gene A-related serine/threonine kinase family that plays an important role in the initiation of mitotic cell cycle progression. This work is an attempt to emphasize the structural and functional relationship of Nek6 protein based on homology modeling and binding pocket analysis. The three-dimensional structure of Nek6 was constructed by molecular modeling studies and the best model was further assessed by PROCHECK, ProSA, and ERRAT plot in order to analyze the quality and consistency of generated model. The overall quality of computed model showed 87.4% amino acid residues under the favored region. A 3 ns molecular dynamics simulation confirmed that the structure was reliable and stable. Two lead compounds (Binding database ID: 15666, 18602 were retrieved through structure-based virtual screening and induced fit docking approaches as novel Nek6 inhibitors. Hence, we concluded that the potential compounds may act as new leads for Nek6 inhibitors designing.

  3. Exploration of freely available web-interfaces for comparative homology modelling of microbial proteins.

    Science.gov (United States)

    Nema, Vijay; Pal, Sudhir Kumar

    2013-01-01

    This study was conducted to find the best suited freely available software for modelling of proteins by taking a few sample proteins. The proteins used were small to big in size with available crystal structures for the purpose of benchmarking. Key players like Phyre2, Swiss-Model, CPHmodels-3.0, Homer, (PS)2, (PS)(2)-V(2), Modweb were used for the comparison and model generation. Benchmarking process was done for four proteins, Icl, InhA, and KatG of Mycobacterium tuberculosis and RpoB of Thermus Thermophilus to get the most suited software. Parameters compared during analysis gave relatively better values for Phyre2 and Swiss-Model. This comparative study gave the information that Phyre2 and Swiss-Model make good models of small and large proteins as compared to other screened software. Other software was also good but is often not very efficient in providing full-length and properly folded structure.

  4. Some hybrid models applicable to dose-response relationships

    International Nuclear Information System (INIS)

    Kumazawa, Shigeru

    1992-01-01

    A new type of models of dose-response relationships has been studied as an initial stage to explore a reliable extrapolation of the relationships decided by high dose data to the range of low dose covered by radiation protection. The approach is to use a 'hybrid scale' of linear and logarithmic scales; the first model is that the normalized surviving fraction (ρ S > 0) in a hybrid scale decreases linearly with dose in a linear scale, and the second is that the induction in a log scale increases linearly with the normalized dose (τ D > 0) in a hybrid scale. The hybrid scale may reflect an overall effectiveness of a complex system against adverse events caused by various agents. Some data of leukemia in the atomic bomb survivors and of rodent experiments were used to show the applicability of hybrid scale models. The results proved that proposed models fit these data not less than the popular linear-quadratic models, providing the possible interpretation of shapes of dose-response curves, e.g. shouldered survival curves varied by recovery time. (author)

  5. A hybrid agent-based approach for modeling microbiological systems.

    Science.gov (United States)

    Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

    2008-11-21

    Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

  6. Mutational analysis of the high-affinity zinc binding site validates a refined human dopamine transporter homology model.

    Directory of Open Access Journals (Sweden)

    Thomas Stockner

    Full Text Available The high-resolution crystal structure of the leucine transporter (LeuT is frequently used as a template for homology models of the dopamine transporter (DAT. Although similar in structure, DAT differs considerably from LeuT in a number of ways: (i when compared to LeuT, DAT has very long intracellular amino and carboxyl termini; (ii LeuT and DAT share a rather low overall sequence identity (22% and (iii the extracellular loop 2 (EL2 of DAT is substantially longer than that of LeuT. Extracellular zinc binds to DAT and restricts the transporter's movement through the conformational cycle, thereby resulting in a decrease in substrate uptake. Residue H293 in EL2 praticipates in zinc binding and must be modelled correctly to allow for a full understanding of its effects. We exploited the high-affinity zinc binding site endogenously present in DAT to create a model of the complete transmemberane domain of DAT. The zinc binding site provided a DAT-specific molecular ruler for calibration of the model. Our DAT model places EL2 at the transporter lipid interface in the vicinity of the zinc binding site. Based on the model, D206 was predicted to represent a fourth co-ordinating residue, in addition to the three previously described zinc binding residues H193, H375 and E396. This prediction was confirmed by mutagenesis: substitution of D206 by lysine and cysteine affected the inhibitory potency of zinc and the maximum inhibition exerted by zinc, respectively. Conversely, the structural changes observed in the model allowed for rationalizing the zinc-dependent regulation of DAT: upon binding, zinc stabilizes the outward-facing state, because its first coordination shell can only be completed in this conformation. Thus, the model provides a validated solution to the long extracellular loop and may be useful to address other aspects of the transport cycle.

  7. A new adaptive hybrid electromagnetic damper: modelling, optimization, and experiment

    International Nuclear Information System (INIS)

    Asadi, Ehsan; Ribeiro, Roberto; Behrad Khamesee, Mir; Khajepour, Amir

    2015-01-01

    This paper presents the development of a new electromagnetic hybrid damper which provides regenerative adaptive damping force for various applications. Recently, the introduction of electromagnetic technologies to the damping systems has provided researchers with new opportunities for the realization of adaptive semi-active damping systems with the added benefit of energy recovery. In this research, a hybrid electromagnetic damper is proposed. The hybrid damper is configured to operate with viscous and electromagnetic subsystems. The viscous medium provides a bias and fail-safe damping force while the electromagnetic component adds adaptability and the capacity for regeneration to the hybrid design. The electromagnetic component is modeled and analyzed using analytical (lumped equivalent magnetic circuit) and electromagnetic finite element method (FEM) (COMSOL ® software package) approaches. By implementing both modeling approaches, an optimization for the geometric aspects of the electromagnetic subsystem is obtained. Based on the proposed electromagnetic hybrid damping concept and the preliminary optimization solution, a prototype is designed and fabricated. A good agreement is observed between the experimental and FEM results for the magnetic field distribution and electromagnetic damping forces. These results validate the accuracy of the modeling approach and the preliminary optimization solution. An analytical model is also presented for viscous damping force, and is compared with experimental results The results show that the damper is able to produce damping coefficients of 1300 and 0–238 N s m −1 through the viscous and electromagnetic components, respectively. (paper)

  8. In silico sequence analysis and homology modeling of predicted beta-amylase 7-like protein in Brachypodium distachyon L.

    Directory of Open Access Journals (Sweden)

    ERTUĞRUL FILIZ

    2014-04-01

    Full Text Available Beta-amylase (β-amylase, EC 3.2.1.2 is an enzyme that catalyses hydrolysis of glucosidic bonds in polysaccharides. In this study, we analyzed protein sequence of predicted beta-amylase 7-like protein in Brachypodium distachyon. pI (isoelectric point value was found as 5.23 in acidic character, while the instability index (II was found as 50.28 with accepted unstable protein. The prediction of subcellular localization was revealed that the protein may reside in chloroplast by using CELLO v.2.5. The 3D structure of protein was performed using comparative homology modeling with SWISS-MODEL. The accuracy of the predicted 3D structure was checked using Ramachandran plot analysis showed that 95.4% in favored region. The results of our study contribute to understanding of β-amylase protein structure in grass species and will be scientific base for 3D modeling of beta-amylase proteins in further studies.

  9. QSAR models for prediction of chromatographic behavior of homologous Fab variants.

    Science.gov (United States)

    Robinson, Julie R; Karkov, Hanne S; Woo, James A; Krogh, Berit O; Cramer, Steven M

    2017-06-01

    While quantitative structure activity relationship (QSAR) models have been employed successfully for the prediction of small model protein chromatographic behavior, there have been few reports to date on the use of this methodology for larger, more complex proteins. Recently our group generated focused libraries of antibody Fab fragment variants with different combinations of surface hydrophobicities and electrostatic potentials, and demonstrated that the unique selectivities of multimodal resins can be exploited to separate these Fab variants. In this work, results from linear salt gradient experiments with these Fabs were employed to develop QSAR models for six chromatographic systems, including multimodal (Capto MMC, Nuvia cPrime, and two novel ligand prototypes), hydrophobic interaction chromatography (HIC; Capto Phenyl), and cation exchange (CEX; CM Sepharose FF) resins. The models utilized newly developed "local descriptors" to quantify changes around point mutations in the Fab libraries as well as novel cluster descriptors recently introduced by our group. Subsequent rounds of feature selection and linearized machine learning algorithms were used to generate robust, well-validated models with high training set correlations (R 2  > 0.70) that were well suited for predicting elution salt concentrations in the various systems. The developed models then were used to predict the retention of a deamidated Fab and isotype variants, with varying success. The results represent the first successful utilization of QSAR for the prediction of chromatographic behavior of complex proteins such as Fab fragments in multimodal chromatographic systems. The framework presented here can be employed to facilitate process development for the purification of biological products from product-related impurities by in silico screening of resin alternatives. Biotechnol. Bioeng. 2017;114: 1231-1240. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  10. Homology modeling of Leishmania donovani enolase and its molecular interaction with novel inhibitors

    Directory of Open Access Journals (Sweden)

    Jay Prakash Mahato

    2017-01-01

    Full Text Available Introduction: The treatment of Indian tropical disease such as kala-azar is likely to be troublesome to the clinicians as AmpB- and miltefosine-resistant Leishmania donovani has been reported. The rationale behind designed a novel inhibitors of model of L. donovani enolase and performing a binding study with its inhibitors to gain details of the interaction between protein residues and ligand molecules. Methods and Materials: The L. donovani enolase model consists of two typical domains. The N-terminal one contains three-stranded antiparallel β-sheets, followed by six α-helices. The C-terminal domain composes of eleven-stranded mixed α/β-barrel with connectivity. The first α-helix within the C-terminal domain, H7, and the second β-strand, S7, of the barrel domain was arranged in an antiparallel fashion compared to all other α-helices and β-strands. The root-mean-square deviation between predicted model and template is 0.4 Å. The overall conformation of L. donovani enolase model is similar to those of Trypanosoma cruzi enolase and Streptococcus pneumoniae enolase crystal structures. Result: The key amino acid residues within the docking complex model involved in the interaction between model enolase structure and ligand molecule are Lys70, Asn165, Ala168, Asp17, and Asn213. Conclusion: Our theoretical prediction may lead to the establishment of prophylactic and therapeutic approaches for the treatment of kala-azar. This biomedical informatics analysis will help us to combat future kala-azar.

  11. Hybrid programming model for implicit PDE simulations on multicore architectures

    KAUST Repository

    Kaushik, Dinesh; Keyes, David E.; Balay, Satish; Smith, Barry F.

    2011-01-01

    The complexity of programming modern multicore processor based clusters is rapidly rising, with GPUs adding further demand for fine-grained parallelism. This paper analyzes the performance of the hybrid (MPI+OpenMP) programming model in the context of an implicit unstructured mesh CFD code. At the implementation level, the effects of cache locality, update management, work division, and synchronization frequency are studied. The hybrid model presents interesting algorithmic opportunities as well: the convergence of linear system solver is quicker than the pure MPI case since the parallel preconditioner stays stronger when hybrid model is used. This implies significant savings in the cost of communication and synchronization (explicit and implicit). Even though OpenMP based parallelism is easier to implement (with in a subdomain assigned to one MPI process for simplicity), getting good performance needs attention to data partitioning issues similar to those in the message-passing case. © 2011 Springer-Verlag.

  12. Defining the limits of homology modeling in information-driven protein docking

    NARCIS (Netherlands)

    Garcia Lopes Maia Rodrigues, João; Melquiond, A S J; Karaca, E; Trellet, M; van Dijk, M; van Zundert, G C P; Schmitz, C; de Vries, S J; Bordogna, A; Bonati, L; Kastritis, P L; Bonvin, Alexandre M J J; Garcia Lopes Maia Rodrigues, João

    2013-01-01

    Information-driven docking is currently one of the most successful approaches to obtain structural models of protein interactions as demonstrated in the latest round of CAPRI. While various experimental and computational techniques can be used to retrieve information about the binding mode, the

  13. Homology modelling and docking studies on Neuraminidase enzyme as a natural product target for combating influenza

    Directory of Open Access Journals (Sweden)

    Nisha Singh

    2017-10-01

    Full Text Available Influenza remains to be dreadful with yearly epidemics and sudden pandemic outbreaks causing significant mortality, even in nations with the most advanced health care systems. Thus, there has been a long-standing interest to develop effective and safe antiviral agents to treat infected individuals. Attempt to identify suitable molecular targets as antiviral compounds have focused recently on the influenza virus neuraminidase (NA, a key enzyme in viral replication [1]. In this research, virtual screening was done on a total of 600 natural compounds from 22 ethno medicinal Indian herbs for activity against neuraminidase enzyme exploiting representative protein conformations selected from molecular dynamics simulations. Neuraminidase enzyme sequences from different existing strains available on National Center of Biotechnology Information [2] (NCBI protein database were aligned using Clustal W [3] and CLC workbench 10 [4] to find the conserved residues. Neuraminidase protein sequence from H1N1 strain available on NCBI was used to structure 3D target model predicted against dataset from Protein data bank using modeller [5]. The target model was validated on different parameter at SAVES Server [6]. Using this target model a pharmacophore model was developed using ligand based strategy exploiting the three known inhibitors. The docking parameters were validated by redocking Zanamivir to its co-complex 2009 H1N1 NA crystal structure (PDB ID: 3TI5 generating best pose with a RMSD value of 0.7543 A°. This model was then used for in silico analysis of a library of natural compounds from 22 ethno medicinal Indian herbs known to have antiviral activity taken downloaded from PubChem database and selected on the basis of drug likeliness. All the compounds were docked in the binding pocket of neuraminidase. Top compounds having binding affinity better than or comparable to the control drug Zanamivir were selected and analyzed for their ADME and toxicity

  14. Nuclear Hybrid Energy Systems FY16 Modeling Efforts at ORNL

    Energy Technology Data Exchange (ETDEWEB)

    Cetiner, Sacit M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Greenwood, Michael Scott [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Harrison, Thomas J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Qualls, A. L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Guler Yigitoglu, Askin [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Fugate, David W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2016-09-01

    A nuclear hybrid system uses a nuclear reactor as the basic power generation unit. The power generated by the nuclear reactor is utilized by one or more power customers as either thermal power, electrical power, or both. In general, a nuclear hybrid system will couple the nuclear reactor to at least one thermal power user in addition to the power conversion system. The definition and architecture of a particular nuclear hybrid system is flexible depending on local markets needs and opportunities. For example, locations in need of potable water may be best served by coupling a desalination plant to the nuclear system. Similarly, an area near oil refineries may have a need for emission-free hydrogen production. A nuclear hybrid system expands the nuclear power plant from its more familiar central power station role by diversifying its immediately and directly connected customer base. The definition, design, analysis, and optimization work currently performed with respect to the nuclear hybrid systems represents the work of three national laboratories. Idaho National Laboratory (INL) is the lead lab working with Argonne National Laboratory (ANL) and Oak Ridge National Laboratory. Each laboratory is providing modeling and simulation expertise for the integration of the hybrid system.

  15. Static stiffness modeling of a novel hybrid redundant robot machine

    International Nuclear Information System (INIS)

    Li Ming; Wu Huapeng; Handroos, Heikki

    2011-01-01

    This paper presents a modeling method to study the stiffness of a hybrid serial-parallel robot IWR (Intersector Welding Robot) for the assembly of ITER vacuum vessel. The stiffness matrix of the basic element in the robot is evaluated using matrix structural analysis (MSA); the stiffness of the parallel mechanism is investigated by taking account of the deformations of both hydraulic limbs and joints; the stiffness of the whole integrated robot is evaluated by employing the virtual joint method and the principle of virtual work. The obtained stiffness model of the hybrid robot is analytical and the deformation results of the robot workspace under certain external load are presented.

  16. Homology modeling and virtual screening to discover potent inhibitors targeting the imidazole glycerophosphate dehydratase protein in Staphylococcus xylosus

    Science.gov (United States)

    Chen, Xing-Ru; Wang, Xiao-Ting; Hao, Mei-Qi; Zhou, Yong-Hui; Cui, Wen-Qiang; Xing, Xiao-Xu; Xu, Chang-Geng; Bai, Jing-Wen; Li, Yan-Hua

    2017-11-01

    The imidazole glycerophosphate dehydratase (IGPD) protein is a therapeutic target for herbicide discovery. It is also regarded as a possible target in Staphylococcus xylosus (S. xylosus) for solving mastitis in the dairy cow. The 3D structure of IGPD protein is essential for discovering novel inhibitors during high-throughput virtual screening. However, to date, the 3D structure of IGPD protein of S. xylosus has not been solved. In this study, a series of computational techniques including homology modeling, Ramachandran Plots, and Verify 3D were performed in order to construct an appropriate 3D model of IGPD protein of S. xylosus. Nine hits were identified from 2500 compounds by docking studies. Then, these 9 compounds were first tested in vitro in S. xylosus biofilm formation using crystal violet staining. One of the potential compounds, baicalin was shown to significantly inhibit S. xylosus biofilm formation. Finally, the baicalin was further evaluated, which showed better inhibition of biofilm formation capability in S. xylosus by scanning electron microscopy. Hence, we have predicted the structure of IGPD protein of S. xylosus using computational techniques. We further discovered the IGPD protein was targeted by baicalin compound which inhibited the biofilm formation in S. xylosus. Our findings here would provide implications for the further development of novel IGPD inhibitors for the treatment of dairy mastitis.

  17. Modeling of hybrid vehicle fuel economy and fuel engine efficiency

    Science.gov (United States)

    Wu, Wei

    "Near-CV" (i.e., near-conventional vehicle) hybrid vehicles, with an internal combustion engine, and a supplementary storage with low-weight, low-energy but high-power capacity, are analyzed. This design avoids the shortcoming of the "near-EV" and the "dual-mode" hybrid vehicles that need a large energy storage system (in terms of energy capacity and weight). The small storage is used to optimize engine energy management and can provide power when needed. The energy advantage of the "near-CV" design is to reduce reliance on the engine at low power, to enable regenerative braking, and to provide good performance with a small engine. The fuel consumption of internal combustion engines, which might be applied to hybrid vehicles, is analyzed by building simple analytical models that reflect the engines' energy loss characteristics. Both diesel and gasoline engines are modeled. The simple analytical models describe engine fuel consumption at any speed and load point by describing the engine's indicated efficiency and friction. The engine's indicated efficiency and heat loss are described in terms of several easy-to-obtain engine parameters, e.g., compression ratio, displacement, bore and stroke. Engine friction is described in terms of parameters obtained by fitting available fuel measurements on several diesel and spark-ignition engines. The engine models developed are shown to conform closely to experimental fuel consumption and motored friction data. A model of the energy use of "near-CV" hybrid vehicles with different storage mechanism is created, based on simple algebraic description of the components. With powertrain downsizing and hybridization, a "near-CV" hybrid vehicle can obtain a factor of approximately two in overall fuel efficiency (mpg) improvement, without considering reductions in the vehicle load.

  18. Cutis laxa: reduced elastin gene expression in skin fibroblast cultures as determined by hybridizations with a homologous cDNA and an exon 1-specific oligonucleotide

    International Nuclear Information System (INIS)

    Olsen, D.R.; Fazio, M.J.; Shamban, A.T.; Rosenbloom, J.; Uitto, J.

    1988-01-01

    Fibroblast cultures were established from six patients with cutis laxa, and elastin gene expression was analyzed by RNA hybridizations with a 2.5-kilobase human elastin cDNA or an exon 1-specific 35-base oligomer. Northern analyses using either probe detected mRNA transcripts of ∼ 3.5 kilobases, and no qualitative difference between the control and cutis laxa mRNAs was detected. However, quantitation of the elastin mRNA abundance by slot blot hybridizations revealed markedly reduced levels in all cutis laxa cell strains. Assuming equal translational activity of the control and cutix laxa mRNAs, the reduced mRNA levels could result in diminished elastin production, providing an explanation for the paucity of elastic fibers in the skin and other tissues in cutis laxa

  19. Hybrid attacks on model-based social recommender systems

    Science.gov (United States)

    Yu, Junliang; Gao, Min; Rong, Wenge; Li, Wentao; Xiong, Qingyu; Wen, Junhao

    2017-10-01

    With the growing popularity of the online social platform, the social network based approaches to recommendation emerged. However, because of the open nature of rating systems and social networks, the social recommender systems are susceptible to malicious attacks. In this paper, we present a certain novel attack, which inherits characteristics of the rating attack and the relation attack, and term it hybrid attack. Furtherly, we explore the impact of the hybrid attack on model-based social recommender systems in multiple aspects. The experimental results show that, the hybrid attack is more destructive than the rating attack in most cases. In addition, users and items with fewer ratings will be influenced more when attacked. Last but not the least, the findings suggest that spammers do not depend on the feedback links from normal users to become more powerful, the unilateral links can make the hybrid attack effective enough. Since unilateral links are much cheaper, the hybrid attack will be a great threat to model-based social recommender systems.

  20. Tumor necrosis factor alpha of teleosts: in silico characterization and homology modeling

    Directory of Open Access Journals (Sweden)

    Tran Ngoc Tuan

    2016-10-01

    Full Text Available Tumor necrosis factor alpha (TNF- is known to be crucial in many biological activities of organisms. In this study, physicochemical properties and modeling of TNF- protein of fish was analyzed using in silico approach. TNF- proteins selected from fish species, including grass carp (Ctenopharyngodon idella, zebra fish (Danio rerio, Nile tilapia (Oreochromis niloticus, goldfish (Carassius auratus, and rainbow trout (Oncorhynchus mykiss were used in this study. Physicochemical characteristics with molecular weight, theoretical isoelectric point, extinction coefficient, aliphatic index, instability index, total number of negatively charged residues and positively charged residues, and grand average of hydropathicity were computed. All proteins were classified as transmembrane proteins. The “transmembrane region” and “TNF” domain were identified from protein sequences. The function prediction of proteins was also performed. Alpha helices and random coils were dominating in the secondary structure of the proteins. Three-dimensional structures were predicted and verified as good structures for the investigation of TNF- of fish by online server validation.

  1. Solution structure of tRNA{sup Val} from refinement of homology model against residual dipolar coupling and SAXS data

    Energy Technology Data Exchange (ETDEWEB)

    Grishaev, Alexander, E-mail: AlexanderG@intra.niddk.nih.gov; Ying, Jinfa [National Institutes of Health, Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases (United States); Canny, Marella D.; Pardi, Arthur [University of Colorado, Boulder, Department of Chemistry and Biochemistry, 215 UCB (United States)], E-mail: Arthur.Pardi@Colorado.edu; Bax, Ad [National Institutes of Health, Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases (United States)], E-mail: bax@nih.gov

    2008-10-15

    A procedure is presented for refinement of a homology model of E. coli tRNA{sup Val}, originally based on the X-ray structure of yeast tRNA{sup Phe}, using experimental residual dipolar coupling (RDC) and small angle X-ray scattering (SAXS) data. A spherical sampling algorithm is described for refinement against SAXS data that does not require a globbic approximation, which is particularly important for nucleic acids where such approximations are less appropriate. Substantially higher speed of the algorithm also makes its application favorable for proteins. In addition to the SAXS data, the structure refinement employed a sparse set of NMR data consisting of 24 imino N-H{sup N} RDCs measured with Pf1 phage alignment, and 20 imino N-H{sup N} RDCs obtained from magnetic field dependent alignment of tRNA{sup Val}. The refinement strategy aims to largely retain the local geometry of the 58% identical tRNA{sup Phe} by ensuring that the atomic coordinates for short, overlapping segments of the ribose-phosphate backbone and the conserved base pairs remain close to those of the starting model. Local coordinate restraints are enforced using the non-crystallographic symmetry (NCS) term in the XPLOR-NIH or CNS software package, while still permitting modest movements of adjacent segments. The RDCs mainly drive the relative orientation of the helical arms, whereas the SAXS restraints ensure an overall molecular shape compatible with experimental scattering data. The resulting structure exhibits good cross-validation statistics (jack-knifed Q{sub free} = 14% for the Pf1 RDCs, compared to 25% for the starting model) and exhibits a larger angle between the two helical arms than observed in the X-ray structure of tRNA{sup Phe}, in agreement with previous NMR-based tRNA{sup Val} models.

  2. Hybrid photovoltaic–thermal solar collectors dynamic modeling

    International Nuclear Information System (INIS)

    Amrizal, N.; Chemisana, D.; Rosell, J.I.

    2013-01-01

    Highlights: ► A hybrid photovoltaic/thermal dynamic model is presented. ► The model, once calibrated, can predict the power output for any set of climate data. ► The physical electrical model includes explicitly thermal and irradiance dependences. ► The results agree with those obtained through steady-state characterization. ► The model approaches the junction cell temperature through the system energy balance. -- Abstract: A hybrid photovoltaic/thermal transient model has been developed and validated experimentally. The methodology extends the quasi-dynamic thermal model stated in the EN 12975 in order to involve the electrical performance and consider the dynamic behavior minimizing constraints when characterizing the collector. A backward moving average filtering procedure has been applied to improve the model response for variable working conditions. Concerning the electrical part, the model includes the thermal and radiation dependences in its variables. The results revealed that the characteristic parameters included in the model agree reasonably well with the experimental values obtained from the standard steady-state and IV characteristic curve measurements. After a calibration process, the model is a suitable tool to predict the thermal and electrical performance of a hybrid solar collector, for a specific weather data set.

  3. A New Model for Baryogenesis through Hybrid Inflation

    International Nuclear Information System (INIS)

    Delepine, D.; Prieto, C. Martinez; Lopez, L. A. Urena

    2009-01-01

    We propose a hybrid inflation model with a complex waterfall field which contains an interaction term that breaks the U(1) global symmetry associated to the waterfall field charge. The asymmetric evolution of the real and imaginary parts of the complex field during the phase transition at the end of inflation translates into a charge asymmetry.

  4. Model Predictive Control of the Hybrid Ventilation for Livestock

    DEFF Research Database (Denmark)

    Wu, Zhuang; Stoustrup, Jakob; Trangbæk, Klaus

    2006-01-01

    In this paper, design and simulation results of Model Predictive Control (MPC) strategy for livestock hybrid ventilation systems and associated indoor climate through variable valve openings and exhaust fans are presented. The design is based on thermal comfort parameters for poultry in barns...

  5. A novel Monte Carlo approach to hybrid local volatility models

    NARCIS (Netherlands)

    A.W. van der Stoep (Anton); L.A. Grzelak (Lech Aleksander); C.W. Oosterlee (Cornelis)

    2017-01-01

    textabstractWe present in a Monte Carlo simulation framework, a novel approach for the evaluation of hybrid local volatility [Risk, 1994, 7, 18–20], [Int. J. Theor. Appl. Finance, 1998, 1, 61–110] models. In particular, we consider the stochastic local volatility model—see e.g. Lipton et al. [Quant.

  6. Evaluation of models generated via hybrid evolutionary algorithms ...

    African Journals Online (AJOL)

    2016-04-02

    Apr 2, 2016 ... Evaluation of models generated via hybrid evolutionary algorithms for the prediction of Microcystis ... evolutionary algorithms (HEA) proved to be highly applica- ble to the hypertrophic reservoirs of South Africa. .... discovered and optimised using a large-scale parallel computational device and relevant soft-.

  7. New Models of Hybrid Leadership in Global Higher Education

    Science.gov (United States)

    Tonini, Donna C.; Burbules, Nicholas C.; Gunsalus, C. K.

    2016-01-01

    This manuscript highlights the development of a leadership preparation program known as the Nanyang Technological University Leadership Academy (NTULA), exploring the leadership challenges unique to a university undergoing rapid growth in a highly multicultural context, and the hybrid model of leadership it developed in response to globalization.…

  8. Modeling of Hybrid Growth Wastewater Bio-reactor

    International Nuclear Information System (INIS)

    EI Nashaei, S.; Garhyan, P.; Prasad, P.; Abdel Halim, H.S.; Ibrahim, G.

    2004-01-01

    The attached/suspended growth mixed reactors are considered one of the recently tried approaches to improve the performance of the biological treatment by increasing the volume of the accumulated biomass in terms of attached growth as well as suspended growth. Moreover, the domestic WW can be easily mixed with a high strength non-hazardous industrial wastewater and treated together in these bio-reactors if the need arises. Modeling of Hybrid hybrid growth wastewater reactor addresses the need of understanding the rational of such system in order to achieve better design and operation parameters. This paper aims at developing a heterogeneous mathematical model for hybrid growth system considering the effect of diffusion, external mass transfer, and power input to the system in a rational manner. The model will be based on distinguishing between liquid/solid phase (bio-film and bio-floc). This model would be a step ahead to the fine tuning the design of hybrid systems based on the experimental data of a pilot plant to be implemented in near future

  9. Hybrid time/frequency domain modeling of nonlinear components

    DEFF Research Database (Denmark)

    Wiechowski, Wojciech Tomasz; Lykkegaard, Jan; Bak, Claus Leth

    2007-01-01

    This paper presents a novel, three-phase hybrid time/frequency methodology for modelling of nonlinear components. The algorithm has been implemented in the DIgSILENT PowerFactory software using the DIgSILENT Programming Language (DPL), as a part of the work described in [1]. Modified HVDC benchmark...

  10. Efficient Proof Engines for Bounded Model Checking of Hybrid Systems

    DEFF Research Database (Denmark)

    Fränzle, Martin; Herde, Christian

    2005-01-01

    In this paper we present HySat, a new bounded model checker for linear hybrid systems, incorporating a tight integration of a DPLL-based pseudo-Boolean SAT solver and a linear programming routine as core engine. In contrast to related tools like MathSAT, ICS, or CVC, our tool exploits all...

  11. Generation of a homology model of the human histamine H3 receptor for ligand docking and pharmacophore-based screening

    Science.gov (United States)

    Schlegel, Birgit; Laggner, Christian; Meier, Rene; Langer, Thierry; Schnell, David; Seifert, Roland; Stark, Holger; Höltje, Hans-Dieter; Sippl, Wolfgang

    2007-08-01

    The human histamine H3 receptor (hH3R) is a G-protein coupled receptor (GPCR), which modulates the release of various neurotransmitters in the central and peripheral nervous system and therefore is a potential target in the therapy of numerous diseases. Although ligands addressing this receptor are already known, the discovery of alternative lead structures represents an important goal in drug design. The goal of this work was to study the hH3R and its antagonists by means of molecular modelling tools. For this purpose, a strategy was pursued in which a homology model of the hH3R based on the crystal structure of bovine rhodopsin was generated and refined by molecular dynamics simulations in a dipalmitoylphosphatidylcholine (DPPC)/water membrane mimic before the resulting binding pocket was used for high-throughput docking using the program GOLD. Alternatively, a pharmacophore-based procedure was carried out where the alleged bioactive conformations of three different potent hH3R antagonists were used as templates for the generation of pharmacophore models. A pharmacophore-based screening was then carried out using the program Catalyst. Based upon a database of 418 validated hH3R antagonists both strategies could be validated in respect of their performance. Seven hits obtained during this screening procedure were commercially purchased, and experimentally tested in a [3H]Nα-methylhistamine binding assay. The compounds tested showed affinities at hH3R with K i values ranging from 0.079 to 6.3 μM.

  12. Travelling Waves in Hybrid Chemotaxis Models

    KAUST Repository

    Franz, Benjamin; Xue, Chuan; Painter, Kevin J.; Erban, Radek

    2013-01-01

    . Bacteria are modelled using an agent-based (individual-based) approach with internal dynamics describing signal transduction. In addition to the chemotactic behaviour of the bacteria, the individual-based model also includes cell proliferation and death

  13. Hybrid modelling of soil-structure interaction for embedded structures

    International Nuclear Information System (INIS)

    Gupta, S.; Penzien, J.

    1981-01-01

    The basic methods currently being used for the analysis of soil-structure interaction fail to properly model three-dimensional embedded structures with flexible foundations. A hybrid model for the analysis of soil-structure interaction is developed in this investigation which takes advantage of the desirable features of both the finite element and substructure methods and which minimizes their undesirable features. The hybrid model is obtained by partitioning the total soil-structure system into a nearfield and a far-field with a smooth hemispherical interface. The near-field consists of the structure and a finite region of soil immediately surrounding its base. The entire near-field may be modelled in three-dimensional form using the finite element method; thus, taking advantage of its ability to model irregular geometries, and the non-linear soil behavior in the immediate vicinity of the structure. (orig./WL)

  14. A hybrid parallel framework for the cellular Potts model simulations

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Yi [Los Alamos National Laboratory; He, Kejing [SOUTH CHINA UNIV; Dong, Shoubin [SOUTH CHINA UNIV

    2009-01-01

    The Cellular Potts Model (CPM) has been widely used for biological simulations. However, most current implementations are either sequential or approximated, which can't be used for large scale complex 3D simulation. In this paper we present a hybrid parallel framework for CPM simulations. The time-consuming POE solving, cell division, and cell reaction operation are distributed to clusters using the Message Passing Interface (MPI). The Monte Carlo lattice update is parallelized on shared-memory SMP system using OpenMP. Because the Monte Carlo lattice update is much faster than the POE solving and SMP systems are more and more common, this hybrid approach achieves good performance and high accuracy at the same time. Based on the parallel Cellular Potts Model, we studied the avascular tumor growth using a multiscale model. The application and performance analysis show that the hybrid parallel framework is quite efficient. The hybrid parallel CPM can be used for the large scale simulation ({approx}10{sup 8} sites) of complex collective behavior of numerous cells ({approx}10{sup 6}).

  15. Modelling and analysis of real-time and hybrid systems

    Energy Technology Data Exchange (ETDEWEB)

    Olivero, A

    1994-09-29

    This work deals with the modelling and analysis of real-time and hybrid systems. We first present the timed-graphs as model for the real-time systems and we recall the basic notions of the analysis of real-time systems. We describe the temporal properties on the timed-graphs using TCTL formulas. We consider two methods for property verification: in one hand we study the symbolic model-checking (based on backward analysis) and in the other hand we propose a verification method derived of the construction of the simulation graph (based on forward analysis). Both methods have been implemented within the KRONOS verification tool. Their application for the automatic verification on several real-time systems confirms the practical interest of our approach. In a second part we study the hybrid systems, systems combining discrete components with continuous ones. As in the general case the analysis of this king of systems is not decidable, we identify two sub-classes of hybrid systems and we give a construction based method for the generation of a timed-graph from an element into the sub-classes. We prove that in one case the timed-graph obtained is bi-similar with the considered system and that there exists a simulation in the other case. These relationships allow the application of the described technics on the hybrid systems into the defined sub-classes. (authors). 60 refs., 43 figs., 8 tabs., 2 annexes.

  16. A 'simple' hybrid model for power derivatives

    International Nuclear Information System (INIS)

    Lyle, Matthew R.; Elliott, Robert J.

    2009-01-01

    This paper presents a method for valuing power derivatives using a supply-demand approach. Our method extends work in the field by incorporating randomness into the base load portion of the supply stack function and equating it with a noisy demand process. We obtain closed form solutions for European option prices written on average spot prices considering two different supply models: a mean-reverting model and a Markov chain model. The results are extensions of the classic Black-Scholes equation. The model provides a relatively simple approach to describe the complicated price behaviour observed in electricity spot markets and also allows for computationally efficient derivatives pricing. (author)

  17. On the Likely Utility of Hybrid Weights Optimized for Variances in Hybrid Error Covariance Models

    Science.gov (United States)

    Satterfield, E.; Hodyss, D.; Kuhl, D.; Bishop, C. H.

    2017-12-01

    Because of imperfections in ensemble data assimilation schemes, one cannot assume that the ensemble covariance is equal to the true error covariance of a forecast. Previous work demonstrated how information about the distribution of true error variances given an ensemble sample variance can be revealed from an archive of (observation-minus-forecast, ensemble-variance) data pairs. Here, we derive a simple and intuitively compelling formula to obtain the mean of this distribution of true error variances given an ensemble sample variance from (observation-minus-forecast, ensemble-variance) data pairs produced by a single run of a data assimilation system. This formula takes the form of a Hybrid weighted average of the climatological forecast error variance and the ensemble sample variance. Here, we test the extent to which these readily obtainable weights can be used to rapidly optimize the covariance weights used in Hybrid data assimilation systems that employ weighted averages of static covariance models and flow-dependent ensemble based covariance models. Univariate data assimilation and multi-variate cycling ensemble data assimilation are considered. In both cases, it is found that our computationally efficient formula gives Hybrid weights that closely approximate the optimal weights found through the simple but computationally expensive process of testing every plausible combination of weights.

  18. A hybrid society model for simulating residential electricity consumption

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Minjie [School of Electrical Engineering, Beijing Jiaotong University, Beijing (China); State Power Economic Research Institute, Beijing (China); Hu, Zhaoguang [State Power Economic Research Institute, Beijing (China); Wu, Junyong; Zhou, Yuhui [School of Electrical Engineering, Beijing Jiaotong University, Beijing (China)

    2008-12-15

    In this paper, a hybrid social model of econometric model and social influence model is proposed for evaluating the influence of pricing policy and public education policy on residential habit of electricity using in power resources management. And, a hybrid society simulation platform based on the proposed model, called residential electricity consumption multi-agent systems (RECMAS), is designed for simulating residential electricity consumption by multi-agent system. RECMAS is composed of consumer agent, power supplier agent, and policy maker agent. It provides the policy makers with a useful tool to evaluate power price policies and public education campaigns in different scenarios. According to an influenced diffusion mechanism, RECMAS can simulate the residential electricity demand-supply chain and analyze impacts of the factors on residential electricity consumption. Finally, the proposed method is used to simulate urban residential electricity consumption in China. (author)

  19. A hybrid society model for simulating residential electricity consumption

    International Nuclear Information System (INIS)

    Xu, Minjie; Hu, Zhaoguang; Wu, Junyong; Zhou, Yuhui

    2008-01-01

    In this paper, a hybrid social model of econometric model and social influence model is proposed for evaluating the influence of pricing policy and public education policy on residential habit of electricity using in power resources management. And, a hybrid society simulation platform based on the proposed model, called residential electricity consumption multi-agent systems (RECMAS), is designed for simulating residential electricity consumption by multi-agent system. RECMAS is composed of consumer agent, power supplier agent, and policy maker agent. It provides the policy makers with a useful tool to evaluate power price policies and public education campaigns in different scenarios. According to an influenced diffusion mechanism, RECMAS can simulate the residential electricity demand-supply chain and analyze impacts of the factors on residential electricity consumption. Finally, the proposed method is used to simulate urban residential electricity consumption in China. (author)

  20. Hybrid nested sampling algorithm for Bayesian model selection applied to inverse subsurface flow problems

    KAUST Repository

    Elsheikh, Ahmed H.; Wheeler, Mary Fanett; Hoteit, Ibrahim

    2014-01-01

    A Hybrid Nested Sampling (HNS) algorithm is proposed for efficient Bayesian model calibration and prior model selection. The proposed algorithm combines, Nested Sampling (NS) algorithm, Hybrid Monte Carlo (HMC) sampling and gradient estimation using

  1. The semantics of hybrid process models

    NARCIS (Netherlands)

    Slaats, T.; Schunselaar, D.M.M.; Maggi, F.M.; Reijers, H.A.; Debruyne, C.; Panetto, H.; Meersman, R.; Dillon, T.; Kuhn, E.; O'Sullivan, D.; Agostino Ardagna, C.

    2016-01-01

    In the area of business process modelling, declarative notations have been proposed as alternatives to notations that follow the dominant, imperative paradigm. Yet, the choice between an imperative or declarative style of modelling is not always easy to make. Instead, a mixture of these styles is

  2. A computational model for lower hybrid current drive

    International Nuclear Information System (INIS)

    Englade, R.C.; Bonoli, P.T.; Porkolab, M.

    1983-01-01

    A detailed simulation model for lower hybrid (LH) current drive in toroidal devices is discussed. This model accounts reasonably well for the magnitude of radio frequency (RF) current observed in the PLT and Alcator C devices. It also reproduces the experimental dependencies of RF current generation on toroidal magnetic field and has provided insights about mechanisms which may underlie the observed density limit of current drive. (author)

  3. A Hybrid Model for Forecasting Sales in Turkish Paint Industry

    OpenAIRE

    Alp Ustundag

    2009-01-01

    Sales forecasting is important for facilitating effective and efficient allocation of scarce resources. However, how to best model and forecast sales has been a long-standing issue. There is no best forecasting method that is applicable in all circumstances. Therefore, confidence in the accuracy of sales forecasts is achieved by corroborating the results using two or more methods. This paper proposes a hybrid forecasting model that uses an artificial intelligence method (AI) w...

  4. Hybrid Neuro-Fuzzy Classifier Based On Nefclass Model

    Directory of Open Access Journals (Sweden)

    Bogdan Gliwa

    2011-01-01

    Full Text Available The paper presents hybrid neuro-fuzzy classifier, based on NEFCLASS model, which wasmodified. The presented classifier was compared to popular classifiers – neural networks andk-nearest neighbours. Efficiency of modifications in classifier was compared with methodsused in original model NEFCLASS (learning methods. Accuracy of classifier was testedusing 3 datasets from UCI Machine Learning Repository: iris, wine and breast cancer wisconsin.Moreover, influence of ensemble classification methods on classification accuracy waspresented.

  5. Apricot - An Object-Oriented Modeling Language for Hybrid Systems

    OpenAIRE

    Fang, Huixing; Zhu, Huibiao; Shi, Jianqi

    2013-01-01

    We propose Apricot as an object-oriented language for modeling hybrid systems. The language combines the features in domain specific language and object-oriented language, that fills the gap between design and implementation, as a result, we put forward the modeling language with simple and distinct syntax, structure and semantics. In addition, we introduce the concept of design by convention into Apricot.As the characteristic of object-oriented and the component architecture in Apricot, we c...

  6. Hierarchical models and iterative optimization of hybrid systems

    Energy Technology Data Exchange (ETDEWEB)

    Rasina, Irina V. [Ailamazyan Program Systems Institute, Russian Academy of Sciences, Peter One str. 4a, Pereslavl-Zalessky, 152021 (Russian Federation); Baturina, Olga V. [Trapeznikov Control Sciences Institute, Russian Academy of Sciences, Profsoyuznaya str. 65, 117997, Moscow (Russian Federation); Nasatueva, Soelma N. [Buryat State University, Smolina str.24a, Ulan-Ude, 670000 (Russian Federation)

    2016-06-08

    A class of hybrid control systems on the base of two-level discrete-continuous model is considered. The concept of this model was proposed and developed in preceding works as a concretization of the general multi-step system with related optimality conditions. A new iterative optimization procedure for such systems is developed on the base of localization of the global optimality conditions via contraction the control set.

  7. Homology modeling of dissimilatory APS reductases (AprBA of sulfur-oxidizing and sulfate-reducing prokaryotes.

    Directory of Open Access Journals (Sweden)

    Birte Meyer

    Full Text Available BACKGROUND: The dissimilatory adenosine-5'-phosphosulfate (APS reductase (cofactors flavin adenine dinucleotide, FAD, and two [4Fe-4S] centers catalyzes the transformation of APS to sulfite and AMP in sulfate-reducing prokaryotes (SRP; in sulfur-oxidizing bacteria (SOB it has been suggested to operate in the reverse direction. Recently, the three-dimensional structure of the Archaeoglobus fulgidus enzyme has been determined in different catalytically relevant states providing insights into its reaction cycle. METHODOLOGY/PRINCIPAL FINDINGS: Full-length AprBA sequences from 20 phylogenetically distinct SRP and SOB species were used for homology modeling. In general, the average accuracy of the calculated models was sufficiently good to allow a structural and functional comparison between the beta- and alpha-subunit structures (78.8-99.3% and 89.5-96.8% of the AprB and AprA main chain atoms, respectively, had root mean square deviations below 1 A with respect to the template structures. Besides their overall conformity, the SRP- and SOB-derived models revealed the existence of individual adaptations at the electron-transferring AprB protein surface presumably resulting from docking to different electron donor/acceptor proteins. These structural alterations correlated with the protein phylogeny (three major phylogenetic lineages: (1 SRP including LGT-affected Archaeoglobi and SOB of Apr lineage II, (2 crenarchaeal SRP Caldivirga and Pyrobaculum, and (3 SOB of the distinct Apr lineage I and the presence of potential APS reductase-interacting redox complexes. The almost identical protein matrices surrounding both [4Fe-4S] clusters, the FAD cofactor, the active site channel and center within the AprB/A models of SRP and SOB point to a highly similar catalytic process of APS reduction/sulfite oxidation independent of the metabolism type the APS reductase is involved in and the species it has been originated from. CONCLUSIONS: Based on the comparative

  8. A generic approach for expanding homolog-targeted residue screening of sulfonamides using a fast matrix separation and class-specific fragmentation-dependent acquisition with a hybrid quadrupole-linear ion trap mass spectrometer

    International Nuclear Information System (INIS)

    Huang Chunlin; Guo Bin; Wang Xiaoying; Li Jie; Zhu Weitao; Chen Bo; Ouyang Shan; Yao Shouzhuo

    2012-01-01

    Highlights: ► Generic homolog-targeted screening approach for multi-residual sulfonamide analogs. ► Single-tube extraction/partitioning-multifunction adsorption cleanup for direct injection. ► Class-specific fragmentation for expanding coverage of N 4 -acetyl and N-OH metabolites. ► PreS–IDA–EPI in LC–QqLIT for simultaneous screening and confirmation of real samples. - Abstract: A generic and efficient homolog-targeted approach was used to expand screening and detection of target class of sulfonamides and structural analogs, based on a fast single-tube extraction/partitioning-multifunction adsorption cleanup (SEP/MAC) for class-specific fragmentation-dependent acquisition with a liquid chromatography–hybrid triple-quadrupole linear ion trap mass spectrometer (LC–QqLIT). By combining the two-stage process conducted in a single tube as one-pot protocol, the straightforward SEP/MAC procedure was optimized to offer clean extracts with reasonable recovery (71–109% with RSDs 4 -acetyl and hydroxylamine metabolites plus their possible dimers. Moreover, the PreS-triggered automatically enhanced product ion spectral acquisition enabled simultaneous screening, profiling and confirmation of an unlimited number of analytes belonging to the sulfonamide class within a single analysis. The validation and application results of the generic SEP/MAC-based LC–QqLIT strategy consistently demonstrated favorable performances with acceptable accuracy (67–116%), precision (RSDs −1 ) to meet the acceptance criteria for all the sulfonamide–tissue combinations. Thus, the integration of the matrix-independent SEP/MAC procedure and the multiparameter matching algorithm with the unit-resolution LC–QqLIT instrument can serve as a valuable semi-targeted discovery strategy for rapid screening and reliable quantitative/confirmatory analysis of real samples.

  9. A model for particle acceleration in lower hybrid collapse

    International Nuclear Information System (INIS)

    Retterer, J.M.

    1997-01-01

    A model for particle acceleration during the nonlinear collapse of lower hybrid waves is described. Using the Musher-Sturman wave equation to describe the effects of nonlinear processes and a velocity diffusion equation for the particle velocity distribution, the model self-consistently describes the exchange of energy between the fields and the particles in the local plasma. Two-dimensional solutions are presented for the modulational instability of a plane wave and the collapse of a cylindrical wave packet. These calculations were motivated by sounding rocket observations in the vicinity of auroral arcs in the Earth close-quote s ionosphere, which have revealed the existence of large-amplitude lower-hybrid wave packets associated with ions accelerated to energies of 100 eV. The scaling of the sizes of these wave packets is consistent with the theory of lower-hybrid collapse and the observed lower-hybrid field amplitudes are adequate to accelerate the ionospheric ions to the observed energies

  10. Hybrid reduced order modeling for assembly calculations

    International Nuclear Information System (INIS)

    Bang, Youngsuk; Abdel-Khalik, Hany S.; Jessee, Matthew A.; Mertyurek, Ugur

    2015-01-01

    Highlights: • Reducing computational cost in engineering calculations. • Reduced order modeling algorithm for multi-physics problem like assembly calculation. • Non-intrusive algorithm with random sampling. • Pattern recognition in the components with high sensitive and large variation. - Abstract: While the accuracy of assembly calculations has considerably improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the use of the reduced order modeling for a single physics code, such as a radiation transport calculation. This manuscript extends those works to coupled code systems as currently employed in assembly calculations. Numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system.

  11. Hybrid reduced order modeling for assembly calculations

    Energy Technology Data Exchange (ETDEWEB)

    Bang, Youngsuk, E-mail: ysbang00@fnctech.com [FNC Technology, Co. Ltd., Yongin-si (Korea, Republic of); Abdel-Khalik, Hany S., E-mail: abdelkhalik@purdue.edu [Purdue University, West Lafayette, IN (United States); Jessee, Matthew A., E-mail: jesseema@ornl.gov [Oak Ridge National Laboratory, Oak Ridge, TN (United States); Mertyurek, Ugur, E-mail: mertyurek@ornl.gov [Oak Ridge National Laboratory, Oak Ridge, TN (United States)

    2015-12-15

    Highlights: • Reducing computational cost in engineering calculations. • Reduced order modeling algorithm for multi-physics problem like assembly calculation. • Non-intrusive algorithm with random sampling. • Pattern recognition in the components with high sensitive and large variation. - Abstract: While the accuracy of assembly calculations has considerably improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the use of the reduced order modeling for a single physics code, such as a radiation transport calculation. This manuscript extends those works to coupled code systems as currently employed in assembly calculations. Numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system.

  12. A Hybrid Model for Forecasting Sales in Turkish Paint Industry

    Directory of Open Access Journals (Sweden)

    Alp Ustundag

    2009-12-01

    Full Text Available Sales forecasting is important for facilitating effective and efficient allocation of scarce resources. However, how to best model and forecast sales has been a long-standing issue. There is no best forecasting method that is applicable in all circumstances. Therefore, confidence in the accuracy of sales forecasts is achieved by corroborating the results using two or more methods. This paper proposes a hybrid forecasting model that uses an artificial intelligence method (AI with multiple linear regression (MLR to predict product sales for the largest Turkish paint producer. In the hybrid model, three different AI methods, fuzzy rule-based system (FRBS, artificial neural network (ANN and adaptive neuro fuzzy network (ANFIS, are used and compared to each other. The results indicate that FRBS yields better forecasting accuracy in terms of root mean squared error (RMSE and mean absolute percentage error (MAPE.

  13. Hybrid reduced order modeling for assembly calculations

    Energy Technology Data Exchange (ETDEWEB)

    Bang, Y.; Abdel-Khalik, H. S. [North Carolina State University, Raleigh, NC (United States); Jessee, M. A.; Mertyurek, U. [Oak Ridge National Laboratory, Oak Ridge, TN (United States)

    2013-07-01

    While the accuracy of assembly calculations has considerably improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the use of the reduced order modeling for a single physics code, such as a radiation transport calculation. This manuscript extends those works to coupled code systems as currently employed in assembly calculations. Numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system. (authors)

  14. Hybrid neural network bushing model for vehicle dynamics simulation

    International Nuclear Information System (INIS)

    Sohn, Jeong Hyun; Lee, Seung Kyu; Yoo, Wan Suk

    2008-01-01

    Although the linear model was widely used for the bushing model in vehicle suspension systems, it could not express the nonlinear characteristics of bushing in terms of the amplitude and the frequency. An artificial neural network model was suggested to consider the hysteretic responses of bushings. This model, however, often diverges due to the uncertainties of the neural network under the unexpected excitation inputs. In this paper, a hybrid neural network bushing model combining linear and neural network is suggested. A linear model was employed to represent linear stiffness and damping effects, and the artificial neural network algorithm was adopted to take into account the hysteretic responses. A rubber test was performed to capture bushing characteristics, where sine excitation with different frequencies and amplitudes is applied. Random test results were used to update the weighting factors of the neural network model. It is proven that the proposed model has more robust characteristics than a simple neural network model under step excitation input. A full car simulation was carried out to verify the proposed bushing models. It was shown that the hybrid model results are almost identical to the linear model under several maneuvers

  15. The Cheshire Cat principle for hybrid bag models

    International Nuclear Information System (INIS)

    Nielsen, H.B.

    1987-05-01

    The Cheshire Cat point of view where the bag in the chiral bag model has no physical significance, but only a notational one is argued for. It is explained how a fermion - in, say, a 1+1 dimensional exact Cheshire Cat model - escapes the bag by means of an anomaly. The possibility to construct sophisticated hybrid bag models is suggested which use the lack of physical significance of the bag to fix the many parameters so as to anyway give hope of a phenomenologically sensible model. (orig.)

  16. Modelling of a Hybrid Energy System for Autonomous Application

    Directory of Open Access Journals (Sweden)

    Yang He

    2013-10-01

    Full Text Available A hybrid energy system (HES is a trending power supply solution for autonomous devices. With the help of an accurate system model, the HES development will be efficient and oriented. In spite of various precise unit models, a HES system is hardly developed. This paper proposes a system modelling approach, which applies the power flux conservation as the governing equation and adapts and modifies unit models of solar cells, piezoelectric generators, a Li-ion battery and a super-capacitor. A generalized power harvest, storage and management strategy is also suggested to adapt to various application scenarios.

  17. Studies on 16α-Hydroxylation of Steroid Molecules and Regioselective Binding Mode in Homology-Modeled Cytochrome P450-2C11

    Directory of Open Access Journals (Sweden)

    Hamed I. Ali

    2011-01-01

    Full Text Available We investigated the 16α-hydroxylation of steroid molecules and regioselective binding mode in homology-modeled cytochrome P450-2C11 to correlate the biological study with the computational molecular modeling. It revealed that there was a positive relationship between the observed inhibitory potencies and the binding free energies. Docking of steroid molecules into this homology-modeled CYP2C11 indicated that 16α-hydroxylation is favored with steroidal molecules possessing the following components, (1 a bent A-B ring configuration (5β-reduced, (2 C-3 α-hydroxyl group, (3 C-17β-acetyl group, and (4 methyl group at both the C-18 and C-19. These respective steroid components requirements were defined as the inhibitory contribution factor. Overall studies of the male rat CYP2C11 metabolism revealed that the above-mentioned steroid components requirements were essential to induce an effective inhibition of [3H]progesterone 16α-hydroxylation. As far as docking of homology-modeled CYP2C11 against investigated steroids is concerned, they are docked at the active site superimposed with flurbiprofen. It was also found that the distance between heme iron and C16α-H was between 4 to 6 Å and that the related angle was in the range of 180±45∘.

  18. SCRINING IN SILICO ACTIVE COMPOUND OF Pachyrrhizus erosus AS ANTITIROSINASE ON Aspergillus oryzae (COMPUTATTIONAL STUDY WITH HOMOLOGY MODELING AND MOLECULAR DOCKING

    Directory of Open Access Journals (Sweden)

    Endang Lukitaningsih

    2015-11-01

    Full Text Available Bengkoang telah banyak digunakan dalam industri kosmetika sebagai whitening agent. Berdasarkan penelitian Lukitaningsih (2009, bengkoang mengandung 6 senyawa aktif yang mampu berperan sebagai whitening agent dengan menghambat aktivitas enzim tirosinase dari jamur Aspergillus oryzae (TyrAo. Namun interaksi senyawa aktif bengkoang dalam menghambat enzim tirosinase belum dapat diketahui. Interaksi senyawa-senyawa aktif bengkoang dengan enzim TyrAo dapat diketahui dengan studi komputasional (in silico. Pemodelan interaksi senyawa aktif bengkoang dengan enzim TyrAo dilakukan dengan metode homology modeling dan molecular docking. Homology modeling dilakukan untuk memodelkan struktur tiga dimensi (3D enzim tirosinase Aspergillus oryzae (TyrAo melalui template berupa protein homolog yang sudah diketahui struktur 3D-nya yaitu enzim TyrAb (PDBID: 2Y9X. Model TyrAo digunakan sebagai target makromolekul dalam metode molecular docking. Metode molecular docking merupakan metode untuk menggambarkan posisi ligan (senyawa-senyawa aktif bengkoang pada sisi aktif reseptor (model TyrAo. Berdasarkan docking yang dilakukan diketahui bahwa residu-residu yang banyak berpengaruh pada interaksi ligan pada sisi aktif adalah residu Thr275 yang berinteraksi secara ikatan hidrogen dengan ligan dan residu His294 yang berinteraksi secara hidrofobik pada cincin aromatik ligan. Penelitian in silico dan in vitro yang telah dilakukan memiliki korelasi (R2 sebesar -0,8366. Korelasi ini menandakan bahwa aktivitas senyawa-senyawa aktif pada bengkoang dalam menghambat enzim TyrAo memiliki hasil yang serupa pada penelitian yang  dilakukan secara in silico dan in vitro.

  19. Pure homology of algebraic varieties

    OpenAIRE

    Weber, Andrzej

    2003-01-01

    We show that for a complete complex algebraic variety the pure component of homology coincides with the image of intersection homology. Therefore pure homology is topologically invariant. To obtain slightly more general results we introduce "image homology" for noncomplete varieties.

  20. HYBRID WAYS OF DOING: A MODEL FOR TEACHING PUBLIC SPACE

    Directory of Open Access Journals (Sweden)

    Gabrielle Bendiner-Viani

    2010-07-01

    Full Text Available This paper addresses an exploratory practice undertaken by the authors in a co-taught class to hybridize theory, research and practice. This experiment in critical transdisciplinary design education took the form of a “critical studio + practice-based seminar on public space”, two interlinked classes co-taught by landscape architect Elliott Maltby and environmental psychologist Gabrielle Bendiner-Viani at the Parsons, The New School for Design. This design process was grounded in the political and social context of the contested East River waterfront of New York City and valued both intensive study (using a range of social science and design methods and a partnership with a local community organization, engaging with the politics, issues and human needs of a complex site. The paper considers how we encouraged interdisciplinary collaboration and dialogue between teachers as well as between liberal arts and design students and developed strategies to overcome preconceived notions of traditional “studio” and “seminar” work. By exploring the challenges and adjustments made during the semester and the process of teaching this class, this paper addresses how we moved from a model of intertwining theory, research and practice, to a hybrid model of multiple ways of doing, a model particularly apt for teaching public space. Through examples developed for and during our course, the paper suggests practical ways of supporting this transdisciplinary hybrid model.

  1. Modelling the solar wind interaction with Mercury by a quasi-neutral hybrid model

    Directory of Open Access Journals (Sweden)

    E. Kallio

    2003-11-01

    Full Text Available Quasi-neutral hybrid model is a self-consistent modelling approach that includes positively charged particles and an electron fluid. The approach has received an increasing interest in space plasma physics research because it makes it possible to study several plasma physical processes that are difficult or impossible to model by self-consistent fluid models, such as the effects associated with the ions’ finite gyroradius, the velocity difference between different ion species, or the non-Maxwellian velocity distribution function. By now quasi-neutral hybrid models have been used to study the solar wind interaction with the non-magnetised Solar System bodies of Mars, Venus, Titan and comets. Localized, two-dimensional hybrid model runs have also been made to study terrestrial dayside magnetosheath. However, the Hermean plasma environment has not yet been analysed by a global quasi-neutral hybrid model. In this paper we present a new quasi-neutral hybrid model developed to study various processes associated with the Mercury-solar wind interaction. Emphasis is placed on addressing advantages and disadvantages of the approach to study different plasma physical processes near the planet. The basic assumptions of the approach and the algorithms used in the new model are thoroughly presented. Finally, some of the first three-dimensional hybrid model runs made for Mercury are presented. The resulting macroscopic plasma parameters and the morphology of the magnetic field demonstrate the applicability of the new approach to study the Mercury-solar wind interaction globally. In addition, the real advantage of the kinetic hybrid model approach is to study the property of individual ions, and the study clearly demonstrates the large potential of the approach to address these more detailed issues by a quasi-neutral hybrid model in the future.Key words. Magnetospheric physics (planetary magnetospheres; solar wind-magnetosphere interactions – Space plasma

  2. Properties of hybrid stars in an extended MIT bag model

    International Nuclear Information System (INIS)

    Bao Tmurbagan; Liu Guangzhou; Zhu Mingfeng

    2009-01-01

    The properties of hybrid stars are investigated in the framework of the relativistic mean field theory (RMFT) and an MIT bag model with density-dependent bag constant to describe the hadron phase (HP) and quark phase (QP), respectively. We find that the density-dependent B(ρ) decreases with baryon density ρ; this decrement makes the strange quark matter become more energetically favorable than ever; which makes the threshold densities of the hadron-quark phase transition lower than those of the original bag constant case. In this case, the hyperon degrees of freedom can not be considered. As a result, the equations of state of a star in the mixed phase (MP) become softer whereas those in the QP become stiffer, and the radii of the star obviously decrease. This indicates that the extended MIT bag model is more suitable to describe hybrid stars with small radii. (authors)

  3. Analysis of Host Range Restriction Determinants in the Rabbit Model: Comparison of Homologous and Heterologous Rotavirus Infections

    Science.gov (United States)

    Ciarlet, Max; Estes, Mary K.; Barone, Christopher; Ramig, Robert F.; Conner, Margaret E.

    1998-01-01

    The main limitation of both the rabbit and mouse models of rotavirus infection is that human rotavirus (HRV) strains do not replicate efficiently in either animal. The identification of individual genes necessary for conferring replication competence in a heterologous host is important to an understanding of the host range restriction of rotavirus infections. We recently reported the identification of the P type of the spike protein VP4 of four lapine rotavirus strains as being P[14]. To determine whether VP4 is involved in host range restriction in rabbits, we evaluated infection in rotavirus antibody-free rabbits inoculated orally with two P[14] HRVs, PA169 (G6) and HAL1166 (G8), and with several other HRV strains and animal rotavirus strains of different P and G types. We also evaluated whether the parental rhesus rotavirus (RRV) (P5B[3], G3) and the derived RRV-HRV reassortant candidate vaccine strains RRV × D (G1), RRV × DS-1 (G2), and RRV × ST3 (G4) would productively infect rabbits. Based on virus shedding, limited replication was observed with the P[14] HRV strains and with the SA11 Cl3 (P[2], G3) and SA11 4F (P6[1], G3) animal rotavirus strains, compared to the homologous ALA strain (P[14], G3). However, even limited infection provided complete protection from rotavirus infection when rabbits were challenged orally 28 days postinoculation (DPI) with 103 50% infective doses of ALA rabbit rotavirus. Other HRVs did not productively infect rabbits and provided no significant protection from challenge, in spite of occasional seroconversion. Simian RRV replicated as efficiently as lapine ALA rotavirus in rabbits and provided complete protection from ALA challenge. Live attenuated RRV reassortant vaccine strains resulted in no, limited, or productive infection of rabbits, but all rabbits were completely protected from heterotypic ALA challenge. The altered replication efficiency of the reassortants in rabbits suggests a role for VP7 in host range restriction

  4. Homology Modeling and Analysis of Structure Predictions of the Bovine Rhinitis B Virus RNA Dependent RNA Polymerase (RdRp

    Directory of Open Access Journals (Sweden)

    Devendra K. Rai

    2012-07-01

    Full Text Available Bovine Rhinitis B Virus (BRBV is a picornavirus responsible for mild respiratory infection of cattle. It is probably the least characterized among the aphthoviruses. BRBV is the closest relative known to Foot and Mouth Disease virus (FMDV with a ~43% identical polyprotein sequence and as much as 67% identical sequence for the RNA dependent RNA polymerase (RdRp, which is also known as 3D polymerase (3Dpol. In the present study we carried out phylogenetic analysis, structure based sequence alignment and prediction of three-dimensional structure of BRBV 3Dpol using a combination of different computational tools. Model structures of BRBV 3Dpol were verified for their stereochemical quality and accuracy. The BRBV 3Dpol structure predicted by SWISS-MODEL exhibited highest scores in terms of stereochemical quality and accuracy, which were in the range of 2Å resolution crystal structures. The active site, nucleic acid binding site and overall structure were observed to be in agreement with the crystal structure of unliganded as well as template/primer (T/P, nucleotide tri-phosphate (NTP and pyrophosphate (PPi bound FMDV 3Dpol (PDB, 1U09 and 2E9Z. The closest proximity of BRBV and FMDV 3Dpol as compared to human rhinovirus type 16 (HRV-16 and rabbit hemorrhagic disease virus (RHDV 3Dpols is also substantiated by phylogeny analysis and root-mean square deviation (RMSD between C-α traces of the polymerase structures. The absence of positively charged α-helix at C terminal, significant differences in non-covalent interactions especially salt bridges and CH-pi interactions around T/P channel of BRBV 3Dpol compared to FMDV 3Dpol, indicate that despite a very high homology to FMDV 3Dpol, BRBV 3Dpol may adopt a different mechanism for handling its substrates and adapting to physiological requirements. Our findings will be valuable in the

  5. Homology in Electromagnetic Boundary Value Problems

    Directory of Open Access Journals (Sweden)

    Pellikka Matti

    2010-01-01

    Full Text Available We discuss how homology computation can be exploited in computational electromagnetism. We represent various cellular mesh reduction techniques, which enable the computation of generators of homology spaces in an acceptable time. Furthermore, we show how the generators can be used for setting up and analysis of an electromagnetic boundary value problem. The aim is to provide a rationale for homology computation in electromagnetic modeling software.

  6. A light neutralino in hybrid models of supersymmetry breaking

    CERN Document Server

    Dudas, Emilian; Parmentier, Jeanne; 10.1016

    2008-01-01

    We show that in gauge mediation models where heavy messenger masses are provided by the adjoint Higgs field of an underlying SU(5) theory, a generalized gauge mediation spectrum arises with the characteristic feature of having a neutralino much lighter than in the standard gauge or gravity mediation schemes. This naturally fits in a hybrid scenario where gravity mediation, while subdominant with respect to gauge mediation, provides mu and B mu parameters in the TeV range.

  7. A Novel of Hybrid Maintenance Management Models for Industrial Applications

    OpenAIRE

    Tahir, Zulkifli

    2010-01-01

    It is observed through empirical studies that the effectiveness of industrial process have been increased by a well organized of machines maintenance structure. In current research, a novel of maintenance concept has been designed by hybrid several maintenance management models with Decision Making Grid (DMG), Analytic Hierarchy Process (AHP) and Fuzzy Logic. The concept is designed for maintenance personnel to evaluate and benchmark the maintenance operations and to reveal important maintena...

  8. A light neutralino in hybrid models of supersymmetry breaking

    International Nuclear Information System (INIS)

    Dudas, Emilian; Lavignac, Stephane; Parmentier, Jeanne

    2009-01-01

    We show that in gauge mediation models where heavy messenger masses are provided by the adjoint Higgs field of an underlying SU(5) theory, a generalized gauge mediation spectrum arises with the characteristic feature of having a neutralino LSP much lighter than in the standard gauge or gravity mediation schemes. This naturally fits in a hybrid scenario where gravity mediation, while subdominant with respect to gauge mediation, provides μ and Bμ parameters of the appropriate size for electroweak symmetry breaking

  9. Hybrid Model for e-Learning Quality Evaluation

    Directory of Open Access Journals (Sweden)

    Suzana M. Savic

    2012-02-01

    Full Text Available E-learning is becoming increasingly important for the competitive advantage of economic organizations and higher education institutions. Therefore, it is becoming a significant aspect of quality which has to be integrated into the management system of every organization or institution. The paper examines e-learning quality characteristics, standards, criteria and indicators and presents a multi-criteria hybrid model for e-learning quality evaluation based on the method of Analytic Hierarchy Process, trend analysis, and data comparison.

  10. Hybrid Speaker Recognition Using Universal Acoustic Model

    Science.gov (United States)

    Nishimura, Jun; Kuroda, Tadahiro

    We propose a novel speaker recognition approach using a speaker-independent universal acoustic model (UAM) for sensornet applications. In sensornet applications such as “Business Microscope”, interactions among knowledge workers in an organization can be visualized by sensing face-to-face communication using wearable sensor nodes. In conventional studies, speakers are detected by comparing energy of input speech signals among the nodes. However, there are often synchronization errors among the nodes which degrade the speaker recognition performance. By focusing on property of the speaker's acoustic channel, UAM can provide robustness against the synchronization error. The overall speaker recognition accuracy is improved by combining UAM with the energy-based approach. For 0.1s speech inputs and 4 subjects, speaker recognition accuracy of 94% is achieved at the synchronization error less than 100ms.

  11. Stochastic linear hybrid systems: Modeling, estimation, and application

    Science.gov (United States)

    Seah, Chze Eng

    Hybrid systems are dynamical systems which have interacting continuous state and discrete state (or mode). Accurate modeling and state estimation of hybrid systems are important in many applications. We propose a hybrid system model, known as the Stochastic Linear Hybrid System (SLHS), to describe hybrid systems with stochastic linear system dynamics in each mode and stochastic continuous-state-dependent mode transitions. We then develop a hybrid estimation algorithm, called the State-Dependent-Transition Hybrid Estimation (SDTHE) algorithm, to estimate the continuous state and discrete state of the SLHS from noisy measurements. It is shown that the SDTHE algorithm is more accurate or more computationally efficient than existing hybrid estimation algorithms. Next, we develop a performance analysis algorithm to evaluate the performance of the SDTHE algorithm in a given operating scenario. We also investigate sufficient conditions for the stability of the SDTHE algorithm. The proposed SLHS model and SDTHE algorithm are illustrated to be useful in several applications. In Air Traffic Control (ATC), to facilitate implementations of new efficient operational concepts, accurate modeling and estimation of aircraft trajectories are needed. In ATC, an aircraft's trajectory can be divided into a number of flight modes. Furthermore, as the aircraft is required to follow a given flight plan or clearance, its flight mode transitions are dependent of its continuous state. However, the flight mode transitions are also stochastic due to navigation uncertainties or unknown pilot intents. Thus, we develop an aircraft dynamics model in ATC based on the SLHS. The SDTHE algorithm is then used in aircraft tracking applications to estimate the positions/velocities of aircraft and their flight modes accurately. Next, we develop an aircraft conformance monitoring algorithm to detect any deviations of aircraft trajectories in ATC that might compromise safety. In this application, the SLHS

  12. The Cheshire Cat principle applied to hybrid bag models

    International Nuclear Information System (INIS)

    Nielsen, H.B.; Wirzba, A.

    1987-05-01

    Here is argued for the Cheshire Cat point of view according to which the bag (itself) has only notational, but no physical significance. It is explained in a 1+1 dimensional exact Cheshire Cat model how a fermion can escape from the bag by means of an anomaly. We also suggest that suitably constructed hybrid bag models may be used to fix such parameters of effective Lagrangians that can otherwise be obtained from experiments only. This idea is illustrated in a calculation of the mass of the pseudoscalar η' meson in 1+1 dimension. Thus there is hope to find a construction principle for a phenomenologically sensible model. (orig.)

  13. Hybrid model for the decay of nuclear giant resonances

    International Nuclear Information System (INIS)

    Hussein, M.S.

    1986-12-01

    The decay properties of nuclear giant multipole resonances are discussed within a hybrid model that incorporates, in a unitary consistent way, both the coherent and statistical features. It is suggested that the 'direct' decay of the GR is described with continuum first RPA and the statistical decay calculated with a modified Hauser-Feshbach model. Application is made to the decay of the giant monopole resonance in 208 Pb. Suggestions are made concerning the calculation of the mixing parameter using the statistical properties of the shell model eigenstates at high excitation energies. (Author) [pt

  14. Model Predictive Control for Connected Hybrid Electric Vehicles

    Directory of Open Access Journals (Sweden)

    Kaijiang Yu

    2015-01-01

    Full Text Available This paper presents a new model predictive control system for connected hybrid electric vehicles to improve fuel economy. The new features of this study are as follows. First, the battery charge and discharge profile and the driving velocity profile are simultaneously optimized. One is energy management for HEV for Pbatt; the other is for the energy consumption minimizing problem of acc control of two vehicles. Second, a system for connected hybrid electric vehicles has been developed considering varying drag coefficients and the road gradients. Third, the fuel model of a typical hybrid electric vehicle is developed using the maps of the engine efficiency characteristics. Fourth, simulations and analysis (under different parameters, i.e., road conditions, vehicle state of charge, etc. are conducted to verify the effectiveness of the method to achieve higher fuel efficiency. The model predictive control problem is solved using numerical computation method: continuation and generalized minimum residual method. Computer simulation results reveal improvements in fuel economy using the proposed control method.

  15. Lectures on functor homology

    CERN Document Server

    Touzé, Antoine

    2015-01-01

    This book features a series of lectures that explores three different fields in which functor homology (short for homological algebra in functor categories) has recently played a significant role. For each of these applications, the functor viewpoint provides both essential insights and new methods for tackling difficult mathematical problems. In the lectures by Aurélien Djament, polynomial functors appear as coefficients in the homology of infinite families of classical groups, e.g. general linear groups or symplectic groups, and their stabilization. Djament’s theorem states that this stable homology can be computed using only the homology with trivial coefficients and the manageable functor homology. The series includes an intriguing development of Scorichenko’s unpublished results. The lectures by Wilberd van der Kallen lead to the solution of the general cohomological finite generation problem, extending Hilbert’s fourteenth problem and its solution to the context of cohomology. The focus here is o...

  16. Parametric Linear Hybrid Automata for Complex Environmental Systems Modeling

    Directory of Open Access Journals (Sweden)

    Samar Hayat Khan Tareen

    2015-07-01

    Full Text Available Environmental systems, whether they be weather patterns or predator-prey relationships, are dependent on a number of different variables, each directly or indirectly affecting the system at large. Since not all of these factors are known, these systems take on non-linear dynamics, making it difficult to accurately predict meaningful behavioral trends far into the future. However, such dynamics do not warrant complete ignorance of different efforts to understand and model close approximations of these systems. Towards this end, we have applied a logical modeling approach to model and analyze the behavioral trends and systematic trajectories that these systems exhibit without delving into their quantification. This approach, formalized by René Thomas for discrete logical modeling of Biological Regulatory Networks (BRNs and further extended in our previous studies as parametric biological linear hybrid automata (Bio-LHA, has been previously employed for the analyses of different molecular regulatory interactions occurring across various cells and microbial species. As relationships between different interacting components of a system can be simplified as positive or negative influences, we can employ the Bio-LHA framework to represent different components of the environmental system as positive or negative feedbacks. In the present study, we highlight the benefits of hybrid (discrete/continuous modeling which lead to refinements among the fore-casted behaviors in order to find out which ones are actually possible. We have taken two case studies: an interaction of three microbial species in a freshwater pond, and a more complex atmospheric system, to show the applications of the Bio-LHA methodology for the timed hybrid modeling of environmental systems. Results show that the approach using the Bio-LHA is a viable method for behavioral modeling of complex environmental systems by finding timing constraints while keeping the complexity of the model

  17. Scalability of Sustainable Business Models in Hybrid Organizations

    Directory of Open Access Journals (Sweden)

    Adam Jabłoński

    2016-02-01

    Full Text Available The dynamics of change in modern business create new mechanisms for company management to determine their pursuit and the achievement of their high performance. This performance maintained over a long period of time becomes a source of ensuring business continuity by companies. An ontological being enabling the adoption of such assumptions is such a business model that has the ability to generate results in every possible market situation and, moreover, it has the features of permanent adaptability. A feature that describes the adaptability of the business model is its scalability. Being a factor ensuring more work and more efficient work with an increasing number of components, scalability can be applied to the concept of business models as the company’s ability to maintain similar or higher performance through it. Ensuring the company’s performance in the long term helps to build the so-called sustainable business model that often balances the objectives of stakeholders and shareholders, and that is created by the implemented principles of value-based management and corporate social responsibility. This perception of business paves the way for building hybrid organizations that integrate business activities with pro-social ones. The combination of an approach typical of hybrid organizations in designing and implementing sustainable business models pursuant to the scalability criterion seems interesting from the cognitive point of view. Today, hybrid organizations are great spaces for building effective and efficient mechanisms for dialogue between business and society. This requires the appropriate business model. The purpose of the paper is to present the conceptualization and operationalization of scalability of sustainable business models that determine the performance of a hybrid organization in the network environment. The paper presents the original concept of applying scalability in sustainable business models with detailed

  18. Numerical modeling of hybrid fiber-reinforced concrete (hyfrc)

    International Nuclear Information System (INIS)

    Hameed, R.; Turatsinze, A.

    2015-01-01

    A model for numerical simulation of mechanical response of concrete reinforced with slipping and non slipping metallic fibers in hybrid form is presented in this paper. Constitutive law used to model plain concrete behaviour is based on plasticity and damage theories, and is capable to determine localized crack opening in three dimensional (3-D) systems. Behaviour law used for slipping metallic fibers is formulated based on effective stress carried by these fibers after when concrete matrix is cracked. A continuous approach is proposed to model the effect of addition of non-slipping metallic fibers in plain concrete. This approach considers the constitutive law of concrete matrix with increased fracture energy in tension obtained experimentally in direct tension tests on Fiber Reinforced Concrete (FRC). To simulate the mechanical behaviour of hybrid fiber-reinforced concrete (HyFRC), proposed approaches to model non-slipping metallic fibers and constitutive law of plain concrete and slipping fibers are used simultaneously without any additive equation. All the parameters used by the proposed model have physical meanings and are determined through experiments or drawn from literature. The model was implemented in Finite Element (FE) Code CASTEM and tested on FRC prismatic notched specimens in flexure. Model prediction showed good agreement with experimental results. (author)

  19. Modelling and control of a light-duty hybrid electric truck

    OpenAIRE

    Park, Jong-Kyu

    2006-01-01

    This study is concentrated on modelling and developing the controller for the light-duty hybrid electric truck. The hybrid electric vehicle has advantages in fuel economy. However, there have been relatively few studies on commercial HEVs, whilst a considerable number of studies on the hybrid electric system have been conducted in the field of passenger cars. So the current status and the methodologies to develop the LD hybrid electric truck model have been studied through the ...

  20. Maximum Mass of Hybrid Stars in the Quark Bag Model

    Science.gov (United States)

    Alaverdyan, G. B.; Vartanyan, Yu. L.

    2017-12-01

    The effect of model parameters in the equation of state for quark matter on the magnitude of the maximum mass of hybrid stars is examined. Quark matter is described in terms of the extended MIT bag model including corrections for one-gluon exchange. For nucleon matter in the range of densities corresponding to the phase transition, a relativistic equation of state is used that is calculated with two-particle correlations taken into account based on using the Bonn meson-exchange potential. The Maxwell construction is used to calculate the characteristics of the first order phase transition and it is shown that for a fixed value of the strong interaction constant αs, the baryon concentrations of the coexisting phases grow monotonically as the bag constant B increases. It is shown that for a fixed value of the strong interaction constant αs, the maximum mass of a hybrid star increases as the bag constant B decreases. For a given value of the bag parameter B, the maximum mass rises as the strong interaction constant αs increases. It is shown that the configurations of hybrid stars with maximum masses equal to or exceeding the mass of the currently known most massive pulsar are possible for values of the strong interaction constant αs > 0.6 and sufficiently low values of the bag constant.

  1. MODEL APLIKASI FIKIH MUAMALAH PADA FORMULASI HYBRID CONTRACT

    Directory of Open Access Journals (Sweden)

    Ali Murtadho

    2013-10-01

    Full Text Available Modern literatures of fiqh mu’āmalah talk alot about various contract formulation with capability of maximizing profit in shariah finance industry. This new contract modification is the synthesis among existing contracts which is formulated in such a way to be an integrated contract. This formulation is known as a hybrid contract or multicontract (al-'uqūd al-murakkabah. Some of them are, bay' bi thaman 'ājil, Ijārah muntahiyah bi ’l-tamlīk dan mushārakah mutanāqiṣah. This study intends to further describe models of hybrid contract, and explore the shari'ah principles in modern financial institutions. This study found a potential shift from the ideal values of the spirit of shari'ah into the spirit of competition based shari'ah formally.

  2. A Simple Hybrid Model for Short-Term Load Forecasting

    Directory of Open Access Journals (Sweden)

    Suseelatha Annamareddi

    2013-01-01

    Full Text Available The paper proposes a simple hybrid model to forecast the electrical load data based on the wavelet transform technique and double exponential smoothing. The historical noisy load series data is decomposed into deterministic and fluctuation components using suitable wavelet coefficient thresholds and wavelet reconstruction method. The variation characteristics of the resulting series are analyzed to arrive at reasonable thresholds that yield good denoising results. The constitutive series are then forecasted using appropriate exponential adaptive smoothing models. A case study performed on California energy market data demonstrates that the proposed method can offer high forecasting precision for very short-term forecasts, considering a time horizon of two weeks.

  3. Calibrated and Interactive Modelling of Form-Active Hybrid Structures

    DEFF Research Database (Denmark)

    Quinn, Gregory; Holden Deleuran, Anders; Piker, Daniel

    2016-01-01

    Form-active hybrid structures (FAHS) couple two or more different structural elements of low self weight and low or negligible bending flexural stiffness (such as slender beams, cables and membranes) into one structural assembly of high global stiffness. They offer high load-bearing capacity...... software packages which introduce interruptions and data exchange issues in the modelling pipeline. The mechanical precision, stability and open software architecture of Kangaroo has facilitated the development of proof-of-concept modelling pipelines which tackle this challenge and enable powerful...... materially-informed sketching. Making use of a projection-based dynamic relaxation solver for structural analysis, explorative design has proven to be highly effective....

  4. Homological stabilizer codes

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Jonas T., E-mail: jonastyleranderson@gmail.com

    2013-03-15

    In this paper we define homological stabilizer codes on qubits which encompass codes such as Kitaev's toric code and the topological color codes. These codes are defined solely by the graphs they reside on. This feature allows us to use properties of topological graph theory to determine the graphs which are suitable as homological stabilizer codes. We then show that all toric codes are equivalent to homological stabilizer codes on 4-valent graphs. We show that the topological color codes and toric codes correspond to two distinct classes of graphs. We define the notion of label set equivalencies and show that under a small set of constraints the only homological stabilizer codes without local logical operators are equivalent to Kitaev's toric code or to the topological color codes. - Highlights: Black-Right-Pointing-Pointer We show that Kitaev's toric codes are equivalent to homological stabilizer codes on 4-valent graphs. Black-Right-Pointing-Pointer We show that toric codes and color codes correspond to homological stabilizer codes on distinct graphs. Black-Right-Pointing-Pointer We find and classify all 2D homological stabilizer codes. Black-Right-Pointing-Pointer We find optimal codes among the homological stabilizer codes.

  5. A generic approach for expanding homolog-targeted residue screening of sulfonamides using a fast matrix separation and class-specific fragmentation-dependent acquisition with a hybrid quadrupole-linear ion trap mass spectrometer

    Energy Technology Data Exchange (ETDEWEB)

    Huang Chunlin [Department of Biochemistry and Molecular Biology, School of Pharmacy and Life Science, University of South China, Hengyang 421001 (China); Guo Bin, E-mail: binnguo@126.com [Key Laboratory of Chemical Biology and Traditional Chinese Medicine Research (Ministry of Education of China), Hunan Normal University, Changsha 410081 (China); Wang Xiaoying [Key Laboratory of Chemical Biology and Traditional Chinese Medicine Research (Ministry of Education of China), Hunan Normal University, Changsha 410081 (China); Li Jie [Department of Biochemistry and Molecular Biology, School of Pharmacy and Life Science, University of South China, Hengyang 421001 (China); Zhu Weitao; Chen Bo [Key Laboratory of Chemical Biology and Traditional Chinese Medicine Research (Ministry of Education of China), Hunan Normal University, Changsha 410081 (China); Ouyang Shan [Food Inspection and Quarantine Center, Shenzhen Entry-Exit Inspection and Quarantine Bureau of the People' s Republic of China, Shenzhen 518067 (China); Yao Shouzhuo [Key Laboratory of Chemical Biology and Traditional Chinese Medicine Research (Ministry of Education of China), Hunan Normal University, Changsha 410081 (China)

    2012-08-06

    Highlights: Black-Right-Pointing-Pointer Generic homolog-targeted screening approach for multi-residual sulfonamide analogs. Black-Right-Pointing-Pointer Single-tube extraction/partitioning-multifunction adsorption cleanup for direct injection. Black-Right-Pointing-Pointer Class-specific fragmentation for expanding coverage of N{sup 4}-acetyl and N-OH metabolites. Black-Right-Pointing-Pointer PreS-IDA-EPI in LC-QqLIT for simultaneous screening and confirmation of real samples. - Abstract: A generic and efficient homolog-targeted approach was used to expand screening and detection of target class of sulfonamides and structural analogs, based on a fast single-tube extraction/partitioning-multifunction adsorption cleanup (SEP/MAC) for class-specific fragmentation-dependent acquisition with a liquid chromatography-hybrid triple-quadrupole linear ion trap mass spectrometer (LC-QqLIT). By combining the two-stage process conducted in a single tube as one-pot protocol, the straightforward SEP/MAC procedure was optimized to offer clean extracts with reasonable recovery (71-109% with RSDs < 20%) and decreased matrix interferences (-9 to 19%) of multiresidual sulfonamide extraction from different tissue samples. The novel use of neutral loss scan of 66 Da (NLS) or precursor ion scanning of m/z 108 (PreS) in positive ion mode was found to achieve more comprehensive coverage of protonated molecular ions of a wide array of sulfonamides including N{sup 4}-acetyl and hydroxylamine metabolites plus their possible dimers. Moreover, the PreS-triggered automatically enhanced product ion spectral acquisition enabled simultaneous screening, profiling and confirmation of an unlimited number of analytes belonging to the sulfonamide class within a single analysis. The validation and application results of the generic SEP/MAC-based LC-QqLIT strategy consistently demonstrated favorable performances with acceptable accuracy (67-116%), precision (RSDs < 25%), and sensitivity (LOQs {<=} 7.5 ng

  6. Hybrid Adaptive Flight Control with Model Inversion Adaptation

    Science.gov (United States)

    Nguyen, Nhan

    2011-01-01

    This study investigates a hybrid adaptive flight control method as a design possibility for a flight control system that can enable an effective adaptation strategy to deal with off-nominal flight conditions. The hybrid adaptive control blends both direct and indirect adaptive control in a model inversion flight control architecture. The blending of both direct and indirect adaptive control provides a much more flexible and effective adaptive flight control architecture than that with either direct or indirect adaptive control alone. The indirect adaptive control is used to update the model inversion controller by an on-line parameter estimation of uncertain plant dynamics based on two methods. The first parameter estimation method is an indirect adaptive law based on the Lyapunov theory, and the second method is a recursive least-squares indirect adaptive law. The model inversion controller is therefore made to adapt to changes in the plant dynamics due to uncertainty. As a result, the modeling error is reduced that directly leads to a decrease in the tracking error. In conjunction with the indirect adaptive control that updates the model inversion controller, a direct adaptive control is implemented as an augmented command to further reduce any residual tracking error that is not entirely eliminated by the indirect adaptive control.

  7. Design, test and model of a hybrid magnetostrictive hydraulic actuator

    International Nuclear Information System (INIS)

    Chaudhuri, Anirban; Yoo, Jin-Hyeong; Wereley, Norman M

    2009-01-01

    The basic operation of hybrid hydraulic actuators involves high frequency bi-directional operation of an active material that is converted to uni-directional motion of hydraulic fluid using valves. A hybrid actuator was developed using magnetostrictive material Terfenol-D as the driving element and hydraulic oil as the working fluid. Two different lengths of Terfenol-D rod, 51 and 102 mm, with the same diameter, 12.7 mm, were used. Tests with no load and with load were carried out to measure the performance for uni-directional motion of the output piston at different pumping frequencies. The maximum no-load flow rates were 24.8 cm 3 s −1 and 22.7 cm 3 s −1 with the 51 mm and 102 mm long rods respectively, and the peaks were noted around 325 Hz pumping frequency. The blocked force of the actuator was close to 89 N in both cases. A key observation was that, at these high pumping frequencies, the inertial effects of the fluid mass dominate over the viscous effects and the problem becomes unsteady in nature. In this study, we also develop a mathematical model of the hydraulic hybrid actuator in the time domain to show the basic operational principle under varying conditions and to capture phenomena affecting system performance. Governing equations for the pumping piston and output shaft were obtained from force equilibrium considerations, while compressibility of the working fluid was taken into account by incorporating the bulk modulus. Fluid inertia was represented by a lumped parameter approach to the transmission line model, giving rise to strongly coupled ordinary differential equations. The model was then used to calculate the no-load velocities of the actuator at different pumping frequencies and simulation results were compared with experimental data for model validation

  8. Hybrid perturbation methods based on statistical time series models

    Science.gov (United States)

    San-Juan, Juan Félix; San-Martín, Montserrat; Pérez, Iván; López, Rosario

    2016-04-01

    In this work we present a new methodology for orbit propagation, the hybrid perturbation theory, based on the combination of an integration method and a prediction technique. The former, which can be a numerical, analytical or semianalytical theory, generates an initial approximation that contains some inaccuracies derived from the fact that, in order to simplify the expressions and subsequent computations, not all the involved forces are taken into account and only low-order terms are considered, not to mention the fact that mathematical models of perturbations not always reproduce physical phenomena with absolute precision. The prediction technique, which can be based on either statistical time series models or computational intelligence methods, is aimed at modelling and reproducing missing dynamics in the previously integrated approximation. This combination results in the precision improvement of conventional numerical, analytical and semianalytical theories for determining the position and velocity of any artificial satellite or space debris object. In order to validate this methodology, we present a family of three hybrid orbit propagators formed by the combination of three different orders of approximation of an analytical theory and a statistical time series model, and analyse their capability to process the effect produced by the flattening of the Earth. The three considered analytical components are the integration of the Kepler problem, a first-order and a second-order analytical theories, whereas the prediction technique is the same in the three cases, namely an additive Holt-Winters method.

  9. Bayesian inference for hybrid discrete-continuous stochastic kinetic models

    International Nuclear Information System (INIS)

    Sherlock, Chris; Golightly, Andrew; Gillespie, Colin S

    2014-01-01

    We consider the problem of efficiently performing simulation and inference for stochastic kinetic models. Whilst it is possible to work directly with the resulting Markov jump process (MJP), computational cost can be prohibitive for networks of realistic size and complexity. In this paper, we consider an inference scheme based on a novel hybrid simulator that classifies reactions as either ‘fast’ or ‘slow’ with fast reactions evolving as a continuous Markov process whilst the remaining slow reaction occurrences are modelled through a MJP with time-dependent hazards. A linear noise approximation (LNA) of fast reaction dynamics is employed and slow reaction events are captured by exploiting the ability to solve the stochastic differential equation driving the LNA. This simulation procedure is used as a proposal mechanism inside a particle MCMC scheme, thus allowing Bayesian inference for the model parameters. We apply the scheme to a simple application and compare the output with an existing hybrid approach and also a scheme for performing inference for the underlying discrete stochastic model. (paper)

  10. A viable D-term hybrid inflation model

    Science.gov (United States)

    Kadota, Kenji; Kobayashi, Tatsuo; Sumita, Keigo

    2017-11-01

    We propose a new model of the D-term hybrid inflation in the framework of supergravity. Although our model introduces, analogously to the conventional D-term inflation, the inflaton and a pair of scalar fields charged under a U(1) gauge symmetry, we study the logarithmic and exponential dependence on the inflaton field, respectively, for the Kähler and superpotential. This results in a characteristic one-loop scalar potential consisting of linear and exponential terms, which realizes the small-field inflation dominated by the Fayet-Iliopoulos term. With the reasonable values for the coupling coefficients and, in particular, with the U(1) gauge coupling constant comparable to that of the Standard Model, our D-term inflation model can solve the notorious problems in the conventional D-term inflation, namely, the CMB constraints on the spectral index and the generation of cosmic strings.

  11. Ionocovalency and Applications 1. Ionocovalency Model and Orbital Hybrid Scales

    Directory of Open Access Journals (Sweden)

    Yonghe Zhang

    2010-11-01

    Full Text Available Ionocovalency (IC, a quantitative dual nature of the atom, is defined and correlated with quantum-mechanical potential to describe quantitatively the dual properties of the bond. Orbiotal hybrid IC model scale, IC, and IC electronegativity scale, XIC, are proposed, wherein the ionicity and the covalent radius are determined by spectroscopy. Being composed of the ionic function I and the covalent function C, the model describes quantitatively the dual properties of bond strengths, charge density and ionic potential. Based on the atomic electron configuration and the various quantum-mechanical built-up dual parameters, the model formed a Dual Method of the multiple-functional prediction, which has much more versatile and exceptional applications than traditional electronegativity scales and molecular properties. Hydrogen has unconventional values of IC and XIC, lower than that of boron. The IC model can agree fairly well with the data of bond properties and satisfactorily explain chemical observations of elements throughout the Periodic Table.

  12. A hybrid spatiotemporal drought forecasting model for operational use

    Science.gov (United States)

    Vasiliades, L.; Loukas, A.

    2010-09-01

    Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. This study develops a hybrid spatiotemporal scheme for integrated spatial and temporal forecasting. Temporal forecasting is achieved using feed-forward neural networks and the temporal forecasts are extended to the spatial dimension using a spatial recurrent neural network model. The methodology is demonstrated for an operational meteorological drought index the Standardized Precipitation Index (SPI) calculated at multiple timescales. 48 precipitation stations and 18 independent precipitation stations, located at Pinios river basin in Thessaly region, Greece, were used for the development and spatiotemporal validation of the hybrid spatiotemporal scheme. Several quantitative temporal and spatial statistical indices were considered for the performance evaluation of the models. Furthermore, qualitative statistical criteria based on contingency tables between observed and forecasted drought episodes were calculated. The results show that the lead time of forecasting for operational use depends on the SPI timescale. The hybrid spatiotemporal drought forecasting model could be operationally used for forecasting up to three months ahead for SPI short timescales (e.g. 3-6 months) up to six months ahead for large SPI timescales (e.g. 24 months). The above findings could be useful in developing a drought preparedness plan in the region.

  13. Homology-modeled ligand-binding domains of medaka estrogen receptors and androgen receptors: A model system for the study of reproduction

    International Nuclear Information System (INIS)

    Cui Jianzhou; Shen Xueyan; Yan Zuowei; Zhao Haobin; Nagahama, Yoshitaka

    2009-01-01

    Estrogen and androgen and their receptors play critical roles in physiological processes such as sexual differentiation and development. Using the available structural models for the human estrogen receptors alpha and beta and androgen receptor as templates, we designed in silico agonist and antagonist models of medaka estrogen receptor (meER) alpha, beta-1, and beta-2, and androgen receptor (meAR) alpha and beta. Using these models, we studied (1) the structural relationship between the ligand-binding domains (LBDs) of ERs and ARs of human and medaka, and (2) whether medaka ER and AR can be potential models for studying the ligand-binding activities of various agonists and antagonists of these receptors by docking analysis. A high level of conservation was observed between the sequences of the ligand-binding domains of meERα and huERα, meERβ1 and huERβ, meERβ2, and huERβ with 62.8%, 66.4%, and 65.1% identity, respectively. The sequence conservation between meARα and huAR, meARβ, and huAR was found with 70.1% and 61.0% of identity, respectively. Thirty-three selected endocrine disrupting chemicals (EDCs), including both agonists and antagonists, were docked into the LBD of ER and AR, and the corresponding docking score for medaka models and human templates were calculated. In order to confirm the conservation of the overall geometry and the binding pocket, the backbone root mean square deviation (RMSD) for Cα atoms was derived from the structure superposition of all 10 medaka homology models to the six human templates. Our results suggested conformational conservation between the ERs and ARs of medaka and human, Thus, medaka could be highly useful as a model system for studies involving estrogen and androgen interaction with their receptors.

  14. On The Modelling Of Hybrid Aerostatic - Gas Journal Bearings

    DEFF Research Database (Denmark)

    Morosi, Stefano; Santos, Ilmar

    2011-01-01

    modeling for hybrid lubrication of a compressible fluid film journal bearing. Additional forces are generated by injecting pressurized air into the bearing gap through orifices located on the bearing walls. A modified form of the compressible Reynolds equation for active lubrication is derived. By solving......Gas journal bearing have been increasingly adopted in modern turbo-machinery applications, as they meet the demands of operation at higher rotational speeds, in clean environment and great efficiency. Due to the fact that gaseous lubricants, typically air, have much lower viscosity than more...

  15. Active diagnosis of hybrid systems - A model predictive approach

    DEFF Research Database (Denmark)

    Tabatabaeipour, Seyed Mojtaba; Ravn, Anders P.; Izadi-Zamanabadi, Roozbeh

    2009-01-01

    A method for active diagnosis of hybrid systems is proposed. The main idea is to predict the future output of both normal and faulty model of the system; then at each time step an optimization problem is solved with the objective of maximizing the difference between the predicted normal and fault...... can be used as a test signal for sanity check at the commissioning or for detection of faults hidden by regulatory actions of the controller. The method is tested on the two tank benchmark example. ©2009 IEEE....

  16. Software development infrastructure for the HYBRID modeling and simulation project

    International Nuclear Information System (INIS)

    Epiney, Aaron S.; Kinoshita, Robert A.; Kim, Jong Suk; Rabiti, Cristian; Greenwood, M. Scott

    2016-01-01

    One of the goals of the HYBRID modeling and simulation project is to assess the economic viability of hybrid systems in a market that contains renewable energy sources like wind. The idea is that it is possible for the nuclear plant to sell non-electric energy cushions, which absorb (at least partially) the volatility introduced by the renewable energy sources. This system is currently modeled in the Modelica programming language. To assess the economics of the system, an optimization procedure is trying to find the minimal cost of electricity production. The RAVEN code is used as a driver for the whole problem. It is assumed that at this stage, the HYBRID modeling and simulation framework can be classified as non-safety “research and development” software. The associated quality level is Quality Level 3 software. This imposes low requirements on quality control, testing and documentation. The quality level could change as the application development continues.Despite the low quality requirement level, a workflow for the HYBRID developers has been defined that include a coding standard and some documentation and testing requirements. The repository performs automated unit testing of contributed models. The automated testing is achieved via an open-source python script called BuildingsP from Lawrence Berkeley National Lab. BuildingsPy runs Modelica simulation tests using Dymola in an automated manner and generates and runs unit tests from Modelica scripts written by developers. In order to assure effective communication between the different national laboratories a biweekly videoconference has been set-up, where developers can report their progress and issues. In addition, periodic face-face meetings are organized intended to discuss high-level strategy decisions with management. A second means of communication is the developer email list. This is a list to which everybody can send emails that will be received by the collective of the developers and managers

  17. The Hybrid Airline Model. Generating Quality for Passengers

    Directory of Open Access Journals (Sweden)

    Bogdan AVRAM

    2017-12-01

    Full Text Available This research aims to investigate the different strategies adopted by the airline companies in adapting to the ongoing changes while developing products and services for passengers in order to increase their yield, load factor and passenger satisfaction. Finding a balance between costs and services quality in the airline industry is a crucial task for every airline wanting to gain a competitive advantage on the market. Also, the rise of the hybrid business operating model has brought up many challenges for airlines as the line between legacy carriers and low-cost carriers is getting thinner in terms of costs and innovative ideas to create a superior product for the passengers.

  18. Software development infrastructure for the HYBRID modeling and simulation project

    Energy Technology Data Exchange (ETDEWEB)

    Epiney, Aaron S. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Kinoshita, Robert A. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Kim, Jong Suk [Idaho National Lab. (INL), Idaho Falls, ID (United States); Rabiti, Cristian [Idaho National Lab. (INL), Idaho Falls, ID (United States); Greenwood, M. Scott [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2016-09-01

    One of the goals of the HYBRID modeling and simulation project is to assess the economic viability of hybrid systems in a market that contains renewable energy sources like wind. The idea is that it is possible for the nuclear plant to sell non-electric energy cushions, which absorb (at least partially) the volatility introduced by the renewable energy sources. This system is currently modeled in the Modelica programming language. To assess the economics of the system, an optimization procedure is trying to find the minimal cost of electricity production. The RAVEN code is used as a driver for the whole problem. It is assumed that at this stage, the HYBRID modeling and simulation framework can be classified as non-safety “research and development” software. The associated quality level is Quality Level 3 software. This imposes low requirements on quality control, testing and documentation. The quality level could change as the application development continues.Despite the low quality requirement level, a workflow for the HYBRID developers has been defined that include a coding standard and some documentation and testing requirements. The repository performs automated unit testing of contributed models. The automated testing is achieved via an open-source python script called BuildingsP from Lawrence Berkeley National Lab. BuildingsPy runs Modelica simulation tests using Dymola in an automated manner and generates and runs unit tests from Modelica scripts written by developers. In order to assure effective communication between the different national laboratories a biweekly videoconference has been set-up, where developers can report their progress and issues. In addition, periodic face-face meetings are organized intended to discuss high-level strategy decisions with management. A second means of communication is the developer email list. This is a list to which everybody can send emails that will be received by the collective of the developers and managers

  19. A Lookahead Behavior Model for Multi-Agent Hybrid Simulation

    Directory of Open Access Journals (Sweden)

    Mei Yang

    2017-10-01

    Full Text Available In the military field, multi-agent simulation (MAS plays an important role in studying wars statistically. For a military simulation system, which involves large-scale entities and generates a very large number of interactions during the runtime, the issue of how to improve the running efficiency is of great concern for researchers. Current solutions mainly use hybrid simulation to gain fewer updates and synchronizations, where some important continuous models are maintained implicitly to keep the system dynamics, and partial resynchronization (PR is chosen as the preferable state update mechanism. However, problems, such as resynchronization interval selection and cyclic dependency, remain unsolved in PR, which easily lead to low update efficiency and infinite looping of the state update process. To address these problems, this paper proposes a lookahead behavior model (LBM to implement a PR-based hybrid simulation. In LBM, a minimal safe time window is used to predict the interactions between implicit models, upon which the resynchronization interval can be efficiently determined. Moreover, the LBM gives an estimated state value in the lookahead process so as to break the state-dependent cycle. The simulation results show that, compared with traditional mechanisms, LBM requires fewer updates and synchronizations.

  20. Causality in Psychiatry: A Hybrid Symptom Network Construct Model

    Directory of Open Access Journals (Sweden)

    Gerald eYoung

    2015-11-01

    Full Text Available Causality or etiology in psychiatry is marked by standard biomedical, reductionistic models (symptoms reflect the construct involved that inform approaches to nosology, or classification, such as in the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition; American Psychiatric Association, 2013. However, network approaches to symptom interaction (i.e., symptoms are formative of the construct; e.g., McNally, Robinaugh, Wu, Wang, Deserno, & Borsboom, 2014, for PTSD (posttraumatic stress disorder are being developed that speak to bottom-up processes in mental disorder, in contrast to the typical top-down psychological construct approach. The present article presents a hybrid top-down, bottom-up model of the relationship between symptoms and mental disorder, viewing symptom expression and their causal complex as a reciprocally dynamic system with multiple levels, from lower-order symptoms in interaction to higher-order constructs affecting them. The hybrid model hinges on good understanding of systems theory in which it is embedded, so that the article reviews in depth nonlinear dynamical systems theory (NLDST. The article applies the concept of emergent circular causality (Young, 2011 to symptom development, as well. Conclusions consider that symptoms vary over several dimensions, including: subjectivity; objectivity; conscious motivation effort; and unconscious influences, and the degree to which individual (e.g., meaning and universal (e.g., causal processes are involved. The opposition between science and skepticism is a complex one that the article addresses in final comments.

  1. Hybrid CFD/CAA Modeling for Liftoff Acoustic Predictions

    Science.gov (United States)

    Strutzenberg, Louise L.; Liever, Peter A.

    2011-01-01

    This paper presents development efforts at the NASA Marshall Space flight Center to establish a hybrid Computational Fluid Dynamics and Computational Aero-Acoustics (CFD/CAA) simulation system for launch vehicle liftoff acoustics environment analysis. Acoustic prediction engineering tools based on empirical jet acoustic strength and directivity models or scaled historical measurements are of limited value in efforts to proactively design and optimize launch vehicles and launch facility configurations for liftoff acoustics. CFD based modeling approaches are now able to capture the important details of vehicle specific plume flow environment, identifY the noise generation sources, and allow assessment of the influence of launch pad geometric details and sound mitigation measures such as water injection. However, CFD methodologies are numerically too dissipative to accurately capture the propagation of the acoustic waves in the large CFD models. The hybrid CFD/CAA approach combines the high-fidelity CFD analysis capable of identifYing the acoustic sources with a fast and efficient Boundary Element Method (BEM) that accurately propagates the acoustic field from the source locations. The BEM approach was chosen for its ability to properly account for reflections and scattering of acoustic waves from launch pad structures. The paper will present an overview of the technology components of the CFD/CAA framework and discuss plans for demonstration and validation against test data.

  2. Efficient Vaccine Distribution Based on a Hybrid Compartmental Model.

    Directory of Open Access Journals (Sweden)

    Zhiwen Yu

    Full Text Available To effectively and efficiently reduce the morbidity and mortality that may be caused by outbreaks of emerging infectious diseases, it is very important for public health agencies to make informed decisions for controlling the spread of the disease. Such decisions must incorporate various kinds of intervention strategies, such as vaccinations, school closures and border restrictions. Recently, researchers have paid increased attention to searching for effective vaccine distribution strategies for reducing the effects of pandemic outbreaks when resources are limited. Most of the existing research work has been focused on how to design an effective age-structured epidemic model and to select a suitable vaccine distribution strategy to prevent the propagation of an infectious virus. Models that evaluate age structure effects are common, but models that additionally evaluate geographical effects are less common. In this paper, we propose a new SEIR (susceptible-exposed-infectious šC recovered model, named the hybrid SEIR-V model (HSEIR-V, which considers not only the dynamics of infection prevalence in several age-specific host populations, but also seeks to characterize the dynamics by which a virus spreads in various geographic districts. Several vaccination strategies such as different kinds of vaccine coverage, different vaccine releasing times and different vaccine deployment methods are incorporated into the HSEIR-V compartmental model. We also design four hybrid vaccination distribution strategies (based on population size, contact pattern matrix, infection rate and infectious risk for controlling the spread of viral infections. Based on data from the 2009-2010 H1N1 influenza epidemic, we evaluate the effectiveness of our proposed HSEIR-V model and study the effects of different types of human behaviour in responding to epidemics.

  3. Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review

    Science.gov (United States)

    Fahimi, Farzad; Yaseen, Zaher Mundher; El-shafie, Ahmed

    2017-05-01

    Since the middle of the twentieth century, artificial intelligence (AI) models have been used widely in engineering and science problems. Water resource variable modeling and prediction are the most challenging issues in water engineering. Artificial neural network (ANN) is a common approach used to tackle this problem by using viable and efficient models. Numerous ANN models have been successfully developed to achieve more accurate results. In the current review, different ANN models in water resource applications and hydrological variable predictions are reviewed and outlined. In addition, recent hybrid models and their structures, input preprocessing, and optimization techniques are discussed and the results are compared with similar previous studies. Moreover, to achieve a comprehensive view of the literature, many articles that applied ANN models together with other techniques are included. Consequently, coupling procedure, model evaluation, and performance comparison of hybrid models with conventional ANN models are assessed, as well as, taxonomy and hybrid ANN models structures. Finally, current challenges and recommendations for future researches are indicated and new hybrid approaches are proposed.

  4. Hybrid Modeling Method for a DEP Based Particle Manipulation

    Directory of Open Access Journals (Sweden)

    Mohamad Sawan

    2013-01-01

    Full Text Available In this paper, a new modeling approach for Dielectrophoresis (DEP based particle manipulation is presented. The proposed method fulfills missing links in finite element modeling between the multiphysic simulation and the biological behavior. This technique is amongst the first steps to develop a more complex platform covering several types of manipulations such as magnetophoresis and optics. The modeling approach is based on a hybrid interface using both ANSYS and MATLAB to link the propagation of the electrical field in the micro-channel to the particle motion. ANSYS is used to simulate the electrical propagation while MATLAB interprets the results to calculate cell displacement and send the new information to ANSYS for another turn. The beta version of the proposed technique takes into account particle shape, weight and its electrical properties. First obtained results are coherent with experimental results.

  5. The influence of nonlocal hybridization on ground-state properties of the Falicov-Kimball model

    International Nuclear Information System (INIS)

    Farkasovsky, Pavol

    2005-01-01

    The density matrix renormalization group is used to examine effects of nonlocal hybridization on ground-state properties of the Falicov-Kimball model (FKM) in one dimension. Special attention is devoted to the problem of hybridization-induced insulator-metal transition. It is shown that the picture of insulator-metal transitions found for the FKM with nonlocal hybridization strongly differs from one found for the FKM without hybridization (as well as with local hybridization). The effect of nonlocal hybridization is so strong that it can induce the insulator-metal transition, even in the half-filled band case where the ground states of the FKM without hybridization are insulating for all finite Coulomb interactions. Outside the half-filled band case the metal-insulator transition driven by pressure is found for finite values of nonlocal hybridization

  6. Dynamic Modeling and Simulation of a Switched Reluctance Motor in a Series Hybrid Electric Vehicle

    OpenAIRE

    Siavash Sadeghi; Mojtaba Mirsalim; Arash Hassanpour Isfahani

    2010-01-01

    Dynamic behavior analysis of electric motors is required in order to accuratelyevaluate the performance, energy consumption and pollution level of hybrid electricvehicles. Simulation tools for hybrid electric vehicles are divided into steady state anddynamic models. Tools with steady-state models are useful for system-level analysiswhereas tools that utilize dynamic models give in-depth information about the behavior ofsublevel components. For the accurate prediction of hybrid electric vehicl...

  7. An Interactive Personalized Recommendation System Using the Hybrid Algorithm Model

    Directory of Open Access Journals (Sweden)

    Yan Guo

    2017-10-01

    Full Text Available With the rapid development of e-commerce, the contradiction between the disorder of business information and customer demand is increasingly prominent. This study aims to make e-commerce shopping more convenient, and avoid information overload, by an interactive personalized recommendation system using the hybrid algorithm model. The proposed model first uses various recommendation algorithms to get a list of original recommendation results. Combined with the customer’s feedback in an interactive manner, it then establishes the weights of corresponding recommendation algorithms. Finally, the synthetic formula of evidence theory is used to fuse the original results to obtain the final recommendation products. The recommendation performance of the proposed method is compared with that of traditional methods. The results of the experimental study through a Taobao online dress shop clearly show that the proposed method increases the efficiency of data mining in the consumer coverage, the consumer discovery accuracy and the recommendation recall. The hybrid recommendation algorithm complements the advantages of the existing recommendation algorithms in data mining. The interactive assigned-weight method meets consumer demand better and solves the problem of information overload. Meanwhile, our study offers important implications for e-commerce platform providers regarding the design of product recommendation systems.

  8. A Probability-Based Hybrid User Model for Recommendation System

    Directory of Open Access Journals (Sweden)

    Jia Hao

    2016-01-01

    Full Text Available With the rapid development of information communication technology, the available information or knowledge is exponentially increased, and this causes the well-known information overload phenomenon. This problem is more serious in product design corporations because over half of the valuable design time is consumed in knowledge acquisition, which highly extends the design cycle and weakens the competitiveness. Therefore, the recommender systems become very important in the domain of product domain. This research presents a probability-based hybrid user model, which is a combination of collaborative filtering and content-based filtering. This hybrid model utilizes user ratings and item topics or classes, which are available in the domain of product design, to predict the knowledge requirement. The comprehensive analysis of the experimental results shows that the proposed method gains better performance in most of the parameter settings. This work contributes a probability-based method to the community for implement recommender system when only user ratings and item topics are available.

  9. Hybrid quantum-classical modeling of quantum dot devices

    Science.gov (United States)

    Kantner, Markus; Mittnenzweig, Markus; Koprucki, Thomas

    2017-11-01

    The design of electrically driven quantum dot devices for quantum optical applications asks for modeling approaches combining classical device physics with quantum mechanics. We connect the well-established fields of semiclassical semiconductor transport theory and the theory of open quantum systems to meet this requirement. By coupling the van Roosbroeck system with a quantum master equation in Lindblad form, we introduce a new hybrid quantum-classical modeling approach, which provides a comprehensive description of quantum dot devices on multiple scales: it enables the calculation of quantum optical figures of merit and the spatially resolved simulation of the current flow in realistic semiconductor device geometries in a unified way. We construct the interface between both theories in such a way, that the resulting hybrid system obeys the fundamental axioms of (non)equilibrium thermodynamics. We show that our approach guarantees the conservation of charge, consistency with the thermodynamic equilibrium and the second law of thermodynamics. The feasibility of the approach is demonstrated by numerical simulations of an electrically driven single-photon source based on a single quantum dot in the stationary and transient operation regime.

  10. Axelrod Model of Social Influence with Cultural Hybridization

    Science.gov (United States)

    Radillo-Díaz, Alejandro; Pérez, Luis A.; Del Castillo-Mussot, Marcelo

    2012-10-01

    Since cultural interactions between a pair of social agents involve changes in both individuals, we present simulations of a new model based on Axelrod's homogenization mechanism that includes hybridization or mixture of the agents' features. In this new hybridization model, once a cultural feature of a pair of agents has been chosen for the interaction, the average of the values for this feature is reassigned as the new value for both agents after interaction. Moreover, a parameter representing social tolerance is implemented in order to quantify whether agents are similar enough to engage in interaction, as well as to determine whether they belong to the same cluster of similar agents after the system has reached the frozen state. The transitions from a homogeneous state to a fragmented one decrease in abruptness as tolerance is increased. Additionally, the entropy associated to the system presents a maximum within the transition, the width of which increases as tolerance does. Moreover, a plateau was found inside the transition for a low-tolerance system of agents with only two cultural features.

  11. Modelling the solar wind interaction with Mercury by a quasi-neutral hybrid model

    Directory of Open Access Journals (Sweden)

    E. Kallio

    Full Text Available Quasi-neutral hybrid model is a self-consistent modelling approach that includes positively charged particles and an electron fluid. The approach has received an increasing interest in space plasma physics research because it makes it possible to study several plasma physical processes that are difficult or impossible to model by self-consistent fluid models, such as the effects associated with the ions’ finite gyroradius, the velocity difference between different ion species, or the non-Maxwellian velocity distribution function. By now quasi-neutral hybrid models have been used to study the solar wind interaction with the non-magnetised Solar System bodies of Mars, Venus, Titan and comets. Localized, two-dimensional hybrid model runs have also been made to study terrestrial dayside magnetosheath. However, the Hermean plasma environment has not yet been analysed by a global quasi-neutral hybrid model.

    In this paper we present a new quasi-neutral hybrid model developed to study various processes associated with the Mercury-solar wind interaction. Emphasis is placed on addressing advantages and disadvantages of the approach to study different plasma physical processes near the planet. The basic assumptions of the approach and the algorithms used in the new model are thoroughly presented. Finally, some of the first three-dimensional hybrid model runs made for Mercury are presented.

    The resulting macroscopic plasma parameters and the morphology of the magnetic field demonstrate the applicability of the new approach to study the Mercury-solar wind interaction globally. In addition, the real advantage of the kinetic hybrid model approach is to study the property of individual ions, and the study clearly demonstrates the large potential of the approach to address these more detailed issues by a quasi-neutral hybrid model in the future.

    Key words. Magnetospheric physics

  12. Geometric homology revisited

    OpenAIRE

    Ruffino, Fabio Ferrari

    2013-01-01

    Given a cohomology theory, there is a well-known abstract way to define the dual homology theory using the theory of spectra. In [4] the author provides a more geometric construction of the homology theory, using a generalization of the bordism groups. Such a generalization involves in its definition the vector bundle modification, which is a particular case of the Gysin map. In this paper we provide a more natural variant of that construction, which replaces the vector bundle modification wi...

  13. Electromagnetic moments of hadrons and quarks in a hybrid model

    International Nuclear Information System (INIS)

    Gerasimov, S.B.

    1989-01-01

    Magnetic moments of baryons are analyzed on the basis of general sum rules following from the theory of broken symmetries and quark models including the relativistic effects and hadronic corrections due to the meson exchange currents. A new sum rule is proposed for the hyperon magnetic moments, which is in accord with the most precise new data and also with a theory of the electromagnetic ΛΣ 0 mixing. The numerical values of the quark electromagnetic moments are obtained within a hybrid model treating the pion cloud effects through the local coupling of the pion field with the constituent massive quarks. Possible sensitivity of the weak neutral current magnetic moments to violation of the Okubo-Zweig-Izuki rule is emphasized nand discussed. 39 refs.; 1 fig

  14. A Hybrid Multiple Criteria Decision Making Model for Supplier Selection

    Directory of Open Access Journals (Sweden)

    Chung-Min Wu

    2013-01-01

    Full Text Available The sustainable supplier selection would be the vital part in the management of a sustainable supply chain. In this study, a hybrid multiple criteria decision making (MCDM model is applied to select optimal supplier. The fuzzy Delphi method, which can lead to better criteria selection, is used to modify criteria. Considering the interdependence among the selection criteria, analytic network process (ANP is then used to obtain their weights. To avoid calculation and additional pairwise comparisons of ANP, a technique for order preference by similarity to ideal solution (TOPSIS is used to rank the alternatives. The use of a combination of the fuzzy Delphi method, ANP, and TOPSIS, proposing an MCDM model for supplier selection, and applying these to a real case are the unique features of this study.

  15. Hybrid continuum-coarse-grained modeling of erythrocytes

    Science.gov (United States)

    Lyu, Jinming; Chen, Paul G.; Boedec, Gwenn; Leonetti, Marc; Jaeger, Marc

    2018-06-01

    The red blood cell (RBC) membrane is a composite structure, consisting of a phospholipid bilayer and an underlying membrane-associated cytoskeleton. Both continuum and particle-based coarse-grained RBC models make use of a set of vertices connected by edges to represent the RBC membrane, which can be seen as a triangular surface mesh for the former and a spring network for the latter. Here, we present a modeling approach combining an existing continuum vesicle model with a coarse-grained model for the cytoskeleton. Compared to other two-component approaches, our method relies on only one mesh, representing the cytoskeleton, whose velocity in the tangential direction of the membrane may be different from that of the lipid bilayer. The finitely extensible nonlinear elastic (FENE) spring force law in combination with a repulsive force defined as a power function (POW), called FENE-POW, is used to describe the elastic properties of the RBC membrane. The mechanical interaction between the lipid bilayer and the cytoskeleton is explicitly computed and incorporated into the vesicle model. Our model includes the fundamental mechanical properties of the RBC membrane, namely fluidity and bending rigidity of the lipid bilayer, and shear elasticity of the cytoskeleton while maintaining surface-area and volume conservation constraint. We present three simulation examples to demonstrate the effectiveness of this hybrid continuum-coarse-grained model for the study of RBCs in fluid flows.

  16. A hybrid absorbing boundary condition for frequency-domain finite-difference modelling

    International Nuclear Information System (INIS)

    Ren, Zhiming; Liu, Yang

    2013-01-01

    Liu and Sen (2010 Geophysics 75 A1–6; 2012 Geophys. Prospect. 60 1114–32) proposed an efficient hybrid scheme to significantly absorb boundary reflections for acoustic and elastic wave modelling in the time domain. In this paper, we extend the hybrid absorbing boundary condition (ABC) into the frequency domain and develop specific strategies for regular-grid and staggered-grid modelling, respectively. Numerical modelling tests of acoustic, visco-acoustic, elastic and vertically transversely isotropic (VTI) equations show significant absorptions for frequency-domain modelling. The modelling results of the Marmousi model and the salt model also demonstrate the effectiveness of the hybrid ABC. For elastic modelling, the hybrid Higdon ABC and the hybrid Clayton and Engquist (CE) ABC are implemented, respectively. Numerical simulations show that the hybrid Higdon ABC gets better absorption than the hybrid CE ABC, especially for S-waves. We further compare the hybrid ABC with the classical perfectly matched layer (PML). Results show that the two ABCs cost the same computation time and memory space for the same absorption width. However, the hybrid ABC is more effective than the PML for the same small absorption width and the absorption effects of the two ABCs gradually become similar when the absorption width is increased. (paper)

  17. A new approach to flow simulation using hybrid models

    Science.gov (United States)

    Solgi, Abazar; Zarei, Heidar; Nourani, Vahid; Bahmani, Ramin

    2017-11-01

    The necessity of flow prediction in rivers, for proper management of water resource, and the need for determining the inflow to the dam reservoir, designing efficient flood warning systems and so forth, have always led water researchers to think about models with high-speed response and low error. In the recent years, the development of Artificial Neural Networks and Wavelet theory and using the combination of models help researchers to estimate the river flow better and better. In this study, daily and monthly scales were used for simulating the flow of Gamasiyab River, Nahavand, Iran. The first simulation was done using two types of ANN and ANFIS models. Then, using wavelet theory and decomposing input signals of the used parameters, sub-signals were obtained and were fed into the ANN and ANFIS to obtain hybrid models of WANN and WANFIS. In this study, in addition to the parameters of precipitation and flow, parameters of temperature and evaporation were used to analyze their effects on the simulation. The results showed that using wavelet transform improved the performance of the models in both monthly and daily scale. However, it had a better effect on the monthly scale and the WANFIS was the best model.

  18. Modeling integrated cellular machinery using hybrid Petri-Boolean networks.

    Directory of Open Access Journals (Sweden)

    Natalie Berestovsky

    Full Text Available The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them

  19. Modeling and optimization of batteryless hybrid PV (photovoltaic)/Diesel systems for off-grid applications

    International Nuclear Information System (INIS)

    Tsuanyo, David; Azoumah, Yao; Aussel, Didier; Neveu, Pierre

    2015-01-01

    This paper presents a new model and optimization procedure for off-grid hybrid PV (photovoltaic)/Diesel systems operating without battery storage. The proposed technico-economic model takes into account the variability of both the solar irradiation and the electrical loads. It allows optimizing the design and the operation of the hybrid systems by searching their lowest LCOE (Levelized Cost of Electricity). Two cases have been investigated: identical Diesel generators and Diesel generators with different sizes, and both are compared to conventional standalone Diesel generator systems. For the same load profile, the optimization results show that the LCOE of the optimized batteryless hybrid solar PV/Diesel (0.289 €/kWh for the hybrid system with identical Diesel generators and 0.284 €/kWh for the hybrid system with different sizes of Diesel generators) is lower than the LCOE obtained with standalone Diesel generators (0.32 €/kWh for the both cases). The obtained results are then confirmed by HOMER (Hybrid Optimization Model for Electric Renewables) software. - Highlights: • A technico-economic model for optimal design and operation management of batteryless hybrid systems is developed. • The model allows optimizing design and operation of hybrid systems by ensuring their lowest LCOE. • The model was validated by HOMER. • Batteryless hybrid system are suitable for off-grid applications

  20. Modelling of hybrid energy system - Part I: Problem formulation and model development

    Energy Technology Data Exchange (ETDEWEB)

    Gupta, Ajai; Saini, R.P.; Sharma, M.P. [Alternate Hydro Energy Centre, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667 (India)

    2011-02-15

    A well designed hybrid energy system can be cost effective, has a high reliability and can improve the quality of life in remote rural areas. The economic constraints can be met, if these systems are fundamentally well designed, use appropriate technology and make use effective dispatch control techniques. The first paper of this tri-series paper, presents the analysis and design of a mixed integer linear mathematical programming model (time series) to determine the optimal operation and cost optimization for a hybrid energy generation system consisting of a photovoltaic array, biomass (fuelwood), biogas, small/micro-hydro, a battery bank and a fossil fuel generator. The optimization is aimed at minimizing the cost function based on demand and potential constraints. Further, mathematical models of all other components of hybrid energy system are also developed. This is the generation mix of the remote rural of India; it may be applied to other rural areas also. (author)

  1. Simulation of hybrid vehicle propulsion with an advanced battery model

    Energy Technology Data Exchange (ETDEWEB)

    Nallabolu, S.; Kostetzer, L.; Rudnyi, E. [CADFEM GmbH, Grafing (Germany); Geppert, M.; Quinger, D. [LION Smart GmbH, Frieding (Germany)

    2011-07-01

    In the recent years there has been observed an increasing concern about global warming and greenhouse gas emissions. In addition to the environmental issues the predicted scarcity of oil supplies and the dramatic increase in oil price puts new demands on vehicle design. As a result energy efficiency and reduced emission have become one of main selling point for automobiles. Hybrid electric vehicles (HEV) have therefore become an interesting technology for the governments and automotive industries. HEV are more complicated compared to conventional vehicles due to the fact that these vehicles contain more electrical components such as electric machines, power electronics, electronic continuously variable transmissions (CVT), and embedded powertrain controllers. Advanced energy storage devices and energy converters, such as Li-ion batteries, ultracapacitors, and fuel cells are also considered. A detailed vehicle model used for an energy flow analysis and vehicle performance simulation is necessary. Computer simulation is indispensible to facilitate the examination of the vast hybrid electric vehicle design space with the aim to predict the vehicle performance over driving profiles, estimate fuel consumption and the pollution emissions. There are various types of mathematical models and simulators available to perform system simulation of vehicle propulsion. One of the standard methods to model the complete vehicle powertrain is ''backward quasistatic modeling''. In this method vehicle subsystems are defined based on experiential models in the form of look-up tables and efficiency maps. The interaction between adjacent subsystems of the vehicle is defined through the amount of power flow. Modeling the vehicle subsystems like motor, engine, gearbox and battery is under this technique is based on block diagrams. The vehicle model is applied in two case studies to evaluate the vehicle performance and fuel consumption. In the first case study the affect

  2. Cloning, expression, and homology modeling of GroEL protein from Leptospira interrogans serovar autumnalis strain N2.

    Science.gov (United States)

    Natarajaseenivasan, Kalimuthusamy; Shanmughapriya, Santhanam; Velineni, Sridhar; Artiushin, Sergey C; Timoney, John F

    2011-10-01

    Leptospirosis is an infectious bacterial disease caused by Leptospira species. In this study, we cloned and sequenced the gene encoding the immunodominant protein GroEL from L. interrogans serovar Autumnalis strain N2, which was isolated from the urine of a patient during an outbreak of leptospirosis in Chennai, India. This groEL gene encodes a protein of 60 kDa with a high degree of homology (99% similarity) to those of other leptospiral serovars. Recombinant GroEL was overexpressed in Escherichia coli. Immunoblot analysis indicated that the sera from confirmed leptospirosis patients showed strong reactivity with the recombinant GroEL while no reactivity was observed with the sera from seronegative control patient. In addition, the 3D structure of GroEL was constructed using chaperonin complex cpn60 from Thermus thermophilus as template and validated. The results indicated a Z-score of -8.35, which is in good agreement with the expected value for a protein. The superposition of the Ca traces of cpn60 structure and predicted structure of leptospiral GroEL indicates good agreement of secondary structure elements with an RMSD value of 1.5 Å. Further study is necessary to evaluate GroEL for serological diagnosis of leptospirosis and for its potential as a vaccine component. Copyright © 2011 Beijing Genomics Institute. Published by Elsevier Ltd. All rights reserved.

  3. Recent developments on the UrQMD hybrid model

    Energy Technology Data Exchange (ETDEWEB)

    Steinheimer, J., E-mail: steinheimer@th.physik.uni-frankfurt.de; Nahrgang, M., E-mail: nahrgang@th.physik.uni-frankfurt.de; Gerhard, J., E-mail: jochen.gerhard@compeng.uni-frankfurt.de; Schramm, S., E-mail: schramm@fias.uni-frankfurt.de; Bleicher, M., E-mail: bleicher@fias.uni-frankfurt.de [Frankfurt Institute for Advanced Studies (FIAS) (Germany)

    2012-06-15

    We present recent results from the UrQMD hybrid approach investigating the influence of a deconfinement phase transition on the dynamics of hot and dense nuclear matter. In the hydrodynamic stage an equation of state that incorporates a critical end-point (CEP) in line with lattice data is used. The equation of state describes chiral restoration as well as the deconfinement phase transition. We compare the results from this new equation of state to results obtained by applying a hadron resonance gas equation of state, focusing on bulk observables. Furthermore we will discuss future improvements of the hydrodynamic model. This includes the formulation of chiral fluid dynamics to be able to study the effects of a chiral critical point as well as considerable improvements in terms of computational time which would open up possibilities for observables that require high statistics.

  4. Modeling of Hybrid Permanent Magnetic-Gas Bearings

    DEFF Research Database (Denmark)

    Morosi, Stefano; Santos, Ilmar

    2009-01-01

    Modern turbomachinery applications require nowadays ever-growing rotational speeds and high degree of reliability. It then becomes natural to focus the attention of the research to contact-free bearings elements. The present alternatives focus on gas lubricated journal bearings or magnetic bearings....... In the present paper, a detailed mathematical modeling of the gas bearing based on the compressible form of the Reynolds equation is presented. Perturbation theory is applied in order to identify the dynamic characteristic of the bearing. Due to the simple design of the magnetic bearings elements - being...... the rotor equilibrium position can be made independent on the rotational speed and applied load; it becomes function of the passive magnetic bearing offset. By adjusting the offset it is possible to significantly influence the dynamic coefficients of the hybrid bearing....

  5. Applying a Hybrid MCDM Model for Six Sigma Project Selection

    Directory of Open Access Journals (Sweden)

    Fu-Kwun Wang

    2014-01-01

    Full Text Available Six Sigma is a project-driven methodology; the projects that provide the maximum financial benefits and other impacts to the organization must be prioritized. Project selection (PS is a type of multiple criteria decision making (MCDM problem. In this study, we present a hybrid MCDM model combining the decision-making trial and evaluation laboratory (DEMATEL technique, analytic network process (ANP, and the VIKOR method to evaluate and improve Six Sigma projects for reducing performance gaps in each criterion and dimension. We consider the film printing industry of Taiwan as an empirical case. The results show that our study not only can use the best project selection, but can also be used to analyze the gaps between existing performance values and aspiration levels for improving the gaps in each dimension and criterion based on the influential network relation map.

  6. RF modeling of the ITER-relevant lower hybrid antenna

    International Nuclear Information System (INIS)

    Hillairet, J.; Ceccuzzi, S.; Belo, J.; Marfisi, L.; Artaud, J.F.; Bae, Y.S.; Berger-By, G.; Bernard, J.M.; Cara, Ph.; Cardinali, A.; Castaldo, C.; Cesario, R.; Decker, J.; Delpech, L.; Ekedahl, A.; Garcia, J.; Garibaldi, P.; Goniche, M.; Guilhem, D.; Hoang, G.T.

    2011-01-01

    In the frame of the EFDA task HCD-08-03-01, a 5 GHz Lower Hybrid system which should be able to deliver 20 MW CW on ITER and sustain the expected high heat fluxes has been reviewed. The design and overall dimensions of the key RF elements of the launcher and its subsystem has been updated from the 2001 design in collaboration with ITER organization. Modeling of the LH wave propagation and absorption into the plasma shows that the optimal parallel index must be chosen between 1.9 and 2.0 for the ITER steady-state scenario. The present study has been made with n || = 2.0 but can be adapted for n || = 1.9. Individual components have been studied separately giving confidence on the global RF design of the whole antenna.

  7. Modelling and Investigation of a Hybrid Thermal Energy Harvester

    Directory of Open Access Journals (Sweden)

    Todorov Todor

    2018-01-01

    Full Text Available The presented paper deals with dynamical and experimental investigations of a hybrid energy harvester containing shape memory alloy (SMA wire and elastic cantilever with piezoelectric layer. The SMA wire periodically changes its temperature under the influence of a heated plate that approaches and moves away from the SMA wire. The change of SMA wire length causes rotation of the hot plate. The plate is heated by a heater with constant temperature. The repeated SMA wire extensions and contractions bend the piezoelectric cantilever which generates electric charges. The shape memory effect is presented as a temperature approximation of the Young’s modulus. A dynamical model of the energy harvester is created and some analytical investigations are presented. With the help of an experimental setup the acceleration, the force, the temperature, and the output voltage have been measured. The theoretical results are validated experimentally. Some conclusions are made about the best performance of the energy harvester.

  8. Exploring the lambda model of the hybrid superstring

    Energy Technology Data Exchange (ETDEWEB)

    Schmidtt, David M. [Instituto de Física Teórica IFT/UNESP,Rua Dr. Bento Teobaldo Ferraz 271, Bloco II, CEP 01140-070, São Paulo-SP (Brazil)

    2016-10-26

    The purpose of this contribution is to initiate the study of integrable deformations for different superstring theory formalisms that manifest the property of (classical) integrability. In this paper we choose the hybrid formalism of the superstring in the background AdS{sub 2}×S{sup 2} and explore in detail the most immediate consequences of its λ-deformation. The resulting action functional corresponds to the λ-model of the matter part of the fairly more sophisticated pure spinor formalism, which is also known to be classical integrable. In particular, the deformation preserves the integrability and the one-loop conformal invariance of its parent theory, hence being a marginal deformation.

  9. Hybrid Reduced Order Modeling Algorithms for Reactor Physics Calculations

    Science.gov (United States)

    Bang, Youngsuk

    hybrid ROM algorithms which can be readily integrated into existing methods and offer higher computational efficiency and defendable accuracy of the reduced models. For example, the snapshots ROM algorithm is hybridized with the range finding algorithm to render reduction in the state space, e.g. the flux in reactor calculations. In another implementation, the perturbation theory used to calculate first order derivatives of responses with respect to parameters is hybridized with a forward sensitivity analysis approach to render reduction in the parameter space. Reduction at the state and parameter spaces can be combined to render further reduction at the interface between different physics codes in a multi-physics model with the accuracy quantified in a similar manner to the single physics case. Although the proposed algorithms are generic in nature, we focus here on radiation transport models used in support of the design and analysis of nuclear reactor cores. In particular, we focus on replacing the traditional assembly calculations by ROM models to facilitate the generation of homogenized cross-sections for downstream core calculations. The implication is that assembly calculations could be done instantaneously therefore precluding the need for the expensive evaluation of the few-group cross-sections for all possible core conditions. Given the generic natures of the algorithms, we make an effort to introduce the material in a general form to allow non-nuclear engineers to benefit from this work.

  10. Bounded Model Checking and Inductive Verification of Hybrid Discrete-Continuous Systems

    DEFF Research Database (Denmark)

    Becker, Bernd; Behle, Markus; Eisenbrand, Fritz

    2004-01-01

    We present a concept to signicantly advance the state of the art for bounded model checking (BMC) and inductive verication (IV) of hybrid discrete-continuous systems. Our approach combines the expertise of partners coming from dierent domains, like hybrid systems modeling and digital circuit veri...

  11. Pedagogy and Process: A Case Study of Writing in a Hybrid Learning Model

    Science.gov (United States)

    Keiner, Jason F.

    2017-01-01

    This qualitative case study explored the perceived experiences and outcomes of writing in a hybrid model of instruction in a large suburban high school. In particular, the impact of a hybrid model on the writing process and on future writing performance were examined. In addition, teacher expectation and teacher attitude and their impact upon…

  12. Control-relevant modeling and simulation of a SOFC-GT hybrid system

    Directory of Open Access Journals (Sweden)

    Rambabu Kandepu

    2006-07-01

    Full Text Available In this paper, control-relevant models of the most important components in a SOFC-GT hybrid system are described. Dynamic simulations are performed on the overall hybrid system. The model is used to develop a simple control structure, but the simulations show that more elaborate control is needed.

  13. Control-relevant modeling and simulation of a SOFC-GT hybrid system

    OpenAIRE

    Rambabu Kandepu; Lars Imsland; Christoph Stiller; Bjarne A. Foss; Vinay Kariwala

    2006-01-01

    In this paper, control-relevant models of the most important components in a SOFC-GT hybrid system are described. Dynamic simulations are performed on the overall hybrid system. The model is used to develop a simple control structure, but the simulations show that more elaborate control is needed.

  14. A hybrid multiview stereo algorithm for modeling urban scenes.

    Science.gov (United States)

    Lafarge, Florent; Keriven, Renaud; Brédif, Mathieu; Vu, Hoang-Hiep

    2013-01-01

    We present an original multiview stereo reconstruction algorithm which allows the 3D-modeling of urban scenes as a combination of meshes and geometric primitives. The method provides a compact model while preserving details: Irregular elements such as statues and ornaments are described by meshes, whereas regular structures such as columns and walls are described by primitives (planes, spheres, cylinders, cones, and tori). We adopt a two-step strategy consisting first in segmenting the initial meshbased surface using a multilabel Markov Random Field-based model and second in sampling primitive and mesh components simultaneously on the obtained partition by a Jump-Diffusion process. The quality of a reconstruction is measured by a multi-object energy model which takes into account both photo-consistency and semantic considerations (i.e., geometry and shape layout). The segmentation and sampling steps are embedded into an iterative refinement procedure which provides an increasingly accurate hybrid representation. Experimental results on complex urban structures and large scenes are presented and compared to state-of-the-art multiview stereo meshing algorithms.

  15. Status and modeling improvements of hybrid wind/PV/diesel power systems for Brazilian applications

    Energy Technology Data Exchange (ETDEWEB)

    McGowan, J.G.; Manwell, J.F.; Avelar, C. [Univ. of Massachusetts, Amherst, MA (United States); Taylor, R. [National Renewable Energy Lab., Golden, CO (United States)

    1997-12-31

    This paper present a summary of the ongoing work on the modeling and system design of hybrid wind/PV/diesel systems for two different sites in the Amazonia region of Brazil. The work incorporates the latest resource data and is based on the use of the Hybrid2 simulation code developed by the University of Massachusetts and NREL. Details of the baseline operating hybrid systems are reviewed, and the results of the latest detailed hybrid system evaluation for each site are summarized. Based on the system modeling results, separate recommendations for system modification and improvements are made.

  16. Structural modelling and comparative analysis of homologous, analogous and specific proteins from Trypanosoma cruzi versus Homo sapiens: putative drug targets for chagas' disease treatment.

    Science.gov (United States)

    Capriles, Priscila V S Z; Guimarães, Ana C R; Otto, Thomas D; Miranda, Antonio B; Dardenne, Laurent E; Degrave, Wim M

    2010-10-29

    Trypanosoma cruzi is the etiological agent of Chagas' disease, an endemic infection that causes thousands of deaths every year in Latin America. Therapeutic options remain inefficient, demanding the search for new drugs and/or new molecular targets. Such efforts can focus on proteins that are specific to the parasite, but analogous enzymes and enzymes with a three-dimensional (3D) structure sufficiently different from the corresponding host proteins may represent equally interesting targets. In order to find these targets we used the workflows MHOLline and AnEnΠ obtaining 3D models from homologous, analogous and specific proteins of Trypanosoma cruzi versus Homo sapiens. We applied genome wide comparative modelling techniques to obtain 3D models for 3,286 predicted proteins of T. cruzi. In combination with comparative genome analysis to Homo sapiens, we were able to identify a subset of 397 enzyme sequences, of which 356 are homologous, 3 analogous and 38 specific to the parasite. In this work, we present a set of 397 enzyme models of T. cruzi that can constitute potential structure-based drug targets to be investigated for the development of new strategies to fight Chagas' disease. The strategies presented here support the concept of structural analysis in conjunction with protein functional analysis as an interesting computational methodology to detect potential targets for structure-based rational drug design. For example, 2,4-dienoyl-CoA reductase (EC 1.3.1.34) and triacylglycerol lipase (EC 3.1.1.3), classified as analogous proteins in relation to H. sapiens enzymes, were identified as new potential molecular targets.

  17. Multi-level and hybrid modelling approaches for systems biology.

    Science.gov (United States)

    Bardini, R; Politano, G; Benso, A; Di Carlo, S

    2017-01-01

    During the last decades, high-throughput techniques allowed for the extraction of a huge amount of data from biological systems, unveiling more of their underling complexity. Biological systems encompass a wide range of space and time scales, functioning according to flexible hierarchies of mechanisms making an intertwined and dynamic interplay of regulations. This becomes particularly evident in processes such as ontogenesis, where regulative assets change according to process context and timing, making structural phenotype and architectural complexities emerge from a single cell, through local interactions. The information collected from biological systems are naturally organized according to the functional levels composing the system itself. In systems biology, biological information often comes from overlapping but different scientific domains, each one having its own way of representing phenomena under study. That is, the different parts of the system to be modelled may be described with different formalisms. For a model to have improved accuracy and capability for making a good knowledge base, it is good to comprise different system levels, suitably handling the relative formalisms. Models which are both multi-level and hybrid satisfy both these requirements, making a very useful tool in computational systems biology. This paper reviews some of the main contributions in this field.

  18. Mobile phone use while driving: a hybrid modeling approach.

    Science.gov (United States)

    Márquez, Luis; Cantillo, Víctor; Arellana, Julián

    2015-05-01

    The analysis of the effects that mobile phone use produces while driving is a topic of great interest for the scientific community. There is consensus that using a mobile phone while driving increases the risk of exposure to traffic accidents. The purpose of this research is to evaluate the drivers' behavior when they decide whether or not to use a mobile phone while driving. For that, a hybrid modeling approach that integrates a choice model with the latent variable "risk perception" was used. It was found that workers and individuals with the highest education level are more prone to use a mobile phone while driving than others. Also, "risk perception" is higher among individuals who have been previously fined and people who have been in an accident or almost been in an accident. It was also found that the tendency to use mobile phones while driving increases when the traffic speed reduces, but it decreases when the fine increases. Even though the urgency of the phone call is the most important explanatory variable in the choice model, the cost of the fine is an important attribute in order to control mobile phone use while driving. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. Kalman Filtered Bio Heat Transfer Model Based Self-adaptive Hybrid Magnetic Resonance Thermometry.

    Science.gov (United States)

    Zhang, Yuxin; Chen, Shuo; Deng, Kexin; Chen, Bingyao; Wei, Xing; Yang, Jiafei; Wang, Shi; Ying, Kui

    2017-01-01

    To develop a self-adaptive and fast thermometry method by combining the original hybrid magnetic resonance thermometry method and the bio heat transfer equation (BHTE) model. The proposed Kalman filtered Bio Heat Transfer Model Based Self-adaptive Hybrid Magnetic Resonance Thermometry, abbreviated as KalBHT hybrid method, introduced the BHTE model to synthesize a window on the regularization term of the hybrid algorithm, which leads to a self-adaptive regularization both spatially and temporally with change of temperature. Further, to decrease the sensitivity to accuracy of the BHTE model, Kalman filter is utilized to update the window at each iteration time. To investigate the effect of the proposed model, computer heating simulation, phantom microwave heating experiment and dynamic in-vivo model validation of liver and thoracic tumor were conducted in this study. The heating simulation indicates that the KalBHT hybrid algorithm achieves more accurate results without adjusting λ to a proper value in comparison to the hybrid algorithm. The results of the phantom heating experiment illustrate that the proposed model is able to follow temperature changes in the presence of motion and the temperature estimated also shows less noise in the background and surrounding the hot spot. The dynamic in-vivo model validation with heating simulation demonstrates that the proposed model has a higher convergence rate, more robustness to susceptibility problem surrounding the hot spot and more accuracy of temperature estimation. In the healthy liver experiment with heating simulation, the RMSE of the hot spot of the proposed model is reduced to about 50% compared to the RMSE of the original hybrid model and the convergence time becomes only about one fifth of the hybrid model. The proposed model is able to improve the accuracy of the original hybrid algorithm and accelerate the convergence rate of MR temperature estimation.

  20. Discovery of novel inhibitors of Mycobacterium tuberculosis MurG: homology modelling, structure based pharmacophore, molecular docking, and molecular dynamics simulations.

    Science.gov (United States)

    Saxena, Shalini; Abdullah, Maaged; Sriram, Dharmarajan; Guruprasad, Lalitha

    2017-10-17

    MurG (Rv2153c) is a key player in the biosynthesis of the peptidoglycan layer in Mycobacterium tuberculosis (Mtb). This work is an attempt to highlight the structural and functional relationship of Mtb MurG, the three-dimensional (3D) structure of protein was constructed by homology modelling using Discovery Studio 3.5 software. The quality and consistency of generated model was assessed by PROCHECK, ProSA and ERRAT. Later, the model was optimized by molecular dynamics (MD) simulations and the optimized model complex with substrate Uridine-diphosphate-N-acetylglucosamine (UD1) facilitated us to employ structure-based virtual screening approach to obtain new hits from Asinex database using energy-optimized pharmacophore modelling (e-pharmacophore). The pharmacophore model was validated using enrichment calculations, and finally, validated model was employed for high-throughput virtual screening and molecular docking to identify novel Mtb MurG inhibitors. This study led to the identification of 10 potential compounds with good fitness, docking score, which make important interactions with the protein active site. The 25 ns MD simulations of three potential lead compounds with protein confirmed that the structure was stable and make several non-bonding interactions with amino acids, such as Leu290, Met310 and Asn167. Hence, we concluded that the identified compounds may act as new leads for the design of Mtb MurG inhibitors.

  1. Modeling, hybridization, and optimal charging of electrical energy storage systems

    Science.gov (United States)

    Parvini, Yasha

    The rising rate of global energy demand alongside the dwindling fossil fuel resources has motivated research for alternative and sustainable solutions. Within this area of research, electrical energy storage systems are pivotal in applications including electrified vehicles, renewable power generation, and electronic devices. The approach of this dissertation is to elucidate the bottlenecks of integrating supercapacitors and batteries in energy systems and propose solutions by the means of modeling, control, and experimental techniques. In the first step, the supercapacitor cell is modeled in order to gain fundamental understanding of its electrical and thermal dynamics. The dependence of electrical parameters on state of charge (SOC), current direction and magnitude (20-200 A), and temperatures ranging from -40°C to 60°C was embedded in this computationally efficient model. The coupled electro-thermal model was parameterized using specifically designed temporal experiments and then validated by the application of real world duty cycles. Driving range is one of the major challenges of electric vehicles compared to combustion vehicles. In order to shed light on the benefits of hybridizing a lead-acid driven electric vehicle via supercapacitors, a model was parameterized for the lead-acid battery and combined with the model already developed for the supercapacitor, to build the hybrid battery-supercapacitor model. A hardware in the loop (HIL) setup consisting of a custom built DC/DC converter, micro-controller (muC) to implement the power management strategy, 12V lead-acid battery, and a 16.2V supercapacitor module was built to perform the validation experiments. Charging electrical energy storage systems in an efficient and quick manner, motivated to solve an optimal control problem with the objective of maximizing the charging efficiency for supercapacitors, lead-acid, and lithium ion batteries. Pontryagins minimum principle was used to solve the problems

  2. Validation of a homology model of Mycobacterium tuberculosis DXS: rationalization of observed activities of thiamine derivatives as potent inhibitors of two orthologues of DXS.

    Science.gov (United States)

    Masini, T; Lacy, B; Monjas, L; Hawksley, D; de Voogd, A R; Illarionov, B; Iqbal, A; Leeper, F J; Fischer, M; Kontoyianni, M; Hirsch, A K H

    2015-12-14

    The enzyme DXS catalyzes the first, rate-limiting step of the 2-C-methyl-d-erythritol-4-phosphate (MEP, 1) pathway using thiamine diphosphate (ThDP) as cofactor; the DXS-catalyzed reaction constitutes also the first step in vitamin B1 and B6 metabolism in bacteria. DXS is the least studied among the enzymes of this pathway in terms of crystallographic information, with only one complete crystal structure deposited in the Protein Data Bank (Deinococcus radiodurans DXS, PDB: ). We synthesized a series of thiamine and ThDP derivatives and tested them for their biochemical activity against two DXS orthologues, namely D. radiodurans DXS and Mycobacterium tuberculosis DXS. These experimental results, combined with advanced docking studies, led to the development and validation of a homology model of M. tuberculosis DXS, which, in turn, will guide medicinal chemists in rationally designing potential inhibitors for M. tuberculosis DXS.

  3. Dynamic Model of Islamic Hybrid Securities: Empirical Evidence From Malaysia Islamic Capital Market

    Directory of Open Access Journals (Sweden)

    Jaafar Pyeman

    2016-12-01

    Full Text Available Capital structure selection is fundamentally important in corporate financial management as it influence on mutually return and risk to stakeholders. Despite of Malaysia’s position as one of the major players of Islamic Financial Market, there are still lack of studies has been conducted on the capital structure of shariah compliant firms especially related to hybrid securities. The objective of this study is to determine the hybrid securities issuance model among the shariah compliant firms in Malaysia. As such, this study is to expand the literature review by providing comprehensive analysis on the hybrid capital structure and to develop dynamic Islamic hybrid securities model for shariah compliant firms. We use panel data of 50 companies that have been issuing the hybrid securities from the year of 2004- 2012. The outcomes of the studies are based on the dynamic model GMM estimation for the determinants of hybrid securities. Based on our model, risk and growth are considered as the most determinant factors for issuing convertible bond and loan stock. These results suggest that, the firms that have high risk but having good growth prospect will choose hybrid securities of convertible bond. The model also support the backdoor equity listing hypothesis by Stein (1992 where the hybrid securities enable the profitable firms to venture into positive NPV project by issuing convertible bond as it offer lower coupon rate as compare to the normal debt rate

  4. Development of hybrid 3-D hydrological modeling for the NCAR Community Earth System Model (CESM)

    Energy Technology Data Exchange (ETDEWEB)

    Zeng, Xubin [Univ. of Arizona, Tucson, AZ (United States); Troch, Peter [Univ. of Arizona, Tucson, AZ (United States); Pelletier, Jon [Univ. of Arizona, Tucson, AZ (United States); Niu, Guo-Yue [Univ. of Arizona, Tucson, AZ (United States); Gochis, David [NCAR Research Applications Lab., Boulder, CO (United States)

    2015-11-15

    This is the Final Report of our four-year (3-year plus one-year no cost extension) collaborative project between the University of Arizona (UA) and the National Center for Atmospheric Research (NCAR). The overall objective of our project is to develop and evaluate the first hybrid 3-D hydrological model with a horizontal grid spacing of 1 km for the NCAR Community Earth System Model (CESM).

  5. A hybrid simulation model for a stable auroral arc

    Directory of Open Access Journals (Sweden)

    P. Janhunen

    Full Text Available We present a new type of hybrid simulation model, intended to simulate a single stable auroral arc in the latitude/altitude plane. The ionospheric ions are treated as particles, the electrons are assumed to follow a Boltzmann response and the magnetospheric ions are assumed to be so hot that they form a background population unaffected by the electric fields that arise. The system is driven by assumed parallel electron energisation causing a primary negative charge cloud and an associated potential structure to build up. The results show how a closed potential structure and density depletion of an auroral arc build up and how they decay after the driver is turned off. The model also produces upgoing energetic ion beams and predicts strong static perpendicular electric fields to be found in a relatively narrow altitude range (~ 5000–11 000 km.

    Key words. Magnetospheric physics (magnetosphere-ionosphere interactions; auroral phenomena – Space plasma physics (numerical simulation studies

  6. Hybrid CMS methods with model reduction for assembly of structures

    Science.gov (United States)

    Farhat, Charbel

    1991-01-01

    Future on-orbit structures will be designed and built in several stages, each with specific control requirements. Therefore there must be a methodology which can predict the dynamic characteristics of the assembled structure, based on the dynamic characteristics of the subassemblies and their interfaces. The methodology developed by CSC to address this issue is Hybrid Component Mode Synthesis (HCMS). HCMS distinguishes itself from standard component mode synthesis algorithms in the following features: (1) it does not require the subcomponents to have displacement compatible models, which makes it ideal for analyzing the deployment of heterogeneous flexible multibody systems, (2) it incorporates a second-level model reduction scheme at the interface, which makes it much faster than other algorithms and therefore suitable for control purposes, and (3) it does answer specific questions such as 'how does the global fundamental frequency vary if I change the physical parameters of substructure k by a specified amount?'. Because it is based on an energy principle rather than displacement compatibility, this methodology can also help the designer to define an assembly process. Current and future efforts are devoted to applying the HCMS method to design and analyze docking and berthing procedures in orbital construction.

  7. A Hybrid Fuzzy Model for Lean Product Development Performance Measurement

    Science.gov (United States)

    Osezua Aikhuele, Daniel; Mohd Turan, Faiz

    2016-02-01

    In the effort for manufacturing companies to meet up with the emerging consumer demands for mass customized products, many are turning to the application of lean in their product development process, and this is gradually moving from being a competitive advantage to a necessity. However, due to lack of clear understanding of the lean performance measurements, many of these companies are unable to implement and fully integrated the lean principle into their product development process. Extensive literature shows that only few studies have focus systematically on the lean product development performance (LPDP) evaluation. In order to fill this gap, the study therefore proposed a novel hybrid model based on Fuzzy Reasoning Approach (FRA), and the extension of Fuzzy-AHP and Fuzzy-TOPSIS methods for the assessment of the LPDP. Unlike the existing methods, the model considers the importance weight of each of the decision makers (Experts) since the performance criteria/attributes are required to be rated, and these experts have different level of expertise. The rating is done using a new fuzzy Likert rating scale (membership-scale) which is designed such that it can address problems resulting from information lost/distortion due to closed-form scaling and the ordinal nature of the existing Likert scale.

  8. An SVM model with hybrid kernels for hydrological time series

    Science.gov (United States)

    Wang, C.; Wang, H.; Zhao, X.; Xie, Q.

    2017-12-01

    Support Vector Machine (SVM) models have been widely applied to the forecast of climate/weather and its impact on other environmental variables such as hydrologic response to climate/weather. When using SVM, the choice of the kernel function plays the key role. Conventional SVM models mostly use one single type of kernel function, e.g., radial basis kernel function. Provided that there are several featured kernel functions available, each having its own advantages and drawbacks, a combination of these kernel functions may give more flexibility and robustness to SVM approach, making it suitable for a wide range of application scenarios. This paper presents such a linear combination of radial basis kernel and polynomial kernel for the forecast of monthly flowrate in two gaging stations using SVM approach. The results indicate significant improvement in the accuracy of predicted series compared to the approach with either individual kernel function, thus demonstrating the feasibility and advantages of such hybrid kernel approach for SVM applications.

  9. A hybrid model of primary radiation damage in crystals

    International Nuclear Information System (INIS)

    Samarin, S.I.; Dremov, V.V.

    2009-01-01

    The paper offers a hybrid model which combines molecular dynamics and Monte Carlo (MD+MC) methods to describe primary radiation damage in crystals, caused by particles whose energies are no higher than several tens of keV. The particles are tracked in accord with equations of motion with account for pair interaction. The model also considers particle interaction with the mean-field potential (MFP) of the crystal. Only particles involved in cascading are tracked. Equations of motion for these particles include dissipative forces which describe energy exchange between cascade particles and electrons. New particles - the atoms of the crystal in the cascade region - have stochastic parameters (phase coordinates); they are sampled by the Monte Carlo method from the distribution that describes the classic canonical ensemble of non-interacting particles subjected to the external MFP. The introduction of particle interaction with the MFP helps avoid difficulties related to crystal stability and the choice of an adequate interparticle interaction potential in the traditional MD methods. Our technique is many times as fast as the traditional MD methods because we consider only particles which are involved in cascading and apply special methods to speedup the calculation of forces by accounting for the short-range pair potential used

  10. Hybrid network defense model based on fuzzy evaluation.

    Science.gov (United States)

    Cho, Ying-Chiang; Pan, Jen-Yi

    2014-01-01

    With sustained and rapid developments in the field of information technology, the issue of network security has become increasingly prominent. The theme of this study is network data security, with the test subject being a classified and sensitive network laboratory that belongs to the academic network. The analysis is based on the deficiencies and potential risks of the network's existing defense technology, characteristics of cyber attacks, and network security technologies. Subsequently, a distributed network security architecture using the technology of an intrusion prevention system is designed and implemented. In this paper, first, the overall design approach is presented. This design is used as the basis to establish a network defense model, an improvement over the traditional single-technology model that addresses the latter's inadequacies. Next, a distributed network security architecture is implemented, comprising a hybrid firewall, intrusion detection, virtual honeynet projects, and connectivity and interactivity between these three components. Finally, the proposed security system is tested. A statistical analysis of the test results verifies the feasibility and reliability of the proposed architecture. The findings of this study will potentially provide new ideas and stimuli for future designs of network security architecture.

  11. Hybrid Simulation Modeling to Estimate U.S. Energy Elasticities

    Science.gov (United States)

    Baylin-Stern, Adam C.

    This paper demonstrates how an U.S. application of CIMS, a technologically explicit and behaviourally realistic energy-economy simulation model which includes macro-economic feedbacks, can be used to derive estimates of elasticity of substitution (ESUB) and autonomous energy efficiency index (AEEI) parameters. The ability of economies to reduce greenhouse gas emissions depends on the potential for households and industry to decrease overall energy usage, and move from higher to lower emissions fuels. Energy economists commonly refer to ESUB estimates to understand the degree of responsiveness of various sectors of an economy, and use estimates to inform computable general equilibrium models used to study climate policies. Using CIMS, I have generated a set of future, 'pseudo-data' based on a series of simulations in which I vary energy and capital input prices over a wide range. I then used this data set to estimate the parameters for transcendental logarithmic production functions using regression techniques. From the production function parameter estimates, I calculated an array of elasticity of substitution values between input pairs. Additionally, this paper demonstrates how CIMS can be used to calculate price-independent changes in energy-efficiency in the form of the AEEI, by comparing energy consumption between technologically frozen and 'business as usual' simulations. The paper concludes with some ideas for model and methodological improvement, and how these might figure into future work in the estimation of ESUBs from CIMS. Keywords: Elasticity of substitution; hybrid energy-economy model; translog; autonomous energy efficiency index; rebound effect; fuel switching.

  12. Three hybridization models based on local search scheme for job shop scheduling problem

    Science.gov (United States)

    Balbi Fraga, Tatiana

    2015-05-01

    This work presents three different hybridization models based on the general schema of Local Search Heuristics, named Hybrid Successive Application, Hybrid Neighborhood, and Hybrid Improved Neighborhood. Despite similar approaches might have already been presented in the literature in other contexts, in this work these models are applied to analyzes the solution of the job shop scheduling problem, with the heuristics Taboo Search and Particle Swarm Optimization. Besides, we investigate some aspects that must be considered in order to achieve better solutions than those obtained by the original heuristics. The results demonstrate that the algorithms derived from these three hybrid models are more robust than the original algorithms and able to get better results than those found by the single Taboo Search.

  13. Modeling and design of a high-performance hybrid actuator

    Science.gov (United States)

    Aloufi, Badr; Behdinan, Kamran; Zu, Jean

    2016-12-01

    This paper presents the model and design of a novel hybrid piezoelectric actuator which provides high active and passive performances for smart structural systems. The actuator is composed of a pair of curved pre-stressed piezoelectric actuators, so-called commercially THUNDER actuators, installed opposite each other using two clamping mechanisms constructed of in-plane fixable hinges, grippers and solid links. A fully mathematical model is developed to describe the active and passive dynamics of the actuator and investigate the effects of its geometrical parameters on the dynamic stiffness, free displacement and blocked force properties. Among the literature that deals with piezoelectric actuators in which THUNDER elements are used as a source of electromechanical power, the proposed study is unique in that it presents a mathematical model that has the ability to predict the actuator characteristics and achieve other phenomena, such as resonances, mode shapes, phase shifts, dips, etc. For model validation, the measurements of the free dynamic response per unit voltage and passive acceleration transmissibility of a particular actuator design are used to check the accuracy of the results predicted by the model. The results reveal that there is a good agreement between the model and experiment. Another experiment is performed to teste the linearity of the actuator system by examining the variation of the output dynamic responses with varying forces and voltages at different frequencies. From the results, it can be concluded that the actuator acts approximately as a linear system at frequencies up to 1000 Hz. A parametric study is achieved here by applying the developed model to analyze the influence of the geometrical parameters of the fixable hinges on the active and passive actuator properties. The model predictions in the frequency range of 0-1000 Hz show that the hinge thickness, radius, and opening angle parameters have great effects on the frequency dynamic

  14. Hybrid model for forecasting time series with trend, seasonal and salendar variation patterns

    Science.gov (United States)

    Suhartono; Rahayu, S. P.; Prastyo, D. D.; Wijayanti, D. G. P.; Juliyanto

    2017-09-01

    Most of the monthly time series data in economics and business in Indonesia and other Moslem countries not only contain trend and seasonal, but also affected by two types of calendar variation effects, i.e. the effect of the number of working days or trading and holiday effects. The purpose of this research is to develop a hybrid model or a combination of several forecasting models to predict time series that contain trend, seasonal and calendar variation patterns. This hybrid model is a combination of classical models (namely time series regression and ARIMA model) and/or modern methods (artificial intelligence method, i.e. Artificial Neural Networks). A simulation study was used to show that the proposed procedure for building the hybrid model could work well for forecasting time series with trend, seasonal and calendar variation patterns. Furthermore, the proposed hybrid model is applied for forecasting real data, i.e. monthly data about inflow and outflow of currency at Bank Indonesia. The results show that the hybrid model tend to provide more accurate forecasts than individual forecasting models. Moreover, this result is also in line with the third results of the M3 competition, i.e. the hybrid model on average provides a more accurate forecast than the individual model.

  15. Rapid isolation of gene homologs across taxa: Efficient identification and isolation of gene orthologs from non-model organism genomes, a technical report

    Directory of Open Access Journals (Sweden)

    Heffer Alison

    2011-03-01

    Full Text Available Abstract Background Tremendous progress has been made in the field of evo-devo through comparisons of related genes from diverse taxa. While the vast number of species in nature precludes a complete analysis of the molecular evolution of even one single gene family, this would not be necessary to understand fundamental mechanisms underlying gene evolution if experiments could be designed to systematically sample representative points along the path of established phylogenies to trace changes in regulatory and coding gene sequence. This isolation of homologous genes from phylogenetically diverse, representative species can be challenging, especially if the gene is under weak selective pressure and evolving rapidly. Results Here we present an approach - Rapid Isolation of Gene Homologs across Taxa (RIGHT - to efficiently isolate specific members of gene families. RIGHT is based upon modification and a combination of degenerate polymerase chain reaction (PCR and gene-specific amplified fragment length polymorphism (AFLP. It allows targeted isolation of specific gene family members from any organism, only requiring genomic DNA. We describe this approach and how we used it to isolate members of several different gene families from diverse arthropods spanning millions of years of evolution. Conclusions RIGHT facilitates systematic isolation of one gene from large gene families. It allows for efficient gene isolation without whole genome sequencing, RNA extraction, or culturing of non-model organisms. RIGHT will be a generally useful method for isolation of orthologs from both distant and closely related species, increasing sample size and facilitating the tracking of molecular evolution of gene families and regulatory networks across the tree of life.

  16. Concept analysis of moral courage in nursing: A hybrid model.

    Science.gov (United States)

    Sadooghiasl, Afsaneh; Parvizy, Soroor; Ebadi, Abbas

    2018-02-01

    Moral courage is one of the most fundamental virtues in the nursing profession, however, little attention has been paid to it. As a result, no exact and clear definition of moral courage has ever been accessible. This study is carried out for the purposes of defining and clarifying its concept in the nursing profession. This study used a hybrid model of concept analysis comprising three phases, namely, a theoretical phase, field work phase, and a final analysis phase. To find relevant literature, electronic search of valid databases was utilized using keywords related to the concept of courage. Field work data were collected over an 11 months' time period from 2013 to 2014. In the field work phase, in-depth interviews were performed with 10 nurses. The conventional content analysis was used in two theoretical and field work phases using Graneheim and Lundman stages, and the results were combined in the final analysis phase. Ethical consideration: Permission for this study was obtained from the ethics committee of Tehran University of Medical Sciences. Oral and written informed consent was received from the participants. From the sum of 750 gained titles in theoretical phase, 26 texts were analyzed. The analysis resulted in 494 codes in text analysis and 226 codes in interview analysis. The literature review in the theoretical phase revealed two features of inherent-transcendental characteristics, two of which possessed a difficult nature. Working in the field phase added moral self-actualization characteristic, rationalism, spiritual beliefs, and scientific-professional qualifications to the feature of the concept. Moral courage is a pure and prominent characteristic of human beings. The antecedents of moral courage include model orientation, model acceptance, rationalism, individual excellence, acquiring academic and professional qualification, spiritual beliefs, organizational support, organizational repression, and internal and external personal barriers

  17. Modeling, control, and simulation of grid connected intelligent hybrid battery/photovoltaic system using new hybrid fuzzy-neural method.

    Science.gov (United States)

    Rezvani, Alireza; Khalili, Abbas; Mazareie, Alireza; Gandomkar, Majid

    2016-07-01

    Nowadays, photovoltaic (PV) generation is growing increasingly fast as a renewable energy source. Nevertheless, the drawback of the PV system is its dependence on weather conditions. Therefore, battery energy storage (BES) can be considered to assist for a stable and reliable output from PV generation system for loads and improve the dynamic performance of the whole generation system in grid connected mode. In this paper, a novel topology of intelligent hybrid generation systems with PV and BES in a DC-coupled structure is presented. Each photovoltaic cell has a specific point named maximum power point on its operational curve (i.e. current-voltage or power-voltage curve) in which it can generate maximum power. Irradiance and temperature changes affect these operational curves. Therefore, the nonlinear characteristic of maximum power point to environment has caused to development of different maximum power point tracking techniques. In order to capture the maximum power point (MPP), a hybrid fuzzy-neural maximum power point tracking (MPPT) method is applied in the PV system. Obtained results represent the effectiveness and superiority of the proposed method, and the average tracking efficiency of the hybrid fuzzy-neural is incremented by approximately two percentage points in comparison to the conventional methods. It has the advantages of robustness, fast response and good performance. A detailed mathematical model and a control approach of a three-phase grid-connected intelligent hybrid system have been proposed using Matlab/Simulink. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  18. Daily air quality index forecasting with hybrid models: A case in China

    International Nuclear Information System (INIS)

    Zhu, Suling; Lian, Xiuyuan; Liu, Haixia; Hu, Jianming; Wang, Yuanyuan; Che, Jinxing

    2017-01-01

    Air quality is closely related to quality of life. Air pollution forecasting plays a vital role in air pollution warnings and controlling. However, it is difficult to attain accurate forecasts for air pollution indexes because the original data are non-stationary and chaotic. The existing forecasting methods, such as multiple linear models, autoregressive integrated moving average (ARIMA) and support vector regression (SVR), cannot fully capture the information from series of pollution indexes. Therefore, new effective techniques need to be proposed to forecast air pollution indexes. The main purpose of this research is to develop effective forecasting models for regional air quality indexes (AQI) to address the problems above and enhance forecasting accuracy. Therefore, two hybrid models (EMD-SVR-Hybrid and EMD-IMFs-Hybrid) are proposed to forecast AQI data. The main steps of the EMD-SVR-Hybrid model are as follows: the data preprocessing technique EMD (empirical mode decomposition) is utilized to sift the original AQI data to obtain one group of smoother IMFs (intrinsic mode functions) and a noise series, where the IMFs contain the important information (level, fluctuations and others) from the original AQI series. LS-SVR is applied to forecast the sum of the IMFs, and then, S-ARIMA (seasonal ARIMA) is employed to forecast the residual sequence of LS-SVR. In addition, EMD-IMFs-Hybrid first separately forecasts the IMFs via statistical models and sums the forecasting results of the IMFs as EMD-IMFs. Then, S-ARIMA is employed to forecast the residuals of EMD-IMFs. To certify the proposed hybrid model, AQI data from June 2014 to August 2015 collected from Xingtai in China are utilized as a test case to investigate the empirical research. In terms of some of the forecasting assessment measures, the AQI forecasting results of Xingtai show that the two proposed hybrid models are superior to ARIMA, SVR, GRNN, EMD-GRNN, Wavelet-GRNN and Wavelet-SVR. Therefore, the

  19. Develop a Hybrid Coordinate Ocean Model with Data Assimilation Capabilities

    National Research Council Canada - National Science Library

    Thacker, W. C

    2003-01-01

    .... The objectives of the research are as follows: (1) to develop a methodology for assimilating temperature and salinity profiles from XBT, CTD, and ARGO float data that accommodates the peculiarities of HYCOM's hybrid vertical coordinates, allowing...

  20. A Hybrid Physical and Maximum-Entropy Landslide Susceptibility Model

    Directory of Open Access Journals (Sweden)

    Jerry Davis

    2015-06-01

    Full Text Available The clear need for accurate landslide susceptibility mapping has led to multiple approaches. Physical models are easily interpreted and have high predictive capabilities but rely on spatially explicit and accurate parameterization, which is commonly not possible. Statistical methods can include other factors influencing slope stability such as distance to roads, but rely on good landslide inventories. The maximum entropy (MaxEnt model has been widely and successfully used in species distribution mapping, because data on absence are often uncertain. Similarly, knowledge about the absence of landslides is often limited due to mapping scale or methodology. In this paper a hybrid approach is described that combines the physically-based landslide susceptibility model “Stability INdex MAPping” (SINMAP with MaxEnt. This method is tested in a coastal watershed in Pacifica, CA, USA, with a well-documented landslide history including 3 inventories of 154 scars on 1941 imagery, 142 in 1975, and 253 in 1983. Results indicate that SINMAP alone overestimated susceptibility due to insufficient data on root cohesion. Models were compared using SINMAP stability index (SI or slope alone, and SI or slope in combination with other environmental factors: curvature, a 50-m trail buffer, vegetation, and geology. For 1941 and 1975, using slope alone was similar to using SI alone; however in 1983 SI alone creates an Areas Under the receiver operator Curve (AUC of 0.785, compared with 0.749 for slope alone. In maximum-entropy models created using all environmental factors, the stability index (SI from SINMAP represented the greatest contributions in all three years (1941: 48.1%; 1975: 35.3; and 1983: 48%, with AUC of 0.795, 0822, and 0.859, respectively; however; using slope instead of SI created similar overall AUC values, likely due to the combined effect with plan curvature indicating focused hydrologic inputs and vegetation identifying the effect of root cohesion

  1. Dynamic Modeling and Simulation on a Hybrid Power System for Electric Vehicle Applications

    Directory of Open Access Journals (Sweden)

    Hong-Wen He

    2010-11-01

    Full Text Available Hybrid power systems, formed by combining high-energy-density batteries and high-power-density ultracapacitors in appropriate ways, provide high-performance and high-efficiency power systems for electric vehicle applications. This paper first establishes dynamic models for the ultracapacitor, the battery and a passive hybrid power system, and then based on the dynamic models a comparative simulation between a battery only power system and the proposed hybrid power system was done under the UDDS (Urban Dynamometer Driving Schedule. The simulation results showed that the hybrid power system could greatly optimize and improve the efficiency of the batteries and their dynamic current was also decreased due to the participation of the ultracapacitors, which would have a good influence on batteries’ cycle life. Finally, the parameter matching for the passive hybrid power system was studied by simulation and comparisons.

  2. HyLTL: a temporal logic for model checking hybrid systems

    Directory of Open Access Journals (Sweden)

    Davide Bresolin

    2013-08-01

    Full Text Available The model-checking problem for hybrid systems is a well known challenge in the scientific community. Most of the existing approaches and tools are limited to safety properties only, or operates by transforming the hybrid system to be verified into a discrete one, thus loosing information on the continuous dynamics of the system. In this paper we present a logic for specifying complex properties of hybrid systems called HyLTL, and we show how it is possible to solve the model checking problem by translating the formula into an equivalent hybrid automaton. In this way the problem is reduced to a reachability problem on hybrid automata that can be solved by using existing tools.

  3. Mouse model for Usher syndrome: linkage mapping suggests homology to Usher type I reported at human chromosome 11p15.

    OpenAIRE

    Heckenlively, J R; Chang, B; Erway, L C; Peng, C; Hawes, N L; Hageman, G S; Roderick, T H

    1995-01-01

    Usher syndrome is a group of diseases with autosomal recessive inheritance, congenital hearing loss, and the development of retinitis pigmentosa, a progressive retinal degeneration characterized by night blindness and visual field loss over several decades. The causes of Usher syndrome are unknown and no animal models have been available for study. Four human gene sites have been reported, suggesting at least four separate forms of Usher syndrome. We report a mouse model of type I Usher syndr...

  4. Hybrid modelling of bed-discordant river confluences

    Science.gov (United States)

    Franca, M. J.; Guillén-Ludeña, S.; Cheng, Z.; Cardoso, A. H.; Constantinescu, G.

    2016-12-01

    In fluvial networks, tributaries are the main providers of sediment and water to the main rivers. Furthermore, confluences are environmental hotspots since they provide ecological connectivity and flow and morphology diversity. Mountain confluences, in particular, are characterized by narrow and steep tributaries that provide important sediment load to the confluence, whereas the main channel supplies the dominant flow discharge. This results in a marked bed discordance between the tributary and main channel. This discordance has been observed to be a key feature that alters the dynamics of the confluence, when compared to concordant confluences. The processes of initiation and maintenance of the morphology of confluences is still unknown, and research linking morphodynamics and hydrodynamics of river confluences is required to understand this. Here, a hybrid approach combining laboratory experiments made in a live-bed model of a river confluence, with 3D numerical simulations using advanced turbulence models is presented. We use the laboratory experiments performed by Guillén-Ludeña et al. (2016) for a 70o channel confluence, which focused on sediment transport and morphology changes rather than on the structure of the flow. Highly eddy resolving simulations were performed for two extreme bathymetric conditions, at the start of the experiment and at equilibrium scour conditions. The first allows to understand the initiation mechanisms which will condition later the equilibrium morphology. The second allows to understand the hydrodynamics actions which keep the equilibrium morphology. The patterns of the mean flow, turbulence and dynamics of the large-scale coherent structures, show how the main sediment-entrainment mechanisms evolve during the scour process. The present results contribute to a better understanding of the interaction between bed morphology and flow dynamics at discordant mountain river confluences.

  5. Passive immunization with a polyclonal antiserum to the hemoglobin receptor of Haemophilus ducreyi confers protection against a homologous challenge in the experimental swine model of chancroid.

    Science.gov (United States)

    Leduc, Isabelle; Fusco, William G; Choudhary, Neelima; Routh, Patty A; Cholon, Deborah M; Hobbs, Marcia M; Almond, Glen W; Orndorff, Paul E; Elkins, Christopher

    2011-08-01

    Haemophilus ducreyi, the etiologic agent of chancroid, has an obligate requirement for heme. Heme is acquired by H. ducreyi from its human host via TonB-dependent transporters expressed at its bacterial surface. Of 3 TonB-dependent transporters encoded in the genome of H. ducreyi, only the hemoglobin receptor, HgbA, is required to establish infection during the early stages of the experimental human model of chancroid. Active immunization with a native preparation of HgbA (nHgbA) confers complete protection in the experimental swine model of chancroid, using either Freund's or monophosphoryl lipid A as adjuvants. To determine if transfer of anti-nHgbA serum is sufficient to confer protection, a passive immunization experiment using pooled nHgbA antiserum was conducted in the experimental swine model of chancroid. Pigs receiving this pooled nHgbA antiserum were protected from a homologous, but not a heterologous, challenge. Passively transferred polyclonal antibodies elicited to nHgbA bound the surface of H. ducreyi and partially blocked hemoglobin binding by nHgbA, but were not bactericidal. Taken together, these data suggest that the humoral immune response to the HgbA vaccine is protective against an H. ducreyi infection, possibly by preventing acquisition of the essential nutrient heme.

  6. Passive Immunization with a Polyclonal Antiserum to the Hemoglobin Receptor of Haemophilus ducreyi Confers Protection against a Homologous Challenge in the Experimental Swine Model of Chancroid▿

    Science.gov (United States)

    Leduc, Isabelle; Fusco, William G.; Choudhary, Neelima; Routh, Patty A.; Cholon, Deborah M.; Hobbs, Marcia M.; Almond, Glen W.; Orndorff, Paul E.; Elkins, Christopher

    2011-01-01

    Haemophilus ducreyi, the etiologic agent of chancroid, has an obligate requirement for heme. Heme is acquired by H. ducreyi from its human host via TonB-dependent transporters expressed at its bacterial surface. Of 3 TonB-dependent transporters encoded in the genome of H. ducreyi, only the hemoglobin receptor, HgbA, is required to establish infection during the early stages of the experimental human model of chancroid. Active immunization with a native preparation of HgbA (nHgbA) confers complete protection in the experimental swine model of chancroid, using either Freund's or monophosphoryl lipid A as adjuvants. To determine if transfer of anti-nHgbA serum is sufficient to confer protection, a passive immunization experiment using pooled nHgbA antiserum was conducted in the experimental swine model of chancroid. Pigs receiving this pooled nHgbA antiserum were protected from a homologous, but not a heterologous, challenge. Passively transferred polyclonal antibodies elicited to nHgbA bound the surface of H. ducreyi and partially blocked hemoglobin binding by nHgbA, but were not bactericidal. Taken together, these data suggest that the humoral immune response to the HgbA vaccine is protective against an H. ducreyi infection, possibly by preventing acquisition of the essential nutrient heme. PMID:21646451

  7. Evaluation of vertical coordinate and vertical mixing algorithms in the HYbrid-Coordinate Ocean Model (HYCOM)

    Science.gov (United States)

    Halliwell, George R.

    Vertical coordinate and vertical mixing algorithms included in the HYbrid Coordinate Ocean Model (HYCOM) are evaluated in low-resolution climatological simulations of the Atlantic Ocean. The hybrid vertical coordinates are isopycnic in the deep ocean interior, but smoothly transition to level (pressure) coordinates near the ocean surface, to sigma coordinates in shallow water regions, and back again to level coordinates in very shallow water. By comparing simulations to climatology, the best model performance is realized using hybrid coordinates in conjunction with one of the three available differential vertical mixing models: the nonlocal K-Profile Parameterization, the NASA GISS level 2 turbulence closure, and the Mellor-Yamada level 2.5 turbulence closure. Good performance is also achieved using the quasi-slab Price-Weller-Pinkel dynamical instability model. Differences among these simulations are too small relative to other errors and biases to identify the "best" vertical mixing model for low-resolution climate simulations. Model performance deteriorates slightly when the Kraus-Turner slab mixed layer model is used with hybrid coordinates. This deterioration is smallest when solar radiation penetrates beneath the mixed layer and when shear instability mixing is included. A simulation performed using isopycnic coordinates to emulate the Miami Isopycnic Coordinate Ocean Model (MICOM), which uses Kraus-Turner mixing without penetrating shortwave radiation and shear instability mixing, demonstrates that the advantages of switching from isopycnic to hybrid coordinates and including more sophisticated turbulence closures outweigh the negative numerical effects of maintaining hybrid vertical coordinates.

  8. Probabilistic modelling and analysis of stand-alone hybrid power systems

    International Nuclear Information System (INIS)

    Lujano-Rojas, Juan M.; Dufo-López, Rodolfo; Bernal-Agustín, José L.

    2013-01-01

    As a part of the Hybrid Intelligent Algorithm, a model based on an ANN (artificial neural network) has been proposed in this paper to represent hybrid system behaviour considering the uncertainty related to wind speed and solar radiation, battery bank lifetime, and fuel prices. The Hybrid Intelligent Algorithm suggests a combination of probabilistic analysis based on a Monte Carlo simulation approach and artificial neural network training embedded in a genetic algorithm optimisation model. The installation of a typical hybrid system was analysed. Probabilistic analysis was used to generate an input–output dataset of 519 samples that was later used to train the ANNs to reduce the computational effort required. The generalisation ability of the ANNs was measured in terms of RMSE (Root Mean Square Error), MBE (Mean Bias Error), MAE (Mean Absolute Error), and R-squared estimators using another data group of 200 samples. The results obtained from the estimation of the expected energy not supplied, the probability of a determined reliability level, and the estimation of expected value of net present cost show that the presented model is able to represent the main characteristics of a typical hybrid power system under uncertain operating conditions. - Highlights: • This paper presents a probabilistic model for stand-alone hybrid power system. • The model considers the main sources of uncertainty related to renewable resources. • The Hybrid Intelligent Algorithm has been applied to represent hybrid system behaviour. • The installation of a typical hybrid system was analysed. • The results obtained from the study case validate the presented model

  9. Hybrid ATDL-gamma distribution model for predicting area source acid gas concentrations

    Energy Technology Data Exchange (ETDEWEB)

    Jakeman, A J; Taylor, J A

    1985-01-01

    An air quality model is developed to predict the distribution of concentrations of acid gas in an urban airshed. The model is hybrid in character, combining reliable features of a deterministic ATDL-based model with statistical distributional approaches. The gamma distribution was identified from a range of distributional models as the best model. The paper shows that the assumptions of a previous hybrid model may be relaxed and presents a methodology for characterizing the uncertainty associated with model predictions. Results are demonstrated for the 98-percentile predictions of 24-h average data over annual periods at six monitoring sites. This percentile relates to the World Health Organization goal for acid gas concentrations.

  10. A hybrid fuzzy multi-criteria decision making model for green ...

    African Journals Online (AJOL)

    A hybrid fuzzy multi-criteria decision making model for green supplier selection. ... Hence,supplier selection is significant factor in supply chain success. ... reduce purchasing cost, lead time and improve quality and environmental issue.

  11. Hybrid Computational Model for High-Altitude Aeroassist Vehicles, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — A hybrid continuum/noncontinuum computational model will be developed for analyzing the aerodynamics and heating on aeroassist vehicles. Unique features of this...

  12. Activity Recognition Using Hybrid Generative/Discriminative Models on Home Environments Using Binary Sensors

    Directory of Open Access Journals (Sweden)

    Araceli Sanchis

    2013-04-01

    Full Text Available Activities of daily living are good indicators of elderly health status, and activity recognition in smart environments is a well-known problem that has been previously addressed by several studies. In this paper, we describe the use of two powerful machine learning schemes, ANN (Artificial Neural Network and SVM (Support Vector Machines, within the framework of HMM (Hidden Markov Model in order to tackle the task of activity recognition in a home setting. The output scores of the discriminative models, after processing, are used as observation probabilities of the hybrid approach. We evaluate our approach by comparing these hybrid models with other classical activity recognition methods using five real datasets. We show how the hybrid models achieve significantly better recognition performance, with significance level p < 0:05, proving that the hybrid approach is better suited for the addressed domain.

  13. A new hybrid model optimized by an intelligent optimization algorithm for wind speed forecasting

    International Nuclear Information System (INIS)

    Su, Zhongyue; Wang, Jianzhou; Lu, Haiyan; Zhao, Ge

    2014-01-01

    Highlights: • A new hybrid model is developed for wind speed forecasting. • The model is based on the Kalman filter and the ARIMA. • An intelligent optimization method is employed in the hybrid model. • The new hybrid model has good performance in western China. - Abstract: Forecasting the wind speed is indispensable in wind-related engineering studies and is important in the management of wind farms. As a technique essential for the future of clean energy systems, reducing the forecasting errors related to wind speed has always been an important research subject. In this paper, an optimized hybrid method based on the Autoregressive Integrated Moving Average (ARIMA) and Kalman filter is proposed to forecast the daily mean wind speed in western China. This approach employs Particle Swarm Optimization (PSO) as an intelligent optimization algorithm to optimize the parameters of the ARIMA model, which develops a hybrid model that is best adapted to the data set, increasing the fitting accuracy and avoiding over-fitting. The proposed method is subsequently examined on the wind farms of western China, where the proposed hybrid model is shown to perform effectively and steadily

  14. Hybrid Electric Vehicle Experimental Model with CAN Network Real Time Control

    Directory of Open Access Journals (Sweden)

    RATOI, M.

    2010-05-01

    Full Text Available In this paper an experimental model with a distributed control system of a hybrid electrical vehicle is presented. A communication CAN network of high speed (1 Mbps assures a distributed control of the all components. The modeling and the control of different operating regimes are realized on an experimental test-bench of a hybrid electrical vehicle. The experimental results concerning the variations of the mains variables (currents, torques, speeds are presented.

  15. Structural characterization of respiratory syncytial virus fusion inhibitor escape mutants: homology model of the F protein and a syncytium formation assay

    International Nuclear Information System (INIS)

    Morton, Craig J.; Cameron, Rachel; Lawrence, Lynne J.; Lin Bo; Lowe, Melinda; Luttick, Angela; Mason, Anthony; McKimm-Breschkin, Jenny; Parker, Michael W.; Ryan, Jane; Smout, Michael; Sullivan, Jayne; Tucker, Simon P.; Young, Paul R.

    2003-01-01

    Respiratory syncytial virus (RSV) is a ubiquitous human pathogen and the leading cause of lower respiratory tract infections in infants. Infection of cells and subsequent formation of syncytia occur through membrane fusion mediated by the RSV fusion protein (RSV-F). A novel in vitro assay of recombinant RSV-F function has been devised and used to characterize a number of escape mutants for three known inhibitors of RSV-F that have been isolated. Homology modeling of the RSV-F structure has been carried out on the basis of a chimera derived from the crystal structures of the RSV-F core and a fragment from the orthologous fusion protein from Newcastle disease virus (NDV). The structure correlates well with the appearance of RSV-F in electron micrographs, and the residues identified as contributing to specific binding sites for several monoclonal antibodies are arranged in appropriate solvent-accessible clusters. The positions of the characterized resistance mutants in the model structure identify two promising regions for the design of fusion inhibitors

  16. Homology modeling and docking analyses of M. leprae Mur ligases reveals the common binding residues for structure based drug designing to eradicate leprosy.

    Science.gov (United States)

    Shanmugam, Anusuya; Natarajan, Jeyakumar

    2012-06-01

    Multi drug resistance capacity for Mycobacterium leprae (MDR-Mle) demands the profound need for developing new anti-leprosy drugs. Since most of the drugs target a single enzyme, mutation in the active site renders the antibiotic ineffective. However, structural and mechanistic information on essential bacterial enzymes in a pathway could lead to the development of antibiotics that targets multiple enzymes. Peptidoglycan is an important component of the cell wall of M. leprae. The biosynthesis of bacterial peptidoglycan represents important targets for the development of new antibacterial drugs. Biosynthesis of peptidoglycan is a multi-step process that involves four key Mur ligase enzymes: MurC (EC:6.3.2.8), MurD (EC:6.3.2.9), MurE (EC:6.3.2.13) and MurF (EC:6.3.2.10). Hence in our work, we modeled the three-dimensional structure of the above Mur ligases using homology modeling method and analyzed its common binding features. The residues playing an important role in the catalytic activity of each of the Mur enzymes were predicted by docking these Mur ligases with their substrates and ATP. The conserved sequence motifs significant for ATP binding were predicted as the probable residues for structure based drug designing. Overall, the study was successful in listing significant and common binding residues of Mur enzymes in peptidoglycan pathway for multi targeted therapy.

  17. The existence of fertile hybrids of closely related model earthworm species, Eisenia andrei and E. fetida.

    Directory of Open Access Journals (Sweden)

    Barbara Plytycz

    Full Text Available Lumbricid earthworms Eisenia andrei (Ea and E. fetida (Ef are simultaneous hermaphrodites with reciprocal insemination capable of self-fertilization while the existence of hybridization of these two species was still debatable. During the present investigation fertile hybrids of Ea and Ef were detected. Virgin specimens of Ea and Ef were laboratory crossed (Ea+Ef and their progeny was doubly identified. 1 -identified by species-specific maternally derived haploid mitochondrial DNA sequences of the COI gene being either 'a' for worms hatched from Ea ova or 'f' for worms hatched from Ef ova. 2 -identified by the diploid maternal/paternal nuclear DNA sequences of 28s rRNA gene being either 'AA' for Ea, 'FF' for Ef, or AF/FA for their hybrids derived either from the 'aA' or 'fF' ova, respectively. Among offspring of Ea+Ef pairs in F1 generation there were mainly aAA and fFF earthworms resulted from the facilitated self-fertilization and some aAF hybrids from aA ova but none fFA hybrids from fF ova. In F2 generation resulting from aAF hybrids mated with aAA a new generations of aAA and aAF hybrids were noticed, while aAF hybrids mated with fFF gave fFF and both aAF and fFA hybrids. Hybrids intercrossed together produced plenty of cocoons but no hatchlings independently whether aAF+aAF or aAF+fFA were mated. These results indicated that Ea and Ef species, easy to maintain in laboratory and commonly used as convenient models in biomedicine and ecotoxicology, may also serve in studies on molecular basis of interspecific barriers and mechanisms of introgression and speciation. Hypothetically, their asymmetrical hybridization can be modified by some external factors.

  18. Model-on-Demand Predictive Control for Nonlinear Hybrid Systems With Application to Adaptive Behavioral Interventions

    Science.gov (United States)

    Nandola, Naresh N.; Rivera, Daniel E.

    2011-01-01

    This paper presents a data-centric modeling and predictive control approach for nonlinear hybrid systems. System identification of hybrid systems represents a challenging problem because model parameters depend on the mode or operating point of the system. The proposed algorithm applies Model-on-Demand (MoD) estimation to generate a local linear approximation of the nonlinear hybrid system at each time step, using a small subset of data selected by an adaptive bandwidth selector. The appeal of the MoD approach lies in the fact that model parameters are estimated based on a current operating point; hence estimation of locations or modes governed by autonomous discrete events is achieved automatically. The local MoD model is then converted into a mixed logical dynamical (MLD) system representation which can be used directly in a model predictive control (MPC) law for hybrid systems using multiple-degree-of-freedom tuning. The effectiveness of the proposed MoD predictive control algorithm for nonlinear hybrid systems is demonstrated on a hypothetical adaptive behavioral intervention problem inspired by Fast Track, a real-life preventive intervention for improving parental function and reducing conduct disorder in at-risk children. Simulation results demonstrate that the proposed algorithm can be useful for adaptive intervention problems exhibiting both nonlinear and hybrid character. PMID:21874087

  19. Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposal

    Directory of Open Access Journals (Sweden)

    Narong Wichapa

    2017-11-01

    Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

  20. Frog: Asynchronous Graph Processing on GPU with Hybrid Coloring Model

    Energy Technology Data Exchange (ETDEWEB)

    Shi, Xuanhua; Luo, Xuan; Liang, Junling; Zhao, Peng; Di, Sheng; He, Bingsheng; Jin, Hai

    2018-01-01

    GPUs have been increasingly used to accelerate graph processing for complicated computational problems regarding graph theory. Many parallel graph algorithms adopt the asynchronous computing model to accelerate the iterative convergence. Unfortunately, the consistent asynchronous computing requires locking or atomic operations, leading to significant penalties/overheads when implemented on GPUs. As such, coloring algorithm is adopted to separate the vertices with potential updating conflicts, guaranteeing the consistency/correctness of the parallel processing. Common coloring algorithms, however, may suffer from low parallelism because of a large number of colors generally required for processing a large-scale graph with billions of vertices. We propose a light-weight asynchronous processing framework called Frog with a preprocessing/hybrid coloring model. The fundamental idea is based on Pareto principle (or 80-20 rule) about coloring algorithms as we observed through masses of realworld graph coloring cases. We find that a majority of vertices (about 80%) are colored with only a few colors, such that they can be read and updated in a very high degree of parallelism without violating the sequential consistency. Accordingly, our solution separates the processing of the vertices based on the distribution of colors. In this work, we mainly answer three questions: (1) how to partition the vertices in a sparse graph with maximized parallelism, (2) how to process large-scale graphs that cannot fit into GPU memory, and (3) how to reduce the overhead of data transfers on PCIe while processing each partition. We conduct experiments on real-world data (Amazon, DBLP, YouTube, RoadNet-CA, WikiTalk and Twitter) to evaluate our approach and make comparisons with well-known non-preprocessed (such as Totem, Medusa, MapGraph and Gunrock) and preprocessed (Cusha) approaches, by testing four classical algorithms (BFS, PageRank, SSSP and CC). On all the tested applications and

  1. Synthesis of a hybrid model of the VSC FACTS devices and HVDC technologies

    Science.gov (United States)

    Borovikov, Yu S.; Gusev, A. S.; Sulaymanov, A. O.; Ufa, R. A.

    2014-10-01

    The motivation of the presented research is based on the need for development of new methods and tools for adequate simulation of FACTS devices and HVDC systems as part of real electric power systems (EPS). The Research object: An alternative hybrid approach for synthesizing VSC-FACTS and -HVDC hybrid model is proposed. The results: the VSC- FACTS and -HVDC hybrid model is designed in accordance with the presented concepts of hybrid simulation. The developed model allows us to carry out adequate simulation in real time of all the processes in HVDC, FACTS devices and EPS as a whole without any decomposition and limitation on their duration, and also use the developed tool for effective solution of a design, operational and research tasks of EPS containing such devices.

  2. Synthesis of a hybrid model of the VSC FACTS devices and HVDC technologies

    International Nuclear Information System (INIS)

    Borovikov, Yu S; Gusev, A S; Sulaymanov, A O; Ufa, R A

    2014-01-01

    The motivation of the presented research is based on the need for development of new methods and tools for adequate simulation of FACTS devices and HVDC systems as part of real electric power systems (EPS). The Research object: An alternative hybrid approach for synthesizing VSC-FACTS and -HVDC hybrid model is proposed. The results: the VSC- FACTS and -HVDC hybrid model is designed in accordance with the presented concepts of hybrid simulation. The developed model allows us to carry out adequate simulation in real time of all the processes in HVDC, FACTS devices and EPS as a whole without any decomposition and limitation on their duration, and also use the developed tool for effective solution of a design, operational and research tasks of EPS containing such devices

  3. Insight into the intermolecular recognition mechanism between Keap1 and IKKβ combining homology modelling, protein-protein docking, molecular dynamics simulations and virtual alanine mutation.

    Directory of Open Access Journals (Sweden)

    Zheng-Yu Jiang

    Full Text Available Degradation of certain proteins through the ubiquitin-proteasome pathway is a common strategy taken by the key modulators responsible for stress responses. Kelch-like ECH-associated protein-1(Keap1, a substrate adaptor component of the Cullin3 (Cul3-based ubiquitin E3 ligase complex, mediates the ubiquitination of two key modulators, NF-E2-related factor 2 (Nrf2 and IκB kinase β (IKKβ, which are involved in the redox control of gene transcription. However, compared to the Keap1-Nrf2 protein-protein interaction (PPI, the intermolecular recognition mechanism of Keap1 and IKKβ has been poorly investigated. In order to explore the binding pattern between Keap1 and IKKβ, the PPI model of Keap1 and IKKβ was investigated. The structure of human IKKβ was constructed by means of the homology modeling method and using reported crystal structure of Xenopus laevis IKKβ as the template. A protein-protein docking method was applied to develop the Keap1-IKKβ complex model. After the refinement and visual analysis of docked proteins, the chosen pose was further optimized through molecular dynamics simulations. The resulting structure was utilized to conduct the virtual alanine mutation for the exploration of hot-spots significant for the intermolecular interaction. Overall, our results provided structural insights into the PPI model of Keap1-IKKβ and suggest that the substrate specificity of Keap1 depend on the interaction with the key tyrosines, namely Tyr525, Tyr574 and Tyr334. The study presented in the current project may be useful to design molecules that selectively modulate Keap1. The selective recognition mechanism of Keap1 with IKKβ or Nrf2 will be helpful to further know the crosstalk between NF-κB and Nrf2 signaling.

  4. Homology modeling, molecular dynamics, and virtual screening of NorA efflux pump inhibitors of Staphylococcus aureus.

    Science.gov (United States)

    Bhaskar, Baki Vijaya; Babu, Tirumalasetty Muni Chandra; Reddy, Netala Vasudeva; Rajendra, Wudayagiri

    2016-01-01

    Emerging drug resistance in clinical isolates of Staphylococcus aureus might be implicated to the overexpression of NorA efflux pump which is capable of extruding numerous structurally diverse compounds. However, NorA efflux pump is considered as a potential drug target for the development of efflux pump inhibitors. In the present study, NorA model was constructed based on the crystal structure of glycerol-3-phosphate transporter (PDBID: 1PW4). Molecular dynamics (MD) simulation was performed using NAMD2.7 for NorA which is embedded in the hydrated lipid bilayer. Structural design of NorA unveils amino (N)- and carboxyl (C)-terminal domains which are connected by long cytoplasmic loop. N and C domains are composed of six transmembrane α-helices (TM) which exhibits pseudo-twofold symmetry and possess voluminous substrate binding cavity between TM helices. Molecular docking of reserpine, totarol, ferruginol, salvin, thioxanthene, phenothiazine, omeprazole, verapamil, nalidixic acid, ciprofloxacin, levofloxacin, and acridine to NorA found that all the molecules were bound at the large hydrophobic cleft and indicated significant interactions with the key residues. In addition, structure-based virtual screening was employed which indicates that 14 potent novel lead molecules such as CID58685302, CID58685367, CID5799283, CID5578487, CID60028372, ZINC12196383, ZINC72140751, ZINC72137843, ZINC39227983, ZINC43742707, ZINC12196375, ZINC66166948, ZINC39228014, and ZINC14616160 have highest binding affinity for NorA. These lead molecules displayed considerable pharmacological properties as evidenced by Lipinski rule of five and prophecy of toxicity risk assessment. Thus, the present study will be helpful in designing and synthesis of a novel class of NorA efflux pump inhibitors that restore the susceptibilities of drug compounds.

  5. Applying a Hybrid Model: Can It Enhance Student Learning Outcomes?

    Science.gov (United States)

    Potter, Jodi

    2015-01-01

    There has been a marked increase in the use of online learning over the past decade. There remains conflict in the current body of research on the efficacy of online versus face to face learning in these environments. One resolution of these issues is the hybrid learning option which is a combination of face-to-face classroom instruction with…

  6. Model-based health monitoring of hybrid systems

    CERN Document Server

    Wang, Danwei; Low, Chang Boon; Arogeti, Shai

    2013-01-01

    Offers in-depth comprehensive study on health monitoring for hybrid systems Includes new concepts, such as GARR, mode tracking and multiple failure prognosis Contains many examples, making the developed techniques easily understandable and accessible Introduces state-of-the-art algorithms and methodologies from experienced researchers

  7. A hybrid model for the play hysteresis operator

    Czech Academy of Sciences Publication Activity Database

    Al Janaideh, M.; Naldi, R.; Marconi, L.; Krejčí, Pavel

    2013-01-01

    Roč. 430, 1 December (2013), s. 95-98 ISSN 0921-4526 R&D Projects: GA ČR GAP201/10/2315 Institutional support: RVO:67985840 Keywords : hysteresis * hybrid * play Subject RIV: BA - General Mathematics Impact factor: 1.276, year: 2013 http://www.sciencedirect.com/science/article/pii/S0921452613004146

  8. A Hybrid Method for Modeling and Solving Supply Chain Optimization Problems with Soft and Logical Constraints

    Directory of Open Access Journals (Sweden)

    Paweł Sitek

    2016-01-01

    Full Text Available This paper presents a hybrid method for modeling and solving supply chain optimization problems with soft, hard, and logical constraints. Ability to implement soft and logical constraints is a very important functionality for supply chain optimization models. Such constraints are particularly useful for modeling problems resulting from commercial agreements, contracts, competition, technology, safety, and environmental conditions. Two programming and solving environments, mathematical programming (MP and constraint logic programming (CLP, were combined in the hybrid method. This integration, hybridization, and the adequate multidimensional transformation of the problem (as a presolving method helped to substantially reduce the search space of combinatorial models for supply chain optimization problems. The operation research MP and declarative CLP, where constraints are modeled in different ways and different solving procedures are implemented, were linked together to use the strengths of both. This approach is particularly important for the decision and combinatorial optimization models with the objective function and constraints, there are many decision variables, and these are summed (common in manufacturing, supply chain management, project management, and logistic problems. The ECLiPSe system with Eplex library was proposed to implement a hybrid method. Additionally, the proposed hybrid transformed model is compared with the MILP-Mixed Integer Linear Programming model on the same data instances. For illustrative models, its use allowed finding optimal solutions eight to one hundred times faster and reducing the size of the combinatorial problem to a significant extent.

  9. Persistent homology and string vacua

    Energy Technology Data Exchange (ETDEWEB)

    Cirafici, Michele [Center for Mathematical Analysis, Geometry and Dynamical Systems,Instituto Superior Técnico, Universidade de Lisboa,Av. Rovisco Pais, 1049-001 Lisboa (Portugal); Institut des Hautes Études Scientifiques,Le Bois-Marie, 35 route de Chartres, F-91440 Bures-sur-Yvette (France)

    2016-03-08

    We use methods from topological data analysis to study the topological features of certain distributions of string vacua. Topological data analysis is a multi-scale approach used to analyze the topological features of a dataset by identifying which homological characteristics persist over a long range of scales. We apply these techniques in several contexts. We analyze N=2 vacua by focusing on certain distributions of Calabi-Yau varieties and Landau-Ginzburg models. We then turn to flux compactifications and discuss how we can use topological data analysis to extract physical information. Finally we apply these techniques to certain phenomenologically realistic heterotic models. We discuss the possibility of characterizing string vacua using the topological properties of their distributions.

  10. Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposaL

    Energy Technology Data Exchange (ETDEWEB)

    Wichapa, Narong; Khokhajaikiat, Porntep

    2017-07-01

    Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

  11. Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposaL

    International Nuclear Information System (INIS)

    Wichapa, Narong; Khokhajaikiat, Porntep

    2017-01-01

    Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

  12. Structure-function relationship of a plant NCS1 member - Homology modeling and mutagenesis identified residues critical for substrate specificity of PLUTO, a nucleobase transporter from arabidopsis

    KAUST Repository

    Witz, Sandra

    2014-03-12

    Plastidic uracil salvage is essential for plant growth and development. So far, PLUTO, the plastidic nucleobase transporter from Arabidopsis thaliana is the only known uracil importer at the inner plastidic membrane which represents the permeability barrier of this organelle. We present the first homology model of PLUTO, the sole plant NCS1 member from Arabidopsis based on the crystal structure of the benzyl hydantoin transporter MHP1 from Microbacterium liquefaciens and validated by molecular dynamics simulations. Polar side chains of residues Glu-227 and backbones of Val-145, Gly-147 and Thr-425 are proposed to form the binding site for the three PLUTO substrates uracil, adenine and guanine. Mutational analysis and competition studies identified Glu-227 as an important residue for uracil and to a lesser extent for guanine transport. A differential response in substrate transport was apparent with PLUTO double mutants E227Q G147Q and E227Q T425A, both of which most strongly affected adenine transport, and in V145A G147Q, which markedly affected guanine transport. These differences could be explained by docking studies, showing that uracil and guanine exhibit a similar binding mode whereas adenine binds deep into the catalytic pocket of PLUTO. Furthermore, competition studies confirmed these results. The present study defines the molecular determinants for PLUTO substrate binding and demonstrates key differences in structure-function relations between PLUTO and other NCS1 family members. 2014 Witz et al.

  13. Modeling and Optimal Control of a Class of Warfare Hybrid Dynamic Systems Based on Lanchester (n,1) Attrition Model

    OpenAIRE

    Chen, Xiangyong; Zhang, Ancai

    2014-01-01

    For the particularity of warfare hybrid dynamic process, a class of warfare hybrid dynamic systems is established based on Lanchester equation in a (n,1) battle, where a heterogeneous force of n different troop types faces a homogeneous force. This model can be characterized by the interaction of continuous-time models (governed by Lanchester equation), and discrete event systems (described by variable tactics). Furthermore, an expository discussion is presented on an optimal variable tact...

  14. AMITIS: A 3D GPU-Based Hybrid-PIC Model for Space and Plasma Physics

    Science.gov (United States)

    Fatemi, Shahab; Poppe, Andrew R.; Delory, Gregory T.; Farrell, William M.

    2017-05-01

    We have developed, for the first time, an advanced modeling infrastructure in space simulations (AMITIS) with an embedded three-dimensional self-consistent grid-based hybrid model of plasma (kinetic ions and fluid electrons) that runs entirely on graphics processing units (GPUs). The model uses NVIDIA GPUs and their associated parallel computing platform, CUDA, developed for general purpose processing on GPUs. The model uses a single CPU-GPU pair, where the CPU transfers data between the system and GPU memory, executes CUDA kernels, and writes simulation outputs on the disk. All computations, including moving particles, calculating macroscopic properties of particles on a grid, and solving hybrid model equations are processed on a single GPU. We explain various computing kernels within AMITIS and compare their performance with an already existing well-tested hybrid model of plasma that runs in parallel using multi-CPU platforms. We show that AMITIS runs ∼10 times faster than the parallel CPU-based hybrid model. We also introduce an implicit solver for computation of Faraday’s Equation, resulting in an explicit-implicit scheme for the hybrid model equation. We show that the proposed scheme is stable and accurate. We examine the AMITIS energy conservation and show that the energy is conserved with an error < 0.2% after 500,000 timesteps, even when a very low number of particles per cell is used.

  15. Investigating actinide compounds within a hybrid MCSCF-DFT model

    International Nuclear Information System (INIS)

    Fromager, E.; Jensen, H.J.A.; Wahlin, P.; Real, F.; Wahlgren, U.

    2007-01-01

    Complete text of publication follows: Investigations of actinide chemistry with quantum chemical methods still remain a complicated task since it requires an accurate and efficient treatment of the environment (crystal or solvent) as well as relativistic and electron correlation effects. Concerning the latter, the current correlated methods, based on either Density-Functional Theory (DFT) or Wave-Function Theory (WFT), have their advantages and drawbacks. On the one hand, Kohn-Sham DFT (KS-DFT) calculates the dynamic correlation quite accurately and at a fairly low computational cost. However, it does not treat adequately the static correlation, which is significant in some actinide compounds because of the near-degeneracy of the 5f orbitals: a first example is the bent geometry obtained in KS-DFT(B3LYP) for the neptunyl ion NpO 2 3+ , which is found to be linear within a Multi-Configurational Self-Consistent Field (MCSCF) model [1]. A second one is the stable and bent geometry obtained in KS-DFT(B3LYP) for the plutonyl ion PuO 2 4+ , which disintegrates at the MCSCF level [1]. On the other hand, WFT can describe the static correlation, using for example a MCSCF model, but then an important part of the dynamic correlation has to be neglected. This can be recovered with perturbation-theory based methods like for example CASPT2 or NEVPT2, but their computational complexity prevents large scale calculations. It is therefore of great interest to develop a hybrid MCSCF-DFT model which combines the best of both WFT and DFT approaches. The merge of WFT and DFT can be achieved by splitting the two-electron interaction into long-range and short-range parts [2]. The long-range part is then treated by WFT and the short-range part by DFT. We use the so-called 'erf' long-range interaction erf(μr 12 )/r 12 , which is based on the standard error function, and where μ is a free parameter which controls the long/short-range decomposition. The newly proposed recipe for the

  16. Modelling biochemical networks with intrinsic time delays: a hybrid semi-parametric approach

    Directory of Open Access Journals (Sweden)

    Oliveira Rui

    2010-09-01

    Full Text Available Abstract Background This paper presents a method for modelling dynamical biochemical networks with intrinsic time delays. Since the fundamental mechanisms leading to such delays are many times unknown, non conventional modelling approaches become necessary. Herein, a hybrid semi-parametric identification methodology is proposed in which discrete time series are incorporated into fundamental material balance models. This integration results in hybrid delay differential equations which can be applied to identify unknown cellular dynamics. Results The proposed hybrid modelling methodology was evaluated using two case studies. The first of these deals with dynamic modelling of transcriptional factor A in mammalian cells. The protein transport from the cytosol to the nucleus introduced a delay that was accounted for by discrete time series formulation. The second case study focused on a simple network with distributed time delays that demonstrated that the discrete time delay formalism has broad applicability to both discrete and distributed delay problems. Conclusions Significantly better prediction qualities of the novel hybrid model were obtained when compared to dynamical structures without time delays, being the more distinctive the more significant the underlying system delay is. The identification of the system delays by studies of different discrete modelling delays was enabled by the proposed structure. Further, it was shown that the hybrid discrete delay methodology is not limited to discrete delay systems. The proposed method is a powerful tool to identify time delays in ill-defined biochemical networks.

  17. Finite-Control-Set Model Predictive Control (FCS-MPC) for Islanded Hybrid Microgrids

    OpenAIRE

    Yi, Zhehan; Babqi, Abdulrahman J.; Wang, Yishen; Shi, Di; Etemadi, Amir H.; Wang, Zhiwei; Huang, Bibin

    2018-01-01

    Microgrids consisting of multiple distributed energy resources (DERs) provide a promising solution to integrate renewable energies, e.g., solar photovoltaic (PV) systems. Hybrid AC/DC microgrids leverage the merits of both AC and DC power systems. In this paper, a control strategy for islanded multi-bus hybrid microgrids is proposed based on the Finite-Control-Set Model Predictive Control (FCS-MPC) technologies. The control loops are expedited by predicting the future states and determining t...

  18. Modeling of the electron distribution based on bremsstrahlung emission during lower hybrid current drive on PLT

    Energy Technology Data Exchange (ETDEWEB)

    Stevens, J.E.; von Goeler, S.; Bernabei, S.; Bitter, M.; Chu, T.K.; Efthimion, P.; Fisch, N.; Hooke, W.; Hosea, J.; Jobes, F.

    1985-03-01

    Lower hybrid current drive requires the generation of a high energy electron tail anisotropic in velocity. Measurements of bremsstrahlung emission produced by this tail are compared with the calculated emission from reasonable model distributions. The physical basis and the sensitivity of this modeling process are described and the plasma properties of current driven discharges which can be derived from the model are discussed.

  19. A hybrid model for the investigation of heavy ion collisions at intermediate energies

    International Nuclear Information System (INIS)

    Heide, B.M.

    1995-09-01

    The following topics were dealt with: The coupling of the Botzmann-Uehling-Uhlenbeck (BUU) model with Kopenhagen multifragmentation model realising a new hybrid model, application on 197 Au+ 197 Au reactions between 100 and 250 A.MeV, calculation of the chracteristics of the fragmentation system including mass number, excitation energy, angular momenta, two-particle correlation function

  20. A hybrid hydrostatic and non-hydrostatic numerical model for shallow flow simulations

    Science.gov (United States)

    Zhang, Jingxin; Liang, Dongfang; Liu, Hua

    2018-05-01

    Hydrodynamics of geophysical flows in oceanic shelves, estuaries, and rivers, are often studied by solving shallow water model equations. Although hydrostatic models are accurate and cost efficient for many natural flows, there are situations where the hydrostatic assumption is invalid, whereby a fully hydrodynamic model is necessary to increase simulation accuracy. There is a growing concern about the decrease of the computational cost of non-hydrostatic pressure models to improve the range of their applications in large-scale flows with complex geometries. This study describes a hybrid hydrostatic and non-hydrostatic model to increase the efficiency of simulating shallow water flows. The basic numerical model is a three-dimensional hydrostatic model solved by the finite volume method (FVM) applied to unstructured grids. Herein, a second-order total variation diminishing (TVD) scheme is adopted. Using a predictor-corrector method to calculate the non-hydrostatic pressure, we extended the hydrostatic model to a fully hydrodynamic model. By localising the computational domain in the corrector step for non-hydrostatic pressure calculations, a hybrid model was developed. There was no prior special treatment on mode switching, and the developed numerical codes were highly efficient and robust. The hybrid model is applicable to the simulation of shallow flows when non-hydrostatic pressure is predominant only in the local domain. Beyond the non-hydrostatic domain, the hydrostatic model is still accurate. The applicability of the hybrid method was validated using several study cases.

  1. Modeling of the electron distribution based on bremsstrahlung emission during lower hybrid current drive on PLT

    International Nuclear Information System (INIS)

    Stevens, J.E.; von Goeler, S.; Bernabei, S.

    1985-03-01

    Lower hybrid current drive requires the generation of a high energy electron tail anisotropic in velocity. Measurements of bremsstrahlung emission produced by this tail are compared with the calculated emission from reasonable model distributions. The physical basis and the sensitivity of this modeling process are described and the plasma properties of current driven discharges which can be derived from the model are discussed

  2. Adaptive control using a hybrid-neural model: application to a polymerisation reactor

    Directory of Open Access Journals (Sweden)

    Cubillos F.

    2001-01-01

    Full Text Available This work presents the use of a hybrid-neural model for predictive control of a plug flow polymerisation reactor. The hybrid-neural model (HNM is based on fundamental conservation laws associated with a neural network (NN used to model the uncertain parameters. By simulations, the performance of this approach was studied for a peroxide-initiated styrene tubular reactor. The HNM was synthesised for a CSTR reactor with a radial basis function neural net (RBFN used to estimate the reaction rates recursively. The adaptive HNM was incorporated in two model predictive control strategies, a direct synthesis scheme and an optimum steady state scheme. Tests for servo and regulator control showed excellent behaviour following different setpoint variations, and rejecting perturbations. The good generalisation and training capacities of hybrid models, associated with the simplicity and robustness characteristics of the MPC formulations, make an attractive combination for the control of a polymerisation reactor.

  3. Optimization of ultrasonic array inspections using an efficient hybrid model and real crack shapes

    Energy Technology Data Exchange (ETDEWEB)

    Felice, Maria V., E-mail: maria.felice@bristol.ac.uk [Department of Mechanical Engineering, University of Bristol, Bristol, U.K. and NDE Laboratory, Rolls-Royce plc., Bristol (United Kingdom); Velichko, Alexander, E-mail: p.wilcox@bristol.ac.uk; Wilcox, Paul D., E-mail: p.wilcox@bristol.ac.uk [Department of Mechanical Engineering, University of Bristol, Bristol (United Kingdom); Barden, Tim; Dunhill, Tony [NDE Laboratory, Rolls-Royce plc., Bristol (United Kingdom)

    2015-03-31

    Models which simulate the interaction of ultrasound with cracks can be used to optimize ultrasonic array inspections, but this approach can be time-consuming. To overcome this issue an efficient hybrid model is implemented which includes a finite element method that requires only a single layer of elements around the crack shape. Scattering Matrices are used to capture the scattering behavior of the individual cracks and a discussion on the angular degrees of freedom of elastodynamic scatterers is included. Real crack shapes are obtained from X-ray Computed Tomography images of cracked parts and these shapes are inputted into the hybrid model. The effect of using real crack shapes instead of straight notch shapes is demonstrated. An array optimization methodology which incorporates the hybrid model, an approximate single-scattering relative noise model and the real crack shapes is then described.

  4. Detection of the antiviral activity of epicatechin isolated from Salacia crassifolia (Celastraceae) against Mayaro virus based on protein C homology modelling and virtual screening.

    Science.gov (United States)

    Ferreira, P G; Ferraz, A C; Figueiredo, J E; Lima, C F; Rodrigues, V G; Taranto, A G; Ferreira, J M S; Brandão, G C; Vieira-Filho, S A; Duarte, L P; de Brito Magalhães, C L; de Magalhães, J C

    2018-02-24

    Mayaro fever, caused by Mayaro virus (MAYV) is a sub-lethal disease with symptoms that are easily confused with those of dengue fever, except for polyarthralgia, which may culminate in physical incapacitation. Recently, outbreaks of MAYV have been documented in metropolitan areas, and to date, there is no therapy or vaccine available. Moreover, there is no information regarding the three-dimensional structure of the viral proteins of MAYV, which is important in the search for antivirals. In this work, we constructed a three-dimensional model of protein C of MAYV by homology modelling, and this was employed in a manner similar to that of receptors in virtual screening studies to evaluate 590 molecules as prospective antiviral agents. In vitro bioassays were utilized to confirm the potential antiviral activity of the flavonoid epicatechin isolated from Salacia crassifolia (Celastraceae). The virtual screening showed that six flavonoids were promising ligands for protein C. The bioassays showed potent antiviral action of epicatechin, which protected the cells from almost all of the effects of viral infection. An effective concentration (EC 50 ) of 0.247 μmol/mL was observed with a selectivity index (SI) of 7. The cytotoxicity assay showed that epicatechin has low toxicity, with a 50% cytotoxic concentration (CC 50 ) greater than 1.723 µmol/mL. Epicatechin was found to be twice as potent as the reference antiviral ribavirin. Furthermore, a replication kinetics assay showed a strong inhibitory effect of epicatechin on MAYV growth, with a reduction of at least four logs in virus production. Our results indicate that epicatechin is a promising candidate for further testing as an antiviral agent against Mayaro virus and other alphaviruses.

  5. GPCR-I-TASSER: A Hybrid Approach to G Protein-Coupled Receptor Structure Modeling and the Application to the Human Genome.

    Science.gov (United States)

    Zhang, Jian; Yang, Jianyi; Jang, Richard; Zhang, Yang

    2015-08-04

    Experimental structure determination remains difficult for G protein-coupled receptors (GPCRs). We propose a new hybrid protocol to construct GPCR structure models that integrates experimental mutagenesis data with ab initio transmembrane (TM) helix assembly simulations. The method was tested on 24 known GPCRs where the ab initio TM-helix assembly procedure constructed the correct fold for 20 cases. When combined with weak homology and sparse mutagenesis restraints, the method generated correct folds for all the tested cases with an average Cα root-mean-square deviation 2.4 Å in the TM regions. The new hybrid protocol was applied to model all 1,026 GPCRs in the human genome, where 923 have a high confidence score and are expected to have correct folds; these contain many pharmaceutically important families with no previously solved structures, including Trace amine, Prostanoids, Releasing hormones, Melanocortins, Vasopressin, and Neuropeptide Y receptors. The results demonstrate new progress on genome-wide structure modeling of TM proteins. Copyright © 2015 Elsevier Ltd. All rights reserved.

  6. Bias-dependent hybrid PKI empirical-neural model of microwave FETs

    Science.gov (United States)

    Marinković, Zlatica; Pronić-Rančić, Olivera; Marković, Vera

    2011-10-01

    Empirical models of microwave transistors based on an equivalent circuit are valid for only one bias point. Bias-dependent analysis requires repeated extractions of the model parameters for each bias point. In order to make model bias-dependent, a new hybrid empirical-neural model of microwave field-effect transistors is proposed in this article. The model is a combination of an equivalent circuit model including noise developed for one bias point and two prior knowledge input artificial neural networks (PKI ANNs) aimed at introducing bias dependency of scattering (S) and noise parameters, respectively. The prior knowledge of the proposed ANNs involves the values of the S- and noise parameters obtained by the empirical model. The proposed hybrid model is valid in the whole range of bias conditions. Moreover, the proposed model provides better accuracy than the empirical model, which is illustrated by an appropriate modelling example of a pseudomorphic high-electron mobility transistor device.

  7. A Hybrid Acoustic and Pronunciation Model Adaptation Approach for Non-native Speech Recognition

    Science.gov (United States)

    Oh, Yoo Rhee; Kim, Hong Kook

    In this paper, we propose a hybrid model adaptation approach in which pronunciation and acoustic models are adapted by incorporating the pronunciation and acoustic variabilities of non-native speech in order to improve the performance of non-native automatic speech recognition (ASR). Specifically, the proposed hybrid model adaptation can be performed at either the state-tying or triphone-modeling level, depending at which acoustic model adaptation is performed. In both methods, we first analyze the pronunciation variant rules of non-native speakers and then classify each rule as either a pronunciation variant or an acoustic variant. The state-tying level hybrid method then adapts pronunciation models and acoustic models by accommodating the pronunciation variants in the pronunciation dictionary and by clustering the states of triphone acoustic models using the acoustic variants, respectively. On the other hand, the triphone-modeling level hybrid method initially adapts pronunciation models in the same way as in the state-tying level hybrid method; however, for the acoustic model adaptation, the triphone acoustic models are then re-estimated based on the adapted pronunciation models and the states of the re-estimated triphone acoustic models are clustered using the acoustic variants. From the Korean-spoken English speech recognition experiments, it is shown that ASR systems employing the state-tying and triphone-modeling level adaptation methods can relatively reduce the average word error rates (WERs) by 17.1% and 22.1% for non-native speech, respectively, when compared to a baseline ASR system.

  8. Modelling of cardiovascular system: development of a hybrid (numerical-physical) model.

    Science.gov (United States)

    Ferrari, G; Kozarski, M; De Lazzari, C; Górczyńska, K; Mimmo, R; Guaragno, M; Tosti, G; Darowski, M

    2003-12-01

    Physical models of the circulation are used for research, training and for testing of implantable active and passive circulatory prosthetic and assistance devices. However, in comparison with numerical models, they are rigid and expensive. To overcome these limitations, we have developed a model of the circulation based on the merging of a lumped parameter physical model into a numerical one (producing therefore a hybrid). The physical model is limited to the barest essentials and, in this application, developed to test the principle, it is a windkessel representing the systemic arterial tree. The lumped parameters numerical model was developed in LabVIEW environment and represents pulmonary and systemic circulation (except the systemic arterial tree). Based on the equivalence between hydraulic and electrical circuits, this prototype was developed connecting the numerical model to an electrical circuit--the physical model. This specific solution is valid mainly educationally but permits the development of software and the verification of preliminary results without using cumbersome hydraulic circuits. The interfaces between numerical and electrical circuits are set up by a voltage controlled current generator and a voltage controlled voltage generator. The behavior of the model is analyzed based on the ventricular pressure-volume loops and on the time course of arterial and ventricular pressures and flow in different circulatory conditions. The model can represent hemodynamic relationships in different ventricular and circulatory conditions.

  9. Homology modeling and docking studies of a Δ9-fatty acid desaturase from a Cold-tolerant Pseudomonas sp. AMS8

    Directory of Open Access Journals (Sweden)

    Lawal Garba

    2018-03-01

    Full Text Available Membrane-bound fatty acid desaturases perform oxygenated desaturation reactions to insert double bonds within fatty acyl chains in regioselective and stereoselective manners. The Δ9-fatty acid desaturase strictly creates the first double bond between C9 and 10 positions of most saturated substrates. As the three-dimensional structures of the bacterial membrane fatty acid desaturases are not available, relevant information about the enzymes are derived from their amino acid sequences, site-directed mutagenesis and domain swapping in similar membrane-bound desaturases. The cold-tolerant Pseudomonas sp. AMS8 was found to produce high amount of monounsaturated fatty acids at low temperature. Subsequently, an active Δ9-fatty acid desaturase was isolated and functionally expressed in Escherichia coli. In this paper we report homology modeling and docking studies of a Δ9-fatty acid desaturase from a Cold-tolerant Pseudomonas sp. AMS8 for the first time to the best of our knowledge. Three dimensional structure of the enzyme was built using MODELLER version 9.18 using a suitable template. The protein model contained the three conserved-histidine residues typical for all membrane-bound desaturase catalytic activity. The structure was subjected to energy minimization and checked for correctness using Ramachandran plots and ERRAT, which showed a good quality model of 91.6 and 65.0%, respectively. The protein model was used to preform MD simulation and docking of palmitic acid using CHARMM36 force field in GROMACS Version 5 and Autodock tool Version 4.2, respectively. The docking simulation with the lowest binding energy, −6.8 kcal/mol had a number of residues in close contact with the docked palmitic acid namely, Ile26, Tyr95, Val179, Gly180, Pro64, Glu203, His34, His206, His71, Arg182, Thr85, Lys98 and His177. Interestingly, among the binding residues are His34, His71 and His206 from the first, second, and third conserved histidine motif, respectively

  10. Mechanical Properties of Graphene Nanoplatelet/Carbon Fiber/Epoxy Hybrid Composites: Multiscale Modeling and Experiments

    Science.gov (United States)

    Hadden, C. M.; Klimek-McDonald, D. R.; Pineda, E. J.; King, J. A.; Reichanadter, A. M.; Miskioglu, I.; Gowtham, S.; Odegard, G. M.

    2015-01-01

    Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite, while the effect on the axial properties is shown to be insignificant.

  11. Mechanical Properties of Graphene Nanoplatelet Carbon Fiber Epoxy Hybrid Composites: Multiscale Modeling and Experiments

    Science.gov (United States)

    Hadden, Cameron M.; Klimek-McDonald, Danielle R.; Pineda, Evan J.; King, Julie A.; Reichanadter, Alex M.; Miskioglu, Ibrahim; Gowtham, S.; Odegard, Gregory M.

    2015-01-01

    Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite, while the effect on the axial properties is shown to be insignificant.

  12. Modeling and Simulation of Renewable Hybrid Power System using Matlab Simulink Environment

    Directory of Open Access Journals (Sweden)

    Cristian Dragoş Dumitru

    2010-12-01

    Full Text Available The paper presents the modeling of a solar-wind-hydroelectric hybrid system in Matlab/Simulink environment. The application is useful for analysis and simulation of a real hybrid solar-wind-hydroelectric system connected to a public grid. Application is built on modular architecture to facilitate easy study of each component module influence. Blocks like wind model, solar model, hydroelectric model, energy conversion and load are implemented and the results of simulation are also presented. As an example, one of the most important studies is the behavior of hybrid system which allows employing renewable and variable in time energy sources while providing a continuous supply. Application represents a useful tool in research activity and also in teaching

  13. Coupled thermal model of photovoltaic-thermoelectric hybrid panel for sample cities in Europe

    DEFF Research Database (Denmark)

    Rezaniakolaei, Alireza; Sera, Dezso; Rosendahl, Lasse Aistrup

    2016-01-01

    of the hybrid system under different weather conditions. The model takes into account solar irradiation, wind speed and ambient temperature as well as convective and radiated heat losses from the front and rear surfaces of the panel. The model is developed for three sample cities in Europe with different......In general, modeling of photovoltaic-thermoelectric (PV/TEG) hybrid panels have been mostly simplified and disconnected from the actual ambient conditions and thermal losses from the panel. In this study, a thermally coupled model of PV/TEG panel is established to precisely predict performance...... weather conditions. The results show that radiated heat loss from the front surface and the convective heat loss due to the wind speed are the most critical parameters on performance of the hybrid panel performance. The results also indicate that, with existing thermoelectric materials, the power...

  14. Non-Poisson counting statistics of a hybrid G-M counter dead time model

    International Nuclear Information System (INIS)

    Lee, Sang Hoon; Jae, Moosung; Gardner, Robin P.

    2007-01-01

    The counting statistics of a G-M counter with a considerable dead time event rate deviates from Poisson statistics. Important characteristics such as observed counting rates as a function true counting rates, variances and interval distributions were analyzed for three dead time models, non-paralyzable, paralyzable and hybrid, with the help of GMSIM, a Monte Carlo dead time effect simulator. The simulation results showed good agreements with the models in observed counting rates and variances. It was found through GMSIM simulations that the interval distribution for the hybrid model showed three distinctive regions, a complete cutoff region for the duration of the total dead time, a degraded exponential and an enhanced exponential regions. By measuring the cutoff and the duration of degraded exponential from the pulse interval distribution, it is possible to evaluate the two dead times in the hybrid model

  15. Performance modeling of hybrid MPI/OpenMP scientific applications on large-scale multicore supercomputers

    KAUST Repository

    Wu, Xingfu; Taylor, Valerie

    2013-01-01

    In this paper, we present a performance modeling framework based on memory bandwidth contention time and a parameterized communication model to predict the performance of OpenMP, MPI and hybrid applications with weak scaling on three large-scale multicore supercomputers: IBM POWER4, POWER5+ and BlueGene/P, and analyze the performance of these MPI, OpenMP and hybrid applications. We use STREAM memory benchmarks and Intel's MPI benchmarks to provide initial performance analysis and model validation of MPI and OpenMP applications on these multicore supercomputers because the measured sustained memory bandwidth can provide insight into the memory bandwidth that a system should sustain on scientific applications with the same amount of workload per core. In addition to using these benchmarks, we also use a weak-scaling hybrid MPI/OpenMP large-scale scientific application: Gyrokinetic Toroidal Code (GTC) in magnetic fusion to validate our performance model of the hybrid application on these multicore supercomputers. The validation results for our performance modeling method show less than 7.77% error rate in predicting the performance of hybrid MPI/OpenMP GTC on up to 512 cores on these multicore supercomputers. © 2013 Elsevier Inc.

  16. Performance modeling of hybrid MPI/OpenMP scientific applications on large-scale multicore supercomputers

    KAUST Repository

    Wu, Xingfu

    2013-12-01

    In this paper, we present a performance modeling framework based on memory bandwidth contention time and a parameterized communication model to predict the performance of OpenMP, MPI and hybrid applications with weak scaling on three large-scale multicore supercomputers: IBM POWER4, POWER5+ and BlueGene/P, and analyze the performance of these MPI, OpenMP and hybrid applications. We use STREAM memory benchmarks and Intel\\'s MPI benchmarks to provide initial performance analysis and model validation of MPI and OpenMP applications on these multicore supercomputers because the measured sustained memory bandwidth can provide insight into the memory bandwidth that a system should sustain on scientific applications with the same amount of workload per core. In addition to using these benchmarks, we also use a weak-scaling hybrid MPI/OpenMP large-scale scientific application: Gyrokinetic Toroidal Code (GTC) in magnetic fusion to validate our performance model of the hybrid application on these multicore supercomputers. The validation results for our performance modeling method show less than 7.77% error rate in predicting the performance of hybrid MPI/OpenMP GTC on up to 512 cores on these multicore supercomputers. © 2013 Elsevier Inc.

  17. Fluid Petri Nets and hybrid model-checking: a comparative case study

    International Nuclear Information System (INIS)

    Gribaudo, M.; Horvath, A.; Bobbio, A.; Tronci, E.; Ciancamerla, E.; Minichino, M.

    2003-01-01

    The modeling and analysis of hybrid systems is a recent and challenging research area which is actually dominated by two main lines: a functional analysis based on the description of the system in terms of discrete state (hybrid) automata (whose goal is to ascertain conformity and reachability properties), and a stochastic analysis (whose aim is to provide performance and dependability measures). This paper investigates a unifying view between formal methods and stochastic methods by proposing an analysis methodology of hybrid systems based on Fluid Petri Nets (FPNs). FPNs can be analyzed directly using appropriate tools. Our paper shows that the same FPN model can be fed to different functional analyzers for model checking. In order to extensively explore the capability of the technique, we have converted the original FPN into languages for discrete as well as hybrid as well as stochastic model checkers. In this way, a first comparison among the modeling power of well known tools can be carried out. Our approach is illustrated by means of a 'real world' hybrid system: the temperature control system of a co-generative plant

  18. Modeling hydraulic regenerative hybrid vehicles using AMESim and Matlab/Simulink

    Science.gov (United States)

    Lynn, Alfred; Smid, Edzko; Eshraghi, Moji; Caldwell, Niall; Woody, Dan

    2005-05-01

    This paper presents the overview of the simulation modeling of a hydraulic system with regenerative braking used to improve vehicle emissions and fuel economy. Two simulation software packages were used together to enhance the simulation capability for fuel economy results and development of vehicle and hybrid control strategy. AMESim, a hydraulic simulation software package modeled the complex hydraulic circuit and component hardware and was interlinked with a Matlab/Simulink model of the vehicle, engine and the control strategy required to operate the vehicle and the hydraulic hybrid system through various North American and European drive cycles.

  19. Heteronuclear multidimensional NMR and homology modelling studies of the C-terminal nucleotide-binding domain of the human mitochondrial ABC transporter ABCB6

    Energy Technology Data Exchange (ETDEWEB)

    Kurashima-Ito, Kaori [RIKEN, Cellular and Molecular Biology Laboratory (Japan); Ikeya, Teppei [National Institute of Advanced Industrial Science and Technology (AIST), (Japan); Senbongi, Hiroshi [Mitochondrial Diseases Group, MRC Dunn Human NutritionUnit (United Kingdom); Tochio, Hidehito [International Graduate School of Arts and Sciences, Supramolecular Biology, Yokohama City University, Molecular Biophysics Laboratory (Japan); Mikawa, Tsutomu [RIKEN, Cellular and Molecular Biology Laboratory (Japan); Shibata, Takehiko [RIKEN, Shibata Distinguished Senior Scientist Laboratory (Japan); Ito, Yutaka [RIKEN, Cellular and Molecular Biology Laboratory (Japan)], E-mail: ito-yutaka@center.tmu.ac.jp

    2006-05-15

    Human ATP-binding cassette, sub-family B, member 6 (ABCB6) is a mitochondrial ABC transporter, and presumably contributes to iron homeostasis. Aimed at understanding the structural basis for the conformational changes accompanying the substrate-transportation cycle, we have studied the C-terminal nucleotide-binding domain of ABCB6 (ABCB6-C) in both the nucleotide-free and ADP-bound states by heteronuclear multidimensional NMR and homology modelling. A non-linear sampling scheme was utilised for indirectly acquired {sup 13}C and {sup 15}N dimensions of all 3D triple-resonance NMR experiments, in order to overcome the instability and the low solubility of ABCB6-C. The backbone resonances for approximately 25% of non-proline residues, which are mostly distributed around the functionally important loops and in the Helical domain, were not observed for nucleotide-free form of ABCB6-C. From the pH, temperature and magnetic field strength dependencies of the resonance intensities, we concluded that this incompleteness in the assignments is mainly due to the exchange between multiple conformations at an intermediate rate on the NMR timescale. These localised conformational dynamics remained in ADP-bound ABCB6-C except for the loops responsible for adenine base and {alpha}/{beta}-phosphate binding. These results revealed that the localised dynamic cooperativity, which was recently proposed for a prokaryotic ABC MJ1267, also exists in a higher eukaryotic ABC, and is presumably shared by all members of the ABC family. Since the Helical domain is the putative interface to the transmembrane domain, this cooperativity may explain the coupled functions between domains in the substrate-transportation cycle.

  20. Hybrid modeling approach to improve the forecasting capability for the gaseous radionuclide in a nuclear site

    International Nuclear Information System (INIS)

    Jeong, Hyojoon; Hwang, Wontae; Kim, Eunhan; Han, Moonhee

    2012-01-01

    Highlights: ► This study is to improve the reliability of air dispersion modeling. ► Tracer experiments assumed gaseous radionuclides were conducted at a nuclear site. ► The performance of a hybrid modeling combined ISC with ANFIS was investigated.. ► Hybrid modeling approach shows better performance rather than a single ISC model. - Abstract: Predicted air concentrations of radioactive materials are important for an environmental impact assessment for the public health. In this study, the performance of a hybrid modeling combined with the industrial source complex (ISC) model and an adaptive neuro-fuzzy inference system (ANFIS) for predicting tracer concentrations was investigated. Tracer dispersion experiments were performed to produce the field data assuming the accidental release of radioactive material. ANFIS was trained in order that the outputs of the ISC model are similar to the measured data. Judging from the higher correlation coefficients between the measured and the calculated ones, the hybrid modeling approach could be an appropriate technique for an improvement of the modeling capability to predict the air concentrations for radioactive materials.

  1. A hybrid modeling with data assimilation to evaluate human exposure level

    Science.gov (United States)

    Koo, Y. S.; Cheong, H. K.; Choi, D.; Kim, A. L.; Yun, H. Y.

    2015-12-01

    Exposure models are designed to better represent human contact with PM (Particulate Matter) and other air pollutants such as CO, SO2, O3, and NO2. The exposure concentrations of the air pollutants to human are determined by global and regional long range transport of global and regional scales from Europe and China as well as local emissions from urban and road vehicle sources. To assess the exposure level in detail, the multiple scale influence from background to local sources should be considered. A hybrid air quality modeling methodology combing a grid-based chemical transport model with a local plume dispersion model was used to provide spatially and temporally resolved air quality concentration for human exposure levels in Korea. In the hybrid modeling approach, concentrations from a grid-based chemical transport model and a local plume dispersion model are added to provide contributions from photochemical interactions, long-range (regional) transport and local-scale dispersion. The CAMx (Comprehensive Air quality Model with Extensions was used for the background concentrations from anthropogenic and natural emissions in East Asia including Korea while the road dispersion by vehicle emission was calculated by CALPUFF model. The total exposure level of the pollutants was finally assessed by summing the background and road contributions. In the hybrid modeling, the data assimilation method based on the optimal interpolation was applied to overcome the discrepancies between the model predicted concentrations and observations. The air quality data from the air quality monitoring stations in Korea. The spatial resolution of the hybrid model was 50m for the Seoul Metropolitan Ares. This example clearly demonstrates that the exposure level could be estimated to the fine scale for the exposure assessment by using the hybrid modeling approach with data assimilation.

  2. Modeling and performance analysis of a concentrated photovoltaic–thermoelectric hybrid power generation system

    International Nuclear Information System (INIS)

    Lamba, Ravita; Kaushik, S.C.

    2016-01-01

    Highlights: • Thermodynamic model of concentrated photovoltaic–thermoelectric system is analysed. • Thomson effect reduces the power output of PV, TE and hybrid PV–TEG system. • Effect of thermocouple number, irradiance, PV and TE current have been studied. • The optimum concentration ratio for maximum power output has been found out. • The overall efficiency and power output of hybrid PV–TEG system has been improved. - Abstract: In this study, a thermodynamic model for analysing the performance of a concentrated photovoltaic–thermoelectric generator (CPV–TEG) hybrid system including Thomson effect in conjunction with Seebeck, Joule and Fourier heat conduction effects has been developed and simulated in MATALB environment. The expressions for calculating the temperature of photovoltaic (PV) module, hot and cold sides of thermoelectric (TE) module are derived analytically as well. The effect of concentration ratio, number of thermocouples in TE module, solar irradiance, PV module current and TE module current on power output and efficiency of the PV, TEG and hybrid PV–TEG system have been studied. The optimum concentration ratio corresponding to maximum power output of the hybrid system has been found out. It has been observed that by considering Thomson effect in TEG module, the power output of the PV, TE and hybrid PV–TEG systems decreases and at C = 1 and 5, it reduces the power output of hybrid system by 0.7% and 4.78% respectively. The results of this study may provide basis for performance optimization of a practical irreversible CPV–TEG hybrid system.

  3. Image Restoration Based on the Hybrid Total-Variation-Type Model

    OpenAIRE

    Shi, Baoli; Pang, Zhi-Feng; Yang, Yu-Fei

    2012-01-01

    We propose a hybrid total-variation-type model for the image restoration problem based on combining advantages of the ROF model with the LLT model. Since two ${L}^{1}$ -norm terms in the proposed model make it difficultly solved by using some classically numerical methods directly, we first employ the alternating direction method of multipliers (ADMM) to solve a general form of the proposed model. Then, based on the ADMM and the Moreau-Yosida decomposition theory, a more efficient method call...

  4. Hybrid microscopic depletion model in nodal code DYN3D

    International Nuclear Information System (INIS)

    Bilodid, Y.; Kotlyar, D.; Shwageraus, E.; Fridman, E.; Kliem, S.

    2016-01-01

    Highlights: • A new hybrid method of accounting for spectral history effects is proposed. • Local concentrations of over 1000 nuclides are calculated using micro depletion. • The new method is implemented in nodal code DYN3D and verified. - Abstract: The paper presents a general hybrid method that combines the micro-depletion technique with correction of micro- and macro-diffusion parameters to account for the spectral history effects. The fuel in a core is subjected to time- and space-dependent operational conditions (e.g. coolant density), which cannot be predicted in advance. However, lattice codes assume some average conditions to generate cross sections (XS) for nodal diffusion codes such as DYN3D. Deviation of local operational history from average conditions leads to accumulation of errors in XS, which is referred as spectral history effects. Various methods to account for the spectral history effects, such as spectral index, burnup-averaged operational parameters and micro-depletion, were implemented in some nodal codes. Recently, an alternative method, which characterizes fuel depletion state by burnup and 239 Pu concentration (denoted as Pu-correction) was proposed, implemented in nodal code DYN3D and verified for a wide range of history effects. The method is computationally efficient, however, it has applicability limitations. The current study seeks to improve the accuracy and applicability range of Pu-correction method. The proposed hybrid method combines the micro-depletion method with a XS characterization technique similar to the Pu-correction method. The method was implemented in DYN3D and verified on multiple test cases. The results obtained with DYN3D were compared to those obtained with Monte Carlo code Serpent, which was also used to generate the XS. The observed differences are within the statistical uncertainties.

  5. PUMP: analog-hybrid reactor coolant hydraulic transient model

    International Nuclear Information System (INIS)

    Grandia, M.R.

    1976-03-01

    The PUMP hybrid computer code simulates flow and pressure distribution; it is used to determine real time response to starting and tripping all combinations of PWR reactor coolant pumps in a closed, pressurized, four-pump, two-loop primary system. The simulation includes the description of flow, pressure, speed, and torque relationships derived through pump affinity laws and from vendor-supplied pump zone maps to describe pump dynamic characteristics. The program affords great flexibility in the type of transients that can be simulated

  6. Improving Hybrid III injury assessment in steering wheel rim to chest impacts using responses from finite element Hybrid III and human body model.

    Science.gov (United States)

    Holmqvist, Kristian; Davidsson, Johan; Mendoza-Vazquez, Manuel; Rundberget, Peter; Svensson, Mats Y; Thorn, Stefan; Törnvall, Fredrik

    2014-01-01

    The main aim of this study was to improve the quality of injury risk assessments in steering wheel rim to chest impacts when using the Hybrid III crash test dummy in frontal heavy goods vehicle (HGV) collision tests. Correction factors for chest injury criteria were calculated as the model chest injury parameter ratios between finite element (FE) Hybrid III, evaluated in relevant load cases, and the Total Human Model for Safety (THUMS). This is proposed to be used to compensate Hybrid III measurements in crash tests where steering wheel rim to chest impacts occur. The study was conducted in an FE environment using an FE-Hybrid III model and the THUMS. Two impactor shapes were used, a circular hub and a long, thin horizontal bar. Chest impacts at velocities ranging from 3.0 to 6.0 m/s were simulated at 3 impact height levels. A ratio between FE-Hybrid III and THUMS chest injury parameters, maximum chest compression C max, and maximum viscous criterion VC max, were calculated for the different chest impact conditions to form a set of correction factors. The definition of the correction factor is based on the assumption that the response from a circular hub impact to the middle of the chest is well characterized and that injury risk measures are independent of impact height. The current limits for these chest injury criteria were used as a basis to develop correction factors that compensate for the limitations in biofidelity of the Hybrid III in steering wheel rim to chest impacts. The hub and bar impactors produced considerably higher C max and VC max responses in the THUMS compared to the FE-Hybrid III. The correction factor for the responses of the FE-Hybrid III showed that the criteria responses for the bar impactor were consistently overestimated. Ratios based on Hybrid III and THUMS responses provided correction factors for the Hybrid III responses ranging from 0.84 to 0.93. These factors can be used to estimate C max and VC max values when the Hybrid III is

  7. A Four-Stage Hybrid Model for Hydrological Time Series Forecasting

    Science.gov (United States)

    Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

    2014-01-01

    Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of ‘denoising, decomposition and ensemble’. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models. PMID:25111782

  8. A four-stage hybrid model for hydrological time series forecasting.

    Science.gov (United States)

    Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

    2014-01-01

    Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of 'denoising, decomposition and ensemble'. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models.

  9. Chemical shift homology in proteins

    International Nuclear Information System (INIS)

    Potts, Barbara C.M.; Chazin, Walter J.

    1998-01-01

    The degree of chemical shift similarity for homologous proteins has been determined from a chemical shift database of over 50 proteins representing a variety of families and folds, and spanning a wide range of sequence homologies. After sequence alignment, the similarity of the secondary chemical shifts of C α protons was examined as a function of amino acid sequence identity for 37 pairs of structurally homologous proteins. A correlation between sequence identity and secondary chemical shift rmsd was observed. Important insights are provided by examining the sequence identity of homologous proteins versus percentage of secondary chemical shifts that fall within 0.1 and 0.3 ppm thresholds. These results begin to establish practical guidelines for the extent of chemical shift similarity to expect among structurally homologous proteins

  10. Examining the Etiology of Reading Disability as Conceptualized by the Hybrid Model

    Science.gov (United States)

    Erbeli, Florina; Hart, Sara A.; Wagner, Richard K.; Taylor, Jeanette

    2018-01-01

    A fairly recent definition of reading disability (RD) is that in the form of a hybrid model. The model views RD as a latent construct that is manifested through various observable unexpected impairments in reading-related skills and through inadequate response to intervention. The current report evaluated this new conceptualization of RD from an…

  11. Assessing the Therapeutic Environment in Hybrid Models of Treatment: Prisoner Perceptions of Staff

    Science.gov (United States)

    Kubiak, Sheryl Pimlott

    2009-01-01

    Hybrid treatment models within prisons are staffed by both criminal justice and treatment professionals. Because these models may be indicative of future trends, examining the perceptions of prisoners/participants may provide important information. This study examines the perceptions of male and female inmates in three prisons, comparing those in…

  12. New Hybrid Variational Recovery Model for Blurred Images with Multiplicative Noise

    DEFF Research Database (Denmark)

    Dong, Yiqiu; Zeng, Tieyong

    2013-01-01

    A new hybrid variational model for recovering blurred images in the presence of multiplicative noise is proposed. Inspired by previous work on multiplicative noise removal, an I-divergence technique is used to build a strictly convex model under a condition that ensures the uniqueness...

  13. Rapidity distributions of hadrons in the HydHSD hybrid model

    Energy Technology Data Exchange (ETDEWEB)

    Khvorostukhin, A. S., E-mail: hvorost@theor.jinr.ru; Toneev, V. D. [Joint Institute for Nuclear Research (Russian Federation)

    2017-03-15

    A multistage hybrid model intended for describing heavy-ion interactions in the energy region of the NICA collider under construction in Dubna is proposed. The model combines the initial, fast, interaction stage described by the model of hadron string dynamics (HSD) and the subsequent evolution that the expanding system formed at the first stage experiences at the second stage and which one treats on the basis of ideal hydrodynamics; after the completion of the second stage, the particles involved may still undergo rescattering (third interaction stage). The model admits three freeze-out scenarios: isochronous, isothermal, and isoenergetic. Generally, the HydHSD hybrid model developed in the present study provides fairly good agreement with available experimental data on proton rapidity spectra. It is shown that, within this hybrid model, the two-humped structure of proton rapidity distributions can be obtained either by increasing the freeze-out temperature and energy density or by more lately going over to the hydrodynamic stage. Although the proposed hybrid model reproduces rapidity spectra of protons, it is unable to describe rapidity distributions of pions, systematically underestimating their yield. It is necessary to refine the model by including viscosity effects at the hydrodynamic stage of evolution of the system and by considering in more detail the third interaction stage.

  14. Hybrid modelling framework by using mathematics-based and information-based methods

    International Nuclear Information System (INIS)

    Ghaboussi, J; Kim, J; Elnashai, A

    2010-01-01

    Mathematics-based computational mechanics involves idealization in going from the observed behaviour of a system into mathematical equations representing the underlying mechanics of that behaviour. Idealization may lead mathematical models that exclude certain aspects of the complex behaviour that may be significant. An alternative approach is data-centric modelling that constitutes a fundamental shift from mathematical equations to data that contain the required information about the underlying mechanics. However, purely data-centric methods often fail for infrequent events and large state changes. In this article, a new hybrid modelling framework is proposed to improve accuracy in simulation of real-world systems. In the hybrid framework, a mathematical model is complemented by information-based components. The role of informational components is to model aspects which the mathematical model leaves out. The missing aspects are extracted and identified through Autoprogressive Algorithms. The proposed hybrid modelling framework has a wide range of potential applications for natural and engineered systems. The potential of the hybrid methodology is illustrated through modelling highly pinched hysteretic behaviour of beam-to-column connections in steel frames.

  15. Data Fusion Modeling for an RT3102 and Dewetron System Application in Hybrid Vehicle Stability Testing

    Directory of Open Access Journals (Sweden)

    Zhibin Miao

    2015-08-01

    Full Text Available More and more hybrid electric vehicles are driven since they offer such advantages as energy savings and better active safety performance. Hybrid vehicles have two or more power driving systems and frequently switch working condition, so controlling stability is very important. In this work, a two-stage Kalman algorithm method is used to fuse data in hybrid vehicle stability testing. First, the RT3102 navigation system and Dewetron system are introduced. Second, a modeling of data fusion is proposed based on the Kalman filter. Then, this modeling is simulated and tested on a sample vehicle, using Carsim and Simulink software to test the results. The results showed the merits of this modeling.

  16. Modular modeling and simulation of hybrid power trains; Modulare Modellbildung und Simulation von hybriden Antriebstraengen

    Energy Technology Data Exchange (ETDEWEB)

    Kelz, Gerald; Hirschberg, Wolfgang [Inst. fuer Fahrzeugtechnik, Technische Univ. Graz (Austria)

    2009-07-01

    The power train of a hybrid vehicle is considerably more complex than that of conventional vehicles. Whilst the topology of a conventional vehicle is normally fixed, the arrangement of the power train components for innovative propulsion systems is a flexible one. The aim is to find those topologies and configurations which are optimal for the intended use. Fuel consumption potentials can be derived with the aid of vehicle longitudinal dynamics simulation. Mostly these simulations are carried out using commercial software which is optimized for the standard topology and do not offer the flexibility to calculate arbitrary topologies. This article covers the modular modeling and the fuel consumption simulation of complex hybrid power trains for topology analysis. A component library for the development of arbitrary hybrid propulsion systems is introduced. The focus lies on an efficient and fast modeling which provides exact simulation results. Several models of power train components are introduced. (orig.)

  17. Design and fabrication of a hybrid maglev model employing PML and SML

    Science.gov (United States)

    Sun, R. X.; Zheng, J.; Zhan, L. J.; Huang, S. Y.; Li, H. T.; Deng, Z. G.

    2017-10-01

    A hybrid maglev model combining permanent magnet levitation (PML) and superconducting magnetic levitation (SML) was designed and fabricated to explore a heavy-load levitation system advancing in passive stability and simple structure. In this system, the PML was designed to levitate the load, and the SML was introduced to guarantee the stability. In order to realize different working gaps of the two maglev components, linear bearings were applied to connect the PML layer (for load) and the SML layer (for stability) of the hybrid maglev model. Experimental results indicate that the hybrid maglev model possesses excellent advantages of heavy-load ability and passive stability at the same time. This work presents a possible way to realize a heavy-load passive maglev concept.

  18. Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †

    Directory of Open Access Journals (Sweden)

    René Felix Reinhart

    2017-02-01

    Full Text Available Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms.

  19. Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control.

    Science.gov (United States)

    Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob

    2017-02-08

    Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant's intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms.

  20. Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †

    Science.gov (United States)

    Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob

    2017-01-01

    Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms. PMID:28208697

  1. Study on driver model for hybrid truck based on driving simulator experimental results

    Directory of Open Access Journals (Sweden)

    Dam Hoang Phuc

    2018-04-01

    Full Text Available In this paper, a proposed car-following driver model taking into account some features of both the compensatory and anticipatory model representing the human pedal operation has been verified by driving simulator experiments with several real drivers. The comparison between computer simulations performed by determined model parameters with the experimental results confirm the correctness of this mathematical driver model and identified model parameters. Then the driver model is joined to a hybrid vehicle dynamics model and the moderate car following maneuver simulations with various driver parameters are conducted to investigate influences of driver parameters on vehicle dynamics response and fuel economy. Finally, major driver parameters involved in the longitudinal control of drivers are clarified. Keywords: Driver model, Driver-vehicle closed-loop system, Car Following, Driving simulator/hybrid electric vehicle (B1

  2. Hybrid Spatial Data Model for Indoor Space: Combined Topology and Grid

    Directory of Open Access Journals (Sweden)

    Zhiyong Lin

    2017-11-01

    Full Text Available The construction and application of an indoor spatial data model is an important prerequisite to meet the requirements of diversified indoor spatial location services. The traditional indoor spatial topology model focuses on the construction of topology information. It has high path analysis and query efficiency, but ignores the spatial location information. The grid model retains the plane position information by grid, but increases the data volume and complexity of the model and reduces the efficiency of the model analysis. This paper presents a hybrid model for interior space based on topology and grid. Based on the spatial meshing and spatial division of the interior space, the model retains the position information and topological connectivity information of the interior space by establishing the connection or affiliation between the grid subspace and the topological subspace. The model improves the speed of interior spatial analysis and solves the problem of the topology information and location information updates not being synchronized. In this study, the A* shortest path query efficiency of typical daily indoor activities under the grid model and the hybrid model were compared for the indoor plane of an apartment and a shopping mall. The results obtained show that the hybrid model is 43% higher than the A* algorithm of the grid model as a result of the existence of topology communication information. This paper provides a useful idea for the establishment of a highly efficient and highly available interior spatial data model.

  3. Modeling, analysis and control of fuel cell hybrid power systems

    Science.gov (United States)

    Suh, Kyung Won

    Transient performance is a key characteristic of fuel cells, that is sometimes more critical than efficiency, due to the importance of accepting unpredictable electric loads. To fulfill the transient requirement in vehicle propulsion and portable fuel cell applications, a fuel cell stack is typically coupled with a battery through a DC/DC converter to form a hybrid power system. Although many power management strategies already exist, they all rely on low level controllers that realize the power split. In this dissertation we design controllers that realize various power split strategies by directly manipulating physical actuators (low level commands). We maintain the causality of the electric dynamics (voltage and current) and investigate how the electric architecture affects the hybridization level and the power management. We first establish the performance limitations associated with a stand-alone and power-autonomous fuel cell system that is not supplemented by an additional energy storage and powers all its auxiliary components by itself. Specifically, we examine the transient performance in fuel cell power delivery as it is limited by the air supplied by a compressor driven by the fuel cell itself. The performance limitations arise from the intrinsic coupling in the fluid and electrical domain between the compressor and the fuel cell stack. Feedforward and feedback control strategies are used to demonstrate these limitations analytically and with simulations. Experimental tests on a small commercial fuel cell auxiliary power unit (APU) confirm the dynamics and the identified limitations. The dynamics associated with the integration of a fuel cell system and a DC/DC converter is then investigated. Decentralized and fully centralized (using linear quadratic techniques) controllers are designed to regulate the power system voltage and to prevent fuel cell oxygen starvation. Regulating these two performance variables is a difficult task and requires a compromise

  4. Switched causual modeling of transmission with clutch in hybrid electric vehicles

    OpenAIRE

    LHOMME, W; TRIGUI, R; DELARU, P; JEANNERET, B; BOUSCAUROL, A; BADIN, F

    2008-01-01

    Certain difficulties arise when attempting to model a clutch in a power train transmission due to its nonlinear behavior. Two different states have to be taken into account-the first being when the clutch is locked and the second being when the clutch is slipping. In this paper, a clutch model is developed using the Energetic Macroscopic Representation, which is, in turn, used in the modeling of complete hybrid electric vehicles (HEVs). Two different models are used, and a specific condition ...

  5. Plausible carrier transport model in organic-inorganic hybrid perovskite resistive memory devices

    Science.gov (United States)

    Park, Nayoung; Kwon, Yongwoo; Choi, Jaeho; Jang, Ho Won; Cha, Pil-Ryung

    2018-04-01

    We demonstrate thermally assisted hopping (TAH) as an appropriate carrier transport model for CH3NH3PbI3 resistive memories. Organic semiconductors, including organic-inorganic hybrid perovskites, have been previously speculated to follow the space-charge-limited conduction (SCLC) model. However, the SCLC model cannot reproduce the temperature dependence of experimental current-voltage curves. Instead, the TAH model with temperature-dependent trap densities and a constant trap level are demonstrated to well reproduce the experimental results.

  6. Solving Problem of Graph Isomorphism by Membrane-Quantum Hybrid Model

    Directory of Open Access Journals (Sweden)

    Artiom Alhazov

    2015-10-01

    Full Text Available This work presents the application of new parallelization methods based on membrane-quantum hybrid computing to graph isomorphism problem solving. Applied membrane-quantum hybrid computational model was developed by authors. Massive parallelism of unconventional computing is used to implement classic brute force algorithm efficiently. This approach does not suppose any restrictions of considered graphs types. The estimated performance of the model is less then quadratic that makes a very good result for the problem of \\textbf{NP} complexity.

  7. Immunogenicity and Protective Efficacy of Brugia malayi Heavy Chain Myosin as Homologous DNA, Protein and Heterologous DNA/Protein Prime Boost Vaccine in Rodent Model.

    Directory of Open Access Journals (Sweden)

    Jyoti Gupta

    Full Text Available We earlier demonstrated the immunoprophylactic efficacy of recombinant heavy chain myosin (Bm-Myo of Brugia malayi (B. malayi in rodent models. In the current study, further attempts have been made to improve this efficacy by employing alternate approaches such as homologous DNA (pcD-Myo and heterologous DNA/protein prime boost (pcD-Myo+Bm-Myo in BALB/c mouse model. The gene bm-myo was cloned in a mammalian expression vector pcDNA 3.1(+ and protein expression was confirmed in mammalian Vero cell line. A significant degree of protection (79.2%±2.32 against L3 challenge in pcD-Myo+Bm-Myo immunized group was observed which was much higher than that exerted by Bm-Myo (66.6%±2.23 and pcD-Myo (41.6%±2.45. In the heterologous immunized group, the percentage of peritoneal leukocytes such as macrophages, neutrophils, B cells and T cells marginally increased and their population augmented further significantly following L3 challenge. pcD-Myo+Bm-Myo immunization elicited robust cellular and humoral immune responses as compared to pcD-Myo and Bm-Myo groups as evidenced by an increased accumulation of CD4+, CD8+ T cells and CD19+ B cells in the mouse spleen and activation of peritoneal macrophages. Though immunized animals produced antigen-specific IgG antibodies and isotypes, sera of mice receiving pcD-Myo+Bm-Myo or Bm-Myo developed much higher antibody levels than other groups and there was profound antibody-dependent cellular adhesion and cytotoxicity (ADCC to B. malayi infective larvae (L3. pcD-Myo+Bm-Myo as well as Bm-Myo mice generated a mixed T helper cell phenotype as evidenced by the production of both pro-inflammatory (IL-2, IFN-γ and anti-inflammatory (IL-4, IL-10 cytokines. Mice receiving pcD-Myo on contrary displayed a polarized pro-inflammatory immune response. The findings suggest that the priming of animals with DNA followed by protein booster generates heightened and mixed pro- and anti-inflammatory immune responses that are capable of

  8. Numerical modeling of lower hybrid heating and current drive

    International Nuclear Information System (INIS)

    Valeo, E.J.; Eder, D.C.

    1986-03-01

    The generation of currents in toroidal plasma by application of waves in the lower hybrid frequency range involves the interplay of several physical phenomena which include: wave propagation in toroidal geometry, absorption via wave-particle resonances, the quasilinear generation of strongly nonequilibrium electron and ion distribution functions, and the self-consistent evolution of the current density in such a nonequilibrium plasma. We describe a code, LHMOD, which we have developed to treat these aspects of current drive and heating in tokamaks. We present results obtained by applying the code to a computation of current ramp-up and to an investigation of the possible importance of minority hydrogen absorption in a deuterium plasma as the ''density limit'' to current drive is approached

  9. Gas ultracentrifuge separative parameters modeling using hybrid neural networks

    International Nuclear Information System (INIS)

    Crus, Maria Ursulina de Lima

    2005-01-01

    A hybrid neural network is developed for the calculation of the separative performance of an ultracentrifuge. A feed forward neural network is trained to estimate the internal flow parameters of a gas ultracentrifuge, and then these parameters are applied in the diffusion equation. For this study, a 573 experimental data set is used to establish the relation between the separative performance and the controlled variables. The process control variables considered are: the feed flow rate F, the cut θ and the product pressure Pp. The mechanical arrangements consider the radial waste scoop dimension, the rotating baffle size D s and the axial feed location Z E . The methodology was validated through the comparison of the calculated separative performance with experimental values. This methodology may be applied to other processes, just by adapting the phenomenological procedures. (author)

  10. A Hybrid Wind-Farm Parametrization for Mesoscale and Climate Models

    Science.gov (United States)

    Pan, Yang; Archer, Cristina L.

    2018-04-01

    To better understand the potential impact of wind farms on weather and climate at the regional to global scales, a new hybrid wind-farm parametrization is proposed for mesoscale and climate models. The proposed parametrization is a hybrid model because it is not based on physical processes or conservation laws, but on the multiple linear regression of the results of large-eddy simulations (LES) with the geometric properties of the wind-farm layout (e.g., the blockage ratio and blockage distance). The innovative aspect is that each wind turbine is treated individually based on its position in the farm and on the wind direction by predicting the velocity upstream of each turbine. The turbine-induced forces and added turbulence kinetic energy (TKE) are first derived analytically and then implemented in the Weather Research and Forecasting model. Idealized simulations of the offshore Lillgrund wind farm are conducted. The wind-speed deficit and TKE predicted with the hybrid model are in excellent agreement with those from the LES results, while the wind-power production estimated with the hybrid model is within 10% of that observed. Three additional wind farms with larger inter-turbine spacing than at Lillgrund are also considered, and a similar agreement with LES results is found, proving that the hybrid parametrization works well with any wind farm regardless of the spacing between turbines. These results indicate the wind-turbine position, wind direction, and added TKE are essential in accounting for the wind-farm effects on the surroundings, for which the hybrid wind-farm parametrization is a promising tool.

  11. Mod two homology and cohomology

    CERN Document Server

    Hausmann, Jean-Claude

    2014-01-01

    Cohomology and homology modulo 2 helps the reader grasp more readily the basics of a major tool in algebraic topology. Compared to a more general approach to (co)homology this refreshing approach has many pedagogical advantages: It leads more quickly to the essentials of the subject, An absence of signs and orientation considerations simplifies the theory, Computations and advanced applications can be presented at an earlier stage, Simple geometrical interpretations of (co)chains. Mod 2 (co)homology was developed in the first quarter of the twentieth century as an alternative to integral homology, before both became particular cases of (co)homology with arbitrary coefficients. The first chapters of this book may serve as a basis for a graduate-level introductory course to (co)homology. Simplicial and singular mod 2 (co)homology are introduced, with their products and Steenrod squares, as well as equivariant cohomology. Classical applications include Brouwer's fixed point theorem, Poincaré duality, Borsuk-Ula...

  12. A global hybrid coupled model based on atmosphere-SST feedbacks

    Energy Technology Data Exchange (ETDEWEB)

    Cimatoribus, Andrea A.; Drijfhout, Sybren S. [Royal Netherlands Meteorological Institute, De Bilt (Netherlands); Dijkstra, Henk A. [Utrecht University, Institute for Marine and Atmospheric Research Utrecht, Utrecht (Netherlands)

    2012-02-15

    A global hybrid coupled model is developed, with the aim of studying the effects of ocean-atmosphere feedbacks on the stability of the Atlantic meridional overturning circulation. The model includes a global ocean general circulation model and a statistical atmosphere model. The statistical atmosphere model is based on linear regressions of data from a fully coupled climate model on sea surface temperature both locally and hemispherically averaged, being the footprint of Atlantic meridional overturning variability. It provides dynamic boundary conditions to the ocean model for heat, freshwater and wind-stress. A basic but consistent representation of ocean-atmosphere feedbacks is captured in the hybrid coupled model and it is more than 10 times faster than the fully coupled climate model. The hybrid coupled model reaches a steady state with a climate close to the one of the fully coupled climate model, and the two models also have a similar response (collapse) of the Atlantic meridional overturning circulation to a freshwater hosing applied in the northern North Atlantic. (orig.)

  13. Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

    Science.gov (United States)

    Yeganeh, B.; Motlagh, M. Shafie Pour; Rashidi, Y.; Kamalan, H.

    2012-08-01

    Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS-SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS-SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65-85% for hybrid PLS-SVM model respectively. Also it was found that the hybrid PLS-SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS-SVM model.

  14. Modeling and Simulation of Multi-scale Environmental Systems with Generalized Hybrid Petri Nets

    Directory of Open Access Journals (Sweden)

    Mostafa eHerajy

    2015-07-01

    Full Text Available Predicting and studying the dynamics and properties of environmental systems necessitates the construction and simulation of mathematical models entailing different levels of complexities. Such type of computational experiments often require the combination of discrete and continuous variables as well as processes operating at different time scales. Furthermore, the iterative steps of constructing and analyzing environmental models might involve researchers with different background. Hybrid Petri nets may contribute in overcoming such challenges as they facilitate the implementation of systems integrating discrete and continuous dynamics. Additionally, the visual depiction of model components will inevitably help to bridge the gap between scientists with distinct expertise working on the same problem. Thus, modeling environmental systems with hybrid Petri nets enables the construction of complex processes while keeping the models comprehensible for researchers working on the same project with significantly divergent education path. In this paper we propose the utilization of a special class of hybrid Petri nets, Generalized Hybrid Petri Nets (GHPN, to model and simulate environmental systems exposing processes interacting at different time-scales. GHPN integrate stochastic and deterministic semantics as well as other types of special basic events. Moreover, a case study is presented to illustrate the use of GHPN in constructing and simulating multi-timescale environmental scenarios.

  15. A control-oriented cycle-life model for hybrid electric vehicle lithium-ion batteries

    International Nuclear Information System (INIS)

    Suri, Girish; Onori, Simona

    2016-01-01

    In this paper, a semi-empirical Lithium-iron phosphate-graphite battery aging model is identified over data mimicking actual cycling conditions that a hybrid electric vehicle battery encounters under real driving scenarios. The aging model is then used to construct the severity factor map, used to characterize relative aging of the battery under different operating conditions. This is used as a battery degradation criterion within a multi-objective optimization problem where battery aging minimization is to be achieved along with fuel consumption minimization. The method proposed is general and can be applied to other battery chemistry as well as different vehicular applications. Finally, simulations conducted using a hybrid electric vehicle simulator show how the two modeling tools developed in this paper, i.e., the severity factor map and the aging model, can be effectively used in a multi-objective optimization problem to predict and control battery degradation. - Highlights: • Battery aging model for hybrid electric vehicles using real driving conditions data. • Development of a modeling tool to assess battery degradation for real time optimization. • "3"1P NMR analysis of an enzyme-treated extract showed expected hydrolysis of P forms. • Development of an energy management strategy to minimize battery degradation. • Simulation results from hybrid electric vehicle simulator.

  16. Accuracy improvement of a hybrid robot for ITER application using POE modeling method

    International Nuclear Information System (INIS)

    Wang, Yongbo; Wu, Huapeng; Handroos, Heikki

    2013-01-01

    Highlights: ► The product of exponential (POE) formula for error modeling of hybrid robot. ► Differential Evolution (DE) algorithm for parameter identification. ► Simulation results are given to verify the effectiveness of the method. -- Abstract: This paper focuses on the kinematic calibration of a 10 degree-of-freedom (DOF) redundant serial–parallel hybrid robot to improve its accuracy. The robot was designed to perform the assembling and repairing tasks of the vacuum vessel (VV) of the international thermonuclear experimental reactor (ITER). By employing the product of exponentials (POEs) formula, we extended the POE-based calibration method from serial robot to redundant serial–parallel hybrid robot. The proposed method combines the forward and inverse kinematics together to formulate a hybrid calibration method for serial–parallel hybrid robot. Because of the high nonlinear characteristics of the error model and too many error parameters need to be identified, the traditional iterative linear least-square algorithms cannot be used to identify the parameter errors. This paper employs a global optimization algorithm, Differential Evolution (DE), to identify parameter errors by solving the inverse kinematics of the hybrid robot. Furthermore, after the parameter errors were identified, the DE algorithm was adopted to numerically solve the forward kinematics of the hybrid robot to demonstrate the accuracy improvement of the end-effector. Numerical simulations were carried out by generating random parameter errors at the allowed tolerance limit and generating a number of configuration poses in the robot workspace. Simulation of the real experimental conditions shows that the accuracy of the end-effector can be improved to the same precision level of the given external measurement device

  17. Accuracy improvement of a hybrid robot for ITER application using POE modeling method

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yongbo, E-mail: yongbo.wang@hotmail.com [Laboratory of Intelligent Machines, Lappeenranta University of Technology, FIN-53851 Lappeenranta (Finland); Wu, Huapeng; Handroos, Heikki [Laboratory of Intelligent Machines, Lappeenranta University of Technology, FIN-53851 Lappeenranta (Finland)

    2013-10-15

    Highlights: ► The product of exponential (POE) formula for error modeling of hybrid robot. ► Differential Evolution (DE) algorithm for parameter identification. ► Simulation results are given to verify the effectiveness of the method. -- Abstract: This paper focuses on the kinematic calibration of a 10 degree-of-freedom (DOF) redundant serial–parallel hybrid robot to improve its accuracy. The robot was designed to perform the assembling and repairing tasks of the vacuum vessel (VV) of the international thermonuclear experimental reactor (ITER). By employing the product of exponentials (POEs) formula, we extended the POE-based calibration method from serial robot to redundant serial–parallel hybrid robot. The proposed method combines the forward and inverse kinematics together to formulate a hybrid calibration method for serial–parallel hybrid robot. Because of the high nonlinear characteristics of the error model and too many error parameters need to be identified, the traditional iterative linear least-square algorithms cannot be used to identify the parameter errors. This paper employs a global optimization algorithm, Differential Evolution (DE), to identify parameter errors by solving the inverse kinematics of the hybrid robot. Furthermore, after the parameter errors were identified, the DE algorithm was adopted to numerically solve the forward kinematics of the hybrid robot to demonstrate the accuracy improvement of the end-effector. Numerical simulations were carried out by generating random parameter errors at the allowed tolerance limit and generating a number of configuration poses in the robot workspace. Simulation of the real experimental conditions shows that the accuracy of the end-effector can be improved to the same precision level of the given external measurement device.

  18. Modeling the geometric formation and powder deposition mass in laser induction hybrid cladding

    International Nuclear Information System (INIS)

    Huang, Yong Jun; Yuan, Sheng Fa

    2012-01-01

    A new laser induction hybrid cladding technique on cylinder work piece is presented. Based on a series of laser induction hybrid experiments by off axial powder feeding, the predicting models of individual clad geometric formation and powder catchment were developed in terms of powder feeding rate, laser special energy and induction energy density using multiple regression analysis. In addition, confirmation tests were performed to make a comparison between the predicting results and measured ones. Via the experiments and analysis, the conclusions can be lead to that the process parameters have crucial influence on the clad geometric formation and powder catchment, and that the predicting model reflects well the relationship between the clad geometric formation and process parameters in laser induction hybrid cladding

  19. Compositional Homology and Creative Thinking

    Directory of Open Access Journals (Sweden)

    Salvatore Tedesco

    2015-05-01

    Full Text Available The concept of homology is the most solid theoretical basis elaborated by the morphological thinking during its history. The enucleation of some general criteria for the interpretation of homology is today a fundamental tool for life sciences, and for restoring their own opening to the question of qualitative innovation that arose so powerfully in the original Darwinian project. The aim of this paper is to verify the possible uses of the concept of compositional homology in order to provide of an adequate understanding of the dynamics of creative thinking.

  20. Comparison of a hybrid model to a global model of atmospheric pressure radio-frequency capacitive discharges

    International Nuclear Information System (INIS)

    Lazzaroni, C; Lieberman, M A; Lichtenberg, A J; Chabert, P

    2012-01-01

    A one-dimensional hybrid analytical-numerical global model of atmospheric pressure radio-frequency (rf) driven capacitive discharges, previously developed, is compared with a basic global model. A helium feed gas with small admixtures of oxygen is studied. For the hybrid model, the electrical characteristics are calculated analytically as a current-driven homogeneous discharge. The electron power balance is solved analytically to determine a time-varying Maxwellian electron temperature, which oscillates on the rf timescale. Averaging over the rf period yields effective rate coefficients for gas phase activated processes. For the basic global model, the electron temperature is constant in time and the sheath physics is neglected. For both models, the particle balance relations for all species are integrated numerically to determine the equilibrium discharge parameters. Variations of discharge parameters with composition and rf power are determined and compared. The rate coefficients for electron-activated processes are strongly temperature dependent, leading to significantly larger neutral and charged particle densities for the hybrid model. For small devices, finite sheath widths limit the operating regimes to low O 2 fractions. This is captured by the hybrid model but cannot be predicted from the basic global model.

  1. Modelling of JET hybrid scenarios with GLF23 transport model: E × B shear stabilization of anomalous transport

    NARCIS (Netherlands)

    Voitsekhovitch, I.; Belo, da Silva Ares; Citrin, J.; Fable, E.; Ferreira, J.; Garcia, J.; Garzotti, L.; Hobirk, J.; Hogeweij, G. M. D.; Joffrin, E.; Kochl, F.; Litaudon, X.; Moradi, S.; Nabais, F.; JET-EFDA Contributors,; EU-ITM ITER Scenario Modelling group,

    2014-01-01

    The E × B shear stabilization of anomalous transport in JET hybrid discharges is studied via self-consistent predictive modelling of electron and ion temperature, ion density and toroidal rotation velocity performed with the GLF23 model. The E × B shear

  2. Physical and JIT Model Based Hybrid Modeling Approach for Building Thermal Load Prediction

    Science.gov (United States)

    Iino, Yutaka; Murai, Masahiko; Murayama, Dai; Motoyama, Ichiro

    Energy conservation in building fields is one of the key issues in environmental point of view as well as that of industrial, transportation and residential fields. The half of the total energy consumption in a building is occupied by HVAC (Heating, Ventilating and Air Conditioning) systems. In order to realize energy conservation of HVAC system, a thermal load prediction model for building is required. This paper propose a hybrid modeling approach with physical and Just-in-Time (JIT) model for building thermal load prediction. The proposed method has features and benefits such as, (1) it is applicable to the case in which past operation data for load prediction model learning is poor, (2) it has a self checking function, which always supervises if the data driven load prediction and the physical based one are consistent or not, so it can find if something is wrong in load prediction procedure, (3) it has ability to adjust load prediction in real-time against sudden change of model parameters and environmental conditions. The proposed method is evaluated with real operation data of an existing building, and the improvement of load prediction performance is illustrated.

  3. Modeling and Optimal Control of a Class of Warfare Hybrid Dynamic Systems Based on Lanchester (n,1 Attrition Model

    Directory of Open Access Journals (Sweden)

    Xiangyong Chen

    2014-01-01

    hybrid dynamic systems is established based on Lanchester equation in a (n,1 battle, where a heterogeneous force of n different troop types faces a homogeneous force. This model can be characterized by the interaction of continuous-time models (governed by Lanchester equation, and discrete event systems (described by variable tactics. Furthermore, an expository discussion is presented on an optimal variable tactics control problem for warfare hybrid dynamic system. The optimal control strategies are designed based on dynamic programming and differential game theory. As an example of the consequences of this optimal control problem, we take the (2, 1 case and solve the optimal strategies in a (2, 1 case. Simulation results show the feasibility of warfare hybrid system model and the effectiveness of the optimal control strategies designed.

  4. Thermal modeling of a hydraulic hybrid vehicle transmission based on thermodynamic analysis

    International Nuclear Information System (INIS)

    Kwon, Hyukjoon; Sprengel, Michael; Ivantysynova, Monika

    2016-01-01

    Hybrid vehicles have become a popular alternative to conventional powertrain architectures by offering improved fuel efficiency along with a range of environmental benefits. Hydraulic Hybrid Vehicles (HHV) offer one approach to hybridization with many benefits over competing technologies. Among these benefits are lower component costs, more environmentally friendly construction materials, and the ability to recover a greater quantity of energy during regenerative braking which make HHVs partially well suited to urban environments. In order to further the knowledge base regarding HHVs, this paper explores the thermodynamic characteristics of such a system. A system model is detailed for both the hydraulic and thermal components of a closed circuit hydraulic hybrid transmission following the FTP-72 driving cycle. Among the new techniques proposed in this paper is a novel method for capturing rapid thermal transients. This paper concludes by comparing the results of this model with experimental data gathered on a Hardware-in-the-Loop (HIL) transmission dynamometer possessing the same architecture, components, and driving cycle used within the simulation model. This approach can be used for several applications such as thermal stability analysis of HHVs, optimal thermal management, and analysis of the system's thermodynamic efficiency. - Highlights: • Thermal modeling for HHVs is introduced. • A model for the hydraulic and thermal system is developed for HHVs. • A novel method for capturing rapid thermal transients is proposed. • The thermodynamic system diagram of a series HHV is predicted.

  5. Ultra-Short-Term Wind Power Prediction Using a Hybrid Model

    Science.gov (United States)

    Mohammed, E.; Wang, S.; Yu, J.

    2017-05-01

    This paper aims to develop and apply a hybrid model of two data analytical methods, multiple linear regressions and least square (MLR&LS), for ultra-short-term wind power prediction (WPP), for example taking, Northeast China electricity demand. The data was obtained from the historical records of wind power from an offshore region, and from a wind farm of the wind power plant in the areas. The WPP achieved in two stages: first, the ratios of wind power were forecasted using the proposed hybrid method, and then the transformation of these ratios of wind power to obtain forecasted values. The hybrid model combines the persistence methods, MLR and LS. The proposed method included two prediction types, multi-point prediction and single-point prediction. WPP is tested by applying different models such as autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN). By comparing results of the above models, the validity of the proposed hybrid model is confirmed in terms of error and correlation coefficient. Comparison of results confirmed that the proposed method works effectively. Additional, forecasting errors were also computed and compared, to improve understanding of how to depict highly variable WPP and the correlations between actual and predicted wind power.

  6. Hybrid models for chemical reaction networks: Multiscale theory and application to gene regulatory systems

    Science.gov (United States)

    Winkelmann, Stefanie; Schütte, Christof

    2017-09-01

    Well-mixed stochastic chemical kinetics are properly modeled by the chemical master equation (CME) and associated Markov jump processes in molecule number space. If the reactants are present in large amounts, however, corresponding simulations of the stochastic dynamics become computationally expensive and model reductions are demanded. The classical model reduction approach uniformly rescales the overall dynamics to obtain deterministic systems characterized by ordinary differential equations, the well-known mass action reaction rate equations. For systems with multiple scales, there exist hybrid approaches that keep parts of the system discrete while another part is approximated either using Langevin dynamics or deterministically. This paper aims at giving a coherent overview of the different hybrid approaches, focusing on their basic concepts and the relation between them. We derive a novel general description of such hybrid models that allows expressing various forms by one type of equation. We also check in how far the approaches apply to model extensions of the CME for dynamics which do not comply with the central well-mixed condition and require some spatial resolution. A simple but meaningful gene expression system with negative self-regulation is analysed to illustrate the different approximation qualities of some of the hybrid approaches discussed. Especially, we reveal the cause of error in the case of small volume approximations.

  7. Hybrid models for chemical reaction networks: Multiscale theory and application to gene regulatory systems.

    Science.gov (United States)

    Winkelmann, Stefanie; Schütte, Christof

    2017-09-21

    Well-mixed stochastic chemical kinetics are properly modeled by the chemical master equation (CME) and associated Markov jump processes in molecule number space. If the reactants are present in large amounts, however, corresponding simulations of the stochastic dynamics become computationally expensive and model reductions are demanded. The classical model reduction approach uniformly rescales the overall dynamics to obtain deterministic systems characterized by ordinary differential equations, the well-known mass action reaction rate equations. For systems with multiple scales, there exist hybrid approaches that keep parts of the system discrete while another part is approximated either using Langevin dynamics or deterministically. This paper aims at giving a coherent overview of the different hybrid approaches, focusing on their basic concepts and the relation between them. We derive a novel general description of such hybrid models that allows expressing various forms by one type of equation. We also check in how far the approaches apply to model extensions of the CME for dynamics which do not comply with the central well-mixed condition and require some spatial resolution. A simple but meaningful gene expression system with negative self-regulation is analysed to illustrate the different approximation qualities of some of the hybrid approaches discussed. Especially, we reveal the cause of error in the case of small volume approximations.

  8. A hybrid modelling approach to simulating foot-and-mouth disease outbreaks in Australian livestock

    Directory of Open Access Journals (Sweden)

    Richard A Bradhurst

    2015-03-01

    Full Text Available Foot-and-mouth disease (FMD is a highly contagious and economically important viral disease of cloven-hoofed animals. Australia's freedom from FMD underpins a valuable trade in live animals and animal products. An outbreak of FMD would result in the loss of export markets and cause severe disruption to domestic markets. The prevention of, and contingency planning for, FMD are of key importance to government, industry, producers and the community. The spread and control of FMD is complex and dynamic due to a highly contagious multi-host pathogen operating in a heterogeneous environment across multiple jurisdictions. Epidemiological modelling is increasingly being recognized as a valuable tool for investigating the spread of disease under different conditions and the effectiveness of control strategies. Models of infectious disease can be broadly classified as: population-based models that are formulated from the top-down and employ population-level relationships to describe individual-level behaviour, individual-based models that are formulated from the bottom-up and aggregate individual-level behaviour to reveal population-level relationships, or hybrid models which combine the two approaches into a single model.The Australian Animal Disease Spread (AADIS hybrid model employs a deterministic equation-based model (EBM to model within-herd spread of FMD, and a stochastic, spatially-explicit agent-based model (ABM to model between-herd spread and control. The EBM provides concise and computationally efficient predictions of herd prevalence and clinical signs over time. The ABM captures the complex, stochastic and heterogeneous environment in which an FMD epidemic operates. The AADIS event-driven hybrid EBM/ABM architecture is a flexible, efficient and extensible framework for modelling the spread and control of disease in livestock on a national scale. We present an overview of the AADIS hybrid approach and a description of the model

  9. Hybrid incompatibility arises in a sequence-based bioenergetic model of transcription factor binding.

    Science.gov (United States)

    Tulchinsky, Alexander Y; Johnson, Norman A; Watt, Ward B; Porter, Adam H

    2014-11-01

    Postzygotic isolation between incipient species results from the accumulation of incompatibilities that arise as a consequence of genetic divergence. When phenotypes are determined by regulatory interactions, hybrid incompatibility can evolve even as a consequence of parallel adaptation in parental populations because interacting genes can produce the same phenotype through incompatible allelic combinations. We explore the evolutionary conditions that promote and constrain hybrid incompatibility in regulatory networks using a bioenergetic model (combining thermodynamics and kinetics) of transcriptional regulation, considering the bioenergetic basis of molecular interactions between transcription factors (TFs) and their binding sites. The bioenergetic parameters consider the free energy of formation of the bond between the TF and its binding site and the availability of TFs in the intracellular environment. Together these determine fractional occupancy of the TF on the promoter site, the degree of subsequent gene expression and in diploids, and the degree of dominance among allelic interactions. This results in a sigmoid genotype-phenotype map and fitness landscape, with the details of the shape determining the degree of bioenergetic evolutionary constraint on hybrid incompatibility. Using individual-based simulations, we subjected two allopatric populations to parallel directional or stabilizing selection. Misregulation of hybrid gene expression occurred under either type of selection, although it evolved faster under directional selection. Under directional selection, the extent of hybrid incompatibility increased with the slope of the genotype-phenotype map near the derived parental expression level. Under stabilizing selection, hybrid incompatibility arose from compensatory mutations and was greater when the bioenergetic properties of the interaction caused the space of nearly neutral genotypes around the stable expression level to be wide. F2's showed higher

  10. A modeling method of semiconductor fabrication flows with extended knowledge hybrid Petri nets

    Institute of Scientific and Technical Information of China (English)

    Zhou Binghai; Jiang Shuyu; Wang Shijin; Wu bin

    2008-01-01

    A modeling method of extended knowledge hybrid Petri nets (EKHPNs), incorporating object-oriented methods into hybrid Petri nets (HPNs), was presented and used for the representation and modeling of semiconductor wafer fabrication flows. To model the discrete and continuous parts of a complex semiconductor wafer fabrication flow, the HPNs were introduced into the EKHPNs. Object-oriented methods were combined into the EKHPNs for coping with the complexity of the fabrication flow. Knowledge annotations were introduced to solve input and output conflicts of the EKHPNs.Finally, to demonstrate the validity of the EKHPN method, a real semiconductor wafer fabrication case was used to illustrate the modeling procedure. The modeling results indicate that the proposed method can be used to model a complex semiconductor wafer fabrication flow expediently.

  11. Simulation of Mercury's magnetosheath with a combined hybrid-paraboloid model

    Science.gov (United States)

    Parunakian, David; Dyadechkin, Sergey; Alexeev, Igor; Belenkaya, Elena; Khodachenko, Maxim; Kallio, Esa; Alho, Markku

    2017-08-01

    In this paper we introduce a novel approach for modeling planetary magnetospheres that involves a combination of the hybrid model and the paraboloid magnetosphere model (PMM); we further refer to it as the combined hybrid model. While both of these individual models have been successfully applied in the past, their combination enables us both to overcome the traditional difficulties of hybrid models to develop a self-consistent magnetic field and to compensate the lack of plasma simulation in the PMM. We then use this combined model to simulate Mercury's magnetosphere and investigate the geometry and configuration of Mercury's magnetosheath controlled by various conditions in the interplanetary medium. The developed approach provides a unique comprehensive view of Mercury's magnetospheric environment for the first time. Using this setup, we compare the locations of the bow shock and the magnetopause as determined by simulations with the locations predicted by stand-alone PMM runs and also verify the magnetic and dynamic pressure balance at the magnetopause. We also compare the results produced by these simulations with observational data obtained by the magnetometer on board the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft along a dusk-dawn orbit and discuss the signatures of the magnetospheric features that appear in these simulations. Overall, our analysis suggests that combining the semiempirical PMM with a self-consistent global kinetic model creates new modeling possibilities which individual models cannot provide on their own.

  12. Improved Hybrid Modeling of Spent Fuel Storage Facilities

    Energy Technology Data Exchange (ETDEWEB)

    Bibber, Karl van [Univ. of California, Berkeley, CA (United States)

    2018-03-21

    This work developed a new computational method for improving the ability to calculate the neutron flux in deep-penetration radiation shielding problems that contain areas with strong streaming. The “gold standard” method for radiation transport is Monte Carlo (MC) as it samples the physics exactly and requires few approximations. Historically, however, MC was not useful for shielding problems because of the computational challenge of following particles through dense shields. Instead, deterministic methods, which are superior in term of computational effort for these problems types but are not as accurate, were used. Hybrid methods, which use deterministic solutions to improve MC calculations through a process called variance reduction, can make it tractable from a computational time and resource use perspective to use MC for deep-penetration shielding. Perhaps the most widespread and accessible of these methods are the Consistent Adjoint Driven Importance Sampling (CADIS) and Forward-Weighted CADIS (FW-CADIS) methods. For problems containing strong anisotropies, such as power plants with pipes through walls, spent fuel cask arrays, active interrogation, and locations with small air gaps or plates embedded in water or concrete, hybrid methods are still insufficiently accurate. In this work, a new method for generating variance reduction parameters for strongly anisotropic, deep penetration radiation shielding studies was developed. This method generates an alternate form of the adjoint scalar flux quantity, ΦΩ, which is used by both CADIS and FW-CADIS to generate variance reduction parameters for local and global response functions, respectively. The new method, called CADIS-Ω, was implemented in the Denovo/ADVANTG software. Results indicate that the flux generated by CADIS-Ω incorporates localized angular anisotropies in the flux more effectively than standard methods. CADIS-Ω outperformed CADIS in several test problems. This initial work

  13. Hybridization alters spontaneous mutation rates in a parent-of-origin-dependent fashion in Arabidopsis.

    Science.gov (United States)

    Bashir, Tufail; Sailer, Christian; Gerber, Florian; Loganathan, Nitin; Bhoopalan, Hemadev; Eichenberger, Christof; Grossniklaus, Ueli; Baskar, Ramamurthy

    2014-05-01

    Over 70 years ago, increased spontaneous mutation rates were observed in Drosophila spp. hybrids, but the genetic basis of this phenomenon is not well understood. The model plant Arabidopsis (Arabidopsis thaliana) offers unique opportunities to study the types of mutations induced upon hybridization and the frequency of their occurrence. Understanding the mutational effects of hybridization is important, as many crop plants are grown as hybrids. Besides, hybridization is important for speciation and its effects on genome integrity could be critical, as chromosomal rearrangements can lead to reproductive isolation. We examined the rates of hybridization-induced point and frameshift mutations as well as homologous recombination events in intraspecific Arabidopsis hybrids using a set of transgenic mutation detector lines that carry mutated or truncated versions of a reporter gene. We found that hybridization alters the frequency of different kinds of mutations. In general, Columbia (Col)×Cape Verde Islands and Col×C24 hybrid progeny had decreased T→G and T→A transversion rates but an increased C→T transition rate. Significant changes in frameshift mutation rates were also observed in some hybrids. In Col×C24 hybrids, there is a trend for increased homologous recombination rates, except for the hybrids from one line, while in Col×Cape Verde Islands hybrids, this rate is decreased. The overall genetic distance of the parents had no influence on mutation rates in the progeny, as closely related accessions on occasion displayed higher mutation rates than accessions that are separated farther apart. However, reciprocal hybrids had significantly different mutation rates, suggesting parent-of-origin-dependent effects on the mutation frequency.

  14. Modeling and control of a hybrid-electric vehicle for drivability and fuel economy improvements

    Science.gov (United States)

    Koprubasi, Kerem

    The gradual decline of oil reserves and the increasing demand for energy over the past decades has resulted in automotive manufacturers seeking alternative solutions to reduce the dependency on fossil-based fuels for transportation. A viable technology that enables significant improvements in the overall tank-to-wheel vehicle energy conversion efficiencies is the hybridization of electrical and conventional drive systems. Sophisticated hybrid powertrain configurations require careful coordination of the actuators and the onboard energy sources for optimum use of the energy saving benefits. The term optimality is often associated with fuel economy, although other measures such as drivability and exhaust emissions are also equally important. This dissertation focuses on the design of hybrid-electric vehicle (HEV) control strategies that aim to minimize fuel consumption while maintaining good vehicle drivability. In order to facilitate the design of controllers based on mathematical models of the HEV system, a dynamic model that is capable of predicting longitudinal vehicle responses in the low-to-mid frequency region (up to 10 Hz) is developed for a parallel HEV configuration. The model is validated using experimental data from various driving modes including electric only, engine only and hybrid. The high fidelity of the model makes it possible to accurately identify critical drivability issues such as time lags, shunt, shuffle, torque holes and hesitation. Using the information derived from the vehicle model, an energy management strategy is developed and implemented on a test vehicle. The resulting control strategy has a hybrid structure in the sense that the main mode of operation (the hybrid mode) is occasionally interrupted by event-based rules to enable the use of the engine start-stop function. The changes in the driveline dynamics during this transition further contribute to the hybrid nature of the system. To address the unique characteristics of the HEV

  15. Hybrid supply chain model for material requirement planning under financial constraints: A case study

    Science.gov (United States)

    Curci, Vita; Dassisti, Michele; Josefa, Mula Bru; Manuel, Díaz Madroñero

    2014-10-01

    Supply chain model (SCM) are potentially capable to integrate different aspects in supporting decision making for enterprise management tasks. The aim of the paper is to propose an hybrid mathematical programming model for optimization of production requirements resources planning. The preliminary model was conceived bottom-up from a real industrial case analysed oriented to maximize cash flow. Despite the intense computational effort required to converge to a solution, optimisation done brought good result in solving the objective function.

  16. Solving Problems in Various Domains by Hybrid Models of High Performance Computations

    Directory of Open Access Journals (Sweden)

    Yurii Rogozhin

    2014-03-01

    Full Text Available This work presents a hybrid model of high performance computations. The model is based on membrane system (P~system where some membranes may contain quantum device that is triggered by the data entering the membrane. This model is supposed to take advantages of both biomolecular and quantum paradigms and to overcome some of their inherent limitations. The proposed approach is demonstrated through two selected problems: SAT, and image retrieving.

  17. Strategy and gaps for modeling, simulation, and control of hybrid systems

    Energy Technology Data Exchange (ETDEWEB)

    Rabiti, Cristian [Idaho National Lab. (INL), Idaho Falls, ID (United States); Garcia, Humberto E. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Hovsapian, Rob [Idaho National Lab. (INL), Idaho Falls, ID (United States); Kinoshita, Robert [Idaho National Lab. (INL), Idaho Falls, ID (United States); Mesina, George L. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Bragg-Sitton, Shannon M. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Boardman, Richard D. [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-04-01

    The purpose of this report is to establish a strategy for modeling and simulation of candidate hybrid energy systems. Modeling and simulation is necessary to design, evaluate, and optimize the system technical and economic performance. Accordingly, this report first establishes the simulation requirements to analysis candidate hybrid systems. Simulation fidelity levels are established based on the temporal scale, real and synthetic data availability or needs, solution accuracy, and output parameters needed to evaluate case-specific figures of merit. Accordingly, the associated computational and co-simulation resources needed are established; including physical models when needed, code assembly and integrated solutions platforms, mathematical solvers, and data processing. This report first attempts to describe the figures of merit, systems requirements, and constraints that are necessary and sufficient to characterize the grid and hybrid systems behavior and market interactions. Loss of Load Probability (LOLP) and effective cost of Effective Cost of Energy (ECE), as opposed to the standard Levelized Cost of Electricty (LCOE), are introduced as technical and economical indices for integrated energy system evaluations. Financial assessment methods are subsequently introduced for evaluation of non-traditional, hybrid energy systems. Algorithms for coupled and iterative evaluation of the technical and economic performance are subsequently discussed. This report further defines modeling objectives, computational tools, solution approaches, and real-time data collection and processing (in some cases using real test units) that will be required to model, co-simulate, and optimize; (a) an energy system components (e.g., power generation unit, chemical process, electricity management unit), (b) system domains (e.g., thermal, electrical or chemical energy generation, conversion, and transport), and (c) systems control modules. Co-simulation of complex, tightly coupled

  18. Performance and robustness of hybrid model predictive control for controllable dampers in building models

    Science.gov (United States)

    Johnson, Erik A.; Elhaddad, Wael M.; Wojtkiewicz, Steven F.

    2016-04-01

    A variety of strategies have been developed over the past few decades to determine controllable damping device forces to mitigate the response of structures and mechanical systems to natural hazards and other excitations. These "smart" damping devices produce forces through passive means but have properties that can be controlled in real time, based on sensor measurements of response across the structure, to dramatically reduce structural motion by exploiting more than the local "information" that is available to purely passive devices. A common strategy is to design optimal damping forces using active control approaches and then try to reproduce those forces with the smart damper. However, these design forces, for some structures and performance objectives, may achieve high performance by selectively adding energy, which cannot be replicated by a controllable damping device, causing the smart damper performance to fall far short of what an active system would provide. The authors have recently demonstrated that a model predictive control strategy using hybrid system models, which utilize both continuous and binary states (the latter to capture the switching behavior between dissipative and non-dissipative forces), can provide reductions in structural response on the order of 50% relative to the conventional clipped-optimal design strategy. This paper explores the robustness of this newly proposed control strategy through evaluating controllable damper performance when the structure model differs from the nominal one used to design the damping strategy. Results from the application to a two-degree-of-freedom structure model confirms the robustness of the proposed strategy.

  19. Development of hybrid 3-D hydrological modeling for the NCAR Community Earth System Model (CESM)

    Energy Technology Data Exchange (ETDEWEB)

    Zeng, Xubin [Univ. of Arizona, Tucson, AZ (United States); Troch, Peter [Univ. of Arizona, Tucson, AZ (United States); Pelletier, Jon [Univ. of Arizona, Tucson, AZ (United States); Niu, Guo-Yue [Univ. of Arizona, Tucson, AZ (United States); Gochis, David [NCAR Research Applications (RAL), Boulder, CO (United States)

    2015-11-15

    This is the Final Report of our four-year (3-year plus one-year no cost extension) collaborative project between the University of Arizona (UA) and the National Center for Atmospheric Research (NCAR). The overall objective of our project is to develop and evaluate the first hybrid 3-D hydrological model with a horizontal grid spacing of 1 km for the NCAR Community Earth System Model (CESM). We have made substantial progress in model development and evaluation, computational efficiencies and software engineering, and data development and evaluation, as discussed in Sections 2-4. Section 5 presents our success in data dissemination, while Section 6 discusses the scientific impacts of our work. Section 7 discusses education and mentoring success of our project, while Section 8 lists our relevant DOE services. All peer-reviewed papers that acknowledged this project are listed in Section 9. Highlights of our achievements include: • We have finished 20 papers (most published already) on model development and evaluation, computational efficiencies and software engineering, and data development and evaluation • The global datasets developed under this project have been permanently archived and publicly available • Some of our research results have already been implemented in WRF and CLM • Patrick Broxton and Michael Brunke have received their Ph.D. • PI Zeng has served on DOE proposal review panels and DOE lab scientific focus area (SFA) review panels

  20. Fuzzy logic-based analogue forecasting and hybrid modelling of horizontal visibility

    Science.gov (United States)

    Tuba, Zoltán; Bottyán, Zsolt

    2018-04-01

    Forecasting visibility is one of the greatest challenges in aviation meteorology. At the same time, high accuracy visibility forecasts can significantly reduce or make avoidable weather-related risk in aviation as well. To improve forecasting visibility, this research links fuzzy logic-based analogue forecasting and post-processed numerical weather prediction model outputs in hybrid forecast. Performance of analogue forecasting model was improved by the application of Analytic Hierarchy Process. Then, linear combination of the mentioned outputs was applied to create ultra-short term hybrid visibility prediction which gradually shifts the focus from statistical to numerical products taking their advantages during the forecast period. It gives the opportunity to bring closer the numerical visibility forecast to the observations even it is wrong initially. Complete verification of categorical forecasts was carried out; results are available for persistence and terminal aerodrome forecasts (TAF) as well in order to compare. The average value of Heidke Skill Score (HSS) of examined airports of analogue and hybrid forecasts shows very similar results even at the end of forecast period where the rate of analogue prediction in the final hybrid output is 0.1-0.2 only. However, in case of poor visibility (1000-2500 m), hybrid (0.65) and analogue forecasts (0.64) have similar average of HSS in the first 6 h of forecast period, and have better performance than persistence (0.60) or TAF (0.56). Important achievement that hybrid model takes into consideration physics and dynamics of the atmosphere due to the increasing part of the numerical weather prediction. In spite of this, its performance is similar to the most effective visibility forecasting methods and does not follow the poor verification results of clearly numerical outputs.

  1. Modelling and simulation of a hybrid solar heating system for greenhouse applications using Matlab/Simulink

    International Nuclear Information System (INIS)

    Kıyan, Metin; Bingöl, Ekin; Melikoğlu, Mehmet; Albostan, Ayhan

    2013-01-01

    Highlights: • Matlab/Simulink modelling of a solar hybrid greenhouse. • Estimation of greenhouse gas emission reductions. • Feasibility and cost analysis of the system. - Abstract: Solar energy is a major renewable energy source and hybrid solar systems are gaining increased academic and industrial attention due to the unique advantages they offer. In this paper, a mathematical model has been developed to investigate the thermal behavior of a greenhouse heated by a hybrid solar collector system. This hybrid system contains an evacuated tube solar heat collector unit, an auxiliary fossil fuel heating unit, a hot water storage unit, control and piping units. A Matlab/Simulink based model and software has been developed to predict the storage water temperature, greenhouse indoor temperature and the amount of auxiliary fuel, as a function of various design parameters of the greenhouse such as location, dimensions, and meteorological data of the region. As a case study, a greenhouse located in Şanlıurfa/Turkey has been simulated based on recent meteorological data and aforementioned hybrid system. The results of simulations performed on an annual basis indicate that revising the existing fossil fuel system with the proposed hybrid system, is economically feasible for most cases, however it requires a slightly longer payback period than expected. On the other hand, by reducing the greenhouse gas emissions significantly, it has a considerable positive environmental impact. The developed dynamic simulation method can be further used for designing heating systems for various solar greenhouses and optimizing the solar collector and thermal storage sizes

  2. Exploring key factors in online shopping with a hybrid model.

    Science.gov (United States)

    Chen, Hsiao-Ming; Wu, Chia-Huei; Tsai, Sang-Bing; Yu, Jian; Wang, Jiangtao; Zheng, Yuxiang

    2016-01-01

    Nowadays, the web increasingly influences retail sales. An in-depth analysis of consumer decision-making in the context of e-business has become an important issue for internet vendors. However, factors affecting e-business are complicated and intertwined. To stimulate online sales, understanding key influential factors and causal relationships among the factors is important. To gain more insights into this issue, this paper introduces a hybrid method, which combines the Decision Making Trial and Evaluation Laboratory (DEMATEL) with the analytic network process, called DANP method, to find out the driving factors that influence the online business mostly. By DEMATEL approach the causal graph showed that "online service" dimension has the highest degree of direct impact on other dimensions; thus, the internet vendor is suggested to made strong efforts on service quality throughout the online shopping process. In addition, the study adopted DANP to measure the importance of key factors, among which "transaction security" proves to be the most important criterion. Hence, transaction security should be treated with top priority to boost the online businesses. From our study with DANP approach, the comprehensive information can be visually detected so that the decision makers can spotlight on the root causes to develop effectual actions.

  3. Hybrid continuum–molecular modelling of multiscale internal gas flows

    International Nuclear Information System (INIS)

    Patronis, Alexander; Lockerby, Duncan A.; Borg, Matthew K.; Reese, Jason M.

    2013-01-01

    We develop and apply an efficient multiscale method for simulating a large class of low-speed internal rarefied gas flows. The method is an extension of the hybrid atomistic–continuum approach proposed by Borg et al. (2013) [28] for the simulation of micro/nano flows of high-aspect ratio. The major new extensions are: (1) incorporation of fluid compressibility; (2) implementation using the direct simulation Monte Carlo (DSMC) method for dilute rarefied gas flows, and (3) application to a broader range of geometries, including periodic, non-periodic, pressure-driven, gravity-driven and shear-driven internal flows. The multiscale method is applied to micro-scale gas flows through a periodic converging–diverging channel (driven by an external acceleration) and a non-periodic channel with a bend (driven by a pressure difference), as well as the flow between two eccentric cylinders (with the inner rotating relative to the outer). In all these cases there exists a wide variation of Knudsen number within the geometries, as well as substantial compressibility despite the Mach number being very low. For validation purposes, our multiscale simulation results are compared to those obtained from full-scale DSMC simulations: very close agreement is obtained in all cases for all flow variables considered. Our multiscale simulation is an order of magnitude more computationally efficient than the full-scale DSMC for the first and second test cases, and two orders of magnitude more efficient for the third case

  4. Hybrid artificial bee colony algorithm for parameter optimization of five-parameter bidirectional reflectance distribution function model.

    Science.gov (United States)

    Wang, Qianqian; Zhao, Jing; Gong, Yong; Hao, Qun; Peng, Zhong

    2017-11-20

    A hybrid artificial bee colony (ABC) algorithm inspired by the best-so-far solution and bacterial chemotaxis was introduced to optimize the parameters of the five-parameter bidirectional reflectance distribution function (BRDF) model. To verify the performance of the hybrid ABC algorithm, we measured BRDF of three kinds of samples and simulated the undetermined parameters of the five-parameter BRDF model using the hybrid ABC algorithm and the genetic algorithm, respectively. The experimental results demonstrate that the hybrid ABC algorithm outperforms the genetic algorithm in convergence speed, accuracy, and time efficiency under the same conditions.

  5. [Analysis of DNA-DNA homologies in obligate methylotrophic bacteria].

    Science.gov (United States)

    Doronina, N V; Govorukhina, N I; Lysenko, A M; Trotsenko, Iu A

    1988-01-01

    The genotypic affinity of 19 bacterial strains obligately dependent on methanol or methylamine as carbon and energy sources was studied by techniques of molecular DNA hybridization. The high homology level (35-88%) between motile strain Methylophilus methanolovorus V-1447D and nonmotile strain Methylobacillus sp. VSB-792 as well as other motile strains (Pseudomonas methanolica ATCC 21704, Methylomonas methanolica NRRL 5458, Pseudomonas sp. W6, strain A3) indicates that all of them belong to one genus. Rather high level of homology (62-63%) was found between Methylobacillus glycogenes ATCC 29475 and Pseudomonas insueta ATCC 21276 and strain G-10. The motile strain Methylophilus methylotrophus NCIB 10515 has a low homology (below 20%) to other of the studied obligate methylobacteria. Therefore, at least two genetically different genera of obligate methylobacteria can be distinguished, namely Methylophilus and Methylobacillus, the latter being represented by both motile and nonmotile forms.

  6. Modeling and Nonlinear Control of Electric Power Stage in Hybrid Electric Vehicle

    DEFF Research Database (Denmark)

    Tahri, A.; El Fadil, H.; Guerrero, Josep M.

    2014-01-01

    This paper deals with the problem of modeling and controlling the electric power stage of hybrid electric vehicle. The controlled system consists of a fuel cell (FC) as a main source, a supercapacitor as an auxiliary source, two DC-DC power converters, an inverter and a traction induction motor...

  7. Model predictive control for power fluctuation supression in hybrid wind/PV/battery systems

    DEFF Research Database (Denmark)

    You, Shi; Liu, Zongyu; Zong, Yi

    2015-01-01

    A hybrid energy system, the combination of wind turbines, PV panels and battery storage with effective control mechanism, represents a promising solution to the power fluctuation problem when integrating renewable energy resources (RES) into conventional power systems. This paper proposes a model...

  8. Electrochemical Performance of Low-Carbon Steel in Alkaline Model Solutions Containing Hybrid Aggregates

    NARCIS (Netherlands)

    Koleva, D.A.; Hu, J.; De Wit, J.H.W.; Boshkov, N.; Radeva, T.; Milkova, V.; Van Breugel, K.

    2010-01-01

    This work reports on the electrochemical performance of low-carbon steel electrodes in model alkaline solutions in the presence of 4.9.10-4 g/l hybrid aggregates i.e. cement extract, containing PDADMAC (poly (diallyl, dimethyl ammonium chloride) / PAA (Poly (acrylic acid)/ PDADMAC over a CaO core.

  9. Improving head and neck CTA with hybrid and model-based iterative reconstruction techniques

    NARCIS (Netherlands)

    Niesten, J. M.; van der Schaaf, I. C.; Vos, P. C.; Willemink, MJ; Velthuis, B. K.

    2015-01-01

    AIM: To compare image quality of head and neck computed tomography angiography (CTA) reconstructed with filtered back projection (FBP), hybrid iterative reconstruction (HIR) and model-based iterative reconstruction (MIR) algorithms. MATERIALS AND METHODS: The raw data of 34 studies were

  10. Analytical Modeling and Simulation of Four-Switch Hybrid Power Filter Working with Sixfold Switching Symmetry

    Czech Academy of Sciences Publication Activity Database

    Tlustý, J.; Škramlík, Jiří; Švec, J.; Valouch, Viktor

    2012-01-01

    Roč. 2012, č. 292178 (2012), s. 1-17 ISSN 1024-123X Institutional support: RVO:61388998 Keywords : analytical modeling * four-switch hybrid power filter * sixfold switching symmetry Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering Impact factor: 1.383, year: 2012 http://www.hindawi.com/journals/mpe/2012/292178/

  11. Hybrid Model of Inhomogeneous Solar Wind Plasma Heating by Alfven Wave Spectrum: Parametric Studies

    Science.gov (United States)

    Ofman, L.

    2010-01-01

    Observations of the solar wind plasma at 0.3 AU and beyond show that a turbulent spectrum of magnetic fluctuations is present. Remote sensing observations of the corona indicate that heavy ions are hotter than protons and their temperature is anisotropic (T(sub perpindicular / T(sub parallel) >> 1). We study the heating and the acceleration of multi-ion plasma in the solar wind by a turbulent spectrum of Alfvenic fluctuations using a 2-D hybrid numerical model. In the hybrid model the protons and heavy ions are treated kinetically as particles, while the electrons are included as neutralizing background fluid. This is the first two-dimensional hybrid parametric study of the solar wind plasma that includes an input turbulent wave spectrum guided by observation with inhomogeneous background density. We also investigate the effects of He++ ion beams in the inhomogeneous background plasma density on the heating of the solar wind plasma. The 2-D hybrid model treats parallel and oblique waves, together with cross-field inhomogeneity, self-consistently. We investigate the parametric dependence of the perpendicular heating, and the temperature anisotropy in the H+-He++ solar wind plasma. It was found that the scaling of the magnetic fluctuations power spectrum steepens in the higher-density regions, and the heating is channeled to these regions from the surrounding lower-density plasma due to wave refraction. The model parameters are applicable to the expected solar wind conditions at about 10 solar radii.

  12. Innovation in Doctoral Degrees Designed for Adult Learners: A Hybrid Model in Personal Financial Planning

    Science.gov (United States)

    Grable, John E.

    2011-01-01

    Innovation in doctoral degree program development and delivery provides an effective counterpoint to the expert-apprentice model established in the Middle Ages. The author outlines the importance of innovation in reaching adult learners and describes an innovative hybrid PhD program designed to allow aspiring doctoral adult-age students to pursue…

  13. Putting "Organizations" into an Organization Theory Course: A Hybrid CAO Model for Teaching Organization Theory

    Science.gov (United States)

    Hannah, David R.; Venkatachary, Ranga

    2010-01-01

    In this article, the authors present a retrospective analysis of an instructor's multiyear redesign of a course on organization theory into what is called a hybrid Classroom-as-Organization model. It is suggested that this new course design served to apprentice students to function in quasi-real organizational structures. The authors further argue…

  14. Prediction of Chl-a concentrations in an eutrophic lake using ANN models with hybrid inputs

    Science.gov (United States)

    Aksoy, A.; Yuzugullu, O.

    2017-12-01

    Chlorophyll-a (Chl-a) concentrations in water bodies exhibit both spatial and temporal variations. As a result, frequent sampling is required with higher number of samples. This motivates the use of remote sensing as a monitoring tool. Yet, prediction performances of models that convert radiance values into Chl-a concentrations can be poor in shallow lakes. In this study, Chl-a concentrations in Lake Eymir, a shallow eutrophic lake in Ankara (Turkey), are determined using artificial neural network (ANN) models that use hybrid inputs composed of water quality and meteorological data as well as remotely sensed radiance values to improve prediction performance. Following a screening based on multi-collinearity and principal component analysis (PCA), dissolved-oxygen concentration (DO), pH, turbidity, and humidity were selected among several parameters as the constituents of the hybrid input dataset. Radiance values were obtained from QuickBird-2 satellite. Conversion of the hybrid input into Chl-a concentrations were studied for two different periods in the lake. ANN models were successful in predicting Chl-a concentrations. Yet, prediction performance declined for low Chl-a concentrations in the lake. In general, models with hybrid inputs were superior over the ones that solely used remotely sensed data.

  15. Modeling and simulation using the compositional interchange format for hybrid systems

    NARCIS (Netherlands)

    Sonntag, C.L.W.; Schiffelers, R.R.H.; Beek, van D.A.; Rooda, J.E.; Engell, S.; Troch, I.; Breitenecker, F.

    2009-01-01

    One of the major challenges towards a broad industrial acceptance of hybrid systems techniques and tools is the large number of distinct modeling formalisms and the resulting manual effort for the tool-based solution of many complex design or analysis tasks. A promising approach to achieve

  16. A Generalized Hybrid Multiscale Modeling Approach for Flow and Reactive Transport in Porous Media

    Science.gov (United States)

    Yang, X.; Meng, X.; Tang, Y. H.; Guo, Z.; Karniadakis, G. E.

    2017-12-01

    Using emerging understanding of biological and environmental processes at fundamental scales to advance predictions of the larger system behavior requires the development of multiscale approaches, and there is strong interest in coupling models at different scales together in a hybrid multiscale simulation framework. A limited number of hybrid multiscale simulation methods have been developed for subsurface applications, mostly using application-specific approaches for model coupling. The proposed generalized hybrid multiscale approach is designed with minimal intrusiveness to the at-scale simulators (pre-selected) and provides a set of lightweight C++ scripts to manage a complex multiscale workflow utilizing a concurrent coupling approach. The workflow includes at-scale simulators (using the lattice-Boltzmann method, LBM, at the pore and Darcy scale, respectively), scripts for boundary treatment (coupling and kriging), and a multiscale universal interface (MUI) for data exchange. The current study aims to apply the generalized hybrid multiscale modeling approach to couple pore- and Darcy-scale models for flow and mixing-controlled reaction with precipitation/dissolution in heterogeneous porous media. The model domain is packed heterogeneously that the mixing front geometry is more complex and not known a priori. To address those challenges, the generalized hybrid multiscale modeling approach is further developed to 1) adaptively define the locations of pore-scale subdomains, 2) provide a suite of physical boundary coupling schemes and 3) consider the dynamic change of the pore structures due to mineral precipitation/dissolution. The results are validated and evaluated by comparing with single-scale simulations in terms of velocities, reactive concentrations and computing cost.

  17. A modeling method for hybrid energy behaviors in flexible machining systems

    International Nuclear Information System (INIS)

    Li, Yufeng; He, Yan; Wang, Yan; Wang, Yulin; Yan, Ping; Lin, Shenlong

    2015-01-01

    Increasingly environmental and economic pressures have led to great concerns regarding the energy consumption of machining systems. Understanding energy behaviors of flexible machining systems is a prerequisite for improving energy efficiency of these systems. This paper proposes a modeling method to predict energy behaviors in flexible machining systems. The hybrid energy behaviors not only depend on the technical specification related of machine tools and workpieces, but are significantly affected by individual production scenarios. In the method, hybrid energy behaviors are decomposed into Structure-related energy behaviors, State-related energy behaviors, Process-related energy behaviors and Assignment-related energy behaviors. The modeling method for the hybrid energy behaviors is proposed based on Colored Timed Object-oriented Petri Net (CTOPN). The former two types of energy behaviors are modeled by constructing the structure of CTOPN, whist the latter two types of behaviors are simulated by applying colored tokens and associated attributes. Machining on two workpieces in the experimental workshop were undertaken to verify the proposed modeling method. The results showed that the method can provide multi-perspective transparency on energy consumption related to machine tools, workpieces as well as production management, and is particularly suitable for flexible manufacturing system when frequent changes in machining systems are often encountered. - Highlights: • Energy behaviors in flexible machining systems are modeled in this paper. • Hybrid characteristics of energy behaviors are examined from multiple viewpoints. • Flexible modeling method CTOPN is used to predict the hybrid energy behaviors. • This work offers a multi-perspective transparency on energy consumption

  18. Hybrid Modelling of Individual Movement and Collective Behaviour

    KAUST Repository

    Franz, Benjamin; Erban, Radek

    2013-01-01

    Mathematical models of dispersal in biological systems are often written in terms of partial differential equations (PDEs) which describe the time evolution of population-level variables (concentrations, densities). A more detailed modelling

  19. Modeling and control of a small solar fuel cell hybrid energy system

    Institute of Scientific and Technical Information of China (English)

    LI Wei; ZHU Xin-jian; CAO Guang-yi

    2007-01-01

    This paper describes a solar photovoltaic fuel cell (PVEC) hybrid generation system consisting of a photovoltaic (PV) generator, a proton exchange membrane fuel cell (PEMFC), an electrolyser, a supercapacitor, a storage gas tank and power conditioning unit (PCU). The load is supplied from the PV generator with a fuel cell working in parallel. Excess PV energy when available is converted to hydrogen using an electrolyser for later use in the fuel cell. The individual mathematical model for each component is presented. Control strategy for the system is described. MATLAB/Simulink is used for the simulation of this highly nonlinear hybrid energy system. The simulation results are shown in the paper.

  20. Modeling and Experimental Verification of an Electromagnetic and Piezoelectric Hybrid Energy Harvester

    Directory of Open Access Journals (Sweden)

    Fan Yuanyuan

    2016-11-01

    Full Text Available This paper describes mathematical models of an electromagnetic and piezoelectric hybrid energy harvesting system and provides an analysis of the relationship between the resonance frequency and the configuration parameters of the system. An electromagnetic and piezoelectric energy harvesting device was designed and the experimental results showed good agreement with the analytical results. The maximum load power of the hybrid energy harvesting system achieved 4.25 mW at a resonant frequency of 18 Hz when the acceleration was 0.7 g, which is an increase of 15% compared with the 3.62 mW achieved by a single electromagnetic technique.

  1. Statistical Inference for Porous Materials using Persistent Homology.

    Energy Technology Data Exchange (ETDEWEB)

    Moon, Chul [Univ. of Georgia, Athens, GA (United States); Heath, Jason E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Mitchell, Scott A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-12-01

    We propose a porous materials analysis pipeline using persistent homology. We rst compute persistent homology of binarized 3D images of sampled material subvolumes. For each image we compute sets of homology intervals, which are represented as summary graphics called persistence diagrams. We convert persistence diagrams into image vectors in order to analyze the similarity of the homology of the material images using the mature tools for image analysis. Each image is treated as a vector and we compute its principal components to extract features. We t a statistical model using the loadings of principal components to estimate material porosity, permeability, anisotropy, and tortuosity. We also propose an adaptive version of the structural similarity index (SSIM), a similarity metric for images, as a measure to determine the statistical representative elementary volumes (sREV) for persistence homology. Thus we provide a capability for making a statistical inference of the uid ow and transport properties of porous materials based on their geometry and connectivity.

  2. Model predictive control of an air suspension system with damping multi-mode switching damper based on hybrid model

    Science.gov (United States)

    Sun, Xiaoqiang; Yuan, Chaochun; Cai, Yingfeng; Wang, Shaohua; Chen, Long

    2017-09-01

    This paper presents the hybrid modeling and the model predictive control of an air suspension system with damping multi-mode switching damper. Unlike traditional damper with continuously adjustable damping, in this study, a new damper with four discrete damping modes is applied to vehicle semi-active air suspension. The new damper can achieve different damping modes by just controlling the on-off statuses of two solenoid valves, which makes its damping adjustment more efficient and more reliable. However, since the damping mode switching induces different modes of operation, the air suspension system with the new damper poses challenging hybrid control problem. To model both the continuous/discrete dynamics and the switching between different damping modes, the framework of mixed logical dynamical (MLD) systems is used to establish the system hybrid model. Based on the resulting hybrid dynamical model, the system control problem is recast as a model predictive control (MPC) problem, which allows us to optimize the switching sequences of the damping modes by taking into account the suspension performance requirements. Numerical simulations results demonstrate the efficacy of the proposed control method finally.

  3. Influence of Li-ion Battery Models in the Sizing of Hybrid Storage Systems with Supercapacitors

    DEFF Research Database (Denmark)

    Pinto, Claudio; Barreras, Jorge Varela; de Castro, Ricardo

    2014-01-01

    This paper presents a comparative study of the influence of different aggregated electrical circuit battery models in the sizing process of a hybrid energy storage system (ESS), composed by Li-ion batteries and supercapacitors (SCs). The aim is to find the number of cells required to propel...... a certain vehicle over a predefined driving cycle. During this process, three battery models will be considered. The first consists in a linear static zeroeth order battery model over a restricted operating window. The second is a non-linear static model, while the third takes into account first......-order dynamics of the battery. Simulation results demonstrate that the adoption of a more accurate battery model in the sizing of hybrid ESSs prevents over-sizing, leading to a reduction in the number of cells of up to 29%, and a cost decrease of up to 10%....

  4. Towards Effective Network Intrusion Detection: A Hybrid Model Integrating Gini Index and GBDT with PSO

    Directory of Open Access Journals (Sweden)

    Longjie Li

    2018-01-01

    Full Text Available In order to protect computing systems from malicious attacks, network intrusion detection systems have become an important part in the security infrastructure. Recently, hybrid models that integrating several machine learning techniques have captured more attention of researchers. In this paper, a novel hybrid model was proposed with the purpose of detecting network intrusion effectively. In the proposed model, Gini index is used to select the optimal subset of features, the gradient boosted decision tree (GBDT algorithm is adopted to detect network attacks, and the particle swarm optimization (PSO algorithm is utilized to optimize the parameters of GBDT. The performance of the proposed model is experimentally evaluated in terms of accuracy, detection rate, precision, F1-score, and false alarm rate using the NSL-KDD dataset. Experimental results show that the proposed model is superior to the compared methods.

  5. Complete modeling and software implementation of a virtual solar hydrogen hybrid system

    International Nuclear Information System (INIS)

    Pedrazzi, S.; Zini, G.; Tartarini, P.

    2010-01-01

    A complete mathematical model and software implementation of a solar hydrogen hybrid system has been developed and applied to real data. The mathematical model has been derived from sub-models taken from literature with appropriate modifications and improvements. The model has been implemented as a stand-alone virtual energy system in a model-based, multi-domain software environment. A test run has then been performed on typical residential user data-sets over a year-long period. Results show that the virtual hybrid system can bring about complete grid independence; in particular, hydrogen production balance is positive (+1.25 kg) after a year's operation with a system efficiency of 7%.

  6. Hybrid nested sampling algorithm for Bayesian model selection applied to inverse subsurface flow problems

    International Nuclear Information System (INIS)

    Elsheikh, Ahmed H.; Wheeler, Mary F.; Hoteit, Ibrahim

    2014-01-01

    A Hybrid Nested Sampling (HNS) algorithm is proposed for efficient Bayesian model calibration and prior model selection. The proposed algorithm combines, Nested Sampling (NS) algorithm, Hybrid Monte Carlo (HMC) sampling and gradient estimation using Stochastic Ensemble Method (SEM). NS is an efficient sampling algorithm that can be used for Bayesian calibration and estimating the Bayesian evidence for prior model selection. Nested sampling has the advantage of computational feasibility. Within the nested sampling algorithm, a constrained sampling step is performed. For this step, we utilize HMC to reduce the correlation between successive sampled states. HMC relies on the gradient of the logarithm of the posterior distribution, which we estimate using a stochastic ensemble method based on an ensemble of directional derivatives. SEM only requires forward model runs and the simulator is then used as a black box and no adjoint code is needed. The developed HNS algorithm is successfully applied for Bayesian calibration and prior model selection of several nonlinear subsurface flow problems

  7. A hybrid reliability algorithm using PSO-optimized Kriging model and adaptive importance sampling

    Science.gov (United States)

    Tong, Cao; Gong, Haili

    2018-03-01

    This paper aims to reduce the computational cost of reliability analysis. A new hybrid algorithm is proposed based on PSO-optimized Kriging model and adaptive importance sampling method. Firstly, the particle swarm optimization algorithm (PSO) is used to optimize the parameters of Kriging model. A typical function is fitted to validate improvement by comparing results of PSO-optimized Kriging model with those of the original Kriging model. Secondly, a hybrid algorithm for reliability analysis combined optimized Kriging model and adaptive importance sampling is proposed. Two cases from literatures are given to validate the efficiency and correctness. The proposed method is proved to be more efficient due to its application of small number of sample points according to comparison results.

  8. Hybrid nested sampling algorithm for Bayesian model selection applied to inverse subsurface flow problems

    Energy Technology Data Exchange (ETDEWEB)

    Elsheikh, Ahmed H., E-mail: aelsheikh@ices.utexas.edu [Institute for Computational Engineering and Sciences (ICES), University of Texas at Austin, TX (United States); Institute of Petroleum Engineering, Heriot-Watt University, Edinburgh EH14 4AS (United Kingdom); Wheeler, Mary F. [Institute for Computational Engineering and Sciences (ICES), University of Texas at Austin, TX (United States); Hoteit, Ibrahim [Department of Earth Sciences and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal (Saudi Arabia)

    2014-02-01

    A Hybrid Nested Sampling (HNS) algorithm is proposed for efficient Bayesian model calibration and prior model selection. The proposed algorithm combines, Nested Sampling (NS) algorithm, Hybrid Monte Carlo (HMC) sampling and gradient estimation using Stochastic Ensemble Method (SEM). NS is an efficient sampling algorithm that can be used for Bayesian calibration and estimating the Bayesian evidence for prior model selection. Nested sampling has the advantage of computational feasibility. Within the nested sampling algorithm, a constrained sampling step is performed. For this step, we utilize HMC to reduce the correlation between successive sampled states. HMC relies on the gradient of the logarithm of the posterior distribution, which we estimate using a stochastic ensemble method based on an ensemble of directional derivatives. SEM only requires forward model runs and the simulator is then used as a black box and no adjoint code is needed. The developed HNS algorithm is successfully applied for Bayesian calibration and prior model selection of several nonlinear subsurface flow problems.

  9. Polar representation of centrifugal pump homologous curves

    International Nuclear Information System (INIS)

    Veloso, Marcelo Antonio; Mattos, Joao Roberto Loureiro de

    2008-01-01

    Essential for any mathematical model designed to simulate flow transient events caused by pump operations is the pump performance data. The performance of a centrifugal pump is characterized by four basic parameters: the rotational speed, the volumetric flow rate, the dynamic head, and the hydraulic torque. Any one of these quantities can be expressed as a function of any two others. The curves showing the relationships between these four variables are called the pump characteristic curves, also referred to as four-quadrant curves. The characteristic curves are empirically developed by the pump manufacturer and uniquely describe head and torque as functions of volumetric flow rate and rotation speed. Because of comprising a large amount of points, the four-quadrant configuration is not suitable for computational purposes. However, it can be converted to a simpler form by the development of the homologous curves, in which dynamic head and hydraulic torque ratios are expressed as functions of volumetric flow and rotation speed ratios. The numerical use of the complete set of homologous curves requires specification of sixteen partial curves, being eight for the dynamic head and eight for the hydraulic torque. As a consequence, the handling of homologous curves is still somewhat complicated. In solving flow transient problems that require the pump characteristic data for all the operation zones, the polar form appears as the simplest way to represent the homologous curves. In the polar method, the complete characteristics of a pump can be described by only two closed curves, one for the dynamic head and other for the hydraulic torque, both in function of a single angular coordinate defined adequately in terms of the quotient between volumetric flow ratio and rotation speed ratio. The usefulness and advantages of this alternative method are demonstrated through a practical example in which the homologous curves for a pump of the type used in the main coolant loops of a

  10. Parametric representation of centrifugal pump homologous curves

    International Nuclear Information System (INIS)

    Veloso, Marcelo A.; Mattos, Joao R.L. de

    2015-01-01

    Essential for any mathematical model designed to simulate flow transient events caused by pump operations is the pump performance data. The performance of a centrifugal pump is characterized by four basic quantities: the rotational speed, the volumetric flow rate, the dynamic head, and the hydraulic torque. The curves showing the relationships between these four variables are called the pump characteristic curves. The characteristic curves are empirically developed by the pump manufacturer and uniquely describe head and torque as functions of volumetric flow rate and rotation speed. Because of comprising a large amount of points, this configuration is not suitable for computational purposes. However, it can be converted to a simpler form by the development of the homologous curves, in which dynamic head and hydraulic torque ratios are expressed as functions of volumetric flow and rotation speed ratios. The numerical use of the complete set of homologous curves requires specification of sixteen partial curves, being eight for the dynamic head and eight for the hydraulic torque. As a consequence, the handling of homologous curves is still somewhat complicated. In solving flow transient problems that require the pump characteristic data for all the operation zones, the parametric form appears as the simplest way to deal with the homologous curves. In this approach, the complete characteristics of a pump can be described by only two closed curves, one for the dynamic head and other for the hydraulic torque, both in function of a single angular coordinate defined adequately in terms of the quotient between volumetric flow ratio and rotation speed ratio. The usefulness and advantages of this alternative method are demonstrated through a practical example in which the homologous curves for a pump of the type used in the main coolant loops of a pressurized water reactor (PWR) are transformed to the parametric form. (author)

  11. A general model of distant hybridization reveals the conditions for extinction in Atlantic salmon and brown trout.

    Science.gov (United States)

    Quilodrán, Claudio S; Currat, Mathias; Montoya-Burgos, Juan I

    2014-01-01

    Interspecific hybridization is common in nature but can be increased in frequency or even originated by human actions, such as species introduction or habitat modification, which may threaten species persistence. When hybridization occurs between distantly related species, referred to as "distant hybridization," the resulting hybrids are generally infertile or fertile but do not undergo chromosomal recombination during gametogenesis. Here, we present a model describing this frequent but poorly studied interspecific hybridization to assess its consequences on parental species and to anticipate the conditions under which they can reach extinction. Our general model fully incorporates three important processes: density-dependent competition, dominance/recessivity inheritance of traits and assortative mating. We demonstrate its use and flexibility by assessing population extinction risk between Atlantic salmon and brown trout in Norway, whose interbreeding has recently increased due to farmed fish releases into the wild. We identified the set of conditions under which hybridization may threaten salmonid species. Thanks to the flexibility of our model, we evaluated the effect of an additional risk factor, a parasitic disease, and showed that the cumulative effects dramatically increase the extinction risk. The consequences of distant hybridization are not genetically, but demographically mediated. Our general model is useful to better comprehend the evolution of such hybrid systems and we demonstrated its importance in the field of conservation biology to set up management recommendations when this increasingly frequent type of hybridization is in action.

  12. A General Model of Distant Hybridization Reveals the Conditions for Extinction in Atlantic Salmon and Brown Trout

    Science.gov (United States)

    Quilodrán, Claudio S.; Currat, Mathias; Montoya-Burgos, Juan I.

    2014-01-01

    Interspecific hybridization is common in nature but can be increased in frequency or even originated by human actions, such as species introduction or habitat modification, which may threaten species persistence. When hybridization occurs between distantly related species, referred to as “distant hybridization,” the resulting hybrids are generally infertile or fertile but do not undergo chromosomal recombination during gametogenesis. Here, we present a model describing this frequent but poorly studied interspecific hybridization to assess its consequences on parental species and to anticipate the conditions under which they can reach extinction. Our general model fully incorporates three important processes: density-dependent competition, dominance/recessivity inheritance of traits and assortative mating. We demonstrate its use and flexibility by assessing population extinction risk between Atlantic salmon and brown trout in Norway, whose interbreeding has recently increased due to farmed fish releases into the wild. We identified the set of conditions under which hybridization may threaten salmonid species. Thanks to the flexibility of our model, we evaluated the effect of an additional risk factor, a parasitic disease, and showed that the cumulative effects dramatically increase the extinction risk. The consequences of distant hybridization are not genetically, but demographically mediated. Our general model is useful to better comprehend the evolution of such hybrid systems and we demonstrated its importance in the field of conservation biology to set up management recommendations when this increasingly frequent type of hybridization is in action. PMID:25003336

  13. A general model of distant hybridization reveals the conditions for extinction in Atlantic salmon and brown trout.

    Directory of Open Access Journals (Sweden)

    Claudio S Quilodrán

    Full Text Available Interspecific hybridization is common in nature but can be increased in frequency or even originated by human actions, such as species introduction or habitat modification, which may threaten species persistence. When hybridization occurs between distantly related species, referred to as "distant hybridization," the resulting hybrids are generally infertile or fertile but do not undergo chromosomal recombination during gametogenesis. Here, we present a model describing this frequent but poorly studied interspecific hybridization to assess its consequences on parental species and to anticipate the conditions under which they can reach extinction. Our general model fully incorporates three important processes: density-dependent competition, dominance/recessivity inheritance of traits and assortative mating. We demonstrate its use and flexibility by assessing population extinction risk between Atlantic salmon and brown trout in Norway, whose interbreeding has recently increased due to farmed fish releases into the wild. We identified the set of conditions under which hybridization may threaten salmonid species. Thanks to the flexibility of our model, we evaluated the effect of an additional risk factor, a parasitic disease, and showed that the cumulative effects dramatically increase the extinction risk. The consequences of distant hybridization are not genetically, but demographically mediated. Our general model is useful to better comprehend the evolution of such hybrid systems and we demonstrated its importance in the field of conservation biology to set up management recommendations when this increasingly frequent type of hybridization is in action.

  14. Simulation-optimization framework for multi-site multi-season hybrid stochastic streamflow modeling

    Science.gov (United States)

    Srivastav, Roshan; Srinivasan, K.; Sudheer, K. P.

    2016-11-01

    A simulation-optimization (S-O) framework is developed for the hybrid stochastic modeling of multi-site multi-season streamflows. The multi-objective optimization model formulated is the driver and the multi-site, multi-season hybrid matched block bootstrap model (MHMABB) is the simulation engine within this framework. The multi-site multi-season simulation model is the extension of the existing single-site multi-season simulation model. A robust and efficient evolutionary search based technique, namely, non-dominated sorting based genetic algorithm (NSGA - II) is employed as the solution technique for the multi-objective optimization within the S-O framework. The objective functions employed are related to the preservation of the multi-site critical deficit run sum and the constraints introduced are concerned with the hybrid model parameter space, and the preservation of certain statistics (such as inter-annual dependence and/or skewness of aggregated annual flows). The efficacy of the proposed S-O framework is brought out through a case example from the Colorado River basin. The proposed multi-site multi-season model AMHMABB (whose parameters are obtained from the proposed S-O framework) preserves the temporal as well as the spatial statistics of the historical flows. Also, the other multi-site deficit run characteristics namely, the number of runs, the maximum run length, the mean run sum and the mean run length are well preserved by the AMHMABB model. Overall, the proposed AMHMABB model is able to show better streamflow modeling performance when compared with the simulation based SMHMABB model, plausibly due to the significant role played by: (i) the objective functions related to the preservation of multi-site critical deficit run sum; (ii) the huge hybrid model parameter space available for the evolutionary search and (iii) the constraint on the preservation of the inter-annual dependence. Split-sample validation results indicate that the AMHMABB model is

  15. Statistical comparison of a hybrid approach with approximate and exact inference models for Fusion 2+

    Science.gov (United States)

    Lee, K. David; Wiesenfeld, Eric; Gelfand, Andrew

    2007-04-01

    One of the greatest challenges in modern combat is maintaining a high level of timely Situational Awareness (SA). In many situations, computational complexity and accuracy considerations make the development and deployment of real-time, high-level inference tools very difficult. An innovative hybrid framework that combines Bayesian inference, in the form of Bayesian Networks, and Possibility Theory, in the form of Fuzzy Logic systems, has recently been introduced to provide a rigorous framework for high-level inference. In previous research, the theoretical basis and benefits of the hybrid approach have been developed. However, lacking is a concrete experimental comparison of the hybrid framework with traditional fusion methods, to demonstrate and quantify this benefit. The goal of this research, therefore, is to provide a statistical analysis on the comparison of the accuracy and performance of hybrid network theory, with pure Bayesian and Fuzzy systems and an inexact Bayesian system approximated using Particle Filtering. To accomplish this task, domain specific models will be developed under these different theoretical approaches and then evaluated, via Monte Carlo Simulation, in comparison to situational ground truth to measure accuracy and fidelity. Following this, a rigorous statistical analysis of the performance results will be performed, to quantify the benefit of hybrid inference to other fusion tools.

  16. Promoting Student Autonomy and Competence Using a Hybrid Model for Teaching Physical Activity

    Directory of Open Access Journals (Sweden)

    Christine Bachman

    2015-01-01

    Full Text Available For approximately twenty-years, Web-enhanced learning environments have been popular in higher education. Much research has examined how best practices can integrate technology, pedagogical theories, and resources to enhance learning. Numerous studies of hybrid teaching have revealed mostly positive effects. Yet, very little research has examined how to teach a successful physical activity course using a hybrid format. Review of the literature: We reviewed the research regarding the design and implementation of a Web-enhanced physical activity course in a college population using pedagogical principles of learning and the10 self-determination theory. Method: Data were collected from students at the beginning and end of the course. The hybrid course consisted of completing weekly online activities, and selecting and participating in a face-to-face physical activity based on student’s choice. Conclusion: The authors propose this template as a model to assist faculty in designing and implementing a blended physical activity course.

  17. Numerical weather prediction (NWP) and hybrid ARMA/ANN model to predict global radiation

    International Nuclear Information System (INIS)

    Voyant, Cyril; Muselli, Marc; Paoli, Christophe; Nivet, Marie-Laure

    2012-01-01

    We propose in this paper an original technique to predict global radiation using a hybrid ARMA/ANN model and data issued from a numerical weather prediction model (NWP). We particularly look at the multi-layer perceptron (MLP). After optimizing our architecture with NWP and endogenous data previously made stationary and using an innovative pre-input layer selection method, we combined it to an ARMA model from a rule based on the analysis of hourly data series. This model has been used to forecast the hourly global radiation for five places in Mediterranean area. Our technique outperforms classical models for all the places. The nRMSE for our hybrid model MLP/ARMA is 14.9% compared to 26.2% for the naïve persistence predictor. Note that in the standalone ANN case the nRMSE is 18.4%. Finally, in order to discuss the reliability of the forecaster outputs, a complementary study concerning the confidence interval of each prediction is proposed. -- Highlights: ► Time series forecasting with hybrid method based on the use of ALADIN numerical weather model, ANN and ARMA. ► Innovative pre-input layer selection method. ► Combination of optimized MLP and ARMA model obtained from a rule based on the analysis of hourly data series. ► Stationarity process (method and control) for the global radiation time series.

  18. Wind speed forecasting in three different regions of Mexico, using a hybrid ARIMA-ANN model

    Energy Technology Data Exchange (ETDEWEB)

    Cadenas, Erasmo [Facultad de Ingenieria Mecanica, Universidad Michoacana de San Nicolas de Hidalgo, Santiago Tapia No. 403, Centro (Mexico); Rivera, Wilfrido [Centro de Ivestigacion en Energia, Universidad Nacional Autonoma de Mexico, Apartado Postal 34, Temixco 62580, Morelos (Mexico)

    2010-12-15

    In this paper the wind speed forecasting in the Isla de Cedros in Baja California, in the Cerro de la Virgen in Zacatecas and in Holbox in Quintana Roo is presented. The time series utilized are average hourly wind speed data obtained directly from the measurements realized in the different sites during about one month. In order to do wind speed forecasting Hybrid models consisting of Autoregressive Integrated Moving Average (ARIMA) models and Artificial Neural Network (ANN) models were developed. The ARIMA models were first used to do the wind speed forecasting of the time series and then with the obtained errors ANN were built taking into account the nonlinear tendencies that the ARIMA technique could not identify, reducing with this the final errors. Once the Hybrid models were developed 48 data out of sample for each one of the sites were used to do the wind speed forecasting and the results were compared with the ARIMA and the ANN models working separately. Statistical error measures such as the mean error (ME), the mean square error (MSE) and the mean absolute error (MAE) were calculated to compare the three methods. The results showed that the Hybrid models predict the wind velocities with a higher accuracy than the ARIMA and ANN models in the three examined sites. (author)

  19. Kinematic modeling of a 7-degree of freedom spatial hybrid manipulator for medical surgery.

    Science.gov (United States)

    Singh, Amanpreet; Singla, Ekta; Soni, Sanjeev; Singla, Ashish

    2018-01-01

    The prime objective of this work is to deal with the kinematics of spatial hybrid manipulators. In this direction, in 1955, Denavit and Hartenberg proposed a consistent and concise method, known as D-H parameters method, to deal with kinematics of open serial chains. From literature review, it is found that D-H parameter method is widely used to model manipulators consisting of lower pairs. However, the method leads to ambiguities when applied to closed-loop, tree-like and hybrid manipulators. Furthermore, in the dearth of any direct method to model closed-loop, tree-like and hybrid manipulators, revisions of this method have been proposed from time-to-time by different researchers. One such kind of revision using the concept of dummy frames has successfully been proposed and implemented by the authors on spatial hybrid manipulators. In that work, authors have addressed the orientational inconsistency of the D-H parameter method, restricted to body-attached frames only. In the current work, the condition of body-attached frames is relaxed and spatial frame attachment is considered to derive the kinematic model of a 7-degree of freedom spatial hybrid robotic arm, along with the development of closed-loop constraints. The validation of the new kinematic model has been performed with the help of a prototype of this 7-degree of freedom arm, which is being developed at Council of Scientific & Industrial Research-Central Scientific Instruments Organisation Chandigarh to aid the surgeon during a medical surgical task. Furthermore, the developed kinematic model is used to develop the first column of the Jacobian matrix, which helps in providing the estimate of the tip velocity of the 7-degree of freedom manipulator when the first joint velocity is known.

  20. Proposing a Hybrid Model Based on Robson's Classification for Better Impact on Trends of Cesarean Deliveries.

    Science.gov (United States)

    Hans, Punit; Rohatgi, Renu

    2017-06-01

    To construct a hybrid model classification for cesarean section (CS) deliveries based on the woman-characteristics (Robson's classification with additional layers of indications for CS, keeping in view low-resource settings available in India). This is a cross-sectional study conducted at Nalanda Medical College, Patna. All the women delivered from January 2016 to May 2016 in the labor ward were included. Results obtained were compared with the values obtained for India, from secondary analysis of WHO multi-country survey (2010-2011) by Joshua Vogel and colleagues' study published in "The Lancet Global Health." The three classifications (indication-based, Robson's and hybrid model) applied for categorization of the cesarean deliveries from the same sample of data and a semiqualitative evaluations done, considering the main characteristics, strengths and weaknesses of each classification system. The total number of women delivered during study period was 1462, out of which CS deliveries were 471. Overall, CS rate calculated for NMCH, hospital in this specified period, was 32.21% ( p  = 0.001). Hybrid model scored 23/23, and scores of Robson classification and indication-based classification were 21/23 and 10/23, respectively. Single-study centre and referral bias are the limitations of the study. Given the flexibility of the classifications, we constructed a hybrid model based on the woman-characteristics system with additional layers of other classification. Indication-based classification answers why, Robson classification answers on whom, while through our hybrid model we get to know why and on whom cesarean deliveries are being performed.

  1. Modelling grain-scattered ultrasound in austenitic stainless-steel welds: A hybrid model

    International Nuclear Information System (INIS)

    Nowers, O.; Duxbury, D. J.; Velichko, A.; Drinkwater, B. W.

    2015-01-01

    The ultrasonic inspection of austenitic stainless steel welds can be challenging due to their coarse grain structure, charaterised by preferentially oriented, elongated grains. The anisotropy of the weld is manifested as both a ‘steering’ of the beam and the back-scatter of energy due to the macroscopic granular structure of the weld. However, the influence of weld properties, such as mean grain size and orientation distribution, on the magnitude of scattered ultrasound is not well understood. A hybrid model has been developed to allow the study of grain-scatter effects in austenitic welds. An efficient 2D Finite Element (FE) method is used to calculate the complete scattering response from a single elliptical austenitic grain of arbitrary length and width as a function of the specific inspection frequency. A grain allocation model of the weld is presented to approximate the characteristic structures observed in austenitic welds and the complete scattering behaviour of each grain calculated. This model is incorporated into a semi-analytical framework for a single-element inspection of a typical weld in immersion. Experimental validation evidence is demonstrated indicating excellent qualitative agreement of SNR as a function of frequency and a minimum SNR difference of 2 dB at a centre frequency of 2.25 MHz. Additionally, an example Monte-Carlo study is presented detailing the variation of SNR as a function of the anisotropy distribution of the weld, and the application of confidence analysis to inform inspection development

  2. Identification of putative agouti-related protein(87-132)-melanocortin-4 receptor interactions by homology molecular modeling and validation using chimeric peptide ligands.

    Science.gov (United States)

    Wilczynski, Andrzej; Wang, Xiang S; Joseph, Christine G; Xiang, Zhimin; Bauzo, Rayna M; Scott, Joseph W; Sorensen, Nicholas B; Shaw, Amanda M; Millard, William J; Richards, Nigel G; Haskell-Luevano, Carrie

    2004-04-22

    Agouti-related protein (AGRP) is one of only two naturally known antagonists of G-protein-coupled receptors (GPCRs) identified to date. Specifically, AGRP antagonizes the brain melanocortin-3 and -4 receptors involved in energy homeostasis. Alpha-melanocyte stimulating hormone (alpha-MSH) is one of the known endogenous agonists for these melanocortin receptors. Insight into putative interactions between the antagonist AGRP amino acids with the melanocortin-4 receptor (MC4R) may be important for the design of unique ligands for the treatment of obesity related diseases and is currently lacking in the literature. A three-dimensional homology molecular model of the mouse MC4 receptor complex with the hAGRP(87-132) ligand docked into the receptor has been developed to identify putative antagonist ligand-receptor interactions. Key putative AGRP-MC4R interactions include the Arg111 of hAGRP(87-132) interacting in a negatively charged pocket located in a cavity formed by transmembrane spanning (TM) helices 1, 2, 3, and 7, capped by the acidic first extracellular loop (EL1) and specifically with the conserved melanocortin receptor residues mMC4R Glu92 (TM2), mMC4R Asp114 (TM3), and mMC4R Asp118 (TM3). Additionally, Phe112 and Phe113 of hAGRP(87-132) putatively interact with an aromatic hydrophobic pocket formed by the mMC4 receptor residues Phe176 (TM4), Phe193 (TM5), Phe253 (TM6), and Phe254 (TM6). To validate the AGRP-mMC4R model complex presented herein from a ligand perspective, we generated nine chimeric peptide ligands based on a modified antagonist template of the hAGRP(109-118) (Tyr-c[Asp-Arg-Phe-Phe-Asn-Ala-Phe-Dpr]-Tyr-NH(2)). In these chimeric ligands, the antagonist AGRP Arg-Phe-Phe residues were replaced by the melanocortin agonist His/D-Phe-Arg-Trp amino acids. These peptides resulted in agonist activity at the mouse melanocortin receptors (mMC1R and mMC3-5Rs). The most notable results include the identification of a novel subnanomolar melanocortin peptide

  3. A hybrid, coupled approach for modeling charged fluids from the nano to the mesoscale

    Science.gov (United States)

    Cheung, James; Frischknecht, Amalie L.; Perego, Mauro; Bochev, Pavel

    2017-11-01

    We develop and demonstrate a new, hybrid simulation approach for charged fluids, which combines the accuracy of the nonlocal, classical density functional theory (cDFT) with the efficiency of the Poisson-Nernst-Planck (PNP) equations. The approach is motivated by the fact that the more accurate description of the physics in the cDFT model is required only near the charged surfaces, while away from these regions the PNP equations provide an acceptable representation of the ionic system. We formulate the hybrid approach in two stages. The first stage defines a coupled hybrid model in which the PNP and cDFT equations act independently on two overlapping domains, subject to suitable interface coupling conditions. At the second stage we apply the principles of the alternating Schwarz method to the hybrid model by using the interface conditions to define the appropriate boundary conditions and volume constraints exchanged between the PNP and the cDFT subdomains. Numerical examples with two representative examples of ionic systems demonstrate the numerical properties of the method and its potential to reduce the computational cost of a full cDFT calculation, while retaining the accuracy of the latter near the charged surfaces.

  4. Modeling Hybridization Kinetics of Gene Probes in a DNA Biochip Using FEMLAB

    Science.gov (United States)

    Munir, Ahsan; Waseem, Hassan; Williams, Maggie R.; Stedtfeld, Robert D.; Gulari, Erdogan; Tiedje, James M.; Hashsham, Syed A.

    2017-01-01

    Microfluidic DNA biochips capable of detecting specific DNA sequences are useful in medical diagnostics, drug discovery, food safety monitoring and agriculture. They are used as miniaturized platforms for analysis of nucleic acids-based biomarkers. Binding kinetics between immobilized single stranded DNA on the surface and its complementary strand present in the sample are of interest. To achieve optimal sensitivity with minimum sample size and rapid hybridization, ability to predict the kinetics of hybridization based on the thermodynamic characteristics of the probe is crucial. In this study, a computer aided numerical model for the design and optimization of a flow-through biochip was developed using a finite element technique packaged software tool (FEMLAB; package included in COMSOL Multiphysics) to simulate the transport of DNA through a microfluidic chamber to the reaction surface. The model accounts for fluid flow, convection and diffusion in the channel and on the reaction surface. Concentration, association rate constant, dissociation rate constant, recirculation flow rate, and temperature were key parameters affecting the rate of hybridization. The model predicted the kinetic profile and signal intensities of eighteen 20-mer probes targeting vancomycin resistance genes (VRGs). Predicted signal intensities and hybridization kinetics strongly correlated with experimental data in the biochip (R2 = 0.8131). PMID:28555058

  5. Modeling Hybridization Kinetics of Gene Probes in a DNA Biochip Using FEMLAB

    Directory of Open Access Journals (Sweden)

    Ahsan Munir

    2017-05-01

    Full Text Available Microfluidic DNA biochips capable of detecting specific DNA sequences are useful in medical diagnostics, drug discovery, food safety monitoring and agriculture. They are used as miniaturized platforms for analysis of nucleic acids-based biomarkers. Binding kinetics between immobilized single stranded DNA on the surface and its complementary strand present in the sample are of interest. To achieve optimal sensitivity with minimum sample size and rapid hybridization, ability to predict the kinetics of hybridization based on the thermodynamic characteristics of the probe is crucial. In this study, a computer aided numerical model for the design and optimization of a flow-through biochip was developed using a finite element technique packaged software tool (FEMLAB; package included in COMSOL Multiphysics to simulate the transport of DNA through a microfluidic chamber to the reaction surface. The model accounts for fluid flow, convection and diffusion in the channel and on the reaction surface. Concentration, association rate constant, dissociation rate constant, recirculation flow rate, and temperature were key parameters affecting the rate of hybridization. The model predicted the kinetic profile and signal intensities of eighteen 20-mer probes targeting vancomycin resistance genes (VRGs. Predicted signal intensities and hybridization kinetics strongly correlated with experimental data in the biochip (R2 = 0.8131.

  6. A hybrid classical-quantum approach for ultra-scaled confined nanostructures : modeling and simulation*

    Directory of Open Access Journals (Sweden)

    Pietra Paola

    2012-04-01

    Full Text Available We propose a hybrid classical-quantum model to study the motion of electrons in ultra-scaled confined nanostructures. The transport of charged particles, considered as one dimensional, is described by a quantum effective mass model in the active zone coupled directly to a drift-diffusion problem in the rest of the device. We explain how this hybrid model takes into account the peculiarities due to the strong confinement and we present numerical simulations for a simplified carbon nanotube. Nous proposons un modèle hybride classique-quantique pour décrire le mouvement des électrons dans des nanostructures très fortement confinées. Le transport des particules, consideré unidimensionel, est décrit par un modèle quantique avec masse effective dans la zone active couplé à un problème de dérive-diffusion dans le reste du domaine. Nous expliquons comment ce modèle hybride prend en compte les spécificités de ce très fort confinement et nous présentons des résultats numériques pour un nanotube de carbone simplifié.

  7. Hybrid Modelling of a Traveling Wave Piezoelectric Motor

    DEFF Research Database (Denmark)

    El, Ghouti N.

    a theoretical model is derived. Since the dynamic characteristics of the real motor are difficult to capture in an analytical model, and the parameters of the motor are time varying and highly nonlinear, then some assumptions are required in order to simplify the modeling task and thus provide a suitable model......This thesis considers the modeling of the traveling wave piezoelectric motor (PEM). The rotary traveling wave ultrasonic motor "Shinsei type USR60" is the case study considered in this work. The traveling wave PEM has excellent performance and many useful features such as high holding torque, high....... Despite many attempts a lumped motor model of the PEM is unavailable so far. The dynamical characteristics of the PEM are complicated, highly nonlinear, and the motor parameters are time varying due to temperature rise and changes in motor drive operating conditions. Therefore it is difficult to predict...

  8. A hybrid model for the computationally-efficient simulation of the cerebellar granular layer

    Directory of Open Access Journals (Sweden)

    Anna eCattani

    2016-04-01

    Full Text Available The aim of the present paper is to efficiently describe the membrane potential dynamics of neural populations formed by species having a high density difference in specific brain areas. We propose a hybrid model whose main ingredients are a conductance-based model (ODE system and its continuous counterpart (PDE system obtained through a limit process in which the number of neurons confined in a bounded region of the brain tissue is sent to infinity. Specifically, in the discrete model, each cell is described by a set of time-dependent variables, whereas in the continuum model, cells are grouped into populations that are described by a set of continuous variables.Communications between populations, which translate into interactions among the discrete and the continuous models, are the essence of the hybrid model we present here. The cerebellum and cerebellum-like structures show in their granular layer a large difference in the relative density of neuronal species making them a natural testing ground for our hybrid model. By reconstructing the ensemble activity of the cerebellar granular layer network and by comparing our results to a more realistic computational network, we demonstrate that our description of the network activity, even though it is not biophysically detailed, is still capable of reproducing salient features of neural network dynamics. Our modeling approach yields a significant computational cost reduction by increasing the simulation speed at least $270$ times. The hybrid model reproduces interesting dynamics such as local microcircuit synchronization, traveling waves, center-surround and time-windowing.

  9. HYBRID MODELING BASED ON SCSG-BR AND ORTHOPHOTO

    Directory of Open Access Journals (Sweden)

    G. Zhou

    2018-05-01

    Full Text Available With the development of digital city, digital applications are more and more widespread, while the urban buildings are more complex. Therefore, establishing an effective data model is the key to express urban building models accurately. In addition, the combination of 3D building model and remote sensing data become a trend to build digital city there are a large amount of data resulting in data redundancy. In order to solve the limitation of single modelling of constructive solid geometry (CSG, this paper presents a mixed modelling method based on SCSG-BR for urban buildings representation. On one hand, the improved CSG method, which is called as “Spatial CSG (SCSG” representation method, is used to represent the exterior shape of urban buildings. On the other hand, the boundary representation (BR method represents the topological relationship between geometric elements of urban building, in which the textures is considered as the attribute data of the wall and the roof of urban building. What's more, the method combined file database and relational database is used to manage the data of three-dimensional building model, which can decrease the complex processes in texture mapping. During the data processing, the least-squares algorithm with constraints is used to orthogonalize the building polygons and adjust the polygons topology to ensure the accuracy of the modelling data. Finally, this paper matches the urban building model with the corresponding orthophoto. This paper selects data of Denver, Colorado, USA to establish urban building realistic model. The results show that the SCSG-BR method can represent the topological relations of building more precisely. The organization and management of urban building model data reduce the redundancy of data and improve modelling speed. The combination of orthophoto and urban building model further strengthens the application in view analysis and spatial query, which enhance the scope of digital

  10. Hybrid Modeling Based on Scsg-Br and Orthophoto

    Science.gov (United States)

    Zhou, G.; Huang, Y.; Yue, T.; Li, X.; Huang, W.; He, C.; Wu, Z.

    2018-05-01

    With the development of digital city, digital applications are more and more widespread, while the urban buildings are more complex. Therefore, establishing an effective data model is the key to express urban building models accurately. In addition, the combination of 3D building model and remote sensing data become a trend to build digital city there are a large amount of data resulting in data redundancy. In order to solve the limitation of single modelling of constructive solid geometry (CSG), this paper presents a mixed modelling method based on SCSG-BR for urban buildings representation. On one hand, the improved CSG method, which is called as "Spatial CSG (SCSG)" representation method, is used to represent the exterior shape of urban buildings. On the other hand, the boundary representation (BR) method represents the topological relationship between geometric elements of urban building, in which the textures is considered as the attribute data of the wall and the roof of urban building. What's more, the method combined file database and relational database is used to manage the data of three-dimensional building model, which can decrease the complex processes in texture mapping. During the data processing, the least-squares algorithm with constraints is used to orthogonalize the building polygons and adjust the polygons topology to ensure the accuracy of the modelling data. Finally, this paper matches the urban building model with the corresponding orthophoto. This paper selects data of Denver, Colorado, USA to establish urban building realistic model. The results show that the SCSG-BR method can represent the topological relations of building more precisely. The organization and management of urban building model data reduce the redundancy of data and improve modelling speed. The combination of orthophoto and urban building model further strengthens the application in view analysis and spatial query, which enhance the scope of digital city applications.

  11. A Toolkit for Building Hybrid, Multi-Resolution PMESII Models

    National Research Council Canada - National Science Library

    Bachman, John A; Harper, Karen A

    2007-01-01

    ...) models in support of a Commander's Predictive Environment (CPE) was developed. This development environment is based upon Charles River Analytic's Graphical Agent Development Environment (GRADE...

  12. Hybrid morphological modelling of shoreline response to a detached breakwater

    DEFF Research Database (Denmark)

    Kristensen, Sten Esbjørn; Drønen, Nils; Deigaard, Rolf

    2013-01-01

    We present a new type of model for calculating morphological changes induced by the presence of breakwaters. The model combines a process based area model, used to calculate the sediment transport field in the two horizontal dimensions, with a simplified morphological updating scheme where the ev...... in more detail the evolving morphology behind coastal breakwaters. It is demonstrated how the model is able to calculate the evolution of either salient or tombolo planforms, and furthermore it is shown that the results are in reasonable agreement with existing rules....

  13. Application of a New Hybrid RANS/LES Modeling Paradigm to Compressible Flow

    Science.gov (United States)

    Oliver, Todd; Pederson, Clark; Haering, Sigfried; Moser, Robert

    2017-11-01

    It is well-known that traditional hybrid RANS/LES modeling approaches suffer from a number of deficiencies. These deficiencies often stem from overly simplistic blending strategies based on scalar measures of turbulence length scale and grid resolution and from use of isotropic subgrid models in LES regions. A recently developed hybrid modeling approach has shown promise in overcoming these deficiencies in incompressible flows [Haering, 2015]. In the approach, RANS/LES blending is accomplished using a hybridization parameter that is governed by an additional model transport equation and is driven to achieve equilibrium between the resolved and unresolved turbulence for the given grid. Further, the model uses an tensor eddy viscosity that is formulated to represent the effects of anisotropic grid resolution on subgrid quantities. In this work, this modeling approach is extended to compressible flows and implemented in the compressible flow solver SU2 (http://su2.stanford.edu/). We discuss both modeling and implementation challenges and show preliminary results for compressible flow test cases with smooth wall separation.

  14. Two-field axion-monodromy hybrid inflation model: Dante's Waterfall

    Science.gov (United States)

    Carone, Christopher D.; Erlich, Joshua; Sensharma, Anuraag; Wang, Zhen

    2015-02-01

    We describe a hybrid axion-monodromy inflation model motivated by the Dante's Inferno scenario. In Dante's Inferno, a two-field potential features a stable trench along which a linear combination of the two fields slowly rolls, rendering the dynamics essentially identical to that of single-field chaotic inflation. A shift symmetry allows for the Lyth bound to be effectively evaded as in other axion-monodromy models. In our proposal, the potential is concave downward near the origin and the inflaton trajectory is a gradual downward spiral, ending at a point where the trench becomes unstable. There, the fields begin falling rapidly towards the minimum of the potential and inflation terminates as in a hybrid model. We find parameter choices that reproduce observed features of the cosmic microwave background, and discuss our model in light of recent results from the BICEP2 and Planck experiments.

  15. Predictive simulation of bidirectional Glenn shunt using a hybrid blood vessel model.

    Science.gov (United States)

    Li, Hao; Leow, Wee Kheng; Chiu, Ing-Sh

    2009-01-01

    This paper proposes a method for performing predictive simulation of cardiac surgery. It applies a hybrid approach to model the deformation of blood vessels. The hybrid blood vessel model consists of a reference Cosserat rod and a surface mesh. The reference Cosserat rod models the blood vessel's global bending, stretching, twisting and shearing in a physically correct manner, and the surface mesh models the surface details of the blood vessel. In this way, the deformation of blood vessels can be computed efficiently and accurately. Our predictive simulation system can produce complex surgical results given a small amount of user inputs. It allows the surgeon to easily explore various surgical options and evaluate them. Tests of the system using bidirectional Glenn shunt (BDG) as an application example show that the results produc by the system are similar to real surgical results.

  16. Optimal design of supply chain network under uncertainty environment using hybrid analytical and simulation modeling approach

    Science.gov (United States)

    Chiadamrong, N.; Piyathanavong, V.

    2017-12-01

    Models that aim to optimize the design of supply chain networks have gained more interest in the supply chain literature. Mixed-integer linear programming and discrete-event simulation are widely used for such an optimization problem. We present a hybrid approach to support decisions for supply chain network design using a combination of analytical and discrete-event simulation models. The proposed approach is based on iterative procedures until the difference between subsequent solutions satisfies the pre-determined termination criteria. The effectiveness of proposed approach is illustrated by an example, which shows closer to optimal results with much faster solving time than the results obtained from the conventional simulation-based optimization model. The efficacy of this proposed hybrid approach is promising and can be applied as a powerful tool in designing a real supply chain network. It also provides the possibility to model and solve more realistic problems, which incorporate dynamism and uncertainty.

  17. An Advanced Environment for Hybrid Modeling of Biological Systems Based on Modelica

    Directory of Open Access Journals (Sweden)

    Proß Sabrina

    2011-03-01

    Full Text Available Biological systems are often very complex so that an appropriate formalism is needed for modeling their behavior. Hybrid Petri Nets, consisting of time-discrete Petri Net elements as well as continuous ones, have proven to be ideal for this task. Therefore, a new Petri Net library was implemented based on the object-oriented modeling language Modelica which allows the modeling of discrete, stochastic and continuous Petri Net elements by differential, algebraic and discrete equations. An appropriate Modelica-tool performs the hybrid simulation with discrete events and the solution of continuous differential equations. A special sub-library contains so-called wrappers for specific reactions to simplify the modeling process.

  18. Transmission network expansion planning based on hybridization model of neural networks and harmony search algorithm

    Directory of Open Access Journals (Sweden)

    Mohammad Taghi Ameli

    2012-01-01

    Full Text Available Transmission Network Expansion Planning (TNEP is a basic part of power network planning that determines where, when and how many new transmission lines should be added to the network. So, the TNEP is an optimization problem in which the expansion purposes are optimized. Artificial Intelligence (AI tools such as Genetic Algorithm (GA, Simulated Annealing (SA, Tabu Search (TS and Artificial Neural Networks (ANNs are methods used for solving the TNEP problem. Today, by using the hybridization models of AI tools, we can solve the TNEP problem for large-scale systems, which shows the effectiveness of utilizing such models. In this paper, a new approach to the hybridization model of Probabilistic Neural Networks (PNNs and Harmony Search Algorithm (HSA was used to solve the TNEP problem. Finally, by considering the uncertain role of the load based on a scenario technique, this proposed model was tested on the Garver’s 6-bus network.

  19. Non-linear hybrid control oriented modelling of a digital displacement machine

    DEFF Research Database (Denmark)

    Pedersen, Niels Henrik; Johansen, Per; Andersen, Torben O.

    2017-01-01

    Proper feedback control of digital fluid power machines (Pressure, flow, torque or speed control) requires a control oriented model, from where the system dynamics can be analyzed, stability can be proven and design criteria can be specified. The development of control oriented models for hydraulic...... Digital Displacement Machines (DDM) is complicated due to non-smooth machine behavior, where the dynamics comprises both analog, digital and non-linear elements. For a full stroke operated DDM the power throughput is altered in discrete levels based on the ratio of activated pressure chambers....... In this paper, a control oriented hybrid model is established, which combines the continuous non-linear pressure chamber dynamics and the discrete shaft position dependent activation of the pressure chambers. The hybrid machine model is further extended to describe the dynamics of a Digital Fluid Power...

  20. Driving-behavior-aware stochastic model predictive control for plug-in hybrid electric buses

    International Nuclear Information System (INIS)

    Li, Liang; You, Sixiong; Yang, Chao; Yan, Bingjie; Song, Jian; Chen, Zheng

    2016-01-01

    Highlights: • The novel approximated global optimal energy management strategy has been proposed for hybrid powertrains. • Eight typical driving behaviors have been classified with K-means to deal with the multiplicative traffic conditions. • The stochastic driver models of different driving behaviors were established based on the Markov chains. • ECMS was used to modify the SMPC-based energy management strategy to improve its fuel economy. • The approximated global optimal energy management strategy for plug-in hybrid electric buses has been verified and analyzed. - Abstract: Driving cycles of a city bus is statistically characterized by some repetitive features, which makes the predictive energy management strategy very desirable to obtain approximate optimal fuel economy of a plug-in hybrid electric bus. But dealing with the complicated traffic conditions and finding an approximated global optimal strategy which is applicable to the plug-in hybrid electric bus still remains a challenging technique. To solve this problem, a novel driving-behavior-aware modified stochastic model predictive control method is proposed for the plug-in hybrid electric bus. Firstly, the K-means is employed to classify driving behaviors, and the driver models based on Markov chains is obtained under different kinds of driving behaviors. While the obtained driver behaviors are regarded as stochastic disturbance inputs, the local minimum fuel consumption might be obtained with a traditional stochastic model predictive control at each step, taking tracking the reference battery state of charge trajectory into consideration in the finite predictive horizons. However, this technique is still accompanied by some working points with reduced/worsened fuel economy. Thus, the stochastic model predictive control is modified with the equivalent consumption minimization strategy to eliminate these undesirable working points. The results in real-world city bus routines show that the

  1. Hybrid Compensatory-Noncompensatory Choice Sets in Semicompensatory Models

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Bekhor, Shlomo; Shiftan, Yoram

    2013-01-01

    Semicompensatory models represent a choice process consisting of an elimination-based choice set formation on satisfaction of criterion thresholds and a utility-based choice. Current semicompensatory models assume a purely noncompensatory choice set formation and therefore do not support multinom...

  2. Hybrid modeling and empirical analysis of automobile supply chain network

    Science.gov (United States)

    Sun, Jun-yan; Tang, Jian-ming; Fu, Wei-ping; Wu, Bing-ying

    2017-05-01

    Based on the connection mechanism of nodes which automatically select upstream and downstream agents, a simulation model for dynamic evolutionary process of consumer-driven automobile supply chain is established by integrating ABM and discrete modeling in the GIS-based map. Firstly, the rationality is proved by analyzing the consistency of sales and changes in various agent parameters between the simulation model and a real automobile supply chain. Second, through complex network theory, hierarchical structures of the model and relationships of networks at different levels are analyzed to calculate various characteristic parameters such as mean distance, mean clustering coefficients, and degree distributions. By doing so, it verifies that the model is a typical scale-free network and small-world network. Finally, the motion law of this model is analyzed from the perspective of complex self-adaptive systems. The chaotic state of the simulation system is verified, which suggests that this system has typical nonlinear characteristics. This model not only macroscopically illustrates the dynamic evolution of complex networks of automobile supply chain but also microcosmically reflects the business process of each agent. Moreover, the model construction and simulation of the system by means of combining CAS theory and complex networks supplies a novel method for supply chain analysis, as well as theory bases and experience for supply chain analysis of auto companies.

  3. A Hybrid Setarx Model for Spikes in Tight Electricity Markets

    Directory of Open Access Journals (Sweden)

    Carlo Lucheroni

    2012-01-01

    Full Text Available The paper discusses a simple looking but highly nonlinear regime-switching, self-excited threshold model for hourly electricity prices in continuous and discrete time. The regime structure of the model is linked to organizational features of the market. In continuous time, the model can include spikes without using jumps, by defining stochastic orbits. In passing from continuous time to discrete time, the stochastic orbits survive discretization and can be identified again as spikes. A calibration technique suitable for the discrete version of this model, which does not need deseasonalization or spike filtering, is developed, tested and applied to market data. The discussion of the properties of the model uses phase-space analysis, an approach uncommon in econometrics. (original abstract

  4. A Novel Hybrid Model for Drawing Trace Reconstruction from Multichannel Surface Electromyographic Activity.

    Science.gov (United States)

    Chen, Yumiao; Yang, Zhongliang

    2017-01-01

    Recently, several researchers have considered the problem of reconstruction of handwriting and other meaningful arm and hand movements from surface electromyography (sEMG). Although much progress has been made, several practical limitations may still affect the clinical applicability of sEMG-based techniques. In this paper, a novel three-step hybrid model of coordinate state transition, sEMG feature extraction and gene expression programming (GEP) prediction is proposed for reconstructing drawing traces of 12 basic one-stroke shapes from multichannel surface electromyography. Using a specially designed coordinate data acquisition system, we recorded the coordinate data of drawing traces collected in accordance with the time series while 7-channel EMG signals were recorded. As a widely-used time domain feature, Root Mean Square (RMS) was extracted with the analysis window. The preliminary reconstruction models can be established by GEP. Then, the original drawing traces can be approximated by a constructed prediction model. Applying the three-step hybrid model, we were able to convert seven channels of EMG activity recorded from the arm muscles into smooth reconstructions of drawing traces. The hybrid model can yield a mean accuracy of 74% in within-group design (one set of prediction models for all shapes) and 86% in between-group design (one separate set of prediction models for each shape), averaged for the reconstructed x and y coordinates. It can be concluded that it is feasible for the proposed three-step hybrid model to improve the reconstruction ability of drawing traces from sEMG.

  5. Development and evaluation of a watershed-scale hybrid hydrologic model

    OpenAIRE

    Cho, Younghyun

    2016-01-01

    A watershed-scale hybrid hydrologic model (Distributed-Clark), which is a lumped conceptual and distributed feature model, was developed to predict spatially distributed short- and long-term rainfall runoff generation and routing using relatively simple methodologies and state-of-the-art spatial data in a GIS environment. In Distributed-Clark, spatially distributed excess rainfall estimated with the SCS curve number method and a GIS-based set of separated unit hydrographs (spatially distribut...

  6. An Introduction to the Hybrid Approach of Neural Networks and the Linear Regression Model : An Illustration in the Hedonic Pricing Model of Building Costs

    OpenAIRE

    浅野, 美代子; マーコ, ユー K.W.

    2007-01-01

    This paper introduces the hybrid approach of neural networks and linear regression model proposed by Asano and Tsubaki (2003). Neural networks are often credited with its superiority in data consistency whereas the linear regression model provides simple interpretation of the data enabling researchers to verify their hypotheses. The hybrid approach aims at combing