Complementing the characterization of in vivo generated N-glucuronic acid conjugates of stanozolol by collision cross section computation and analysis.

PubMed

Thevis, Mario; Dib, Josef; Thomas, Andreas; Höppner, Sebastian; Lagojda, Andreas; Kuehne, Dirk; Sander, Mark; Opfermann, Georg; Schänzer, Wilhelm

2015-01-01

Detailed structural information on metabolites serving as target analytes in clinical, forensic, and sports drug testing programmes is of paramount importance to ensure unequivocal test results. In the present study, the utility of collision cross section (CCS) analysis by travelling wave ion mobility measurements to support drug metabolite characterization efforts was tested concerning recently identified glucuronic acid conjugates of the anabolic-androgenic steroid stanozolol. Employing travelling-wave ion mobility spectrometry/quadrupole-time-of-flight mass spectrometry, drift times of five synthetically derived and fully characterized steroid glucuronides were measured and subsequently correlated to respective CCSs as obtained in silico to form an analyte-tailored calibration curve. The CCSs were calculated by equilibrium structure minimization (density functional theory) using the programmes ORCA with the data set B3LYP/6-31G and MOBCAL utilizing the trajectory method (TM) with nitrogen as drift gas. Under identical experimental conditions, synthesized and/or urinary stanozolol-N and O-glucuronides were analyzed to provide complementary information on the location of glucuronidation. Finally, the obtained data were compared to CCS results generated by the system's internal algorithm based on a calibration employing a polyalanine analyte mixture. The CCSs ΩN2 calculated for the five steroid glucuronide calibrants were found between 180 and 208 Å(2) , thus largely covering the observed and computed CCSs for stanozolol-N1'-, stanozolol-N2'-, and stanozolol-O-glucuronide found at values between 195.1 and 212.4 Å(2) . The obtained data corroborated the earlier suggested N- and O-glucuronidation of stanozolol, and demonstrate the exploit of ion mobility and CCS computation in structure characterization of phase-II metabolic products; however, despite reproducibly measurable differences in ion mobility of stanozolol-N1'-, N2'-, and O-glucuronides, the discriminatory power of the chosen CCS computation algorithm was found to be not appropriate to allow for accurate assignments of the two N-conjugated structures. Using polyalanine-based calibrations, significantly different absolute values were obtained for all CCSs, but due to a constant offset of approximately 45 Å(2) an excellent correlation (R(2)  = 0.9997) between both approaches was observed. This suggests a substantially accelerated protocol when patterns of computed and polyalanine-based experimental data can be used for structure elucidations instead of creating individual analyte-specific calibration curves. Copyright © 2015 John Wiley & Sons, Ltd.

High resolution microtomography for density and spatial infomation about wood structures

Treesearch

Barbara Illman; Betsy Dowd

1999-01-01

Microtomography has successfully been used to characterize loss of structural integrity of wood. Tomographic images were generated with the newly developed third generation x-ray computed microtomography (XCMT) instrument at the X27A beamline at the national Synchrotron Light source (NSLS). The beamline is equipped with high-flux x-ray monochromator based on multilayer...

Protein engineering and the use of molecular modeling and simulation: the case of heterodimeric Fc engineering.

PubMed

Spreter Von Kreudenstein, Thomas; Lario, Paula I; Dixit, Surjit B

2014-01-01

Computational and structure guided methods can make significant contributions to the development of solutions for difficult protein engineering problems, including the optimization of next generation of engineered antibodies. In this paper, we describe a contemporary industrial antibody engineering program, based on hypothesis-driven in silico protein optimization method. The foundational concepts and methods of computational protein engineering are discussed, and an example of a computational modeling and structure-guided protein engineering workflow is provided for the design of best-in-class heterodimeric Fc with high purity and favorable biophysical properties. We present the engineering rationale as well as structural and functional characterization data on these engineered designs. Copyright © 2013 Elsevier Inc. All rights reserved.

The hierarchical expert tuning of PID controllers using tools of soft computing.

PubMed

Karray, F; Gueaieb, W; Al-Sharhan, S

2002-01-01

We present soft computing-based results pertaining to the hierarchical tuning process of PID controllers located within the control loop of a class of nonlinear systems. The results are compared with PID controllers implemented either in a stand alone scheme or as a part of conventional gain scheduling structure. This work is motivated by the increasing need in the industry to design highly reliable and efficient controllers for dealing with regulation and tracking capabilities of complex processes characterized by nonlinearities and possibly time varying parameters. The soft computing-based controllers proposed are hybrid in nature in that they integrate within a well-defined hierarchical structure the benefits of hard algorithmic controllers with those having supervisory capabilities. The controllers proposed also have the distinct features of learning and auto-tuning without the need for tedious and computationally extensive online systems identification schemes.

Abdominal Tumor Characterization and Recognition Using Superior-Order Cooccurrence Matrices, Based on Ultrasound Images

PubMed Central

Mitrea, Delia; Mitrea, Paulina; Nedevschi, Sergiu; Badea, Radu; Lupsor, Monica; Socaciu, Mihai; Golea, Adela; Hagiu, Claudia; Ciobanu, Lidia

2012-01-01

The noninvasive diagnosis of the malignant tumors is an important issue in research nowadays. Our purpose is to elaborate computerized, texture-based methods for performing computer-aided characterization and automatic diagnosis of these tumors, using only the information from ultrasound images. In this paper, we considered some of the most frequent abdominal malignant tumors: the hepatocellular carcinoma and the colonic tumors. We compared these structures with the benign tumors and with other visually similar diseases. Besides the textural features that proved in our previous research to be useful in the characterization and recognition of the malignant tumors, we improved our method by using the grey level cooccurrence matrix and the edge orientation cooccurrence matrix of superior order. As resulted from our experiments, the new textural features increased the malignant tumor classification performance, also revealing visual and physical properties of these structures that emphasized the complex, chaotic structure of the corresponding tissue. PMID:22312411

Bernal's road to random packing and the structure of liquids

NASA Astrophysics Data System (ADS)

Finney, John L.

2013-11-01

Until the 1960s, liquids were generally regarded as either dense gases or disordered solids, and theoretical attempts at understanding their structures and properties were largely based on those concepts. Bernal, himself a crystallographer, was unhappy with either approach, preferring to regard simple liquids as 'homogeneous, coherent and essentially irregular assemblages of molecules containing no crystalline regions'. He set about realizing this conceptual model through a detailed examination of the structures and properties of random packings of spheres. In order to test the relevance of the model to real liquids, ways had to be found to realize and characterize random packings. This was at a time when computing was slow and in its infancy, so he and his collaborators set about building models in the laboratory, and examining aspects of their structures in order to characterize them in ways which would enable comparison with the properties of real liquids. Some of the imaginative - often time consuming and frustrating - routes followed are described, as well the comparisons made with the properties of simple liquids. With the increase of the power of computers in the 1960s, computational approaches became increasingly exploited in random packing studies. This enabled the use of packing concepts, and the tools developed to characterize them, in understanding systems as diverse as metallic glasses, crystal-liquid interfaces, protein structures, enzyme-substrate interactions and the distribution of galaxies, as well as their exploitation in, for example, oil extraction, understanding chromatographic separation columns, and packed beds in industrial processes.

Diffraction scattering computed tomography: a window into the structures of complex nanomaterials

PubMed Central

Birkbak, M. E.; Leemreize, H.; Frølich, S.; Stock, S. R.

2015-01-01

Modern functional nanomaterials and devices are increasingly composed of multiple phases arranged in three dimensions over several length scales. Therefore there is a pressing demand for improved methods for structural characterization of such complex materials. An excellent emerging technique that addresses this problem is diffraction/scattering computed tomography (DSCT). DSCT combines the merits of diffraction and/or small angle scattering with computed tomography to allow imaging the interior of materials based on the diffraction or small angle scattering signals. This allows, e.g., one to distinguish the distributions of polymorphs in complex mixtures. Here we review this technique and give examples of how it can shed light on modern nanoscale materials. PMID:26505175

Topology Optimization of Lightweight Lattice Structural Composites Inspired by Cuttlefish Bone

NASA Astrophysics Data System (ADS)

Hu, Zhong; Gadipudi, Varun Kumar; Salem, David R.

2018-03-01

Lattice structural composites are of great interest to various industries where lightweight multifunctionality is important, especially aerospace. However, strong coupling among the composition, microstructure, porous topology, and fabrication of such materials impedes conventional trial-and-error experimental development. In this work, a discontinuous carbon fiber reinforced polymer matrix composite was adopted for structural design. A reliable and robust design approach for developing lightweight multifunctional lattice structural composites was proposed, inspired by biomimetics and based on topology optimization. Three-dimensional periodic lattice blocks were initially designed, inspired by the cuttlefish bone microstructure. The topologies of the three-dimensional periodic blocks were further optimized by computer modeling, and the mechanical properties of the topology optimized lightweight lattice structures were characterized by computer modeling. The lattice structures with optimal performance were identified.

Teachers' Organization of Participation Structures for Teaching Science with Computer Technology

NASA Astrophysics Data System (ADS)

Subramaniam, Karthigeyan

2016-08-01

This paper describes a qualitative study that investigated the nature of the participation structures and how the participation structures were organized by four science teachers when they constructed and communicated science content in their classrooms with computer technology. Participation structures focus on the activity structures and processes in social settings like classrooms thereby providing glimpses into the complex dynamics of teacher-students interactions, configurations, and conventions during collective meaning making and knowledge creation. Data included observations, interviews, and focus group interviews. Analysis revealed that the dominant participation structure evident within participants' instruction with computer technology was ( Teacher) initiation-( Student and Teacher) response sequences-( Teacher) evaluate participation structure. Three key events characterized the how participants organized this participation structure in their classrooms: setting the stage for interactive instruction, the joint activity, and maintaining accountability. Implications include the following: (1) teacher educators need to tap into the knowledge base that underscores science teachers' learning to teach philosophies when computer technology is used in instruction. (2) Teacher educators need to emphasize the essential idea that learning and cognition is not situated within the computer technology but within the pedagogical practices, specifically the participation structures. (3) The pedagogical practices developed with the integration or with the use of computer technology underscored by the teachers' own knowledge of classroom contexts and curriculum needs to be the focus for how students learn science content with computer technology instead of just focusing on how computer technology solely supports students learning of science content.

Computing with volatile memristors: an application of non-pinched hysteresis

NASA Astrophysics Data System (ADS)

Pershin, Y. V.; Shevchenko, S. N.

2017-02-01

The possibility of in-memory computing with volatile memristive devices, namely, memristors requiring a power source to sustain their memory, is demonstrated theoretically. We have adopted a hysteretic graphene-based field emission structure as a prototype of a volatile memristor, which is characterized by a non-pinched hysteresis loop. A memristive model of the structure is developed and used to simulate a polymorphic circuit implementing stateful logic gates, such as the material implication. Specific regions of parameter space realizing useful logic functions are identified. Our results are applicable to other realizations of volatile memory devices, such as certain NEMS switches.

Site-Mutation of Hydrophobic Core Residues Synchronically Poise Super Interleukin 2 for Signaling: Identifying Distant Structural Effects through Affordable Computations.

PubMed

Mei, Longcan; Zhou, Yanping; Zhu, Lizhe; Liu, Changlin; Wu, Zhuo; Wang, Fangkui; Hao, Gefei; Yu, Di; Yuan, Hong; Cui, Yanfang

2018-03-20

A superkine variant of interleukin-2 with six site mutations away from the binding interface developed from the yeast display technique has been previously characterized as undergoing a distal structure alteration which is responsible for its super-potency and provides an elegant case study with which to get insight about how to utilize allosteric effect to achieve desirable protein functions. By examining the dynamic network and the allosteric pathways related to those mutated residues using various computational approaches, we found that nanosecond time scale all-atom molecular dynamics simulations can identify the dynamic network as efficient as an ensemble algorithm. The differentiated pathways for the six core residues form a dynamic network that outlines the area of structure alteration. The results offer potentials of using affordable computing power to predict allosteric structure of mutants in knowledge-based mutagenesis.

Multiscale Structure of UXO Site Characterization: Spatial Estimation and Uncertainty Quantification

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

Ostrouchov, George; Doll, William E.; Beard, Les P.

2009-01-01

Unexploded ordnance (UXO) site characterization must consider both how the contamination is generated and how we observe that contamination. Within the generation and observation processes, dependence structures can be exploited at multiple scales. We describe a conceptual site characterization process, the dependence structures available at several scales, and consider their statistical estimation aspects. It is evident that most of the statistical methods that are needed to address the estimation problems are known but their application-specific implementation may not be available. We demonstrate estimation at one scale and propose a representation for site contamination intensity that takes full account of uncertainty,more » is flexible enough to answer regulatory requirements, and is a practical tool for managing detailed spatial site characterization and remediation. The representation is based on point process spatial estimation methods that require modern computational resources for practical application. These methods have provisions for including prior and covariate information.« less

Guanine base stacking in G-quadruplex nucleic acids

PubMed Central

Lech, Christopher Jacques; Heddi, Brahim; Phan, Anh Tuân

2013-01-01

G-quadruplexes constitute a class of nucleic acid structures defined by stacked guanine tetrads (or G-tetrads) with guanine bases from neighboring tetrads stacking with one another within the G-tetrad core. Individual G-quadruplexes can also stack with one another at their G-tetrad interface leading to higher-order structures as observed in telomeric repeat-containing DNA and RNA. In this study, we investigate how guanine base stacking influences the stability of G-quadruplexes and their stacked higher-order structures. A structural survey of the Protein Data Bank is conducted to characterize experimentally observed guanine base stacking geometries within the core of G-quadruplexes and at the interface between stacked G-quadruplex structures. We couple this survey with a systematic computational examination of stacked G-tetrad energy landscapes using quantum mechanical computations. Energy calculations of stacked G-tetrads reveal large energy differences of up to 12 kcal/mol between experimentally observed geometries at the interface of stacked G-quadruplexes. Energy landscapes are also computed using an AMBER molecular mechanics description of stacking energy and are shown to agree quite well with quantum mechanical calculated landscapes. Molecular dynamics simulations provide a structural explanation for the experimentally observed preference of parallel G-quadruplexes to stack in a 5′–5′ manner based on different accessible tetrad stacking modes at the stacking interfaces of 5′–5′ and 3′–3′ stacked G-quadruplexes. PMID:23268444

Mode extraction on wind turbine blades via phase-based video motion estimation

NASA Astrophysics Data System (ADS)

Sarrafi, Aral; Poozesh, Peyman; Niezrecki, Christopher; Mao, Zhu

2017-04-01

In recent years, image processing techniques are being applied more often for structural dynamics identification, characterization, and structural health monitoring. Although as a non-contact and full-field measurement method, image processing still has a long way to go to outperform other conventional sensing instruments (i.e. accelerometers, strain gauges, laser vibrometers, etc.,). However, the technologies associated with image processing are developing rapidly and gaining more attention in a variety of engineering applications including structural dynamics identification and modal analysis. Among numerous motion estimation and image-processing methods, phase-based video motion estimation is considered as one of the most efficient methods regarding computation consumption and noise robustness. In this paper, phase-based video motion estimation is adopted for structural dynamics characterization on a 2.3-meter long Skystream wind turbine blade, and the modal parameters (natural frequencies, operating deflection shapes) are extracted. Phase-based video processing adopted in this paper provides reliable full-field 2-D motion information, which is beneficial for manufacturing certification and model updating at the design stage. The phase-based video motion estimation approach is demonstrated through processing data on a full-scale commercial structure (i.e. a wind turbine blade) with complex geometry and properties, and the results obtained have a good correlation with the modal parameters extracted from accelerometer measurements, especially for the first four bending modes, which have significant importance in blade characterization.

Distributed computing for macromolecular crystallography

PubMed Central

Krissinel, Evgeny; Uski, Ville; Lebedev, Andrey; Ballard, Charles

2018-01-01

Modern crystallographic computing is characterized by the growing role of automated structure-solution pipelines, which represent complex expert systems utilizing a number of program components, decision makers and databases. They also require considerable computational resources and regular database maintenance, which is increasingly more difficult to provide at the level of individual desktop-based CCP4 setups. On the other hand, there is a significant growth in data processed in the field, which brings up the issue of centralized facilities for keeping both the data collected and structure-solution projects. The paradigm of distributed computing and data management offers a convenient approach to tackling these problems, which has become more attractive in recent years owing to the popularity of mobile devices such as tablets and ultra-portable laptops. In this article, an overview is given of developments by CCP4 aimed at bringing distributed crystallographic computations to a wide crystallographic community. PMID:29533240

Distributed computing for macromolecular crystallography.

PubMed

Krissinel, Evgeny; Uski, Ville; Lebedev, Andrey; Winn, Martyn; Ballard, Charles

2018-02-01

Modern crystallographic computing is characterized by the growing role of automated structure-solution pipelines, which represent complex expert systems utilizing a number of program components, decision makers and databases. They also require considerable computational resources and regular database maintenance, which is increasingly more difficult to provide at the level of individual desktop-based CCP4 setups. On the other hand, there is a significant growth in data processed in the field, which brings up the issue of centralized facilities for keeping both the data collected and structure-solution projects. The paradigm of distributed computing and data management offers a convenient approach to tackling these problems, which has become more attractive in recent years owing to the popularity of mobile devices such as tablets and ultra-portable laptops. In this article, an overview is given of developments by CCP4 aimed at bringing distributed crystallographic computations to a wide crystallographic community.

Exploiting the Complementarity between Dereplication and Computer-Assisted Structure Elucidation for the Chemical Profiling of Natural Cosmetic Ingredients: Tephrosia purpurea as a Case Study.

PubMed

Hubert, Jane; Chollet, Sébastien; Purson, Sylvain; Reynaud, Romain; Harakat, Dominique; Martinez, Agathe; Nuzillard, Jean-Marc; Renault, Jean-Hugues

2015-07-24

The aqueous-ethanolic extract of Tephrosia purpurea seeds is currently exploited in the cosmetic industry as a natural ingredient of skin lotions. The aim of this study was to chemically characterize this ingredient by combining centrifugal partition extraction (CPE) as a fractionation tool with two complementary identification approaches involving dereplication and computer-assisted structure elucidation. Following two rapid fractionations of the crude extract (2 g), seven major compounds namely, caffeic acid, quercetin-3-O-rutinoside, ethyl galactoside, ciceritol, stachyose, saccharose, and citric acid, were unambiguously identified within the CPE-generated simplified mixtures by a recently developed (13)C NMR-based dereplication method. The structures of four additional compounds, patuletin-3-O-rutinoside, kaempferol-3-O-rutinoside, guaiacylglycerol 8-vanillic acid ether, and 2-methyl-2-glucopyranosyloxypropanoic acid, were automatically elucidated by using the Logic for Structure Determination program based on the interpretation of 2D NMR (HSQC, HMBC, and COSY) connectivity data. As more than 80% of the crude extract mass was characterized without need for tedious and labor-intensive multistep purification procedures, the identification tools involved in this work constitute a promising strategy for an efficient and time-saving chemical profiling of natural extracts.

The dynamic micro computed tomography at SSRF

NASA Astrophysics Data System (ADS)

Chen, R.; Xu, L.; Du, G.; Deng, B.; Xie, H.; Xiao, T.

2018-05-01

Synchrotron radiation micro-computed tomography (SR-μCT) is a critical technique for quantitative characterizing the 3D internal structure of samples, recently the dynamic SR-μCT has been attracting vast attention since it can evaluate the three-dimensional structure evolution of a sample. A dynamic μCT method, which is based on monochromatic beam, was developed at the X-ray Imaging and Biomedical Application Beamline at Shanghai Synchrotron Radiation Facility, by combining the compressed sensing based CT reconstruction algorithm and hardware upgrade. The monochromatic beam based method can achieve quantitative information, and lower dose than the white beam base method in which the lower energy beam is absorbed by the sample rather than contribute to the final imaging signal. The developed method is successfully used to investigate the compression of the air sac during respiration in a bell cricket, providing new knowledge for further research on the insect respiratory system.

Mononuclear nickel (II) and copper (II) coordination complexes supported by bispicen ligand derivatives: Experimental and computational studies

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

Singh, Nirupama; Niklas, Jens; Poluektov, Oleg

2017-01-01

The synthesis, characterization and density functional theory calculations of mononuclear Ni and Cu complexes supported by the N,N’-Dimethyl-N,N’-bis-(pyridine-2-ylmethyl)-1,2-diaminoethane ligand and its derivatives are reported. The complexes were characterized by X-ray crystallography as well as by UV-visible absorption spectroscopy and EPR spectroscopy. The solid state structure of these coordination complexes revealed that the geometry of the complex depended on the identity of the metal center. Solution phase characterization data are in accord with the solid phase structure, indicating minimal structural changes in solution. Optical spectroscopy revealed that all of the complexes exhibit color owing to d-d transition bands in the visiblemore » region. Magnetic parameters obtained from EPR spectroscopy with other structural data suggest that the Ni(II) complexes are in pseudo-octahedral geometry and Cu(II) complexes are in a distorted square pyramidal geometry. In order to understand in detail how ligand sterics and electronics affect complex topology detailed computational studies were performed. The series of complexes reported in this article will add significant value in the field of coordination chemistry as Ni(II) and Cu(II) complexes supported by tetradentate pyridyl based ligands are rather scarce.« less

Mode I Cohesive Law Characterization of Through-Crack Propagation in a Multidirectional Laminate

NASA Technical Reports Server (NTRS)

Bergan, Andrew C.; Davila, Carlos G.; Leone, Frank A.; Awerbuch, Jonathan; Tan, Tein-Min

2014-01-01

A method is proposed and assessed for the experimental characterization of through-the-thickness crack propagation in multidirectional composite laminates with a cohesive law. The fracture toughness and crack opening displacement are measured and used to determine a cohesive law. Two methods of computing fracture toughness are assessed and compared. While previously proposed cohesive characterizations based on the R-curve exhibit size effects, the proposed approach results in a cohesive law that is a material property. The compact tension specimen configuration is used to propagate damage while load and full-field displacements are recorded. These measurements are used to compute the fracture toughness and crack opening displacement from which the cohesive law is characterized. The experimental results show that a steady-state fracture toughness is not reached. However, the proposed method extrapolates to steady-state and is demonstrated capable of predicting the structural behavior of geometrically-scaled specimens.

Topological Characterization of Carbon Graphite and Crystal Cubic Carbon Structures.

PubMed

Siddiqui, Wei Gao Muhammad Kamran; Naeem, Muhammad; Rehman, Najma Abdul

2017-09-07

Graph theory is used for modeling, designing, analysis and understanding chemical structures or chemical networks and their properties. The molecular graph is a graph consisting of atoms called vertices and the chemical bond between atoms called edges. In this article, we study the chemical graphs of carbon graphite and crystal structure of cubic carbon. Moreover, we compute and give closed formulas of degree based additive topological indices, namely hyper-Zagreb index, first multiple and second multiple Zagreb indices, and first and second Zagreb polynomials.

Characteristics of middle and upper tropospheric clouds as deduced from rawinsonde data

NASA Technical Reports Server (NTRS)

Starr, D. D. O.; Cox, S. K.

1982-01-01

The static environment of middle and upper tropospheric clouds is characterized. Computed relative humidity with respect to ice is used to diagnose the presence of cloud layer. The deduced seasonal mean cloud cover estimates based on this technique are shown to be reasonable. The cases are stratified by season and pressure thickness, and the dry static stability, vertical wind speed shear, and Richardson number are computed for three layers for each case. Mean values for each parameter are presented for each stratification and layer. The relative frequency of occurrence of various structures is presented for each stratification. The observed values of each parameter and the observed structure of each parameter are quite variable. Structures corresponding to any of a number of different conceptual models may be found. Moist adiabatic conditions are not commonly observed and the stratification based on thickness yields substantially different results for each group.

Multiscale Investigation from Subcellular to Tissue Scale of Onion Epidermal Plant Cell Wall Mechanical Properties

NASA Astrophysics Data System (ADS)

Zamil, Mohammad Shafayet

The physical and mechanical properties of cell walls, their shape, how they are arranged and interact with each other determine the architecture of plant organs and how they mechanically respond to different environmental and loading conditions. Due to the distinctive hierarchy from subcellular to tissue scale, plant materials can exhibit remarkably different mechanical properties. To date, how the subcellular scale arrangement and the mechanical properties of plant cell wall structural constituents give rise to macro or tissue scale mechanical responses is not yet well understood. Although the tissue scale plant cell wall samples are easy to prepare and put to different types of mechanical tests, the hierarchical features that emerge when moving towards a higher scale make it complicated to link the macro scale results to micro or subcellular scale structural components. On the other hand, the microscale size of cell brings formidable challenges to prepare and grip samples and carry mechanical tests under tensile loading at subcellular scale. This study attempted to develop a set of test protocols based on microelectromechanical system (MEMS) tensile testing devices for characterizing plant cell wall materials at different length scales. For the ease of sample preparation and well established database of the composition and conformation of its structural constituents, onion epidermal cell wall profile was chosen as the study material. Based on the results and findings of multiscale mechanical characterization, a framework of architecture-based finite element method (FEM) computational model was developed. The computational model laid the foundation of bridging the subcellular or microscale to the tissue or macroscale mechanical properties. This study suggests that there are important insights of cell wall mechanics and structural features that can only be investigated by carrying tensile characterization of samples not confounded by extracellular parameters. To the best of our knowledge, the plant cell wall at subcellular scale was never characterized under tensile loading. By coupling the structure based multiscale modeling and mechanical characterizations at different length scales, an attempt was made to provide novel insights towards understanding the mechanics and architecture of cell wall. This study also suggests that a multiscale investigation is essential for garnering fundamental insights into the hierarchical deformation of biological systems.

Structure-guided Protein Transition Modeling with a Probabilistic Roadmap Algorithm.

PubMed

Maximova, Tatiana; Plaku, Erion; Shehu, Amarda

2016-07-07

Proteins are macromolecules in perpetual motion, switching between structural states to modulate their function. A detailed characterization of the precise yet complex relationship between protein structure, dynamics, and function requires elucidating transitions between functionally-relevant states. Doing so challenges both wet and dry laboratories, as protein dynamics involves disparate temporal scales. In this paper we present a novel, sampling-based algorithm to compute transition paths. The algorithm exploits two main ideas. First, it leverages known structures to initialize its search and define a reduced conformation space for rapid sampling. This is key to address the insufficient sampling issue suffered by sampling-based algorithms. Second, the algorithm embeds samples in a nearest-neighbor graph where transition paths can be efficiently computed via queries. The algorithm adapts the probabilistic roadmap framework that is popular in robot motion planning. In addition to efficiently computing lowest-cost paths between any given structures, the algorithm allows investigating hypotheses regarding the order of experimentally-known structures in a transition event. This novel contribution is likely to open up new venues of research. Detailed analysis is presented on multiple-basin proteins of relevance to human disease. Multiscaling and the AMBER ff14SB force field are used to obtain energetically-credible paths at atomistic detail.

Discovering the intelligence in molecular biology.

PubMed

Uberbacher, E

1995-12-01

The Third International Conference on Intelligent Systems in Molecular Biology was truly an outstanding event. Computational methods in molecular biology have reached a new level of maturity and utility, resulting in many high-impact applications. The success of this meeting bodes well for the rapid and continuing development of computational methods, intelligent systems and information-based approaches for the biosciences. The basic technology, originally most often applied to 'feasibility' problems, is now dealing effectively with the most difficult real-world problems. Significant progress has been made in understanding protein-structure information, structural classification, and how functional information and the relevant features of active-site geometry can be gleaned from structures by automated computational approaches. The value and limits of homology-based methods, and the ability to classify proteins by structure in the absence of homology, have reached a new level of sophistication. New methods for covariation analysis in the folding of large structures such as RNAs have shown remarkably good results, indicating the long-term potential to understand very complicated molecules and multimolecular complexes using computational means. Novel methods, such as HMMs, context-free grammars and the uses of mutual information theory, have taken center stage as highly valuable tools in our quest to represent and characterize biological information. A focus on creative uses of intelligent systems technologies and the trend toward biological application will undoubtedly continue and grow at the 1996 ISMB meeting in St Louis.

Computational Nanotechnology at NASA Ames Research Center, 1996

NASA Technical Reports Server (NTRS)

Globus, Al; Bailey, David; Langhoff, Steve; Pohorille, Andrew; Levit, Creon; Chancellor, Marisa K. (Technical Monitor)

1996-01-01

Some forms of nanotechnology appear to have enormous potential to improve aerospace and computer systems; computational nanotechnology, the design and simulation of programmable molecular machines, is crucial to progress. NASA Ames Research Center has begun a computational nanotechnology program including in-house work, external research grants, and grants of supercomputer time. Four goals have been established: (1) Simulate a hypothetical programmable molecular machine replicating itself and building other products. (2) Develop molecular manufacturing CAD (computer aided design) software and use it to design molecular manufacturing systems and products of aerospace interest, including computer components. (3) Characterize nanotechnologically accessible materials of aerospace interest. Such materials may have excellent strength and thermal properties. (4) Collaborate with experimentalists. Current in-house activities include: (1) Development of NanoDesign, software to design and simulate a nanotechnology based on functionalized fullerenes. Early work focuses on gears. (2) A design for high density atomically precise memory. (3) Design of nanotechnology systems based on biology. (4) Characterization of diamonoid mechanosynthetic pathways. (5) Studies of the laplacian of the electronic charge density to understand molecular structure and reactivity. (6) Studies of entropic effects during self-assembly. Characterization of properties of matter for clusters up to sizes exhibiting bulk properties. In addition, the NAS (NASA Advanced Supercomputing) supercomputer division sponsored a workshop on computational molecular nanotechnology on March 4-5, 1996 held at NASA Ames Research Center. Finally, collaborations with Bill Goddard at CalTech, Ralph Merkle at Xerox Parc, Don Brenner at NCSU (North Carolina State University), Tom McKendree at Hughes, and Todd Wipke at UCSC are underway.

Characterizing RNA ensembles from NMR data with kinematic models

PubMed Central

Fonseca, Rasmus; Pachov, Dimitar V.; Bernauer, Julie; van den Bedem, Henry

2014-01-01

Functional mechanisms of biomolecules often manifest themselves precisely in transient conformational substates. Researchers have long sought to structurally characterize dynamic processes in non-coding RNA, combining experimental data with computer algorithms. However, adequate exploration of conformational space for these highly dynamic molecules, starting from static crystal structures, remains challenging. Here, we report a new conformational sampling procedure, KGSrna, which can efficiently probe the native ensemble of RNA molecules in solution. We found that KGSrna ensembles accurately represent the conformational landscapes of 3D RNA encoded by NMR proton chemical shifts. KGSrna resolves motionally averaged NMR data into structural contributions; when coupled with residual dipolar coupling data, a KGSrna ensemble revealed a previously uncharacterized transient excited state of the HIV-1 trans-activation response element stem–loop. Ensemble-based interpretations of averaged data can aid in formulating and testing dynamic, motion-based hypotheses of functional mechanisms in RNAs with broad implications for RNA engineering and therapeutic intervention. PMID:25114056

Fast Geostatistical Inversion using Randomized Matrix Decompositions and Sketchings for Heterogeneous Aquifer Characterization

NASA Astrophysics Data System (ADS)

O'Malley, D.; Le, E. B.; Vesselinov, V. V.

2015-12-01

We present a fast, scalable, and highly-implementable stochastic inverse method for characterization of aquifer heterogeneity. The method utilizes recent advances in randomized matrix algebra and exploits the structure of the Quasi-Linear Geostatistical Approach (QLGA), without requiring a structured grid like Fast-Fourier Transform (FFT) methods. The QLGA framework is a more stable version of Gauss-Newton iterates for a large number of unknown model parameters, but provides unbiased estimates. The methods are matrix-free and do not require derivatives or adjoints, and are thus ideal for complex models and black-box implementation. We also incorporate randomized least-square solvers and data-reduction methods, which speed up computation and simulate missing data points. The new inverse methodology is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). Julia is an advanced high-level scientific programing language that allows for efficient memory management and utilization of high-performance computational resources. Inversion results based on series of synthetic problems with steady-state and transient calibration data are presented.

G-LoSA: An efficient computational tool for local structure-centric biological studies and drug design.

PubMed

Lee, Hui Sun; Im, Wonpil

2016-04-01

Molecular recognition by protein mostly occurs in a local region on the protein surface. Thus, an efficient computational method for accurate characterization of protein local structural conservation is necessary to better understand biology and drug design. We present a novel local structure alignment tool, G-LoSA. G-LoSA aligns protein local structures in a sequence order independent way and provides a GA-score, a chemical feature-based and size-independent structure similarity score. Our benchmark validation shows the robust performance of G-LoSA to the local structures of diverse sizes and characteristics, demonstrating its universal applicability to local structure-centric comparative biology studies. In particular, G-LoSA is highly effective in detecting conserved local regions on the entire surface of a given protein. In addition, the applications of G-LoSA to identifying template ligands and predicting ligand and protein binding sites illustrate its strong potential for computer-aided drug design. We hope that G-LoSA can be a useful computational method for exploring interesting biological problems through large-scale comparison of protein local structures and facilitating drug discovery research and development. G-LoSA is freely available to academic users at http://im.compbio.ku.edu/GLoSA/. © 2016 The Protein Society.

Computer-aided design of polymers and composites

NASA Technical Reports Server (NTRS)

Kaelble, D. H.

1985-01-01

This book on computer-aided design of polymers and composites introduces and discusses the subject from the viewpoint of atomic and molecular models. Thus, the origins of stiffness, strength, extensibility, and fracture toughness in composite materials can be analyzed directly in terms of chemical composition and molecular structure. Aspects of polymer composite reliability are considered along with characterization techniques for composite reliability, relations between atomic and molecular properties, computer aided design and manufacture, polymer CAD/CAM models, and composite CAD/CAM models. Attention is given to multiphase structural adhesives, fibrous composite reliability, metal joint reliability, polymer physical states and transitions, chemical quality assurance, processability testing, cure monitoring and management, nondestructive evaluation (NDE), surface NDE, elementary properties, ionic-covalent bonding, molecular analysis, acid-base interactions, the manufacturing science, and peel mechanics.

Databases of Conformations and NMR Structures of Glycan Determinants.

PubMed

Sarkar, Anita; Drouillard, Sophie; Rivet, Alain; Perez, Serge

2015-12-01

The present study reports a comprehensive nuclear magnetic resonance (NMR) characterization and a systematic conformational sampling of the conformational preferences of 170 glycan moieties of glycosphingolipids as produced in large-scale quantities by bacterial fermentation. These glycans span across a variety of families including the blood group antigens (A, B and O), core structures (Types 1, 2 and 4), fucosylated oligosaccharides (core and lacto-series), sialylated oligosaccharides (Types 1 and 2), Lewis antigens, GPI-anchors and globosides. A complementary set of about 100 glycan determinants occurring in glycoproteins and glycosaminoglycans has also been structurally characterized using molecular mechanics-based computation. The experimental and computational data generated are organized in two relational databases that can be queried by the user through a user-friendly search engine. The NMR ((1)H and (13)C, COSY, TOCSY, HMQC, HMBC correlation) spectra and 3D structures are available for visualization and download in commonly used structure formats. Emphasis has been given to the use of a common nomenclature for the structural encoding of the carbohydrates and each glycan molecule is described by four different types of representations in order to cope with the different usages in chemistry and biology. These web-based databases were developed with non-proprietary software and are open access for the scientific community available at http://glyco3d.cermav.cnrs.fr. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Computational Discovery of Materials Using the Firefly Algorithm

NASA Astrophysics Data System (ADS)

Avendaño-Franco, Guillermo; Romero, Aldo

Our current ability to model physical phenomena accurately, the increase computational power and better algorithms are the driving forces behind the computational discovery and design of novel materials, allowing for virtual characterization before their realization in the laboratory. We present the implementation of a novel firefly algorithm, a population-based algorithm for global optimization for searching the structure/composition space. This novel computation-intensive approach naturally take advantage of concurrency, targeted exploration and still keeping enough diversity. We apply the new method in both periodic and non-periodic structures and we present the implementation challenges and solutions to improve efficiency. The implementation makes use of computational materials databases and network analysis to optimize the search and get insights about the geometric structure of local minima on the energy landscape. The method has been implemented in our software PyChemia, an open-source package for materials discovery. We acknowledge the support of DMREF-NSF 1434897 and the Donors of the American Chemical Society Petroleum Research Fund for partial support of this research under Contract 54075-ND10.

Structural characterisation of medically relevant protein assemblies by integrating mass spectrometry with computational modelling.

PubMed

Politis, Argyris; Schmidt, Carla

2018-03-20

Structural mass spectrometry with its various techniques is a powerful tool for the structural elucidation of medically relevant protein assemblies. It delivers information on the composition, stoichiometries, interactions and topologies of these assemblies. Most importantly it can deal with heterogeneous mixtures and assemblies which makes it universal among the conventional structural techniques. In this review we summarise recent advances and challenges in structural mass spectrometric techniques. We describe how the combination of the different mass spectrometry-based methods with computational strategies enable structural models at molecular levels of resolution. These models hold significant potential for helping us in characterizing the function of protein assemblies related to human health and disease. In this review we summarise the techniques of structural mass spectrometry often applied when studying protein-ligand complexes. We exemplify these techniques through recent examples from literature that helped in the understanding of medically relevant protein assemblies. We further provide a detailed introduction into various computational approaches that can be integrated with these mass spectrometric techniques. Last but not least we discuss case studies that integrated mass spectrometry and computational modelling approaches and yielded models of medically important protein assembly states such as fibrils and amyloids. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Synthesis and redox properties of fac-BrRe(CO)3[1,2-(PPh2)2-closo-1,2-C2B10H10]: The first structurally characterized rhenium carbonyl containing a carboranyl-based diphosphine ligand

NASA Astrophysics Data System (ADS)

Lin, Chen-Hao; Nesterov, Vladimir N.; Richmond, Michael G.

2018-03-01

The diphosphine 1,2-(PPh2)2-closo-1,2-C2B10H10 reacts with BrRe(CO)5 and fac-BrRe(CO)3(THF)2 to give fac-BrRe(CO)3[1,2-(PPh2)2-closo-1,2-C2B10H10] (1) in high yields (>80%). Compound 1 is the first structurally characterized rhenium carbonyl that contains an ancillary carborane-based diphosphine ligand. 1 has been characterized in solution by IR and NMR spectroscopies (1H and 31P), and the solid-state structure has been determined by X-ray diffraction analysis. The electrochemical properties of 1 have been investigated by cyclic voltammetry, and the composition of the DFT-computed HOMO and LUMO levels are discussed relative to the electrochemical data. The thermodynamics for the formation of 1 from the rhenium precursors BrRe(CO)5 and fac-BrRe(CO)3(THF)2 have been evaluated by DFT calculations.

Computational analysis of human and mouse CREB3L4 Protein

PubMed Central

Velpula, Kiran Kumar; Rehman, Azeem Abdul; Chigurupati, Soumya; Sanam, Ramadevi; Inampudi, Krishna Kishore; Akila, Chandra Sekhar

2012-01-01

CREB3L4 is a member of the CREB/ATF transcription factor family, characterized by their regulation of gene expression through the cAMP-responsive element. Previous studies identified this protein in mice and humans. Whereas CREB3L4 in mice (referred to as Tisp40) is found in the testes and functions in spermatogenesis, human CREB3L4 is primarily detected in the prostate and has been implicated in cancer. We conducted computational analyses to compare the structural homology between murine Tisp40α human CREB3L4. Our results reveal that the primary and secondary structures of the two proteins contain high similarity. Additionally, predicted helical transmembrane structure reveals that the proteins likely have similar structure and function. This study offers preliminary findings that support the translation of mouse Tisp40α findings into human models, based on structural homology. PMID:22829733

Evaluation of multiple-scale 3D characterization for coal physical structure with DCM method and synchrotron X-ray CT.

PubMed

Wang, Haipeng; Yang, Yushuang; Yang, Jianli; Nie, Yihang; Jia, Jing; Wang, Yudan

2015-01-01

Multiscale nondestructive characterization of coal microscopic physical structure can provide important information for coal conversion and coal-bed methane extraction. In this study, the physical structure of a coal sample was investigated by synchrotron-based multiple-energy X-ray CT at three beam energies and two different spatial resolutions. A data-constrained modeling (DCM) approach was used to quantitatively characterize the multiscale compositional distributions at the two resolutions. The volume fractions of each voxel for four different composition groups were obtained at the two resolutions. Between the two resolutions, the difference for DCM computed volume fractions of coal matrix and pores is less than 0.3%, and the difference for mineral composition groups is less than 0.17%. This demonstrates that the DCM approach can account for compositions beyond the X-ray CT imaging resolution with adequate accuracy. By using DCM, it is possible to characterize a relatively large coal sample at a relatively low spatial resolution with minimal loss of the effect due to subpixel fine length scale structures.

Learning-based stochastic object models for use in optimizing imaging systems

NASA Astrophysics Data System (ADS)

Dolly, Steven R.; Anastasio, Mark A.; Yu, Lifeng; Li, Hua

2017-03-01

It is widely known that the optimization of imaging systems based on objective, or task-based, measures of image quality via computer-simulation requires use of a stochastic object model (SOM). However, the development of computationally tractable SOMs that can accurately model the statistical variations in anatomy within a specified ensemble of patients remains a challenging task. Because they are established by use of image data corresponding a single patient, previously reported numerical anatomical models lack of the ability to accurately model inter- patient variations in anatomy. In certain applications, however, databases of high-quality volumetric images are available that can facilitate this task. In this work, a novel and tractable methodology for learning a SOM from a set of volumetric training images is developed. The proposed method is based upon geometric attribute distribution (GAD) models, which characterize the inter-structural centroid variations and the intra-structural shape variations of each individual anatomical structure. The GAD models are scalable and deformable, and constrained by their respective principal attribute variations learned from training data. By use of the GAD models, random organ shapes and positions can be generated and integrated to form an anatomical phantom. The randomness in organ shape and position will reflect the variability of anatomy present in the training data. To demonstrate the methodology, a SOM corresponding to the pelvis of an adult male was computed and a corresponding ensemble of phantoms was created. Additionally, computer-simulated X-ray projection images corresponding to the phantoms were computed, from which tomographic images were reconstructed.

Using synchrotron-based X-ray micro-computed tomography and high-performance pore-scale simulation to evaluate hydraulic properties in biochar-amended soils

NASA Astrophysics Data System (ADS)

Zhou, H.; Yu, X.; Chen, C.; Zeng, L.; Lu, S.; Wu, L.

2016-12-01

In this research, we combined synchrotron-based X-ray micro-computed tomography (SR-mCT), with three-dimensional lattice Bolzmann (LB) method, to quantify how the change in pore space architecture affected macroscopic hydraulic of two clayey soils amended with biochar. SR-mCT was used to characterize pore structures of the soils before and after biochar addition. The high-resolution soil pore structures were then directly used as internal boundary conditions for three-dimensional water flow simulations with the LB method, which was accelerated by graphics processing unit (GPU) parallel computing. It was shown that, due to the changes in soil pore geometry, the application of biochar increased the soil permeability by at least 1 order of magnitude, and decreased the tortuosity by 20-30%. This work was the first physics based modeling study on the effect of biochar amendment on soil hydraulic properties. The developed theories and techniques have promising potential in understanding the mechanisms of water and nutrient transport in soil at the pore scale.

Computationally Efficient Characterization of Potential Energy Surfaces Based on Fingerprint Distances

NASA Astrophysics Data System (ADS)

Schaefer, Bastian; Goedecker, Stefan; Goedecker Group Team

Based on Lennard-Jones, Silicon, Sodium-Chloride and Gold clusters, it was found that uphill barrier energies of transition states between directly connected minima tend to increase with increasing structural differences of the two minima. Based on this insight it also turned out that post-processing minima hopping data at a negligible computational cost allows to obtain qualitative topological information on potential energy surfaces that can be stored in so called qualitative connectivity databases. These qualitative connectivity databases are used for generating fingerprint disconnectivity graphs that allow to obtain a first qualitative idea on thermodynamic and kinetic properties of a system of interest. This research was supported by the NCCR MARVEL, funded by the Swiss National Science Foundation. Computer time was provided by the Swiss National Supercomputing Centre (CSCS) under Project ID No. s499.

Cartographic Modeling: Computer-assisted Analysis of Spatially Defined Neighborhoods

NASA Technical Reports Server (NTRS)

Berry, J. K.; Tomlin, C. D.

1982-01-01

Cartographic models addressing a wide variety of applications are composed of fundamental map processing operations. These primitive operations are neither data base nor application-specific. By organizing the set of operations into a mathematical-like structure, the basis for a generalized cartographic modeling framework can be developed. Among the major classes of primitive operations are those associated with reclassifying map categories, overlaying maps, determining distance and connectivity, and characterizing cartographic neighborhoods. The conceptual framework of cartographic modeling is established and techniques for characterizing neighborhoods are used as a means of demonstrating some of the more sophisticated procedures of computer-assisted map analysis. A cartographic model for assessing effective roundwood supply is briefly described as an example of a computer analysis. Most of the techniques described have been implemented as part of the map analysis package developed at the Yale School of Forestry and Environmental Studies.

Computational Characterization of Electromagnetic Field Propagation in Complex Structures

DTIC Science & Technology

1998-04-10

34Computational characterization of electromagnetic field propagation in complex structures", DAAH01-91-D-ROOS D.O. 59. Dr. Michael Scalora performed the...Development, and Engineering Center, Bldg. 7804, Room 242 Redstone Arsenal, Alabama 35898-5248 USA Dr. Michael Scalora Quantum Optics Group Tel:(205...scheduled to appear. They are: (1) M. Scalora , J.P. Dowling, A.S. Manka, CM. Bowden, and J.W. Haus, Pulse Propagation Near Highly Reflective

Syntheses, structural, computational, and thermal analysis of acid-base complexes of picric acid with N-heterocyclic bases.

PubMed

Goel, Nidhi; Singh, Udai P

2013-10-10

Four new acid-base complexes using picric acid [(OH)(NO2)3C6H2] (PA) and N-heterocyclic bases (1,10-phenanthroline (phen)/2,2';6',2"-terpyridine (terpy)/hexamethylenetetramine (hmta)/2,4,6-tri(2-pyridyl)-1,3,5-triazine (tptz)) were prepared and characterized by elemental analysis, IR, NMR and X-ray crystallography. Crystal structures provide detailed information of the noncovalent interactions present in different complexes. The optimized structures of the complexes were calculated in terms of the density functional theory. The thermolysis of these complexes was investigated by TG-DSC and ignition delay measurements. The model-free isoconversional and model-fitting kinetic approaches have been applied to isothermal TG data for kinetics investigation of thermal decomposition of these complexes.

Overview of mechanics of materials branch activities in the computational structures area

NASA Technical Reports Server (NTRS)

Poe, C. C., Jr.

1992-01-01

Base programs and system programs are discussed. The base programs include fundamental research of composites and metals for airframes leading to characterization of advanced materials, models of behavior, and methods for predicting damage tolerance. Results from the base programs support the systems programs, which change as NASA's missions change. The National Aerospace Plane (NASP), Advanced Composites Technology (ACT), Airframe Structural Integrity Program (Aging Aircraft), and High Speed Research (HSR) programs are currently being supported. Airframe durability is one of the key issues in each of these system programs. The base program has four major thrusts, which will be reviewed subsequently. Additionally, several technical highlights will be reviewed for each thrust.

Using NMR and molecular dynamics to link structure and dynamics effects of the universal base 8-aza, 7-deaza, N8 linked adenosine analog

PubMed Central

Spring-Connell, Alexander M.; Evich, Marina G.; Debelak, Harald; Seela, Frank; Germann, Markus W.

2016-01-01

A truly universal nucleobase enables a host of novel applications such as simplified templates for PCR primers, randomized sequencing and DNA based devices. A universal base must pair indiscriminately to each of the canonical bases with little or preferably no destabilization of the overall duplex. In reality, many candidates either destabilize the duplex or do not base pair indiscriminatingly. The novel base 8-aza-7-deazaadenine (pyrazolo[3,4-d]pyrimidin- 4-amine) N8-(2′deoxyribonucleoside), a deoxyadenosine analog (UB), pairs with each of the natural DNA bases with little sequence preference. We have utilized NMR complemented with molecular dynamic calculations to characterize the structure and dynamics of a UB incorporated into a DNA duplex. The UB participates in base stacking with little to no perturbation of the local structure yet forms an unusual base pair that samples multiple conformations. These local dynamics result in the complete disappearance of a single UB proton resonance under native conditions. Accommodation of the UB is additionally stabilized via heightened backbone conformational sampling. NMR combined with various computational techniques has allowed for a comprehensive characterization of both structural and dynamic effects of the UB in a DNA duplex and underlines that the UB as a strong candidate for universal base applications. PMID:27566150

integrating Solid State NMR and Computations in Membrane Protein Science

NASA Astrophysics Data System (ADS)

Cross, Timothy

2015-03-01

Helical membrane protein structures are influenced by their native environment. Therefore the characterization of their structure in an environment that models as closely as possible their native environment is critical for achieving not only structural but functional understanding of these proteins. Solid state NMR spectroscopy in liquid crystalline lipid bilayers provides an excellent tool for such characterizations. Two classes of restraints can be obtained - absolute restraints that constrain the structure to a laboratory frame of reference when using uniformly oriented samples (approximately 1° of mosaic spread) and relative restraints that restrain one part of the structure with respect to another part such as torsional and distance restraints. Here, I will discuss unique restraints derived from uniformly oriented samples and the characterization of initial structures utilizing both restraint types, followed by restrained molecular dynamics refinement in the same lipid bilayer environment as that used for the experimental restraint collection. Protein examples will be taken from Influenza virus and Mycobacterium tuberculosis. When available comparisons of structures to those obtained using different membrane mimetic environments will be shown and the causes for structural distortions explained based on an understanding of membrane biophysics and its sophisticated influence on membrane proteins.

An efficient two-stage approach for image-based FSI analysis of atherosclerotic arteries

PubMed Central

Rayz, Vitaliy L.; Mofrad, Mohammad R. K.; Saloner, David

2010-01-01

Patient-specific biomechanical modeling of atherosclerotic arteries has the potential to aid clinicians in characterizing lesions and determining optimal treatment plans. To attain high levels of accuracy, recent models use medical imaging data to determine plaque component boundaries in three dimensions, and fluid–structure interaction is used to capture mechanical loading of the diseased vessel. As the plaque components and vessel wall are often highly complex in shape, constructing a suitable structured computational mesh is very challenging and can require a great deal of time. Models based on unstructured computational meshes require relatively less time to construct and are capable of accurately representing plaque components in three dimensions. These models unfortunately require additional computational resources and computing time for accurate and meaningful results. A two-stage modeling strategy based on unstructured computational meshes is proposed to achieve a reasonable balance between meshing difficulty and computational resource and time demand. In this method, a coarsegrained simulation of the full arterial domain is used to guide and constrain a fine-scale simulation of a smaller region of interest within the full domain. Results for a patient-specific carotid bifurcation model demonstrate that the two-stage approach can afford a large savings in both time for mesh generation and time and resources needed for computation. The effects of solid and fluid domain truncation were explored, and were shown to minimally affect accuracy of the stress fields predicted with the two-stage approach. PMID:19756798

Biomechanics of metastatic disease in the vertebral column.

PubMed

Whyne, Cari M

2014-06-01

Metastatic disease in the vertebral column compromises the structural stability of the spine leading to increased risk of fracture. The complex patterns of osteolytic and osteoblastic disease within the bony spine have motivated a multimodal approach to better characterize the biomechanics of tumor-involved bone. This review presents our current understanding of the biomechanical behavior of metastatically involved vertebrae, and experimental and computational image-based approaches that have been employed to quantify structural integrity in preclinical models with translation to clinical data sets.

Diversity of Streptomyces spp. in Eastern Himalayan region – computational RNomics approach to phylogeny

PubMed Central

Bhattacharjee, Kaushik; Banerjee, Subhro; Joshi, Santa Ram

2012-01-01

Isolation and characterization of actinomycetes from soil samples from altitudinal gradient of North-East India were investigated for computational RNomics based phylogeny. A total of 52 diverse isolates of Streptomyces from the soil samples were isolated on four different media and from these 6 isolates were selected on the basis of cultural characteristics, microscopic and biochemical studies. Sequencing of 16S rDNA of the selected isolates identified them to belong to six different species of Streptomyces. The molecular morphometric and physico-kinetic analysis of 16S rRNA sequences were performed to predict the diversity of the genus. The computational RNomics study revealed the significance of the structural RNA based phylogenetic analysis in a relatively diverse group of Streptomyces. PMID:22829729

An experimental study on the manufacture and characterization of in-plane fibre-waviness defects in composites.

PubMed

Christian, W J R; DiazDelaO, F A; Atherton, K; Patterson, E A

2018-05-01

A new method has been developed for creating localized in-plane fibre waviness in composite coupons and used to create a large batch of specimens. This method could be used by manufacturers to experimentally explore the effect of fibre waviness on composite structures both directly and indirectly to develop and validate computational models. The specimens were assessed using ultrasound, digital image correlation and a novel inspection technique capable of measuring residual strain fields. To explore how the defect affects the performance of composite structures, the specimens were then loaded to failure. Predictions of remnant strength were made using a simple ultrasound damage metric and a new residual strain-based damage metric. The predictions made using residual strain measurements were found to be substantially more effective at characterizing ultimate strength than ultrasound measurements. This suggests that residual strains have a significant effect on the failure of laminates containing fibre waviness and that these strains could be incorporated into computational models to improve their ability to simulate the defect.

Investigation of the effects of aeroelastic deformations on the radar cross section of aircraft

NASA Astrophysics Data System (ADS)

McKenzie, Samuel D.

1991-12-01

The effects of aeroelastic deformations on the radar cross section (RCS) of a T-38 trainer jet and a C-5A transport aircraft are examined and characterized. Realistic representations of structural wing deformations are obtained from a mechanical/computer aided design software package called NASTRAN. NASTRAN is used to evaluate the structural parameters of the aircraft as well as the restraints and loads associated with realistic flight conditions. Geometries for both the non-deformed and deformed airframes are obtained from the NASTRAN models and translated into RCS models. The RCS is analyzed using a numerical modeling code called the Radar Cross Section - Basic Scattering Code, version 2 which was developed at the Ohio State University and is based on the uniform geometric theory of diffraction. The code is used to analyze the effects of aeroelastic deformations on the RCS of the aircraft by comparing the computed RCS representing the deformed airframe to that of the non-deformed airframe and characterizing the differences between them.

Incremental Value of Magnetic Resonance Imaging in Further Characterizing Hypodense Mediastinal and Paracardiac Lesions Identified on Computed Tomography

PubMed Central

Chaturvedi, Abhishek; Gange, Chris; Sahin, Hakan; Chaturvedi, Apeksha

2018-01-01

Mediastinal and paracardiac lesions are usually first diagnosed on a chest radiograph or echocardiogram. Often, a computed tomography is obtained to further delineate these lesions. CT may be suboptimal for evaluation of enhancement characteristics and direct extension into the adjacent mediastinal structures. With its intrinsic superior soft-tissue characterization, magnetic resonance imaging (MRI) can better delineate these lesions, their internal tissue characteristics, and identify adhesion/invasion into adjacent structures. This pictorial essay provides a brief synopsis of the key MRI sequences and their utility in further characterizing mediastinal and paracardiac lesions. PMID:29619281

Ab initio Computations of the Electronic, Mechanical, and Thermal Properties of Ultra High Temperature Ceramics (UHTC) ZrB2 and HfB2

NASA Technical Reports Server (NTRS)

Lawson, John W.; Bauschlicher, Charles W.; Daw, Murray

2011-01-01

Refractory materials such as metallic borides, often considered as ultra high temperature ceramics (UHTC), are characterized by high melting point, high hardness, and good chemical inertness. These materials have many applications which require high temperature materials that can operate with no or limited oxidation. Ab initio, first principles methods are the most accurate modeling approaches available and represent a parameter free description of the material based on the quantum mechanical equations. Using these methods, many of the intrinsic properties of these material can be obtained. We performed ab initio calculations based on density functional theory for the UHTC materials ZrB2 and HfB2. Computational results are presented for structural information (lattice constants, bond lengths, etc), electronic structure (bonding motifs, densities of states, band structure, etc), thermal quantities (phonon spectra, phonon densities of states, specific heat), as well as information about point defects such as vacancy and antisite formation energies.

Content and structure of knowledge base used for virtual control of android arm motion in specified environment

NASA Astrophysics Data System (ADS)

Pritykin, F. N.; Nebritov, V. I.

2018-01-01

The paper presents the configuration of knowledge base necessary for intelligent control of android arm mechanism motion with different positions of certain forbidden regions taken into account. The present structure of the knowledge base characterizes the past experience of arm motion synthesis in the vector of velocities with due regard for the known obstacles. This structure also specifies its intrinsic properties. Knowledge base generation is based on the study of the arm mechanism instantaneous states implementations. Computational experiments connected with the virtual control of android arm motion with known forbidden regions using the developed knowledge base are introduced. Using the developed knowledge base to control virtually the arm motion reduces the time of test assignments calculation. The results of the research can be used in developing control systems of autonomous android robots in the known in advance environment.

Soil structure characterized using computed tomographic images

Treesearch

Zhanqi Cheng; Stephen H. Anderson; Clark J. Gantzer; J. W. Van Sambeek

2003-01-01

Fractal analysis of soil structure is a relatively new method for quantifying the effects of management systems on soil properties and quality. The objective of this work was to explore several methods of studying images to describe and quantify structure of soils under forest management. This research uses computed tomography and a topological method called Multiple...

High-resolution 3D imaging of polymerized photonic crystals by lab-based x-ray nanotomography with 50-nm resolution

NASA Astrophysics Data System (ADS)

Yin, Leilei; Chen, Ying-Chieh; Gelb, Jeff; Stevenson, Darren M.; Braun, Paul A.

2010-09-01

High resolution x-ray computed tomography is a powerful non-destructive 3-D imaging method. It can offer superior resolution on objects that are opaque or low contrast for optical microscopy. Synchrotron based x-ray computed tomography systems have been available for scientific research, but remain difficult to access for broader users. This work introduces a lab-based high-resolution x-ray nanotomography system with 50nm resolution in absorption and Zernike phase contrast modes. Using this system, we have demonstrated high quality 3-D images of polymerized photonic crystals which have been analyzed for band gap structures. The isotropic volumetric data shows excellent consistency with other characterization results.

Computational methods for 2D materials: discovery, property characterization, and application design.

PubMed

Paul, J T; Singh, A K; Dong, Z; Zhuang, H; Revard, B C; Rijal, B; Ashton, M; Linscheid, A; Blonsky, M; Gluhovic, D; Guo, J; Hennig, R G

2017-11-29

The discovery of two-dimensional (2D) materials comes at a time when computational methods are mature and can predict novel 2D materials, characterize their properties, and guide the design of 2D materials for applications. This article reviews the recent progress in computational approaches for 2D materials research. We discuss the computational techniques and provide an overview of the ongoing research in the field. We begin with an overview of known 2D materials, common computational methods, and available cyber infrastructures. We then move onto the discovery of novel 2D materials, discussing the stability criteria for 2D materials, computational methods for structure prediction, and interactions of monolayers with electrochemical and gaseous environments. Next, we describe the computational characterization of the 2D materials' electronic, optical, magnetic, and superconducting properties and the response of the properties under applied mechanical strain and electrical fields. From there, we move on to discuss the structure and properties of defects in 2D materials, and describe methods for 2D materials device simulations. We conclude by providing an outlook on the needs and challenges for future developments in the field of computational research for 2D materials.

Computational methods for 2D materials: discovery, property characterization, and application design

NASA Astrophysics Data System (ADS)

Paul, J. T.; Singh, A. K.; Dong, Z.; Zhuang, H.; Revard, B. C.; Rijal, B.; Ashton, M.; Linscheid, A.; Blonsky, M.; Gluhovic, D.; Guo, J.; Hennig, R. G.

2017-11-01

The discovery of two-dimensional (2D) materials comes at a time when computational methods are mature and can predict novel 2D materials, characterize their properties, and guide the design of 2D materials for applications. This article reviews the recent progress in computational approaches for 2D materials research. We discuss the computational techniques and provide an overview of the ongoing research in the field. We begin with an overview of known 2D materials, common computational methods, and available cyber infrastructures. We then move onto the discovery of novel 2D materials, discussing the stability criteria for 2D materials, computational methods for structure prediction, and interactions of monolayers with electrochemical and gaseous environments. Next, we describe the computational characterization of the 2D materials’ electronic, optical, magnetic, and superconducting properties and the response of the properties under applied mechanical strain and electrical fields. From there, we move on to discuss the structure and properties of defects in 2D materials, and describe methods for 2D materials device simulations. We conclude by providing an outlook on the needs and challenges for future developments in the field of computational research for 2D materials.

Development of a brain MRI-based hidden Markov model for dementia recognition.

PubMed

Chen, Ying; Pham, Tuan D

2013-01-01

Dementia is an age-related cognitive decline which is indicated by an early degeneration of cortical and sub-cortical structures. Characterizing those morphological changes can help to understand the disease development and contribute to disease early prediction and prevention. But modeling that can best capture brain structural variability and can be valid in both disease classification and interpretation is extremely challenging. The current study aimed to establish a computational approach for modeling the magnetic resonance imaging (MRI)-based structural complexity of the brain using the framework of hidden Markov models (HMMs) for dementia recognition. Regularity dimension and semi-variogram were used to extract structural features of the brains, and vector quantization method was applied to convert extracted feature vectors to prototype vectors. The output VQ indices were then utilized to estimate parameters for HMMs. To validate its accuracy and robustness, experiments were carried out on individuals who were characterized as non-demented and mild Alzheimer's diseased. Four HMMs were constructed based on the cohort of non-demented young, middle-aged, elder and demented elder subjects separately. Classification was carried out using a data set including both non-demented and demented individuals with a wide age range. The proposed HMMs have succeeded in recognition of individual who has mild Alzheimer's disease and achieved a better classification accuracy compared to other related works using different classifiers. Results have shown the ability of the proposed modeling for recognition of early dementia. The findings from this research will allow individual classification to support the early diagnosis and prediction of dementia. By using the brain MRI-based HMMs developed in our proposed research, it will be more efficient, robust and can be easily used by clinicians as a computer-aid tool for validating imaging bio-markers for early prediction of dementia.

Spectroscopic characterization, antimicrobial activity, DFT computation and docking studies of sulfonamide Schiff bases

NASA Astrophysics Data System (ADS)

Mondal, Sudipa; Mandal, Santi M.; Mondal, Tapan Kumar; Sinha, Chittaranjan

2017-01-01

Schiff bases synthesised from the condensation of 2-(hydroxy)naphthaldehyde and sulfonamides (sufathiazole (STZ), sulfapyridine (SPY), sulfadiazine (SDZ), sulfamerazine (SMZ) and sulfaguanidine (SGN)) are characterized by different spectroscopic data (FTIR, UV-Vis, Mass, NMR) and two of them, (E)-4-(((2-hydroxynaphthalen-1-yl)methylene)amino)-N-(thiazol-2-yl)benzenesulfonamide (1a) and (E)-N-(diaminomethylene)-4-(((2-hydroxynaphthalen-1-yl)methylene)amino)benzenesulfonamide (1e) have been confirmed by single crystal X-ray structure determination. Antimicrobial activities of the Schiff bases have been evaluated against certified and resistant Gram positive (Staphylococcus aureus, Enterococcus facelis) and Gram negative (Streptococcus pyogenes, Salmonella typhi, Shigella dysenteriae, Shigella flexneri, Klebsiella pneumonia) pathogens. Performance of Schiff base against the resistant pathogens are better than standard stain and MIC data lie 32-128 μg/ml while parent sulfonamides are effectively inactive (MIC >512 μg/ml). The DFT optimized structures of the Schiff bases have been used to accomplish molecular docking studies with DHPS (dihydropteroate synthase) protein structure (downloaded from Protein Data Bank) to establish the most preferred mode of interaction. ADMET filtration, Cytotoxicity (MTT assay) and haemolysis assay have been examined for evaluation of druglike character.

A General, Adaptive, Roadmap-Based Algorithm for Protein Motion Computation.

PubMed

Molloy, Kevin; Shehu, Amarda

2016-03-01

Precious information on protein function can be extracted from a detailed characterization of protein equilibrium dynamics. This remains elusive in wet and dry laboratories, as function-modulating transitions of a protein between functionally-relevant, thermodynamically-stable and meta-stable structural states often span disparate time scales. In this paper we propose a novel, robotics-inspired algorithm that circumvents time-scale challenges by drawing analogies between protein motion and robot motion. The algorithm adapts the popular roadmap-based framework in robot motion computation to handle the more complex protein conformation space and its underlying rugged energy surface. Given known structures representing stable and meta-stable states of a protein, the algorithm yields a time- and energy-prioritized list of transition paths between the structures, with each path represented as a series of conformations. The algorithm balances computational resources between a global search aimed at obtaining a global view of the network of protein conformations and their connectivity and a detailed local search focused on realizing such connections with physically-realistic models. Promising results are presented on a variety of proteins that demonstrate the general utility of the algorithm and its capability to improve the state of the art without employing system-specific insight.

Workload Characterization of CFD Applications Using Partial Differential Equation Solvers

NASA Technical Reports Server (NTRS)

Waheed, Abdul; Yan, Jerry; Saini, Subhash (Technical Monitor)

1998-01-01

Workload characterization is used for modeling and evaluating of computing systems at different levels of detail. We present workload characterization for a class of Computational Fluid Dynamics (CFD) applications that solve Partial Differential Equations (PDEs). This workload characterization focuses on three high performance computing platforms: SGI Origin2000, EBM SP-2, a cluster of Intel Pentium Pro bases PCs. We execute extensive measurement-based experiments on these platforms to gather statistics of system resource usage, which results in workload characterization. Our workload characterization approach yields a coarse-grain resource utilization behavior that is being applied for performance modeling and evaluation of distributed high performance metacomputing systems. In addition, this study enhances our understanding of interactions between PDE solver workloads and high performance computing platforms and is useful for tuning these applications.

New materials and structures for photovoltaics

NASA Astrophysics Data System (ADS)

Zunger, Alex; Wagner, S.; Petroff, P. M.

1993-01-01

Despite the fact that over the years crystal chemists have discovered numerous semiconducting substances, and that modern epitaxial growth techniques are able to produce many novel atomic-scale architectures, current electronic and opto-electronic technologies are based but on a handful of ˜10 traditional semiconductor core materials. This paper surveys a number of yet-unexploited classes of semiconductors, pointing to the much-needed research in screening, growing, and characterizing promising members of these classes. In light of the unmanageably large number of a-priori possibilities, we emphasize the role that structural chemistry and modern computer-aided design must play in screening potentially important candidates. The basic classes of materials discussed here include nontraditional alloys, such as non-isovalent and heterostructural semiconductors, materials at reduced dimensionality, including superlattices, zeolite-caged nanostructures and organic semiconductors, spontaneously ordered alloys, interstitial semiconductors, filled tetrahedral structures, ordered vacancy compounds, and compounds based on d and f electron elements. A collaborative effort among material predictor, material grower, and material characterizer holds the promise for a successful identification of new and exciting systems.

A physics-based algorithm for real-time simulation of electrosurgery procedures in minimally invasive surgery.

PubMed

Lu, Zhonghua; Arikatla, Venkata S; Han, Zhongqing; Allen, Brian F; De, Suvranu

2014-12-01

High-frequency electricity is used in the majority of surgical interventions. However, modern computer-based training and simulation systems rely on physically unrealistic models that fail to capture the interplay of the electrical, mechanical and thermal properties of biological tissue. We present a real-time and physically realistic simulation of electrosurgery by modelling the electrical, thermal and mechanical properties as three iteratively solved finite element models. To provide subfinite-element graphical rendering of vaporized tissue, a dual-mesh dynamic triangulation algorithm based on isotherms is proposed. The block compressed row storage (BCRS) structure is shown to be critical in allowing computationally efficient changes in the tissue topology due to vaporization. We have demonstrated our physics-based electrosurgery cutting algorithm through various examples. Our matrix manipulation algorithms designed for topology changes have shown low computational cost. Our simulator offers substantially greater physical fidelity compared to previous simulators that use simple geometry-based heat characterization. Copyright © 2013 John Wiley & Sons, Ltd.

Memory-Intensive Benchmarks: IRAM vs. Cache-Based Machines

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Gaeke, Brian R.; Husbands, Parry; Li, Xiaoye S.; Oliker, Leonid; Yelick, Katherine A.; Biegel, Bryan (Technical Monitor)

2002-01-01

The increasing gap between processor and memory performance has lead to new architectural models for memory-intensive applications. In this paper, we explore the performance of a set of memory-intensive benchmarks and use them to compare the performance of conventional cache-based microprocessors to a mixed logic and DRAM processor called VIRAM. The benchmarks are based on problem statements, rather than specific implementations, and in each case we explore the fundamental hardware requirements of the problem, as well as alternative algorithms and data structures that can help expose fine-grained parallelism or simplify memory access patterns. The benchmarks are characterized by their memory access patterns, their basic control structures, and the ratio of computation to memory operation.

A chemical and computational approach to comprehensive glycation characterization on antibodies

PubMed Central

Saleem, Ramsey A; Affholter, Brittany R; Deng, Sihong; Campbell, Phil C; Matthies, Kelli; Eakin, Catherine M; Wallace, Alison

2015-01-01

Non-enzymatic glycation is a challenging post-translational modification to characterize due to the structural heterogeneity it generates in proteins. Glycation has become increasingly recognized as an important product quality attribute to monitor, particularly for the biotechnology sector, which produces recombinant proteins under conditions that are amenable to protein glycation. The elucidation of sites of glycation can be problematic using conventional collision-induced dissociation (CID)-based mass spectrometry because of the predominance of neutral loss ions. A method to characterize glycation using an IgG1 monoclonal antibody (mAb) as a model is reported here. The sugars present on this mAb were derivatized using sodium borohydride chemistry to stabilize the linkage and identified using CID-based MS2 mass spectrometry and spectral search engines. Quantification of specific glycation sites was then done using a targeted MS1 based approach, which allowed the identification of a glycation hot spot in the heavy chain complementarity-determining region 3 of the mAb. This targeted approach provided a path forward to developing a structural understanding of the propensity of sites to become glycated on mAbs. Through structural analysis we propose a model in which the number and 3-dimensional distances of carboxylic acid amino acyl residues create a favorable environment for glycation to occur. PMID:26030340

PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework.

PubMed

Song, Jiangning; Li, Fuyi; Takemoto, Kazuhiro; Haffari, Gholamreza; Akutsu, Tatsuya; Chou, Kuo-Chen; Webb, Geoffrey I

2018-04-14

Determining the catalytic residues in an enzyme is critical to our understanding the relationship between protein sequence, structure, function, and enhancing our ability to design novel enzymes and their inhibitors. Although many enzymes have been sequenced, and their primary and tertiary structures determined, experimental methods for enzyme functional characterization lag behind. Because experimental methods used for identifying catalytic residues are resource- and labor-intensive, computational approaches have considerable value and are highly desirable for their ability to complement experimental studies in identifying catalytic residues and helping to bridge the sequence-structure-function gap. In this study, we describe a new computational method called PREvaIL for predicting enzyme catalytic residues. This method was developed by leveraging a comprehensive set of informative features extracted from multiple levels, including sequence, structure, and residue-contact network, in a random forest machine-learning framework. Extensive benchmarking experiments on eight different datasets based on 10-fold cross-validation and independent tests, as well as side-by-side performance comparisons with seven modern sequence- and structure-based methods, showed that PREvaIL achieved competitive predictive performance, with an area under the receiver operating characteristic curve and area under the precision-recall curve ranging from 0.896 to 0.973 and from 0.294 to 0.523, respectively. We demonstrated that this method was able to capture useful signals arising from different levels, leveraging such differential but useful types of features and allowing us to significantly improve the performance of catalytic residue prediction. We believe that this new method can be utilized as a valuable tool for both understanding the complex sequence-structure-function relationships of proteins and facilitating the characterization of novel enzymes lacking functional annotations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Computational Biochemistry-Enzyme Mechanisms Explored.

PubMed

Culka, Martin; Gisdon, Florian J; Ullmann, G Matthias

2017-01-01

Understanding enzyme mechanisms is a major task to achieve in order to comprehend how living cells work. Recent advances in biomolecular research provide huge amount of data on enzyme kinetics and structure. The analysis of diverse experimental results and their combination into an overall picture is, however, often challenging. Microscopic details of the enzymatic processes are often anticipated based on several hints from macroscopic experimental data. Computational biochemistry aims at creation of a computational model of an enzyme in order to explain microscopic details of the catalytic process and reproduce or predict macroscopic experimental findings. Results of such computations are in part complementary to experimental data and provide an explanation of a biochemical process at the microscopic level. In order to evaluate the mechanism of an enzyme, a structural model is constructed which can be analyzed by several theoretical approaches. Several simulation methods can and should be combined to get a reliable picture of the process of interest. Furthermore, abstract models of biological systems can be constructed combining computational and experimental data. In this review, we discuss structural computational models of enzymatic systems. We first discuss various models to simulate enzyme catalysis. Furthermore, we review various approaches how to characterize the enzyme mechanism both qualitatively and quantitatively using different modeling approaches. © 2017 Elsevier Inc. All rights reserved.

Image understanding systems based on the unifying representation of perceptual and conceptual information and the solution of mid-level and high-level vision problems

NASA Astrophysics Data System (ADS)

Kuvychko, Igor

2001-10-01

Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, that is an interpretation of visual information in terms of such knowledge models. A computer vision system based on such principles requires unifying representation of perceptual and conceptual information. Computer simulation models are built on the basis of graphs/networks. The ability of human brain to emulate similar graph/networks models is found. That means a very important shift of paradigm in our knowledge about brain from neural networks to the cortical software. Starting from the primary visual areas, brain analyzes an image as a graph-type spatial structure. Primary areas provide active fusion of image features on a spatial grid-like structure, where nodes are cortical columns. The spatial combination of different neighbor features cannot be described as a statistical/integral characteristic of the analyzed region, but uniquely characterizes such region itself. Spatial logic and topology naturally present in such structures. Mid-level vision processes like clustering, perceptual grouping, multilevel hierarchical compression, separation of figure from ground, etc. are special kinds of graph/network transformations. They convert low-level image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena like shape from shading, occlusion, etc. are results of such analysis. Such approach gives opportunity not only to explain frequently unexplainable results of the cognitive science, but also to create intelligent computer vision systems that simulate perceptional processes in both what and where visual pathways. Such systems can open new horizons for robotic and computer vision industries.

Structural characterization, surface characteristics and non covalent interactions of a heterocyclic Schiff base: Evaluation of antioxidant potential by UV-visible spectroscopy and DFT

NASA Astrophysics Data System (ADS)

Chithiraikumar, S.; Gandhimathi, S.; Neelakantan, M. A.

2017-06-01

A heterocyclic Schiff base, (E)-4-(1-((pyridin-2-ylmethyl)imino)ethyl)benzene-1,3-diol (L) was synthesized and isolated as single crystals. Its structure was characterized by FT-IR, UV, 1H and 13C NMR, and further confirmed by X-ray crystallography. Qualitatively and quantitatively the various interactions in the crystal structure of L has been analyzed by Hirshfeld surfaces and 2D fingerprint plots. Non covalent interactions have been studied by electron localization function (ELF) and mapped with reduced density gradient (RDG) analysis. The molecular structure was studied computationally by DFT-B3LYP/6-311G(d,p) calculations. HOMO-LUMO energy levels, chemical reactivity descriptors and thermodynamic parameters have been investigated at the same level of theory. The antioxidant potential of L was evaluated experimentally by measuring DPPH free radical scavenging effect using UV-visible spectroscopy and theoretically by DFT. Theoretical parameters, such as bond dissociation enthalpy (BDE) and spin density calculated suggests that antioxidant potential of L is due to H atom abstraction from the sbnd OH group.

Computation-Facilitated Assignment of Function in the Enolase Superfamily: A Regiochemically Distinct Galactarate Dehydratase from Oceanobacillus iheyensis†

PubMed Central

Rakus, John F.; Kalyanaraman, Chakrapani; Fedorov, Alexander A.; Fedorov, Elena V.; Mills-Groninger, Fiona P.; Toro, Rafael; Bonanno, Jeffrey; Bain, Kevin; Sauder, J. Michael; Burley, Stephen K.; Almo, Steven C.; Jacobson, Matthew P.; Gerlt, John A.

2009-01-01

The structure of an uncharacterized member of the enolase superfamily from Oceanobacillus iheyensis (GI: 23100298; IMG locus tag Ob2843; PDB Code 2OQY) was determined by the New York SGX Research Center for Structural Genomics (NYSGXRC). The structure contained two Mg2+ ions located 10.4 Å from one another, with one located in the canonical position in the (β/α)7β-barrel domain (although the ligand at the end of the fifth β-strand is His, unprecedented in structurally characterized members of the superfamily); the second is located in a novel site within the capping domain. In silico docking of a library of mono- and diacid sugars to the active site predicted a diacid sugar as a likely substrate. Activity screening of a physical library of acid sugars identified galactarate as the substrate (kcat = 6.8 s−1, KM = 620 μM; kcat/KM = 1.1 × 104 M−1 s−1), allowing functional assignment of Ob2843 as galactarate dehydratase (GalrD-II) The structure of a complex of the catalytically impaired Y90F mutant with Mg2+ and galactarate allowed identification of a Tyr 164-Arg 162 dyad as the base that initiates the reaction by abstraction of the α-proton and Tyr 90 as the acid that facilitates departure of the β-OH leaving group. The enzyme product is 2-keto-3-deoxy-D-threo-4,5-dihydroxyadipate, the enantiomer of the product obtained in the GalrD reaction catalyzed by a previously characterized bifunctional L-talarate/galactarate dehydratase (TalrD/GalrD). On the basis of the different active site structures and different regiochemistries, we recognize that these functions represent an example of apparent, not actual, convergent evolution of function. The structure of GalrD-II and its active site architecture allow identification of the seventh functionally and structurally characterized subgroup in the enolase superfamily. This study provides an additional example that an integrated sequence/structure-based strategy employing computational approaches is a viable approach for directing functional assignment of unknown enzymes discovered in genome projects. PMID:19883118

Structured water in polyelectrolyte dendrimers: Understanding small angle neutron scattering results through atomistic simulation

NASA Astrophysics Data System (ADS)

Wu, Bin; Kerkeni, Boutheïna; Egami, Takeshi; Do, Changwoo; Liu, Yun; Wang, Yongmei; Porcar, Lionel; Hong, Kunlun; Smith, Sean C.; Liu, Emily L.; Smith, Gregory S.; Chen, Wei-Ren

2012-04-01

Based on atomistic molecular dynamics (MD) simulations, the small angle neutron scattering (SANS) intensity behavior of a single generation-4 polyelectrolyte polyamidoamine starburst dendrimer is investigated at different levels of molecular protonation. The SANS form factor, P(Q), and Debye autocorrelation function, γ(r), are calculated from the equilibrium MD trajectory based on a mathematical approach proposed in this work. The consistency found in comparison against previously published experimental findings (W.-R. Chen, L. Porcar, Y. Liu, P. D. Butler, and L. J. Magid, Macromolecules 40, 5887 (2007)) leads to a link between the neutron scattering experiment and MD computation, and fresh perspectives. The simulations enable scattering calculations of not only the hydrocarbons but also the contribution from the scattering length density fluctuations caused by structured, confined water within the dendrimer. Based on our computational results, we explore the validity of using radius of gyration RG for microstructure characterization of a polyelectrolyte dendrimer from the scattering perspective.

A three-dimensional bioprinting system for use with a hydrogel-based biomaterial and printing parameter characterization.

PubMed

Song, Seung-Joon; Choi, Jaesoon; Park, Yong-Doo; Lee, Jung-Joo; Hong, So Young; Sun, Kyung

2010-11-01

Bioprinting is an emerging technology for constructing tissue or bioartificial organs with complex three-dimensional (3D) structures. It provides high-precision spatial shape forming ability on a larger scale than conventional tissue engineering methods, and simultaneous multiple components composition ability. Bioprinting utilizes a computer-controlled 3D printer mechanism for 3D biological structure construction. To implement minimal pattern width in a hydrogel-based bioprinting system, a study on printing characteristics was performed by varying printer control parameters. The experimental results showed that printing pattern width depends on associated printer control parameters such as printing flow rate, nozzle diameter, and nozzle velocity. The system under development showed acceptable feasibility of potential use for accurate printing pattern implementation in tissue engineering applications and is another example of novel techniques for regenerative medicine based on computer-aided biofabrication system. © 2010, Copyright the Authors. Artificial Organs © 2010, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Impact of computational structure-based methods on drug discovery.

PubMed

Reynolds, Charles H

2014-01-01

Structure-based drug design has become an indispensible tool in drug discovery. The emergence of structure-based design is due to gains in structural biology that have provided exponential growth in the number of protein crystal structures, new computational algorithms and approaches for modeling protein-ligand interactions, and the tremendous growth of raw computer power in the last 30 years. Computer modeling and simulation have made major contributions to the discovery of many groundbreaking drugs in recent years. Examples are presented that highlight the evolution of computational structure-based design methodology, and the impact of that methodology on drug discovery.

Micromechanical Characterization and Testing of Carbon Based Woven Thermal Protection Materials

NASA Technical Reports Server (NTRS)

Agrawal, Parul; Pham, John T.; Arnold, James O.; Peterson, Keith; Venkatapathy, Ethiraj

2013-01-01

Woven thermal protection system (TPS) materials are one of the enabling technologies for mechanically deployable hypersonic decelerator systems. These materials can be simultaneously used for thermal protection and as structural load bearing members during the entry, descent and landing operations. In order to ensure successful thermal and structural performance during the atmospheric entry, it is important to characterize the properties of these materials, once they have been subjected to entry like conditions. The present paper focuses on mechanical characteristics of pre-and post arc-jet tested woven TPS samples at different scales. It also presents the observations from scanning electron microscope and computed tomography images, and explains the changes in microstructure after being subjected to combined thermal-mechanical loading environments.

Coupled multi-disciplinary simulation of composite engine structures in propulsion environment

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Singhal, Surendra N.

1992-01-01

A computational simulation procedure is described for the coupled response of multi-layered multi-material composite engine structural components which are subjected to simultaneous multi-disciplinary thermal, structural, vibration, and acoustic loadings including the effect of hostile environments. The simulation is based on a three dimensional finite element analysis technique in conjunction with structural mechanics codes and with acoustic analysis methods. The composite material behavior is assessed at the various composite scales, i.e., the laminate/ply/constituents (fiber/matrix), via a nonlinear material characterization model. Sample cases exhibiting nonlinear geometrical, material, loading, and environmental behavior of aircraft engine fan blades, are presented. Results for deformed shape, vibration frequency, mode shapes, and acoustic noise emitted from the fan blade, are discussed for their coupled effect in hot and humid environments. Results such as acoustic noise for coupled composite-mechanics/heat transfer/structural/vibration/acoustic analyses demonstrate the effectiveness of coupled multi-disciplinary computational simulation and the various advantages of composite materials compared to metals.

A comparative study of multi-sensor data fusion methods for highly accurate assessment of manufactured parts

NASA Astrophysics Data System (ADS)

Hannachi, Ammar; Kohler, Sophie; Lallement, Alex; Hirsch, Ernest

2015-04-01

3D modeling of scene contents takes an increasing importance for many computer vision based applications. In particular, industrial applications of computer vision require efficient tools for the computation of this 3D information. Routinely, stereo-vision is a powerful technique to obtain the 3D outline of imaged objects from the corresponding 2D images. As a consequence, this approach provides only a poor and partial description of the scene contents. On another hand, for structured light based reconstruction techniques, 3D surfaces of imaged objects can often be computed with high accuracy. However, the resulting active range data in this case lacks to provide data enabling to characterize the object edges. Thus, in order to benefit from the positive points of various acquisition techniques, we introduce in this paper promising approaches, enabling to compute complete 3D reconstruction based on the cooperation of two complementary acquisition and processing techniques, in our case stereoscopic and structured light based methods, providing two 3D data sets describing respectively the outlines and surfaces of the imaged objects. We present, accordingly, the principles of three fusion techniques and their comparison based on evaluation criterions related to the nature of the workpiece and also the type of the tackled application. The proposed fusion methods are relying on geometric characteristics of the workpiece, which favour the quality of the registration. Further, the results obtained demonstrate that the developed approaches are well adapted for 3D modeling of manufactured parts including free-form surfaces and, consequently quality control applications using these 3D reconstructions.

Coupling MD Simulations and X-ray Absorption Spectroscopy to Study Ions in Solution

NASA Astrophysics Data System (ADS)

Marcos, E. Sánchez; Beret, E. C.; Martínez, J. M.; Pappalardo, R. R.; Ayala, R.; Muñoz-Páez, A.

2007-12-01

The structure of ionic solutions is a key-point in understanding physicochemical properties of electrolyte solutions. Among the reduced number of experimental techniques which can supply direct information on the ion environment, X-ray Absorption techniques (XAS) have gained importance during the last decades although they are not free of difficulties associated to the data analysis leading to provide reliable structures. Computer simulations of ions in solution is a theoretical alternative to provide information on the solvation structure. Thus, the use of computational chemistry can increase the understanding of these systems although an accurate description of ionic solvation phenomena represents nowadays a significant challenge to theoretical chemistry. We present: (a) the assignment of features in the XANES spectrum to well defined structural motif in the ion environment, (b) MD-based evaluation of EXAFS parameters used in the fitting procedure to make easier the structural resolution, and (c) the use of the agreement between experimental and simulated XANES spectra to help in the choice of a given intermolecular potential for Computer Simulations. Chemical problems examined are: (a) the identification of the second hydration shell in dilute aqueous solutions of highly-charged cations, such as Cr3+, Rh3+, Ir3+, (b) the invisibility by XAS of certain structures characterized by Computer Simulations but exhibiting high dynamical behavior and (c) the solvation of Br- in acetonitrile.

Coupling MD Simulations and X-ray Absorption Spectroscopy to Study Ions in Solution

NASA Astrophysics Data System (ADS)

Marcos, E. Sánchez; Beret, E. C.; Martínez, J. M.; Pappalardo, R. R.; Ayala, R.; Muñoz-Páez, A.

2007-11-01

The structure of ionic solutions is a key-point in understanding physicochemical properties of electrolyte solutions. Among the reduced number of experimental techniques which can supply direct information on the ion environment, X-ray Absorption techniques (XAS) have gained importance during the last decades although they are not free of difficulties associated to the data analysis leading to provide reliable structures. Computer simulations of ions in solution is a theoretical alternative to provide information on the solvation structure. Thus, the use of computational chemistry can increase the understanding of these systems although an accurate description of ionic solvation phenomena represents nowadays a significant challenge to theoretical chemistry. We present: (a) the assignment of features in the XANES spectrum to well defined structural motif in the ion environment, (b) MD-based evaluation of EXAFS parameters used in the fitting procedure to make easier the structural resolution, and (c) the use of the agreement between experimental and simulated XANES spectra to help in the choice of a given intermolecular potential for Computer Simulations. Chemical problems examined are: (a) the identification of the second hydration shell in dilute aqueous solutions of highly-charged cations, such as Cr3+, Rh3+, Ir3+, (b) the invisibility by XAS of certain structures characterized by Computer Simulations but exhibiting high dynamical behavior and (c) the solvation of Br- in acetonitrile.

Probabilistic design of fibre concrete structures

NASA Astrophysics Data System (ADS)

Pukl, R.; Novák, D.; Sajdlová, T.; Lehký, D.; Červenka, J.; Červenka, V.

2017-09-01

Advanced computer simulation is recently well-established methodology for evaluation of resistance of concrete engineering structures. The nonlinear finite element analysis enables to realistically predict structural damage, peak load, failure, post-peak response, development of cracks in concrete, yielding of reinforcement, concrete crushing or shear failure. The nonlinear material models can cover various types of concrete and reinforced concrete: ordinary concrete, plain or reinforced, without or with prestressing, fibre concrete, (ultra) high performance concrete, lightweight concrete, etc. Advanced material models taking into account fibre concrete properties such as shape of tensile softening branch, high toughness and ductility are described in the paper. Since the variability of the fibre concrete material properties is rather high, the probabilistic analysis seems to be the most appropriate format for structural design and evaluation of structural performance, reliability and safety. The presented combination of the nonlinear analysis with advanced probabilistic methods allows evaluation of structural safety characterized by failure probability or by reliability index respectively. Authors offer a methodology and computer tools for realistic safety assessment of concrete structures; the utilized approach is based on randomization of the nonlinear finite element analysis of the structural model. Uncertainty of the material properties or their randomness obtained from material tests are accounted in the random distribution. Furthermore, degradation of the reinforced concrete materials such as carbonation of concrete, corrosion of reinforcement, etc. can be accounted in order to analyze life-cycle structural performance and to enable prediction of the structural reliability and safety in time development. The results can serve as a rational basis for design of fibre concrete engineering structures based on advanced nonlinear computer analysis. The presented methodology is illustrated on results from two probabilistic studies with different types of concrete structures related to practical applications and made from various materials (with the parameters obtained from real material tests).

Characterization of newly synthesized pyrimidine derivatives for corrosion inhibition as inferred from computational chemical analysis

NASA Astrophysics Data System (ADS)

El-Taib Heakal, F.; Rizk, S. A.; Elkholy, A. E.

2018-01-01

Corrosion of metallic constructions is a serious problem in most industries worldwide that can be controlled via addition of special chemicals having adsorption capability on metal surfaces and hence isolating it from the aggressive environment. These chemicals are characterized by being rich in functional groups containing free lone pairs of electrons and/or π-electrons. In the present study four newly imidazole-pyrimidine based ionic derivatives have been synthesized and their structures were characterized by means of elemental analysis and different spectroscopic techniques. Quantum chemical calculations were carried out to give insights into the structural and electronic characteristics of these fabricated compounds. Monte Carlo simulation was also applied to shed the light on our prepared corrosion inhibitor molecules by examining their aptitude to adsorb on iron surface. Our ultimate goal is to help industries in fighting corrosion by providing them with a cheap and efficient anti-corrosion molecules.

A computational prediction of structure and function of novel homologue of Arabidopsis thaliana Vps51/Vps67 subunit in Corchorus olitorius.

PubMed

Zaman, Aubhishek; Fancy, Nurun Nahar

2012-12-01

Vps mediated vesicular transport is important for transferring macromolecules trapped inside a vesicle. Although highly abundant, Vps shows tremendous sequence variation among diverse array of species. However, this difference in sequence, which seems to also translate into substantial functional variation, is hardly characterized in Corchorus spp. Here, our computational study investigates structural and functional features of one of the Vps subunit namely Vps51/Vps67 in C. olitorius. Broad scale structural characterization revealed novel information about the overall Vps structure and binding sites. Moreover, functional analyses indicate interaction partners which were unexplored to date. Since membrane trafficking is essentially associated with nutrient uptake and chemical de-toxification, characterization of the Vps subunit can well provide us with better insight into important agronomic traits such as stress response, immune response and phytoremediation capacity.

Parametric bicubic spline and CAD tools for complex targets shape modelling in physical optics radar cross section prediction

NASA Astrophysics Data System (ADS)

Delogu, A.; Furini, F.

1991-09-01

Increasing interest in radar cross section (RCS) reduction is placing new demands on theoretical, computation, and graphic techniques for calculating scattering properties of complex targets. In particular, computer codes capable of predicting the RCS of an entire aircraft at high frequency and of achieving RCS control with modest structural changes, are becoming of paramount importance in stealth design. A computer code, evaluating the RCS of arbitrary shaped metallic objects that are computer aided design (CAD) generated, and its validation with measurements carried out using ALENIA RCS test facilities are presented. The code, based on the physical optics method, is characterized by an efficient integration algorithm with error control, in order to contain the computer time within acceptable limits, and by an accurate parametric representation of the target surface in terms of bicubic splines.

Evaluating structural pattern recognition for handwritten math via primitive label graphs

NASA Astrophysics Data System (ADS)

Zanibbi, Richard; Mouchère, Harold; Viard-Gaudin, Christian

2013-01-01

Currently, structural pattern recognizer evaluations compare graphs of detected structure to target structures (i.e. ground truth) using recognition rates, recall and precision for object segmentation, classification and relationships. In document recognition, these target objects (e.g. symbols) are frequently comprised of multiple primitives (e.g. connected components, or strokes for online handwritten data), but current metrics do not characterize errors at the primitive level, from which object-level structure is obtained. Primitive label graphs are directed graphs defined over primitives and primitive pairs. We define new metrics obtained by Hamming distances over label graphs, which allow classification, segmentation and parsing errors to be characterized separately, or using a single measure. Recall and precision for detected objects may also be computed directly from label graphs. We illustrate the new metrics by comparing a new primitive-level evaluation to the symbol-level evaluation performed for the CROHME 2012 handwritten math recognition competition. A Python-based set of utilities for evaluating, visualizing and translating label graphs is publicly available.

Toward high-resolution computational design of helical membrane protein structure and function

PubMed Central

Barth, Patrick; Senes, Alessandro

2016-01-01

The computational design of α-helical membrane proteins is still in its infancy but has made important progress. De novo design has produced stable, specific and active minimalistic oligomeric systems. Computational re-engineering can improve stability and modulate the function of natural membrane proteins. Currently, the major hurdle for the field is not computational, but the experimental characterization of the designs. The emergence of new structural methods for membrane proteins will accelerate progress PMID:27273630

Structural characterization of new Schiff bases of sulfamethoxazole and sulfathiazole, their antibacterial activity and docking computation with DHPS protein structure.

PubMed

Mondal, Sudipa; Mandal, Santi M; Mondal, Tapan Kumar; Sinha, Chittaranjan

2015-01-01

New Schiff bases (1, 2) of substituted salicylaldehydes and sulfamethoxazole (SMX)/sulfathiazole (STZ) are synthesized and characterized by elemental analysis and spectroscopic data. Single crystal X-ray structure of one of the compounds (E)-4-((3,5-dichloro-2-hydroxybenzylidene)amino)-N-(5-methylisoxazol-3-yl)benzenesulfonamide (1c) has been determined. Antimicrobial activities of the Schiff bases and parent sulfonamides (SMX, STZ) have been examined against several Gram-positive and Gram-negative bacteria and sulfonamide resistant pathogens; the lowest MIC is observed for (E)-4-((3,5-dichloro-2-hydroxybenzylidene)amino)-N-(thiazol-2-yl)benzene sulfonamide (2c) (8.0 μg mL(-1)) and (E)-4-((3,5-dichloro-2-hydroxybenzylidene)amino)-N-(5-methylisoxazol-3-yl)benzene sulfonamide (1c) (16.0 μg mL(-1)) against sulfonamide resistant pathogens. DFT optimized structures of the Schiff bases have been used to carry out molecular docking studies with DHPS (dihydropteroate synthase) protein structure (downloaded from Protein Data Bank) using Discovery Studio 3.5 to find the most preferred binding mode of the ligand inside the protein cavity. The theoretical data have been well correlated with the experimental results. Cell viability assay and ADMET studies predict that 1c and 2c have good drug like characters. Copyright © 2015 Elsevier B.V. All rights reserved.

Multi-scale analytical investigation of fly ash in concrete

NASA Astrophysics Data System (ADS)

Aboustait, Mohammed B.

Much research has been conducted to find an acceptable concrete ingredient that would act as cement replacement. One promising material is fly ash. Fly ash is a by-product from coal-fired power plants. Throughout this document work on the characterization of fly ash structure and composition will be explored. This effort was conducted through a mixture of cutting edge multi-scale analytical X-ray based techniques that use both bulk experimentation and nano/micro analytical techniques. Furtherly, this examination was coupled by performing Physical/Mechanical ASTM based testing on fly ash-enrolled-concrete to examine the effects of fly ash introduction. The most exotic of the cutting edge characterization techniques endorsed in this work uses the Nano-Computed Tomography and the Nano X-ray Fluorescence at Argonne National Laboratory to investigate single fly ash particles. Additional Work on individual fly ash particles was completed by laboratory-based Micro-Computed Tomography and Scanning Electron Microscopy. By combining the results of individual particles and bulk property tests, a compiled perspective is introduced, and accessed to try and make new insights into the reactivity of fly ash within concrete.

Novel functionalized pyridine-containing DTPA-like ligand. Synthesis, computational studies and characterization of the corresponding Gd(III) complex.

PubMed

Artali, Roberto; Botta, Mauro; Cavallotti, Camilla; Giovenzana, Giovanni B; Palmisano, Giovanni; Sisti, Massimo

2007-08-07

A novel pyridine-containing DTPA-like ligand, carrying additional hydroxymethyl groups on the pyridine side-arms, was synthesized in 5 steps. The corresponding Gd(III) complex, potentially useful as an MRI contrast agent, was prepared and characterized in detail by relaxometric methods and its structure modeled by computational methods.

Computer-based prediction of mitochondria-targeting peptides.

PubMed

Martelli, Pier Luigi; Savojardo, Castrense; Fariselli, Piero; Tasco, Gianluca; Casadio, Rita

2015-01-01

Computational methods are invaluable when protein sequences, directly derived from genomic data, need functional and structural annotation. Subcellular localization is a feature necessary for understanding the protein role and the compartment where the mature protein is active and very difficult to characterize experimentally. Mitochondrial proteins encoded on the cytosolic ribosomes carry specific patterns in the precursor sequence from where it is possible to recognize a peptide targeting the protein to its final destination. Here we discuss to which extent it is feasible to develop computational methods for detecting mitochondrial targeting peptides in the precursor sequences and benchmark our and other methods on the human mitochondrial proteins endowed with experimentally characterized targeting peptides. Furthermore, we illustrate our newly implemented web server and its usage on the whole human proteome in order to infer mitochondrial targeting peptides, their cleavage sites, and whether the targeting peptide regions contain or not arginine-rich recurrent motifs. By this, we add some other 2,800 human proteins to the 124 ones already experimentally annotated with a mitochondrial targeting peptide.

Characterization, Modeling, and Failure Analysis of Composite Structure Materials under Static and Dynamic Loading

NASA Astrophysics Data System (ADS)

Werner, Brian Thomas

Composite structures have long been used in many industries where it is advantageous to reduce weight while maintaining high stiffness and strength. Composites can now be found in an ever broadening range of applications: sporting equipment, automobiles, marine and aerospace structures, and energy production. These structures are typically sandwich panels composed of fiber reinforced polymer composite (FRPC) facesheets which provide the stiffness and the strength and a low density polymeric foam core that adds bending rigidity with little additional weight. The expanding use of composite structures exposes them to high energy, high velocity dynamic loadings which produce multi-axial dynamic states of stress. This circumstance can present quite a challenge to designers, as composite structures are highly anisotropic and display properties that are sensitive to loading rates. Computer codes are continually in development to assist designers in the creation of safe, efficient structures. While the design of an optimal composite structure is more complex, engineers can take advantage of the effect of enhanced energy dissipation displayed by a composite when loaded at high strain rates. In order to build and verify effective computer codes, the underlying assumptions must be verified by laboratory experiments. Many of these codes look to use a micromechanical approach to determine the response of the structure. For this, the material properties of the constituent materials must be verified, three-dimensional constitutive laws must be developed, and failure of these materials must be investigated under static and dynamic loading conditions. In this study, simple models are sought not only to ease their implementation into such codes, but to allow for efficient characterization of new materials that may be developed. Characterization of composite materials and sandwich structures is a costly, time intensive process. A constituent based design approach evaluates potential combinations of materials in a much faster and more efficient manner.

Optical Measurement Technique for Space Column Characterization

NASA Technical Reports Server (NTRS)

Barrows, Danny A.; Watson, Judith J.; Burner, Alpheus W.; Phelps, James E.

2004-01-01

A simple optical technique for the structural characterization of lightweight space columns is presented. The technique is useful for determining the coefficient of thermal expansion during cool down as well as the induced strain during tension and compression testing. The technique is based upon object-to-image plane scaling and does not require any photogrammetric calibrations or computations. Examples of the measurement of the coefficient of thermal expansion are presented for several lightweight space columns. Examples of strain measured during tension and compression testing are presented along with comparisons to results obtained with Linear Variable Differential Transformer (LVDT) position transducers.

Diluted magnetic oxides

NASA Astrophysics Data System (ADS)

Li, XiaoLi; Qi, ShiFei; Jiang, FengXian; Quan, ZhiYong; Xu, XiaoHong

2013-01-01

In this review, we review the progress of research on ZnO- and In2O3-based diluted magnetic oxides (DMOs). Firstly, we present the preparation and characterization of DMOs. The former includes the preparation methods and conditions, and the latter includes the characterization techniques for measuring microstructures. Secondly, we introduce the magnetic and transport properties of DMOs, as well as the relationship between them. Thirdly, the origin and mechanism of the ferromagnetism are discussed. Fourthly, we introduce other related work, including computational work and pertinent heterogeneous structures, such as multilayers and magnetic tunnel junctions. Finally, we provide an overview and outlook for DMOs.

Comprehensive computational design of ordered peptide macrocycles

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

Hosseinzadeh, Parisa; Bhardwaj, Gaurav; Mulligan, Vikram Khipple

Mixed chirality peptide macrocycles such as cyclosporine are among the most potent therapeutics identified to-date, but there is currently no way to systematically search through the structural space spanned by such compounds for new drug candidates. Natural proteins do not provide a useful guide: peptide macrocycles lack regular secondary structures and hydrophobic cores and have different backbone torsional constraints. Hence the development of new peptide macrocycles has been approached by modifying natural products or using library selection methods; the former is limited by the small number of known structures, and the latter by the limited size and diversity accessible throughmore » library-based methods. To overcome these limitations, here we enumerate the stable structures that can be adopted by macrocyclic peptides composed of L and D amino acids. We identify more than 200 designs predicted to fold into single stable structures, many times more than the number of currently available unbound peptide macrocycle structures. We synthesize and characterize by NMR twelve 7-10 residue macrocycles, 9 of which have structures very close to the design models in solution. NMR structures of three 11-14 residue bicyclic designs are also very close to the computational models. Our results provide a nearly complete coverage of the rich space of structures possible for short peptide based macrocycles unparalleled for other molecular systems, and vastly increase the available starting scaffolds for both rational drug design and library selection methods.« less

Unitized Stiffened Composite Textile Panels: Manufacturing, Characterization, Experiments, and Analysis

NASA Astrophysics Data System (ADS)

Kosztowny, Cyrus Joseph Robert

Use of carbon fiber textiles in complex manufacturing methods creates new implementations of structural components by increasing performance, lowering manufacturing costs, and making composites overall more attractive across industry. Advantages of textile composites include high area output, ease of handling during the manufacturing process, lower production costs per material used resulting from automation, and provide post-manufacturing assembly mainstreaming because significantly more complex geometries such as stiffened shell structures can be manufactured with fewer pieces. One significant challenge with using stiffened composite structures is stiffener separation under compression. Axial compression loading conditions have frequently observed catastrophic structural failure due to stiffeners separating from the shell skin. Characterizing stiffener separation behavior is often costly computationally and experimentally. The objectives of this research are to demonstrate unitized stiffened textile composite panels can be manufactured to produce quality test specimens, that existing characterization techniques applied to state-of-the-art high-performance composites provide valuable information in modeling such structures, that the unitized structure concept successfully removes stiffener separation as a primary structural failure mode, and that modeling textile material failure modes are sufficient to accurately capture postbuckling and final failure responses of the stiffened structures. The stiffened panels in this study have taken the integrally stiffened concept to an extent such that the stiffeners and skin are manufactured at the same time, as one single piece, and from the same composite textile layers. Stiffener separation is shown to be removed as a primary structural failure mode for unitized stiffened composite textile panels loaded under axial compression well into the postbuckling regime. Instead of stiffener separation, a material damaging and failure model effectively captures local post-peak material response via incorporating a mesoscale model using a multiscaling framework with a smeared crack element-based failure model in the macroscale stiffened panel. Material damage behavior is characterized by simple experimental tests and incorporated into the post-peak stiffness degradation law in the smeared crack implementation. Computational modeling results are in overall excellent agreement compared to the experimental responses.

Heterocyclic energetic materials: Synthesis, characterization and computational design

NASA Astrophysics Data System (ADS)

Tsyshevsky, Roman; Pagoria, Philip; Smirnov, Aleksander; Kuklja, Maija

2017-06-01

Achievement of the tailored properties (high performance, low sensitivity, etc.) in targeted new energetic materials (EM) remains a great challenge. Recently, attention of researchers has shifted from conventional nitroester-, nitramine-, and nitroaromatic-based explosives to new heterocyclic EM with oxygen- and nitrogenrich molecular structures. They have increased densities and formation enthalpies complemented by attractive performance and high stability to external stimuli. We will demonstrate that oxadiazol-containing heterocycles offer a convenient playground to probe specific chemical functional groups as building blocks for design of EM. We discuss a joint experimental and computational approach for design, characterization, synthesis, and modeling of novel heterocyclic EM. Combinatorically, we comprehensively analyzed how overall stability and performance of each material in the family (BNFF, LLM-172, LLM-175, LLM-191, LLM-192, LLM-200) depends upon their chemical composition and details of the molecular structure (such as a substitution of a nitro group by an amino group and 1,2,5-oxadiazole fragment by 1,2,3- or 1,2,4-oxadiazol ring). We will also discuss proposed new EM with predicted superior chemical and physical properties. P. Pagoria, R. Tsyshevsky, A. Smirnov.

An experimental study on the manufacture and characterization of in-plane fibre-waviness defects in composites

PubMed Central

DiazDelaO, F. A.; Atherton, K.

2018-01-01

A new method has been developed for creating localized in-plane fibre waviness in composite coupons and used to create a large batch of specimens. This method could be used by manufacturers to experimentally explore the effect of fibre waviness on composite structures both directly and indirectly to develop and validate computational models. The specimens were assessed using ultrasound, digital image correlation and a novel inspection technique capable of measuring residual strain fields. To explore how the defect affects the performance of composite structures, the specimens were then loaded to failure. Predictions of remnant strength were made using a simple ultrasound damage metric and a new residual strain-based damage metric. The predictions made using residual strain measurements were found to be substantially more effective at characterizing ultimate strength than ultrasound measurements. This suggests that residual strains have a significant effect on the failure of laminates containing fibre waviness and that these strains could be incorporated into computational models to improve their ability to simulate the defect. PMID:29892446

G‐LoSA: An efficient computational tool for local structure‐centric biological studies and drug design

PubMed Central

2016-01-01

Abstract Molecular recognition by protein mostly occurs in a local region on the protein surface. Thus, an efficient computational method for accurate characterization of protein local structural conservation is necessary to better understand biology and drug design. We present a novel local structure alignment tool, G‐LoSA. G‐LoSA aligns protein local structures in a sequence order independent way and provides a GA‐score, a chemical feature‐based and size‐independent structure similarity score. Our benchmark validation shows the robust performance of G‐LoSA to the local structures of diverse sizes and characteristics, demonstrating its universal applicability to local structure‐centric comparative biology studies. In particular, G‐LoSA is highly effective in detecting conserved local regions on the entire surface of a given protein. In addition, the applications of G‐LoSA to identifying template ligands and predicting ligand and protein binding sites illustrate its strong potential for computer‐aided drug design. We hope that G‐LoSA can be a useful computational method for exploring interesting biological problems through large‐scale comparison of protein local structures and facilitating drug discovery research and development. G‐LoSA is freely available to academic users at http://im.compbio.ku.edu/GLoSA/. PMID:26813336

A novel integrated framework and improved methodology of computer-aided drug design.

PubMed

Chen, Calvin Yu-Chian

2013-01-01

Computer-aided drug design (CADD) is a critical initiating step of drug development, but a single model capable of covering all designing aspects remains to be elucidated. Hence, we developed a drug design modeling framework that integrates multiple approaches, including machine learning based quantitative structure-activity relationship (QSAR) analysis, 3D-QSAR, Bayesian network, pharmacophore modeling, and structure-based docking algorithm. Restrictions for each model were defined for improved individual and overall accuracy. An integration method was applied to join the results from each model to minimize bias and errors. In addition, the integrated model adopts both static and dynamic analysis to validate the intermolecular stabilities of the receptor-ligand conformation. The proposed protocol was applied to identifying HER2 inhibitors from traditional Chinese medicine (TCM) as an example for validating our new protocol. Eight potent leads were identified from six TCM sources. A joint validation system comprised of comparative molecular field analysis, comparative molecular similarity indices analysis, and molecular dynamics simulation further characterized the candidates into three potential binding conformations and validated the binding stability of each protein-ligand complex. The ligand pathway was also performed to predict the ligand "in" and "exit" from the binding site. In summary, we propose a novel systematic CADD methodology for the identification, analysis, and characterization of drug-like candidates.

Material Characterization and Geometric Segmentation of a Composite Structure Using Microfocus X-Ray Computed Tomography Image-Based Finite Element Modeling

NASA Technical Reports Server (NTRS)

Abdul-Aziz, Ali; Roth, D. J.; Cotton, R.; Studor, George F.; Christiansen, Eric; Young, P. C.

2011-01-01

This study utilizes microfocus x-ray computed tomography (CT) slice sets to model and characterize the damage locations and sizes in thermal protection system materials that underwent impact testing. ScanIP/FE software is used to visualize and process the slice sets, followed by mesh generation on the segmented volumetric rendering. Then, the local stress fields around several of the damaged regions are calculated for realistic mission profiles that subject the sample to extreme temperature and other severe environmental conditions. The resulting stress fields are used to quantify damage severity and make an assessment as to whether damage that did not penetrate to the base material can still result in catastrophic failure of the structure. It is expected that this study will demonstrate that finite element modeling based on an accurate three-dimensional rendered model from a series of CT slices is an essential tool to quantify the internal macroscopic defects and damage of a complex system made out of thermal protection material. Results obtained showing details of segmented images; three-dimensional volume-rendered models, finite element meshes generated, and the resulting thermomechanical stress state due to impact loading for the material are presented and discussed. Further, this study is conducted to exhibit certain high-caliber capabilities that the nondestructive evaluation (NDE) group at NASA Glenn Research Center can offer to assist in assessing the structural durability of such highly specialized materials so improvements in their performance and capacities to handle harsh operating conditions can be made.

SKYSINE-II procedure: calculation of the effects of structure design on neutron, primary gamma-ray and secondary gamma-ray dose rates in air

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

Lampley, C.M.

1979-01-01

An updated version of the SKYSHINE Monte Carlo procedure has been developed. The new computer code, SKYSHINE-II, provides a substantial increase in versatility in that the program possesses the ability to address three types of point-isotropic radiation sources: (1) primary gamma rays, (2) neutrons, and (3) secondary gamma rays. In addition, the emitted radiation may now be characterized by an energy emission spectrum product of a new energy-dependent atmospheric transmission data base developed by Radiation Research Associates, Inc. for each of the three source types described above. Most of the computational options present in the original program have been retainedmore » in the new version. Hence, the SKYSHINE-II computer code provides a versatile and viable tool for the analysis of the radiation environment in the vicinity of a building structure containing radiation sources, situated within the confines of a nuclear power plant. This report describes many of the calculational methods employed within the SKYSHINE-II program. A brief description of the new data base is included. Utilization instructions for the program are provided for operation of the SKYSHINE-II code on the Brookhaven National Laboratory Central Scientific Computing Facility. A listing of the source decks, block data routines, and the new atmospheric transmission data base are provided in the appendices of the report.« less

Computed tomographic analysis of the internal structure of the metacarpals and its implications for hand use, pathology, and surgical intervention.

PubMed

Wong, Alison L; Meals, Clifton G; Ruff, Christopher B

2018-03-01

The variation of bone structure and biomechanics between the metacarpals is not well characterized. It was hypothesized that their structure would reflect their common patterns of use (i.e., patterns of hand grip), specifically that trabecular bone density would be greater on the volar aspect of all metacarpal bases, that this would be most pronounced in the thumb, and that the thumb diaphysis would have the greatest bending strength. Cross-sections at basal and mid-diaphyseal locations of 50 metacarpals from 10 human hands were obtained by peripheral quantitative computed tomography. The volar and dorsal trabecular densities of each base were measured and characterized using the volar/dorsal density ratio. The polar stress-strain index (SSIp), a surrogate measure of torsional/bending strength, was measured for each diaphysis and standardized for bone length and mass. Comparisons were made using mixed-model analyses of variance (ANOVAs) and post hoc tests. Volar/dorsal trabecular density ratios showed even distribution in all metacarpal bases except for the thumb, which showed greater values on the volar aspect. The thumb, second, and third metacarpals all had high bending strength (SSIp), but the thumb's SSIp relative to its length and trabecular mass was much higher than those of the other metacarpals. Trabecular density of the metacarpal bases was evenly distributed except in the thumb, which also showed higher bending strength relative to its length and mass. Understanding of how these indicators of strength differ across metacarpals may improve both fracture diagnosis and treatment and lays the groundwork for investigating changes with age, hand dominance, and occupation.

Discrete particle model for cement infiltration within open-cell structures: Prevention of osteoporotic fracture.

PubMed

Ramos-Infante, Samuel Jesús; Ten-Esteve, Amadeo; Alberich-Bayarri, Angel; Pérez, María Angeles

2018-01-01

This paper proposes a discrete particle model based on the random-walk theory for simulating cement infiltration within open-cell structures to prevent osteoporotic proximal femur fractures. Model parameters consider the cement viscosity (high and low) and the desired direction of injection (vertical and diagonal). In vitro and in silico characterizations of augmented open-cell structures validated the computational model and quantified the improved mechanical properties (Young's modulus) of the augmented specimens. The cement injection pattern was successfully predicted in all the simulated cases. All the augmented specimens exhibited enhanced mechanical properties computationally and experimentally (maximum improvements of 237.95 ± 12.91% and 246.85 ± 35.57%, respectively). The open-cell structures with high porosity fraction showed a considerable increase in mechanical properties. Cement augmentation in low porosity fraction specimens resulted in a lesser increase in mechanical properties. The results suggest that the proposed discrete particle model is adequate for use as a femoroplasty planning framework.

FDTD-based computed terahertz wave propagation in multilayer medium structures

NASA Astrophysics Data System (ADS)

Tu, Wan-li; Zhong, Shun-cong; Yao, Hai-zi; Shen, Yao-chun

2013-08-01

The terahertz region of the electromagnetic spectrum spans the frequency range of 0.1THz~10THz, which means it sandwiches between the mid-infrared (IR) and the millimeter/ microwave. With the development and commercialization of terahertz pulsed spectroscopy (TPS) and terahertz pulsed imaging (TPI) systems, terahertz technologies have been widely used in the sensing and imaging fields. It allows high quality cross-sectional images from within scattering media to be obtained nondestructively. Characterizing the interaction of terahertz radiation with multilayer medium structures is critical for the development of nondestructive testing technology. Currently, there was much experimental investigation of using TPI for the characterization of terahertz radiation in materials (e.g., pharmaceutical tablet coatings), but there were few theoretical researches on propagation of terahertz radiation in multilayer medium structures. Finite Difference Time Domain (FDTD) algorithm is a proven method for electromagnetic scattering theory, which analyzes continuous electromagnetic problems by employing finite difference and obtains electromagnetic field value at the sampling point to approach the actual continuous solutions. In the present work, we investigated the propagation of terahertz radiation in multilayer medium structures based on FDTD method. The model of multilayer medium structures under the THz frequency plane wave incidence was established, and the reflected radiation properties were recorded and analyzed. The terahertz radiation used was broad-band in the frequency up to 2 THz. A batch of single layer coated pharmaceutical tablets, whose coating thickness in the range of 40~100μm, was computed by FDTD method. We found that the simulation results on pharmaceutical tablet coatings were in good agreement with the experimental results obtained using a commercial system (TPI imaga 2000, TeraView, Cambridge, UK) , demonstrating its usefulness in simulating and analyzing terahertz responses from a multilayered sample.

Reconstructing Past Admixture Processes from Local Genomic Ancestry Using Wavelet Transformation

PubMed Central

Sanderson, Jean; Sudoyo, Herawati; Karafet, Tatiana M.; Hammer, Michael F.; Cox, Murray P.

2015-01-01

Admixture between long-separated populations is a defining feature of the genomes of many species. The mosaic block structure of admixed genomes can provide information about past contact events, including the time and extent of admixture. Here, we describe an improved wavelet-based technique that better characterizes ancestry block structure from observed genomic patterns. principal components analysis is first applied to genomic data to identify the primary population structure, followed by wavelet decomposition to develop a new characterization of local ancestry information along the chromosomes. For testing purposes, this method is applied to human genome-wide genotype data from Indonesia, as well as virtual genetic data generated using genome-scale sequential coalescent simulations under a wide range of admixture scenarios. Time of admixture is inferred using an approximate Bayesian computation framework, providing robust estimates of both admixture times and their associated levels of uncertainty. Crucially, we demonstrate that this revised wavelet approach, which we have released as the R package adwave, provides improved statistical power over existing wavelet-based techniques and can be used to address a broad range of admixture questions. PMID:25852078

The Memory Aid study: protocol for a randomized controlled clinical trial evaluating the effect of computer-based working memory training in elderly patients with mild cognitive impairment (MCI)

PubMed Central

2014-01-01

Background Mild cognitive impairment (MCI) is a condition characterized by memory problems that are more severe than the normal cognitive changes due to aging, but less severe than dementia. Reduced working memory (WM) is regarded as one of the core symptoms of an MCI condition. Recent studies have indicated that WM can be improved through computer-based training. The objective of this study is to evaluate if WM training is effective in improving cognitive function in elderly patients with MCI, and if cognitive training induces structural changes in the white and gray matter of the brain, as assessed by structural MRI. Methods/Designs The proposed study is a blinded, randomized, controlled trail that will include 90 elderly patients diagnosed with MCI at a hospital-based memory clinic. The participants will be randomized to either a training program or a placebo version of the program. The intervention is computerized WM training performed for 45 minutes of 25 sessions over 5 weeks. The placebo version is identical in duration but is non-adaptive in the difficulty level of the tasks. Neuropsychological assessment and structural MRI will be performed before and 1 month after training, and at a 5-month folllow-up. Discussion If computer-based training results in positive changes to memory functions in patients with MCI this may represent a new, cost-effective treatment for MCI. Secondly, evaluation of any training-induced structural changes to gray or white matter will improve the current understanding of the mechanisms behind effective cognitive interventions in patients with MCI. Trial registration ClinicalTrials.gov NCT01991405. November 18, 2013. PMID:24886034

The Memory Aid study: protocol for a randomized controlled clinical trial evaluating the effect of computer-based working memory training in elderly patients with mild cognitive impairment (MCI).

PubMed

Flak, Marianne M; Hernes, Susanne S; Chang, Linda; Ernst, Thomas; Douet, Vanessa; Skranes, Jon; Løhaugen, Gro C C

2014-05-03

Mild cognitive impairment (MCI) is a condition characterized by memory problems that are more severe than the normal cognitive changes due to aging, but less severe than dementia. Reduced working memory (WM) is regarded as one of the core symptoms of an MCI condition. Recent studies have indicated that WM can be improved through computer-based training. The objective of this study is to evaluate if WM training is effective in improving cognitive function in elderly patients with MCI, and if cognitive training induces structural changes in the white and gray matter of the brain, as assessed by structural MRI. The proposed study is a blinded, randomized, controlled trail that will include 90 elderly patients diagnosed with MCI at a hospital-based memory clinic. The participants will be randomized to either a training program or a placebo version of the program. The intervention is computerized WM training performed for 45 minutes of 25 sessions over 5 weeks. The placebo version is identical in duration but is non-adaptive in the difficulty level of the tasks. Neuropsychological assessment and structural MRI will be performed before and 1 month after training, and at a 5-month folllow-up. If computer-based training results in positive changes to memory functions in patients with MCI this may represent a new, cost-effective treatment for MCI. Secondly, evaluation of any training-induced structural changes to gray or white matter will improve the current understanding of the mechanisms behind effective cognitive interventions in patients with MCI. ClinicalTrials.gov NCT01991405. November 18, 2013.

Assembly of Ultra-Dense Nanowire-Based Computing Systems

DTIC Science & Technology

2006-06-30

34* characterized basic device element properties and statistics "* demonstrated product of sums (POS) validating assembled 2-bit adder structures " Demonstrated...linear region (Vds= 10 mV) from the peak g = 3 jiS at IVg -VTI= 0.13 V using the charge control model, representsmore than a factor of 10 improvement over...disrupted by ionizing particles or thermal fluctuation. Further, when working with such small charges, it is statistically possible that logic

Development of a brain MRI-based hidden Markov model for dementia recognition

PubMed Central

2013-01-01

Background Dementia is an age-related cognitive decline which is indicated by an early degeneration of cortical and sub-cortical structures. Characterizing those morphological changes can help to understand the disease development and contribute to disease early prediction and prevention. But modeling that can best capture brain structural variability and can be valid in both disease classification and interpretation is extremely challenging. The current study aimed to establish a computational approach for modeling the magnetic resonance imaging (MRI)-based structural complexity of the brain using the framework of hidden Markov models (HMMs) for dementia recognition. Methods Regularity dimension and semi-variogram were used to extract structural features of the brains, and vector quantization method was applied to convert extracted feature vectors to prototype vectors. The output VQ indices were then utilized to estimate parameters for HMMs. To validate its accuracy and robustness, experiments were carried out on individuals who were characterized as non-demented and mild Alzheimer's diseased. Four HMMs were constructed based on the cohort of non-demented young, middle-aged, elder and demented elder subjects separately. Classification was carried out using a data set including both non-demented and demented individuals with a wide age range. Results The proposed HMMs have succeeded in recognition of individual who has mild Alzheimer's disease and achieved a better classification accuracy compared to other related works using different classifiers. Results have shown the ability of the proposed modeling for recognition of early dementia. Conclusion The findings from this research will allow individual classification to support the early diagnosis and prediction of dementia. By using the brain MRI-based HMMs developed in our proposed research, it will be more efficient, robust and can be easily used by clinicians as a computer-aid tool for validating imaging bio-markers for early prediction of dementia. PMID:24564961

Unveiling Stability Criteria of DNA-Carbon Nanotubes Constructs by Scanning Tunneling Microscopy and Computational Modeling

DOE PAGES

Kilina, Svetlana; Yarotski, Dzmitry A.; Talin, A. Alec; ...

2011-01-01

We present a combined approach that relies on computational simulations and scanning tunneling microscopy (STM) measurements to reveal morphological properties and stability criteria of carbon nanotube-DNA (CNT-DNA) constructs. Application of STM allows direct observation of very stable CNT-DNA hybrid structures with the well-defined DNA wrapping angle of 63.4 ° and a coiling period of 3.3 nm. Using force field simulations, we determine how the DNA-CNT binding energy depends on the sequence and binding geometry of a single strand DNA. This dependence allows us to quantitatively characterize the stability of a hybrid structure with an optimal π-stacking between DNA nucleotides and themore » tube surface and better interpret STM data. Our simulations clearly demonstrate the existence of a very stable DNA binding geometry for (6,5) CNT as evidenced by the presence of a well-defined minimum in the binding energy as a function of an angle between DNA strand and the nanotube chiral vector. This novel approach demonstrates the feasibility of CNT-DNA geometry studies with subnanometer resolution and paves the way towards complete characterization of the structural and electronic properties of drug-delivering systems based on DNA-CNT hybrids as a function of DNA sequence and a nanotube chirality.« less

Lamb wave tomographic imaging system for aircraft structural health assessment

NASA Astrophysics Data System (ADS)

Schwarz, Willi G.; Read, Michael E.; Kremer, Matthew J.; Hinders, Mark K.; Smith, Barry T.

1999-01-01

A tomographic imaging system using ultrasonic Lamb waves for the nondestructive inspection of aircraft components such as wings and fuselage is being developed. The computer-based system provides large-area inspection capability by electronically scanning an array of transducers that can be easily attached to flat and curved surface without moving parts. Images of the inspected area are produced in near real time employing a tomographic reconstruction method adapted from seismological applications. Changes in material properties caused by structural flaws such as disbonds, corrosion, and fatigue cracks can be effectively detected and characterized utilizing this fast NDE technique.

Structure-sequence based analysis for identification of conserved regions in proteins

DOEpatents

Zemla, Adam T; Zhou, Carol E; Lam, Marisa W; Smith, Jason R; Pardes, Elizabeth

2013-05-28

Disclosed are computational methods, and associated hardware and software products for scoring conservation in a protein structure based on a computationally identified family or cluster of protein structures. A method of computationally identifying a family or cluster of protein structures in also disclosed herein.

Characterization of robotics parallel algorithms and mapping onto a reconfigurable SIMD machine

NASA Technical Reports Server (NTRS)

Lee, C. S. G.; Lin, C. T.

1989-01-01

The kinematics, dynamics, Jacobian, and their corresponding inverse computations are six essential problems in the control of robot manipulators. Efficient parallel algorithms for these computations are discussed and analyzed. Their characteristics are identified and a scheme on the mapping of these algorithms to a reconfigurable parallel architecture is presented. Based on the characteristics including type of parallelism, degree of parallelism, uniformity of the operations, fundamental operations, data dependencies, and communication requirement, it is shown that most of the algorithms for robotic computations possess highly regular properties and some common structures, especially the linear recursive structure. Moreover, they are well-suited to be implemented on a single-instruction-stream multiple-data-stream (SIMD) computer with reconfigurable interconnection network. The model of a reconfigurable dual network SIMD machine with internal direct feedback is introduced. A systematic procedure internal direct feedback is introduced. A systematic procedure to map these computations to the proposed machine is presented. A new scheduling problem for SIMD machines is investigated and a heuristic algorithm, called neighborhood scheduling, that reorders the processing sequence of subtasks to reduce the communication time is described. Mapping results of a benchmark algorithm are illustrated and discussed.

Bioprosthetic heart valve heterograft biomaterials: structure, mechanical behavior and computational simulation.

PubMed

Sacks, Michael S; Mirnajafi, Ali; Sun, Wei; Schmidt, Paul

2006-11-01

The present review surveys significant developments in the biomechanical characterization and computational simulation of biologically derived chemically cross-linked soft tissues, or 'heterograft' biomaterials, used in replacement bioprosthetic heart valve (BHV). A survey of mechanical characterization techniques, relevant mechanical properties and computational simulation approaches is presented for both the source tissues and cross-linked biomaterials. Since durability remains the critical problem with current bioprostheses, changes with the mechanical behavior with fatigue are also presented. Moreover, given the complex nature of the mechanical properties of heterograft biomaterials it is not surprising that most constitutive (stress-strain) models, historically used to characterize their behavior, were oversimplified. Simulations of BHV function utilizing these models have inevitably been inaccurate. Thus, more recent finite element simulations utilizing nonlinear constitutive models, which achieve greater model fidelity, are reviewed. An important conclusion of this review is the need for accurate constitutive models, rigorously validated with appropriate experimental data, in order that the design benefits of computational models can be realized. Finally, for at least the coming 20 years, BHVs fabricated from heterograft biomaterials will continue to be extensively used, and will probably remain as the dominant valve design. We should thus recognize that rational, scientifically based approaches to BHV biomaterial development and design can lead to significantly improved BHV, over the coming decades, which can potentially impact millions of patients worldwide with heart valve disease.

Toward high-resolution computational design of the structure and function of helical membrane proteins.

PubMed

Barth, Patrick; Senes, Alessandro

2016-06-07

The computational design of α-helical membrane proteins is still in its infancy but has already made great progress. De novo design allows stable, specific and active minimal oligomeric systems to be obtained. Computational reengineering can improve the stability and function of naturally occurring membrane proteins. Currently, the major hurdle for the field is the experimental characterization of the designs. The emergence of new structural methods for membrane proteins will accelerate progress.

Structural systems pharmacology: a new frontier in discovering novel drug targets.

PubMed

Tan, Hepan; Ge, Xiaoxia; Xie, Lei

2013-08-01

The modern target-based drug discovery process, characterized by the one-drug-one-gene paradigm, has been of limited success. In contrast, phenotype-based screening produces thousands of active compounds but gives no hint as to what their molecular targets are or which ones merit further research. This presents a question: What is a suitable target for an efficient and safe drug? In this paper, we argue that target selection should take into account the proteome-wide energetic and kinetic landscape of drug-target interactions, as well as their cellular and organismal consequences. We propose a new paradigm of structural systems pharmacology to deconvolute the molecular targets of successful drugs as well as to identify druggable targets and their drug-like binders. Here we face two major challenges in structural systems pharmacology: How do we characterize and analyze the structural and energetic origins of drug-target interactions on a proteome scale? How do we correlate the dynamic molecular interactions to their in vivo activity? We will review recent advances in developing new computational tools for biophysics, bioinformatics, chemoinformatics, and systems biology related to the identification of genome-wide target profiles. We believe that the integration of these tools will realize structural systems pharmacology, enabling us to both efficiently develop effective therapeutics for complex diseases and combat drug resistance.

Creating the New from the Old: Combinatorial Libraries Generation with Machine-Learning-Based Compound Structure Optimization.

PubMed

Podlewska, Sabina; Czarnecki, Wojciech M; Kafel, Rafał; Bojarski, Andrzej J

2017-02-27

The growing computational abilities of various tools that are applied in the broadly understood field of computer-aided drug design have led to the extreme popularity of virtual screening in the search for new biologically active compounds. Most often, the source of such molecules consists of commercially available compound databases, but they can also be searched for within the libraries of structures generated in silico from existing ligands. Various computational combinatorial approaches are based solely on the chemical structure of compounds, using different types of substitutions for new molecules formation. In this study, the starting point for combinatorial library generation was the fingerprint referring to the optimal substructural composition in terms of the activity toward a considered target, which was obtained using a machine learning-based optimization procedure. The systematic enumeration of all possible connections between preferred substructures resulted in the formation of target-focused libraries of new potential ligands. The compounds were initially assessed by machine learning methods using a hashed fingerprint to represent molecules; the distribution of their physicochemical properties was also investigated, as well as their synthetic accessibility. The examination of various fingerprints and machine learning algorithms indicated that the Klekota-Roth fingerprint and support vector machine were an optimal combination for such experiments. This study was performed for 8 protein targets, and the obtained compound sets and their characterization are publically available at http://skandal.if-pan.krakow.pl/comb_lib/ .

Robust estimation of fractal measures for characterizing the structural complexity of the human brain: optimization and reproducibility

PubMed Central

Goñi, Joaquín; Sporns, Olaf; Cheng, Hu; Aznárez-Sanado, Maite; Wang, Yang; Josa, Santiago; Arrondo, Gonzalo; Mathews, Vincent P; Hummer, Tom A; Kronenberger, William G; Avena-Koenigsberger, Andrea; Saykin, Andrew J.; Pastor, María A.

2013-01-01

High-resolution isotropic three-dimensional reconstructions of human brain gray and white matter structures can be characterized to quantify aspects of their shape, volume and topological complexity. In particular, methods based on fractal analysis have been applied in neuroimaging studies to quantify the structural complexity of the brain in both healthy and impaired conditions. The usefulness of such measures for characterizing individual differences in brain structure critically depends on their within-subject reproducibility in order to allow the robust detection of between-subject differences. This study analyzes key analytic parameters of three fractal-based methods that rely on the box-counting algorithm with the aim to maximize within-subject reproducibility of the fractal characterizations of different brain objects, including the pial surface, the cortical ribbon volume, the white matter volume and the grey matter/white matter boundary. Two separate datasets originating from different imaging centers were analyzed, comprising, 50 subjects with three and 24 subjects with four successive scanning sessions per subject, respectively. The reproducibility of fractal measures was statistically assessed by computing their intra-class correlations. Results reveal differences between different fractal estimators and allow the identification of several parameters that are critical for high reproducibility. Highest reproducibility with intra-class correlations in the range of 0.9–0.95 is achieved with the correlation dimension. Further analyses of the fractal dimensions of parcellated cortical and subcortical gray matter regions suggest robustly estimated and region-specific patterns of individual variability. These results are valuable for defining appropriate parameter configurations when studying changes in fractal descriptors of human brain structure, for instance in studies of neurological diseases that do not allow repeated measurements or for disease-course longitudinal studies. PMID:23831414

Introducing SONS, a tool for operational taxonomic unit-based comparisons of microbial community memberships and structures.

PubMed

Schloss, Patrick D; Handelsman, Jo

2006-10-01

The recent advent of tools enabling statistical inferences to be drawn from comparisons of microbial communities has enabled the focus of microbial ecology to move from characterizing biodiversity to describing the distribution of that biodiversity. Although statistical tools have been developed to compare community structures across a phylogenetic tree, we lack tools to compare the memberships and structures of two communities at a particular operational taxonomic unit (OTU) definition. Furthermore, current tests of community structure do not indicate the similarity of the communities but only report the probability of a statistical hypothesis. Here we present a computer program, SONS, which implements nonparametric estimators for the fraction and richness of OTUs shared between two communities.

Computational analysis of protein-protein interfaces involving an alpha helix: insights for terphenyl-like molecules binding.

PubMed

Isvoran, Adriana; Craciun, Dana; Martiny, Virginie; Sperandio, Olivier; Miteva, Maria A

2013-06-14

Protein-Protein Interactions (PPIs) are key for many cellular processes. The characterization of PPI interfaces and the prediction of putative ligand binding sites and hot spot residues are essential to design efficient small-molecule modulators of PPI. Terphenyl and its derivatives are small organic molecules known to mimic one face of protein-binding alpha-helical peptides. In this work we focus on several PPIs mediated by alpha-helical peptides. We performed computational sequence- and structure-based analyses in order to evaluate several key physicochemical and surface properties of proteins known to interact with alpha-helical peptides and/or terphenyl and its derivatives. Sequence-based analysis revealed low sequence identity between some of the analyzed proteins binding alpha-helical peptides. Structure-based analysis was performed to calculate the volume, the fractal dimension roughness and the hydrophobicity of the binding regions. Besides the overall hydrophobic character of the binding pockets, some specificities were detected. We showed that the hydrophobicity is not uniformly distributed in different alpha-helix binding pockets that can help to identify key hydrophobic hot spots. The presence of hydrophobic cavities at the protein surface with a more complex shape than the entire protein surface seems to be an important property related to the ability of proteins to bind alpha-helical peptides and low molecular weight mimetics. Characterization of similarities and specificities of PPI binding sites can be helpful for further development of small molecules targeting alpha-helix binding proteins.

[Computational chemistry in structure-based drug design].

PubMed

Cao, Ran; Li, Wei; Sun, Han-Zi; Zhou, Yu; Huang, Niu

2013-07-01

Today, the understanding of the sequence and structure of biologically relevant targets is growing rapidly and researchers from many disciplines, physics and computational science in particular, are making significant contributions to modern biology and drug discovery. However, it remains challenging to rationally design small molecular ligands with desired biological characteristics based on the structural information of the drug targets, which demands more accurate calculation of ligand binding free-energy. With the rapid advances in computer power and extensive efforts in algorithm development, physics-based computational chemistry approaches have played more important roles in structure-based drug design. Here we reviewed the newly developed computational chemistry methods in structure-based drug design as well as the elegant applications, including binding-site druggability assessment, large scale virtual screening of chemical database, and lead compound optimization. Importantly, here we address the current bottlenecks and propose practical solutions.

Self-assembled nanocages based on the coiled coil bundle motif

NASA Astrophysics Data System (ADS)

Sinha, Nairiti; Villegas, Jose; Saven, Jeffery; Kiick, Kristi; Pochan, Darrin

Computational design of coiled coil peptide bundles that undergo solution phase self-assembly presents a diverse toolbox for engineering new materials with tunable and pre-determined nanostructures that can have various end applications such as in drug delivery, biomineralization and electronics. Self-assembled cages are especially advantageous as the cage geometry provides three distinct functional sites: the interior, the exterior and the solvent-cage interface. In this poster, syntheses and characterization of a peptide cage based on computationally designed homotetrameric coiled coil bundles as building blocks is discussed. Techniques such as Transmission Electron Microscopy (TEM), Small-Angle Neutron Scattering (SANS) and Analytical Ultracentrifugation (AUC) are employed to characterize the size, shape and molecular weight of the self-assembled peptide cages under different pH and temperature conditions. Various self-assembly pathways such as dialysis and thermal quenching are shown to have a significant impact on the final structure of these peptides in solution. Comparison of results with the target cage design can be used to iteratively improve the peptide design and provide greater understanding of its interactions and folding.

High-Throughput Characterization of Porous Materials Using Graphics Processing Units

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

Kim, Jihan; Martin, Richard L.; Rübel, Oliver

We have developed a high-throughput graphics processing units (GPU) code that can characterize a large database of crystalline porous materials. In our algorithm, the GPU is utilized to accelerate energy grid calculations where the grid values represent interactions (i.e., Lennard-Jones + Coulomb potentials) between gas molecules (i.e., CHmore » $$_{4}$$ and CO$$_{2}$$) and material's framework atoms. Using a parallel flood fill CPU algorithm, inaccessible regions inside the framework structures are identified and blocked based on their energy profiles. Finally, we compute the Henry coefficients and heats of adsorption through statistical Widom insertion Monte Carlo moves in the domain restricted to the accessible space. The code offers significant speedup over a single core CPU code and allows us to characterize a set of porous materials at least an order of magnitude larger than ones considered in earlier studies. For structures selected from such a prescreening algorithm, full adsorption isotherms can be calculated by conducting multiple grand canonical Monte Carlo simulations concurrently within the GPU.« less

Crystal structure and functional characterization of SF216 from Shigella flexneri.

PubMed

Kim, Ha-Neul; Seok, Seung-Hyeon; Lee, Yoo-Sup; Won, Hyung-Sik; Seo, Min-Duk

2017-11-01

Shigella flexneri is a Gram-negative anaerobic bacterium that causes highly infectious bacterial dysentery in humans. Here, we solved the crystal structure of SF216, a hypothetical protein from the S. flexneri 5a strain M90T, at 1.7 Å resolution. The crystal structure of SF216 represents a homotrimer stabilized by intersubunit interactions and ion-mediated electrostatic interactions. Each subunit consists of three β-strands and five α-helices with the β-β-β-α-α-α-α-α topology. Based on the structural information, we also demonstrate that SF216 shows weak ribonuclease activity by a fluorescence quenching assay. Furthermore, we identify potential druggable pockets (putative hot spots) on the surface of the SF216 structure by computational mapping. © 2017 Federation of European Biochemical Societies.

Computer Simulations of Intrinsically Disordered Proteins

NASA Astrophysics Data System (ADS)

Chong, Song-Ho; Chatterjee, Prathit; Ham, Sihyun

2017-05-01

The investigation of intrinsically disordered proteins (IDPs) is a new frontier in structural and molecular biology that requires a new paradigm to connect structural disorder to function. Molecular dynamics simulations and statistical thermodynamics potentially offer ideal tools for atomic-level characterizations and thermodynamic descriptions of this fascinating class of proteins that will complement experimental studies. However, IDPs display sensitivity to inaccuracies in the underlying molecular mechanics force fields. Thus, achieving an accurate structural characterization of IDPs via simulations is a challenge. It is also daunting to perform a configuration-space integration over heterogeneous structural ensembles sampled by IDPs to extract, in particular, protein configurational entropy. In this review, we summarize recent efforts devoted to the development of force fields and the critical evaluations of their performance when applied to IDPs. We also survey recent advances in computational methods for protein configurational entropy that aim to provide a thermodynamic link between structural disorder and protein activity.

Investigation of progressive failure robustness and alternate load paths for damage tolerant structures

NASA Astrophysics Data System (ADS)

Marhadi, Kun Saptohartyadi

Structural optimization for damage tolerance under various unforeseen damage scenarios is computationally challenging. It couples non-linear progressive failure analysis with sampling-based stochastic analysis of random damage. The goal of this research was to understand the relationship between alternate load paths available in a structure and its damage tolerance, and to use this information to develop computationally efficient methods for designing damage tolerant structures. Progressive failure of a redundant truss structure subjected to small random variability was investigated to identify features that correlate with robustness and predictability of the structure's progressive failure. The identified features were used to develop numerical surrogate measures that permit computationally efficient deterministic optimization to achieve robustness and predictability of progressive failure. Analysis of damage tolerance on designs with robust progressive failure indicated that robustness and predictability of progressive failure do not guarantee damage tolerance. Damage tolerance requires a structure to redistribute its load to alternate load paths. In order to investigate the load distribution characteristics that lead to damage tolerance in structures, designs with varying degrees of damage tolerance were generated using brute force stochastic optimization. A method based on principal component analysis was used to describe load distributions (alternate load paths) in the structures. Results indicate that a structure that can develop alternate paths is not necessarily damage tolerant. The alternate load paths must have a required minimum load capability. Robustness analysis of damage tolerant optimum designs indicates that designs are tailored to specified damage. A design Optimized under one damage specification can be sensitive to other damages not considered. Effectiveness of existing load path definitions and characterizations were investigated for continuum structures. A load path definition using a relative compliance change measure (U* field) was demonstrated to be the most useful measure of load path. This measure provides quantitative information on load path trajectories and qualitative information on the effectiveness of the load path. The use of the U* description of load paths in optimizing structures for effective load paths was investigated.

Three VO2+ complexes of the pyridoxal-derived Schiff bases: Synthesis, experimental and theoretical characterizations, and catalytic activity in a cyclocondensation reaction

NASA Astrophysics Data System (ADS)

Jafari-Moghaddam, Faezeh; Beyramabadi, S. Ali; Khashi, Maryam; Morsali, Ali

2018-02-01

Three oxovanadium(IV) complexes of the pyridoxal Schiff bases have been newly synthesized and characterized. The used Schiff bases were N,N‧-dipyridoxyl(ethylenediamine), N,N‧-dipyridoxyl(1,3-propanediamine) and N,N‧-dipyridoxyl(1,2-benzenediamine). Also, the optimized geometry, assignment of the IR bands and the Natural Bond Orbital (NBO) analysis of the complexes have been computed using the density functional theory (DFT) methods. Dianionic form of the Schiff bases (L2-) acts as a tetradentate N2O2 ligand. The coordinating atoms of the Schiff base are the phenolate oxygens and imine nitrogens, which occupy four base positions of the square-pyramidal geometry of the complexes. The oxo ligand occupies the apical position of the [VO(L)] complexes. In the optimized geometry of the complexes, the coordinated Schiff bases have more planar structure than their free form. Due to the high-energy gaps, all of the complexes are predicted to be stable. Good agreement between the experimental values and the DFT-computed results supports suitability of the optimized geometries for the complexes. The investigated complexes show high catalytic activities in synthesis of the tetrahydrobenzo[b]pyrans through a three-component cyclocondensation reaction of dimedone, malononitrile and some aromatic aldehydes. The complexes catalyzed the reaction in solvent free conditions and the catalysts were found to be reusable.

The Enzyme Function Initiative†

PubMed Central

Gerlt, John A.; Allen, Karen N.; Almo, Steven C.; Armstrong, Richard N.; Babbitt, Patricia C.; Cronan, John E.; Dunaway-Mariano, Debra; Imker, Heidi J.; Jacobson, Matthew P.; Minor, Wladek; Poulter, C. Dale; Raushel, Frank M.; Sali, Andrej; Shoichet, Brian K.; Sweedler, Jonathan V.

2011-01-01

The Enzyme Function Initiative (EFI) was recently established to address the challenge of assigning reliable functions to enzymes discovered in bacterial genome projects; in this Current Topic we review the structure and operations of the EFI. The EFI includes the Superfamily/Genome, Protein, Structure, Computation, and Data/Dissemination Cores that provide the infrastructure for reliably predicting the in vitro functions of unknown enzymes. The initial targets for functional assignment are selected from five functionally diverse superfamilies (amidohydrolase, enolase, glutathione transferase, haloalkanoic acid dehalogenase, and isoprenoid synthase), with five superfamily-specific Bridging Projects experimentally testing the predicted in vitro enzymatic activities. The EFI also includes the Microbiology Core that evaluates the in vivo context of in vitro enzymatic functions and confirms the functional predictions of the EFI. The deliverables of the EFI to the scientific community include: 1) development of a large-scale, multidisciplinary sequence/structure-based strategy for functional assignment of unknown enzymes discovered in genome projects (target selection, protein production, structure determination, computation, experimental enzymology, microbiology, and structure-based annotation); 2) dissemination of the strategy to the community via publications, collaborations, workshops, and symposia; 3) computational and bioinformatic tools for using the strategy; 4) provision of experimental protocols and/or reagents for enzyme production and characterization; and 5) dissemination of data via the EFI’s website, enzymefunction.org. The realization of multidisciplinary strategies for functional assignment will begin to define the full metabolic diversity that exists in nature and will impact basic biochemical and evolutionary understanding, as well as a wide range of applications of central importance to industrial, medicinal and pharmaceutical efforts. PMID:21999478

The Enzyme Function Initiative.

PubMed

Gerlt, John A; Allen, Karen N; Almo, Steven C; Armstrong, Richard N; Babbitt, Patricia C; Cronan, John E; Dunaway-Mariano, Debra; Imker, Heidi J; Jacobson, Matthew P; Minor, Wladek; Poulter, C Dale; Raushel, Frank M; Sali, Andrej; Shoichet, Brian K; Sweedler, Jonathan V

2011-11-22

The Enzyme Function Initiative (EFI) was recently established to address the challenge of assigning reliable functions to enzymes discovered in bacterial genome projects; in this Current Topic, we review the structure and operations of the EFI. The EFI includes the Superfamily/Genome, Protein, Structure, Computation, and Data/Dissemination Cores that provide the infrastructure for reliably predicting the in vitro functions of unknown enzymes. The initial targets for functional assignment are selected from five functionally diverse superfamilies (amidohydrolase, enolase, glutathione transferase, haloalkanoic acid dehalogenase, and isoprenoid synthase), with five superfamily specific Bridging Projects experimentally testing the predicted in vitro enzymatic activities. The EFI also includes the Microbiology Core that evaluates the in vivo context of in vitro enzymatic functions and confirms the functional predictions of the EFI. The deliverables of the EFI to the scientific community include (1) development of a large-scale, multidisciplinary sequence/structure-based strategy for functional assignment of unknown enzymes discovered in genome projects (target selection, protein production, structure determination, computation, experimental enzymology, microbiology, and structure-based annotation), (2) dissemination of the strategy to the community via publications, collaborations, workshops, and symposia, (3) computational and bioinformatic tools for using the strategy, (4) provision of experimental protocols and/or reagents for enzyme production and characterization, and (5) dissemination of data via the EFI's Website, http://enzymefunction.org. The realization of multidisciplinary strategies for functional assignment will begin to define the full metabolic diversity that exists in nature and will impact basic biochemical and evolutionary understanding, as well as a wide range of applications of central importance to industrial, medicinal, and pharmaceutical efforts. © 2011 American Chemical Society

3DNALandscapes: a database for exploring the conformational features of DNA.

PubMed

Zheng, Guohui; Colasanti, Andrew V; Lu, Xiang-Jun; Olson, Wilma K

2010-01-01

3DNALandscapes, located at: http://3DNAscapes.rutgers.edu, is a new database for exploring the conformational features of DNA. In contrast to most structural databases, which archive the Cartesian coordinates and/or derived parameters and images for individual structures, 3DNALandscapes enables searches of conformational information across multiple structures. The database contains a wide variety of structural parameters and molecular images, computed with the 3DNA software package and known to be useful for characterizing and understanding the sequence-dependent spatial arrangements of the DNA sugar-phosphate backbone, sugar-base side groups, base pairs, base-pair steps, groove structure, etc. The data comprise all DNA-containing structures--both free and bound to proteins, drugs and other ligands--currently available in the Protein Data Bank. The web interface allows the user to link, report, plot and analyze this information from numerous perspectives and thereby gain insight into DNA conformation, deformability and interactions in different sequence and structural contexts. The data accumulated from known, well-resolved DNA structures can serve as useful benchmarks for the analysis and simulation of new structures. The collective data can also help to understand how DNA deforms in response to proteins and other molecules and undergoes conformational rearrangements.

Charge transfer complex between 2,3-diaminopyridine with chloranilic acid. Synthesis, characterization and DFT, TD-DFT computational studies

NASA Astrophysics Data System (ADS)

Al-Ahmary, Khairia M.; Habeeb, Moustafa M.; Al-Obidan, Areej H.

2018-05-01

New charge transfer complex (CTC) between the electron donor 2,3-diaminopyridine (DAP) with the electron acceptor chloranilic (CLA) acid has been synthesized and characterized experimentally and theoretically using a variety of physicochemical techniques. The experimental work included the use of elemental analysis, UV-vis, IR and 1H NMR studies to characterize the complex. Electronic spectra have been carried out in different hydrogen bonded solvents, methanol (MeOH), acetonitrile (AN) and 1:1 mixture from AN-MeOH. The molecular composition of the complex was identified to be 1:1 from Jobs and molar ratio methods. The stability constant was determined using minimum-maximum absorbances method where it recorded high values confirming the high stability of the formed complex. The solid complex was prepared and characterized by elemental analysis that confirmed its formation in 1:1 stoichiometric ratio. Both IR and NMR studies asserted the existence of proton and charge transfers in the formed complex. For supporting the experimental results, DFT computations were carried out using B3LYP/6-31G(d,p) method to compute the optimized structures of the reactants and complex, their geometrical parameters, reactivity parameters, molecular electrostatic potential map and frontier molecular orbitals. The analysis of DFT results strongly confirmed the high stability of the formed complex based on existing charge transfer beside proton transfer hydrogen bonding concordant with experimental results. The origin of electronic spectra was analyzed using TD-DFT method where the observed λmax are strongly consisted with the computed ones. TD-DFT showed the contributed states for various electronic transitions.

Thermography Inspection for Early Detection of Composite Damage in Structures During Fatigue Loading

NASA Technical Reports Server (NTRS)

Zalameda, Joseph N.; Burke, Eric R.; Parker, F. Raymond; Seebo, Jeffrey P.; Wright, Christopher W.; Bly, James B.

2012-01-01

Advanced composite structures are commonly tested under controlled loading. Understanding the initiation and progression of composite damage under load is critical for validating design concepts and structural analysis tools. Thermal nondestructive evaluation (NDE) is used to detect and characterize damage in composite structures during fatigue loading. A difference image processing algorithm is demonstrated to enhance damage detection and characterization by removing thermal variations not associated with defects. In addition, a one-dimensional multilayered thermal model is used to characterize damage. Lastly, the thermography results are compared to other inspections such as non-immersion ultrasonic inspections and computed tomography X-ray.

Automatic identification of abstract online groups

DOEpatents

Engel, David W; Gregory, Michelle L; Bell, Eric B; Cowell, Andrew J; Piatt, Andrew W

2014-04-15

Online abstract groups, in which members aren't explicitly connected, can be automatically identified by computer-implemented methods. The methods involve harvesting records from social media and extracting content-based and structure-based features from each record. Each record includes a social-media posting and is associated with one or more entities. Each feature is stored on a data storage device and includes a computer-readable representation of an attribute of one or more records. The methods further involve grouping records into record groups according to the features of each record. Further still the methods involve calculating an n-dimensional surface representing each record group and defining an outlier as a record having feature-based distances measured from every n-dimensional surface that exceed a threshold value. Each of the n-dimensional surfaces is described by a footprint that characterizes the respective record group as an online abstract group.

Analysis of x-ray tomography data of an extruded low density styrenic foam: an image analysis study

NASA Astrophysics Data System (ADS)

Lin, Jui-Ching; Heeschen, William

2016-10-01

Extruded styrenic foams are low density foams that are widely used for thermal insulation. It is difficult to precisely characterize the structure of the cells in low density foams by traditional cross-section viewing due to the frailty of the walls of the cells. X-ray computed tomography (CT) is a non-destructive, three dimensional structure characterization technique that has great potential for structure characterization of styrenic foams. Unfortunately the intrinsic artifacts of the data and the artifacts generated during image reconstruction are often comparable in size and shape to the thin walls of the foam, making robust and reliable analysis of cell sizes challenging. We explored three different image processing methods to clean up artifacts in the reconstructed images, thus allowing quantitative three dimensional determination of cell size in a low density styrenic foam. Three image processing approaches - an intensity based approach, an intensity variance based approach, and a machine learning based approach - are explored in this study, and the machine learning image feature classification method was shown to be the best. Individual cells are segmented within the images after the images were cleaned up using the three different methods and the cell sizes are measured and compared in the study. Although the collected data with the image analysis methods together did not yield enough measurements for a good statistic of the measurement of cell sizes, the problem can be resolved by measuring multiple samples or increasing imaging field of view.

Characterization of Radial Curved Fin Heat Sink under Natural and Forced Convection

NASA Astrophysics Data System (ADS)

Khadke, Rishikesh; Bhole, Kiran

2018-02-01

Heat exchangers are important structures widely used in power plants, food industries, refrigeration, and air conditioners and now widely used in computing systems. Finned type of heat sink is widely used in computing systems. The main aim of the design of the heat sink is to maintain the optimum temperature level. To achieve this goal so many geometrical configurations are implemented. This paper presents a characterization of radially curved fin heat sink under natural and forced convection. Forced convection is studied for the optimization of temperature for better efficiency. The different alternatives in geometry are considered in characterization are heat intensity, the height of the fin and speed of the fan. By recognizing these alternatives the heat sink is characterized by the heat flux usually generated in high-end PCs. The temperature drop characteristics across height and radial direction are presented for the constant heat input and air flow in the heat sink. The effect of dimensionless elevation height (0 ≤ Z* ≤ 1) and Elenbaas Number (0.4 ≤ El ≤ 2.8) of the heat sink were investigated for study of the Nusselt number. Based on experimental characterization, process plan has been developed for the selection of the similar heat sinks for desired output (heat dissipation and temperature distribution).

Deep hierarchies in the primate visual cortex: what can we learn for computer vision?

PubMed

Krüger, Norbert; Janssen, Peter; Kalkan, Sinan; Lappe, Markus; Leonardis, Ales; Piater, Justus; Rodríguez-Sánchez, Antonio J; Wiskott, Laurenz

2013-08-01

Computational modeling of the primate visual system yields insights of potential relevance to some of the challenges that computer vision is facing, such as object recognition and categorization, motion detection and activity recognition, or vision-based navigation and manipulation. This paper reviews some functional principles and structures that are generally thought to underlie the primate visual cortex, and attempts to extract biological principles that could further advance computer vision research. Organized for a computer vision audience, we present functional principles of the processing hierarchies present in the primate visual system considering recent discoveries in neurophysiology. The hierarchical processing in the primate visual system is characterized by a sequence of different levels of processing (on the order of 10) that constitute a deep hierarchy in contrast to the flat vision architectures predominantly used in today's mainstream computer vision. We hope that the functional description of the deep hierarchies realized in the primate visual system provides valuable insights for the design of computer vision algorithms, fostering increasingly productive interaction between biological and computer vision research.

Surface texture and hardness of dental alloys processed by alternative technologies

NASA Astrophysics Data System (ADS)

Porojan, Liliana; Savencu, Cristina E.; Topală, Florin I.; Porojan, Sorin D.

2017-08-01

Technological developments have led to the implementation of novel digitalized manufacturing methods for the production of metallic structures in prosthetic dentistry. These technologies can be classified as based on subtractive manufacturing, assisted by computer-aided design/computer-aided manufacturing (CAD/CAM) systems, or on additive manufacturing (AM), such as the recently developed laser-based methods. The aim of the study was to assess the surface texture and hardness of metallic structures for dental restorations obtained by alternative technologies: conventional casting (CST), computerized milling (MIL), AM power bed fusion methods, respective selective laser melting (SLM) and selective laser sintering (SLS). For the experimental analyses metallic specimens made of Co-Cr dental alloys were prepared as indicated by the manufacturers. The specimen structure at the macro level was observed by an optical microscope and micro-hardness was measured in all substrates. Metallic frameworks obtained by AM are characterized by increased hardness, depending also on the surface processing. The formation of microstructural defects can be better controlled and avoided during SLM and MIL process. Application of power bed fusion techniques, like SLS and SLM, is currently a challenge in dental alloys processing.

Prediction of physical protein protein interactions

NASA Astrophysics Data System (ADS)

Szilágyi, András; Grimm, Vera; Arakaki, Adrián K.; Skolnick, Jeffrey

2005-06-01

Many essential cellular processes such as signal transduction, transport, cellular motion and most regulatory mechanisms are mediated by protein-protein interactions. In recent years, new experimental techniques have been developed to discover the protein-protein interaction networks of several organisms. However, the accuracy and coverage of these techniques have proven to be limited, and computational approaches remain essential both to assist in the design and validation of experimental studies and for the prediction of interaction partners and detailed structures of protein complexes. Here, we provide a critical overview of existing structure-independent and structure-based computational methods. Although these techniques have significantly advanced in the past few years, we find that most of them are still in their infancy. We also provide an overview of experimental techniques for the detection of protein-protein interactions. Although the developments are promising, false positive and false negative results are common, and reliable detection is possible only by taking a consensus of different experimental approaches. The shortcomings of experimental techniques affect both the further development and the fair evaluation of computational prediction methods. For an adequate comparative evaluation of prediction and high-throughput experimental methods, an appropriately large benchmark set of biophysically characterized protein complexes would be needed, but is sorely lacking.

Space-Time Fluid-Structure Interaction Computation of Flapping-Wing Aerodynamics

DTIC Science & Technology

2013-12-01

SST-VMST." The structural mechanics computations are based on the Kirchhoff -Love shell model. We use a sequential coupling technique, which is...mechanics computations are based on the Kirchhoff -Love shell model. We use a sequential coupling technique, which is ap- plicable to some classes of FSI...we use the ST-VMS method in combination with the ST-SUPS method. The structural mechanics computations are mostly based on the Kirchhoff –Love shell

Advances and trends in structural and solid mechanics; Proceedings of the Symposium, Washington, DC, October 4-7, 1982

NASA Technical Reports Server (NTRS)

Noor, A. K. (Editor); Housner, J. M.

1983-01-01

The mechanics of materials and material characterization are considered, taking into account micromechanics, the behavior of steel structures at elevated temperatures, and an anisotropic plasticity model for inelastic multiaxial cyclic deformation. Other topics explored are related to advances and trends in finite element technology, classical analytical techniques and their computer implementation, interactive computing and computational strategies for nonlinear problems, advances and trends in numerical analysis, database management systems and CAD/CAM, space structures and vehicle crashworthiness, beams, plates and fibrous composite structures, design-oriented analysis, artificial intelligence and optimization, contact problems, random waves, and lifetime prediction. Earthquake-resistant structures and other advanced structural applications are also discussed, giving attention to cumulative damage in steel structures subjected to earthquake ground motions, and a mixed domain analysis of nuclear containment structures using impulse functions.

Self-organized perturbations enhance class IV behavior and 1/f power spectrum in elementary cellular automata.

PubMed

Nakajima, Kohei; Haruna, Taichi

2011-09-01

In this paper, we propose a new class of cellular automata based on the modification of its state space. It is introduced to model a computation which is exposed to an environment. We formalized the computation as extension and projection processes of its state space and resulting misidentifications of the state. This is motivated to embed the role of an environment into the system itself, which naturally induces self-organized internal perturbations rather than the usual external perturbations. Implementing this structure into the elementary cellular automata, we characterized its effect by means of input entropy and power spectral analysis. As a result, the cellular automata with this structure showed robust class IV behavior and a 1/f power spectrum in a wide range of rule space comparative to the notion of the edge of chaos. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Structure-guided statistical textural distinctiveness for salient region detection in natural images.

PubMed

Scharfenberger, Christian; Wong, Alexander; Clausi, David A

2015-01-01

We propose a simple yet effective structure-guided statistical textural distinctiveness approach to salient region detection. Our method uses a multilayer approach to analyze the structural and textural characteristics of natural images as important features for salient region detection from a scale point of view. To represent the structural characteristics, we abstract the image using structured image elements and extract rotational-invariant neighborhood-based textural representations to characterize each element by an individual texture pattern. We then learn a set of representative texture atoms for sparse texture modeling and construct a statistical textural distinctiveness matrix to determine the distinctiveness between all representative texture atom pairs in each layer. Finally, we determine saliency maps for each layer based on the occurrence probability of the texture atoms and their respective statistical textural distinctiveness and fuse them to compute a final saliency map. Experimental results using four public data sets and a variety of performance evaluation metrics show that our approach provides promising results when compared with existing salient region detection approaches.

Implications of the effective one-component analysis of pair correlations in colloidal fluids with polydispersity

NASA Astrophysics Data System (ADS)

Pond, Mark J.; Errington, Jeffrey R.; Truskett, Thomas M.

2011-09-01

Partial pair-correlation functions of colloidal suspensions with continuous polydispersity can be challenging to characterize from optical microscopy or computer simulation data due to inadequate sampling. As a result, it is common to adopt an effective one-component description of the structure that ignores the differences between particle types. Unfortunately, whether this kind of simplified description preserves or averages out information important for understanding the behavior of the fluid depends on the degree of polydispersity and can be difficult to assess, especially when the corresponding multicomponent description of the pair correlations is unavailable for comparison. Here, we present a computer simulation study that examines the implications of adopting an effective one-component structural description of a polydisperse fluid. The square-well model that we investigate mimics key aspects of the experimental behavior of suspended colloids with short-range, polymer-mediated attractions. To characterize the partial pair-correlation functions and thermodynamic excess entropy of this system, we introduce a Monte Carlo sampling strategy appropriate for fluids with a large number of pseudo-components. The data from our simulations at high particle concentrations, as well as exact theoretical results for dilute systems, show how qualitatively different trends between structural order and particle attractions emerge from the multicomponent and effective one-component treatments, even with systems characterized by moderate polydispersity. We examine consequences of these differences for excess-entropy based scalings of shear viscosity, and we discuss how use of the multicomponent treatment reveals similarities between the corresponding dynamic scaling behaviors of attractive colloids and liquid water that the effective one-component analysis does not capture.

Proteins of unknown function in the Protein Data Bank (PDB): an inventory of true uncharacterized proteins and computational tools for their analysis.

PubMed

Nadzirin, Nurul; Firdaus-Raih, Mohd

2012-10-08

Proteins of uncharacterized functions form a large part of many of the currently available biological databases and this situation exists even in the Protein Data Bank (PDB). Our analysis of recent PDB data revealed that only 42.53% of PDB entries (1084 coordinate files) that were categorized under "unknown function" are true examples of proteins of unknown function at this point in time. The remainder 1465 entries also annotated as such appear to be able to have their annotations re-assessed, based on the availability of direct functional characterization experiments for the protein itself, or for homologous sequences or structures thus enabling computational function inference.

Requirements for energy based constitutive modeling in tire mechanics

NASA Technical Reports Server (NTRS)

Luchini, John R.; Peters, Jim M.; Mars, Will V.

1995-01-01

The history, requirements, and theoretical basis of a new energy based constitutive model for (rubber) material elasticity, hysteresis, and failure are presented. Energy based elasticity is handled by many constitutive models, both in one dimension and in three dimensions. Conversion of mechanical energy to heat can be modeled with viscoelasticity or as structural hysteresis. We are seeking unification of elasticity, hysteresis, and failure mechanisms such as fatigue and wear. An energy state characterization for failure criteria of (rubber) materials may provide this unification and also help explain the interaction of temperature effects with failure mechanisms which are described as creation of growth of internal crack surface. Improved structural modeling of tires with FEM should result from such a unified constitutive theory. The theory will also guide experimental work and should enable better interpretation of the results of computational stress analyses.

Computationally efficient characterization of potential energy surfaces based on fingerprint distances

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

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

2016-07-21

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

Challenges in structural approaches to cell modeling

PubMed Central

Im, Wonpil; Liang, Jie; Olson, Arthur; Zhou, Huan-Xiang; Vajda, Sandor; Vakser, Ilya A.

2016-01-01

Computational modeling is essential for structural characterization of biomolecular mechanisms across the broad spectrum of scales. Adequate understanding of biomolecular mechanisms inherently involves our ability to model them. Structural modeling of individual biomolecules and their interactions has been rapidly progressing. However, in terms of the broader picture, the focus is shifting toward larger systems, up to the level of a cell. Such modeling involves a more dynamic and realistic representation of the interactomes in vivo, in a crowded cellular environment, as well as membranes and membrane proteins, and other cellular components. Structural modeling of a cell complements computational approaches to cellular mechanisms based on differential equations, graph models, and other techniques to model biological networks, imaging data, etc. Structural modeling along with other computational and experimental approaches will provide a fundamental understanding of life at the molecular level and lead to important applications to biology and medicine. A cross section of diverse approaches presented in this review illustrates the developing shift from the structural modeling of individual molecules to that of cell biology. Studies in several related areas are covered: biological networks; automated construction of three-dimensional cell models using experimental data; modeling of protein complexes; prediction of non-specific and transient protein interactions; thermodynamic and kinetic effects of crowding; cellular membrane modeling; and modeling of chromosomes. The review presents an expert opinion on the current state-of-the-art in these various aspects of structural modeling in cellular biology, and the prospects of future developments in this emerging field. PMID:27255863

A semi-automatic framework of measuring pulmonary arterial metrics at anatomic airway locations using CT imaging

NASA Astrophysics Data System (ADS)

Jin, Dakai; Guo, Junfeng; Dougherty, Timothy M.; Iyer, Krishna S.; Hoffman, Eric A.; Saha, Punam K.

2016-03-01

Pulmonary vascular dysfunction has been implicated in smoking-related susceptibility to emphysema. With the growing interest in characterizing arterial morphology for early evaluation of the vascular role in pulmonary diseases, there is an increasing need for the standardization of a framework for arterial morphological assessment at airway segmental levels. In this paper, we present an effective and robust semi-automatic framework to segment pulmonary arteries at different anatomic airway branches and measure their cross-sectional area (CSA). The method starts with user-specified endpoints of a target arterial segment through a custom-built graphical user interface. It then automatically detect the centerline joining the endpoints, determines the local structure orientation and computes the CSA along the centerline after filtering out the adjacent pulmonary structures, such as veins or airway walls. Several new techniques are presented, including collision-impact based cost function for centerline detection, radial sample-line based CSA computation, and outlier analysis of radial distance to subtract adjacent neighboring structures in the CSA measurement. The method was applied to repeat-scan pulmonary multirow detector CT (MDCT) images from ten healthy subjects (age: 21-48 Yrs, mean: 28.5 Yrs; 7 female) at functional residual capacity (FRC). The reproducibility of computed arterial CSA from four airway segmental regions in middle and lower lobes was analyzed. The overall repeat-scan intra-class correlation (ICC) of the computed CSA from all four airway regions in ten subjects was 96% with maximum ICC found at LB10 and RB4 regions.

Rapid insights from remote sensing in the geosciences

NASA Astrophysics Data System (ADS)

Plaza, Antonio

2015-03-01

The growing availability of capacity computing for atomistic materials modeling has encouraged the use of high-accuracy computationally intensive interatomic potentials, such as SNAP. These potentials also happen to scale well on petascale computing platforms. SNAP has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected on to a basis of hyperspherical harmonics in four dimensions. The computational cost per atom is much greater than that of simpler potentials such as Lennard-Jones or EAM, while the communication cost remains modest. We discuss a variety of strategies for implementing SNAP in the LAMMPS molecular dynamics package. We present scaling results obtained running SNAP on three different classes of machine: a conventional Intel Xeon CPU cluster; the Titan GPU-based system; and the combined Sequoia and Vulcan BlueGene/Q. The growing availability of capacity computing for atomistic materials modeling has encouraged the use of high-accuracy computationally intensive interatomic potentials, such as SNAP. These potentials also happen to scale well on petascale computing platforms. SNAP has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected on to a basis of hyperspherical harmonics in four dimensions. The computational cost per atom is much greater than that of simpler potentials such as Lennard-Jones or EAM, while the communication cost remains modest. We discuss a variety of strategies for implementing SNAP in the LAMMPS molecular dynamics package. We present scaling results obtained running SNAP on three different classes of machine: a conventional Intel Xeon CPU cluster; the Titan GPU-based system; and the combined Sequoia and Vulcan BlueGene/Q. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corp., for the U.S. Dept. of Energy's National Nuclear Security Admin. under Contract DE-AC04-94AL85000.

Composition-based classification of short metagenomic sequences elucidates the landscapes of taxonomic and functional enrichment of microorganisms

PubMed Central

Liu, Jiemeng; Wang, Haifeng; Yang, Hongxing; Zhang, Yizhe; Wang, Jinfeng; Zhao, Fangqing; Qi, Ji

2013-01-01

Compared with traditional algorithms for long metagenomic sequence classification, characterizing microorganisms’ taxonomic and functional abundance based on tens of millions of very short reads are much more challenging. We describe an efficient composition and phylogeny-based algorithm [Metagenome Composition Vector (MetaCV)] to classify very short metagenomic reads (75–100 bp) into specific taxonomic and functional groups. We applied MetaCV to the Meta-HIT data (371-Gb 75-bp reads of 109 human gut metagenomes), and this single-read-based, instead of assembly-based, classification has a high resolution to characterize the composition and structure of human gut microbiota, especially for low abundance species. Most strikingly, it only took MetaCV 10 days to do all the computation work on a server with five 24-core nodes. To our knowledge, MetaCV, benefited from the strategy of composition comparison, is the first algorithm that can classify millions of very short reads within affordable time. PMID:22941634

Image-based metrology of porous tissue engineering scaffolds

NASA Astrophysics Data System (ADS)

Rajagopalan, Srinivasan; Robb, Richard A.

2006-03-01

Tissue engineering is an interdisciplinary effort aimed at the repair and regeneration of biological tissues through the application and control of cells, porous scaffolds and growth factors. The regeneration of specific tissues guided by tissue analogous substrates is dependent on diverse scaffold architectural indices that can be derived quantitatively from the microCT and microMR images of the scaffolds. However, the randomness of pore-solid distributions in conventional stochastic scaffolds presents unique computational challenges. As a result, image-based characterization of scaffolds has been predominantly qualitative. In this paper, we discuss quantitative image-based techniques that can be used to compute the metrological indices of porous tissue engineering scaffolds. While bulk averaged quantities such as porosity and surface are derived directly from the optimal pore-solid delineations, the spatially distributed geometric indices are derived from the medial axis representations of the pore network. The computational framework proposed (to the best of our knowledge for the first time in tissue engineering) in this paper might have profound implications towards unraveling the symbiotic structure-function relationship of porous tissue engineering scaffolds.

An azodye-rhodamine-based fluorescent and colorimetric probe specific for the detection of Pd(2+) in aqueous ethanolic solution: synthesis, XRD characterization, computational studies and imaging in live cells.

PubMed

Mahapatra, Ajit Kumar; Manna, Saikat Kumar; Maiti, Kalipada; Mondal, Sanchita; Maji, Rajkishor; Mandal, Debasish; Mandal, Sukhendu; Uddin, Md Raihan; Goswami, Shyamaprosad; Quah, Ching Kheng; Fun, Hoong-Kun

2015-02-21

Azodye-rhodamine hybrid colorimetric fluorescent probe (L) has been designed and synthesized. The structure of L has been established based on single crystal XRD. It has been shown to act as a selective turn-on fluorescent chemosensor for Pd(2+) with >40 fold enhancement by exhibiting red emission among the other 27 cations studied in aqueous ethanol. The coordination features of the species of recognition have been computationally evaluated by DFT methods and found to have a distorted tetrahedral Pd(2+) center in the binding core. The probe (L) has been shown to detect Pd up to 0.45 μM at pH 7.4. Furthermore, the probe can be used to image Pd(2+) in living cells.

Ultrasonic characterization of the fiber-matrix interfacial bond in aerospace composites.

PubMed

Aggelis, D G; Kleitsa, D; Matikas, T E

2013-01-01

The properties of advanced composites rely on the quality of the fiber-matrix bonding. Service-induced damage results in deterioration of bonding quality, seriously compromising the load-bearing capacity of the structure. While traditional methods to assess bonding are destructive, herein a nondestructive methodology based on shear wave reflection is numerically investigated. Reflection relies on the bonding quality and results in discernable changes in the received waveform. The key element is the "interphase" model material with varying stiffness. The study is an example of how computational methods enhance the understanding of delicate features concerning the nondestructive evaluation of materials used in advanced structures.

Online social activity reflects economic status

NASA Astrophysics Data System (ADS)

Liu, Jin-Hu; Wang, Jun; Shao, Junming; Zhou, Tao

2016-09-01

To characterize economic development and diagnose the economic health condition, several popular indices such as gross domestic product (GDP), industrial structure and income growth are widely applied. However, computing these indices based on traditional economic census is usually costly and resources consuming, and more importantly, following a long time delay. In this paper, we analyzed nearly 200 million users' activities for four consecutive years in the largest social network (Sina Microblog) in China, aiming at exploring latent relationships between the online social activities and local economic status. Results indicate that online social activity has a strong correlation with local economic development and industrial structure, and more interestingly, allows revealing the macro-economic structure instantaneously with nearly no cost. Beyond, this work also provides a new venue to identify risky signal in local economic structure.

Density Functional Theory Investigations of D-A-D' Structural Molecules as Donor Materials in Organic Solar Cell.

PubMed

Chen, Junxian; Liu, Qingyu; Li, Hao; Zhao, Zhigang; Lu, Zhiyun; Huang, Yan; Xu, Dingguo

2018-01-01

Squaraine core based small molecules in bulk heterojunction organic solar cells have received extensive attentions due to their distinguished photochemical properties in far red and infrared domain. In this paper, combining theoretical simulations and experimental syntheses and characterizations, three major factors (fill factor, short circuit and open-cirvuit voltage) have been carried out together to achieve improvement of power conversion efficiencies of solar cells. As model material systems with D-A-D' framework, two asymmetric squaraines (CNSQ and CCSQ-Tol) as donor materials in bulk heterojunction organic solar cell were synthesized and characterized. Intensive density functional theory computations were applied to identify some direct connections between three factors and corresponding molecular structural properties. It then helps us to predict one new molecule of CCSQ'-Ox that matches all the requirements to improve the power conversion efficiency.

Harmony of computational quantum chemistry and experimental chemistry: Comprehensive DFT studies, microsynthesis, and characterization of mustard gas polysulfide analogues

NASA Astrophysics Data System (ADS)

Saeidian, Hamid; Faraz, Sajjad Mousavi; Mirjafary, Zohreh; Babri, Mehran

2018-05-01

After microsynthesis, structures of mustard gas polysulfide analogues were characterized using electron impact (EI) mass spectrometry. General EI fragmentation pathways for such compounds are proposed. The structure of sulfur mustard (HD) and its two other polysulfide analogues have been examined through B3LYP/6-311++G(2d, 2p) calculations. Geometrical analysis of HD shows that the calculated bond distances are satisfactorily comparable with experimental results. Calculated NMR chemical shifts for HD also were compared with experimental data, indicating good agreement both for 1H and 13C atoms. The vibrational frequencies of HD and polysulfide analogues have been precisely assigned. At the end, based on visual inspection of lowest unoccupied molecular orbitals and the relative difference in the total energies of their episulfonium ions, relative reactivity of HD and its polysulfide analogues were investigated.

Galerkin finite element scheme for magnetostrictive structures and composites

NASA Astrophysics Data System (ADS)

Kannan, Kidambi Srinivasan

The ever increasing-role of magnetostrictives in actuation and sensing applications is an indication of their importance in the emerging field of smart structures technology. As newer, and more complex, applications are developed, there is a growing need for a reliable computational tool that can effectively address the magneto-mechanical interactions and other nonlinearities in these materials and in structures incorporating them. This thesis presents a continuum level quasi-static, three-dimensional finite element computational scheme for modeling the nonlinear behavior of bulk magnetostrictive materials and particulate magnetostrictive composites. Models for magnetostriction must deal with two sources of nonlinearities-nonlinear body forces/moments in equilibrium equations governing magneto-mechanical interactions in deformable and magnetized bodies; and nonlinear coupled magneto-mechanical constitutive models for the material of interest. In the present work, classical differential formulations for nonlinear magneto-mechanical interactions are recast in integral form using the weighted-residual method. A discretized finite element form is obtained by applying the Galerkin technique. The finite element formulation is based upon three dimensional eight-noded (isoparametric) brick element interpolation functions and magnetostatic infinite elements at the boundary. Two alternative possibilities are explored for establishing the nonlinear incremental constitutive model-characterization in terms of magnetic field or in terms of magnetization. The former methodology is the one most commonly used in the literature. In this work, a detailed comparative study of both methodologies is carried out. The computational scheme is validated, qualitatively and quantitatively, against experimental measurements published in the literature on structures incorporating the magnetostrictive material Terfenol-D. The influence of nonlinear body forces and body moments of magnetic origin, on the response of magnetostrictive structures to complex mechanical and magnetic loading conditions, is carefully examined. While monolithic magnetostrictive materials have been commercially-available since the late eighties, attention in the smart structures research community has recently focussed upon building and using magnetostrictive particulate composite structures for conventional actuation applications and novel sensing methodologies in structural health monitoring. A particulate magnetostrictive composite element has been developed in the present work to model such structures. This composite element incorporates interactions between magnetostrictive particles by combining a numerical micromechanical analysis based on magneto-mechanical Green's functions, with a homogenization scheme based upon the Mori-Tanaka approach. This element has been applied to the simulation of particulate actuators and sensors reported in the literature. Simulation results are compared to experimental data for validation purposes. The computational schemes developed, for bulk materials and for composites, are expected to be of great value to researchers and designers of novel applications based on magnetostrictives.

Characterization of Unsteady Flow Structures Around Tandem Cylinders for Component Interaction Studies in Airframe Noise

NASA Technical Reports Server (NTRS)

Jenkins, Luther N.; Khorrami, Mehdi R.; Choudhari, Meelan M.; McGinley, Catherine B.

2005-01-01

A joint computational and experimental study has been performed at NASA Langley Research Center to investigate the unsteady flow generated by the components of an aircraft landing gear system. Because the flow field surrounding a full landing gear is so complex, the study was conducted on a simplified geometry consisting of two cylinders in tandem arrangement to isolate and characterize the pertinent flow phenomena. This paper focuses on the experimental effort where surface pressures, 2-D Particle Image Velocimetry, and hot-wire anemometry were used to document the flow interaction around the two cylinders at a Reynolds Number of 1.66 x 10(exp 5), based on cylinder diameter, and cylinder spacing-todiameter ratios, L/D, of 1.435 and 3.70. Transition strips were applied to the forward cylinder to produce a turbulent boundary layer upstream of the flow separation. For these flow conditions and L/D ratios, surface pressures on both the forward and rear cylinders show the effects of L/D on flow symmetry, base pressure, and the location of flow separation and attachment. Mean velocities and instantaneous vorticity obtained from the PIV data are used to examine the flow structure between and aft of the cylinders. Shedding frequencies and spectra obtained using hot-wire anemometry are presented. These results are compared with unsteady, Reynolds-Averaged Navier-Stokes (URANS) computations for the same configuration in a companion paper by Khorrami, Choudhari, Jenkins, and McGinley (2005). The experimental dataset produced in this study provides information to better understand the mechanisms associated with component interaction noise, develop and validate time-accurate computer methods used to calculate the unsteady flow field, and assist in modeling of the radiated noise from landing gears.

Simplified Models for Accelerated Structural Prediction of Conjugated Semiconducting Polymers

DOE PAGES

Henry, Michael M.; Jones, Matthew L.; Oosterhout, Stefan D.; ...

2017-11-08

We perform molecular dynamics simulations of poly(benzodithiophene-thienopyrrolodione) (BDT-TPD) oligomers in order to evaluate the accuracy with which unoptimized molecular models can predict experimentally characterized morphologies. The predicted morphologies are characterized using simulated grazing-incidence X-ray scattering (GIXS) and compared to the experimental scattering patterns. We find that approximating the aromatic rings in BDT-TPD with rigid bodies, rather than combinations of bond, angle, and dihedral constraints, results in 14% lower computational cost and provides nearly equivalent structural predictions compared to the flexible model case. The predicted glass transition temperature of BDT-TPD (410 +/- 32 K) is found to be in agreement withmore » experiments. Predicted morphologies demonstrate short-range structural order due to stacking of the chain backbones (p-p stacking around 3.9 A), and long-range spatial correlations due to the self-organization of backbone stacks into 'ribbons' (lamellar ordering around 20.9 A), representing the best-to-date computational predictions of structure of complex conjugated oligomers. We find that expensive simulated annealing schedules are not needed to predict experimental structures here, with instantaneous quenches providing nearly equivalent predictions at a fraction of the computational cost of annealing. We therefore suggest utilizing rigid bodies and fast cooling schedules for high-throughput screening studies of semiflexible polymers and oligomers to utilize their significant computational benefits where appropriate.« less

Simplified Models for Accelerated Structural Prediction of Conjugated Semiconducting Polymers

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

Henry, Michael M.; Jones, Matthew L.; Oosterhout, Stefan D.

We perform molecular dynamics simulations of poly(benzodithiophene-thienopyrrolodione) (BDT-TPD) oligomers in order to evaluate the accuracy with which unoptimized molecular models can predict experimentally characterized morphologies. The predicted morphologies are characterized using simulated grazing-incidence X-ray scattering (GIXS) and compared to the experimental scattering patterns. We find that approximating the aromatic rings in BDT-TPD with rigid bodies, rather than combinations of bond, angle, and dihedral constraints, results in 14% lower computational cost and provides nearly equivalent structural predictions compared to the flexible model case. The predicted glass transition temperature of BDT-TPD (410 +/- 32 K) is found to be in agreement withmore » experiments. Predicted morphologies demonstrate short-range structural order due to stacking of the chain backbones (p-p stacking around 3.9 A), and long-range spatial correlations due to the self-organization of backbone stacks into 'ribbons' (lamellar ordering around 20.9 A), representing the best-to-date computational predictions of structure of complex conjugated oligomers. We find that expensive simulated annealing schedules are not needed to predict experimental structures here, with instantaneous quenches providing nearly equivalent predictions at a fraction of the computational cost of annealing. We therefore suggest utilizing rigid bodies and fast cooling schedules for high-throughput screening studies of semiflexible polymers and oligomers to utilize their significant computational benefits where appropriate.« less

KFC Server: interactive forecasting of protein interaction hot spots.

PubMed

Darnell, Steven J; LeGault, Laura; Mitchell, Julie C

2008-07-01

The KFC Server is a web-based implementation of the KFC (Knowledge-based FADE and Contacts) model-a machine learning approach for the prediction of binding hot spots, or the subset of residues that account for most of a protein interface's; binding free energy. The server facilitates the automated analysis of a user submitted protein-protein or protein-DNA interface and the visualization of its hot spot predictions. For each residue in the interface, the KFC Server characterizes its local structural environment, compares that environment to the environments of experimentally determined hot spots and predicts if the interface residue is a hot spot. After the computational analysis, the user can visualize the results using an interactive job viewer able to quickly highlight predicted hot spots and surrounding structural features within the protein structure. The KFC Server is accessible at http://kfc.mitchell-lab.org.

KFC Server: interactive forecasting of protein interaction hot spots

PubMed Central

Darnell, Steven J.; LeGault, Laura; Mitchell, Julie C.

2008-01-01

The KFC Server is a web-based implementation of the KFC (Knowledge-based FADE and Contacts) model—a machine learning approach for the prediction of binding hot spots, or the subset of residues that account for most of a protein interface's; binding free energy. The server facilitates the automated analysis of a user submitted protein–protein or protein–DNA interface and the visualization of its hot spot predictions. For each residue in the interface, the KFC Server characterizes its local structural environment, compares that environment to the environments of experimentally determined hot spots and predicts if the interface residue is a hot spot. After the computational analysis, the user can visualize the results using an interactive job viewer able to quickly highlight predicted hot spots and surrounding structural features within the protein structure. The KFC Server is accessible at http://kfc.mitchell-lab.org. PMID:18539611

Exploratory Item Classification Via Spectral Graph Clustering

PubMed Central

Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Xu, Gongjun; Ying, Zhiliang

2017-01-01

Large-scale assessments are supported by a large item pool. An important task in test development is to assign items into scales that measure different characteristics of individuals, and a popular approach is cluster analysis of items. Classical methods in cluster analysis, such as the hierarchical clustering, K-means method, and latent-class analysis, often induce a high computational overhead and have difficulty handling missing data, especially in the presence of high-dimensional responses. In this article, the authors propose a spectral clustering algorithm for exploratory item cluster analysis. The method is computationally efficient, effective for data with missing or incomplete responses, easy to implement, and often outperforms traditional clustering algorithms in the context of high dimensionality. The spectral clustering algorithm is based on graph theory, a branch of mathematics that studies the properties of graphs. The algorithm first constructs a graph of items, characterizing the similarity structure among items. It then extracts item clusters based on the graphical structure, grouping similar items together. The proposed method is evaluated through simulations and an application to the revised Eysenck Personality Questionnaire. PMID:29033476

A Factor Graph Approach to Automated GO Annotation

PubMed Central

Spetale, Flavio E.; Tapia, Elizabeth; Krsticevic, Flavia; Roda, Fernando; Bulacio, Pilar

2016-01-01

As volume of genomic data grows, computational methods become essential for providing a first glimpse onto gene annotations. Automated Gene Ontology (GO) annotation methods based on hierarchical ensemble classification techniques are particularly interesting when interpretability of annotation results is a main concern. In these methods, raw GO-term predictions computed by base binary classifiers are leveraged by checking the consistency of predefined GO relationships. Both formal leveraging strategies, with main focus on annotation precision, and heuristic alternatives, with main focus on scalability issues, have been described in literature. In this contribution, a factor graph approach to the hierarchical ensemble formulation of the automated GO annotation problem is presented. In this formal framework, a core factor graph is first built based on the GO structure and then enriched to take into account the noisy nature of GO-term predictions. Hence, starting from raw GO-term predictions, an iterative message passing algorithm between nodes of the factor graph is used to compute marginal probabilities of target GO-terms. Evaluations on Saccharomyces cerevisiae, Arabidopsis thaliana and Drosophila melanogaster protein sequences from the GO Molecular Function domain showed significant improvements over competing approaches, even when protein sequences were naively characterized by their physicochemical and secondary structure properties or when loose noisy annotation datasets were considered. Based on these promising results and using Arabidopsis thaliana annotation data, we extend our approach to the identification of most promising molecular function annotations for a set of proteins of unknown function in Solanum lycopersicum. PMID:26771463

A Factor Graph Approach to Automated GO Annotation.

PubMed

Spetale, Flavio E; Tapia, Elizabeth; Krsticevic, Flavia; Roda, Fernando; Bulacio, Pilar

2016-01-01

As volume of genomic data grows, computational methods become essential for providing a first glimpse onto gene annotations. Automated Gene Ontology (GO) annotation methods based on hierarchical ensemble classification techniques are particularly interesting when interpretability of annotation results is a main concern. In these methods, raw GO-term predictions computed by base binary classifiers are leveraged by checking the consistency of predefined GO relationships. Both formal leveraging strategies, with main focus on annotation precision, and heuristic alternatives, with main focus on scalability issues, have been described in literature. In this contribution, a factor graph approach to the hierarchical ensemble formulation of the automated GO annotation problem is presented. In this formal framework, a core factor graph is first built based on the GO structure and then enriched to take into account the noisy nature of GO-term predictions. Hence, starting from raw GO-term predictions, an iterative message passing algorithm between nodes of the factor graph is used to compute marginal probabilities of target GO-terms. Evaluations on Saccharomyces cerevisiae, Arabidopsis thaliana and Drosophila melanogaster protein sequences from the GO Molecular Function domain showed significant improvements over competing approaches, even when protein sequences were naively characterized by their physicochemical and secondary structure properties or when loose noisy annotation datasets were considered. Based on these promising results and using Arabidopsis thaliana annotation data, we extend our approach to the identification of most promising molecular function annotations for a set of proteins of unknown function in Solanum lycopersicum.

Ice water path estimation and characterization using passive microwave radiometry

NASA Technical Reports Server (NTRS)

Vivekanandan, J.; Turk, J.; Bringi, V. N.

1991-01-01

Model computations of top-of-atmospheric microwave brightness temperatures T(B) from layers of precipitation-sized ice of variable bulk density and ice water content (IWC) are presented. It is shown that the 85-GHz T(B) depends essentially on the ice optical thickness. The results demonstrate the potential usefulness of scattering-based channels for characterizing the ice phase and suggest a top-down methodology for retrieval of cloud vertical structure and precipitation estimation from multifrequency passive microwave measurements. Attention is also given to radiative transfer model results based on the multiparameter radar data initialization from the Cooperative Huntsville Meteorological Experiment (COHMEX) in northern Alabama. It is shown that brightness temperature warming effects due to the inclusion of a cloud liquid water profile are especially significant at 85 GHz during later stages of cloud evolution.

Computationally Guided Design of Polymer Electrolytes for Battery Applications

NASA Astrophysics Data System (ADS)

Wang, Zhen-Gang; Webb, Michael; Savoie, Brett; Miller, Thomas

We develop an efficient computational framework for guiding the design of polymer electrolytes for Li battery applications. Short-times molecular dynamics (MD) simulations are employed to identify key structural and dynamic features in the solvation and motion of Li ions, such as the structure of the solvation shells, the spatial distribution of solvation sites, and the polymer segmental mobility. Comparative studies on six polyester-based polymers and polyethylene oxide (PEO) yield good agreement with experimental data on the ion conductivities, and reveal significant differences in the ion diffusion mechanism between PEO and the polyesters. The molecular insights from the MD simulations are used to build a chemically specific coarse-grained model in the spirit of the dynamic bond percolation model of Druger, Ratner and Nitzan. We apply this coarse-grained model to characterize Li ion diffusion in several existing and yet-to-be synthesized polyethers that differ by oxygen content and backbone stiffness. Good agreement is obtained between the predictions of the coarse-grained model and long-timescale atomistic MD simulations, thus providing validation of the model. Our study predicts higher Li ion diffusivity in poly(trimethylene oxide-alt-ethylene oxide) than in PEO. These results demonstrate the potential of this computational framework for rapid screening of new polymer electrolytes based on ion diffusivity.

Joint probabilistic determination of earthquake location and velocity structure: application to local and regional events

NASA Astrophysics Data System (ADS)

Beucler, E.; Haugmard, M.; Mocquet, A.

2016-12-01

The most widely used inversion schemes to locate earthquakes are based on iterative linearized least-squares algorithms and using an a priori knowledge of the propagation medium. When a small amount of observations is available for moderate events for instance, these methods may lead to large trade-offs between outputs and both the velocity model and the initial set of hypocentral parameters. We present a joint structure-source determination approach using Bayesian inferences. Monte-Carlo continuous samplings, using Markov chains, generate models within a broad range of parameters, distributed according to the unknown posterior distributions. The non-linear exploration of both the seismic structure (velocity and thickness) and the source parameters relies on a fast forward problem using 1-D travel time computations. The a posteriori covariances between parameters (hypocentre depth, origin time and seismic structure among others) are computed and explicitly documented. This method manages to decrease the influence of the surrounding seismic network geometry (sparse and/or azimuthally inhomogeneous) and a too constrained velocity structure by inferring realistic distributions on hypocentral parameters. Our algorithm is successfully used to accurately locate events of the Armorican Massif (western France), which is characterized by moderate and apparently diffuse local seismicity.

Joint representation of consistent structural and functional profiles for identification of common cortical landmarks.

PubMed

Zhang, Shu; Zhao, Yu; Jiang, Xi; Shen, Dinggang; Liu, Tianming

2018-06-01

In the brain mapping field, there have been significant interests in representation of structural/functional profiles to establish structural/functional landmark correspondences across individuals and populations. For example, from the structural perspective, our previous studies have identified hundreds of consistent DICCCOL (dense individualized and common connectivity-based cortical landmarks) landmarks across individuals and populations, each of which possess consistent DTI-derived fiber connection patterns. From the functional perspective, a large collection of well-characterized HAFNI (holistic atlases of functional networks and interactions) networks based on sparse representation of whole-brain fMRI signals have been identified in our prior studies. However, due to the remarkable variability of structural and functional architectures in the human brain, it is challenging for earlier studies to jointly represent the connectome-scale structural and functional profiles for establishing a common cortical architecture which can comprehensively encode both structural and functional characteristics across individuals. To address this challenge, we propose an effective computational framework to jointly represent the structural and functional profiles for identification of consistent and common cortical landmarks with both structural and functional correspondences across different brains based on DTI and fMRI data. Experimental results demonstrate that 55 structurally and functionally common cortical landmarks can be successfully identified.

Computational Methods in Drug Discovery

PubMed Central

Sliwoski, Gregory; Kothiwale, Sandeepkumar; Meiler, Jens

2014-01-01

Computer-aided drug discovery/design methods have played a major role in the development of therapeutically important small molecules for over three decades. These methods are broadly classified as either structure-based or ligand-based methods. Structure-based methods are in principle analogous to high-throughput screening in that both target and ligand structure information is imperative. Structure-based approaches include ligand docking, pharmacophore, and ligand design methods. The article discusses theory behind the most important methods and recent successful applications. Ligand-based methods use only ligand information for predicting activity depending on its similarity/dissimilarity to previously known active ligands. We review widely used ligand-based methods such as ligand-based pharmacophores, molecular descriptors, and quantitative structure-activity relationships. In addition, important tools such as target/ligand data bases, homology modeling, ligand fingerprint methods, etc., necessary for successful implementation of various computer-aided drug discovery/design methods in a drug discovery campaign are discussed. Finally, computational methods for toxicity prediction and optimization for favorable physiologic properties are discussed with successful examples from literature. PMID:24381236

Advancing multiscale structural mapping of the brain through fluorescence imaging and analysis across length scales

PubMed Central

Hogstrom, L. J.; Guo, S. M.; Murugadoss, K.; Bathe, M.

2016-01-01

Brain function emerges from hierarchical neuronal structure that spans orders of magnitude in length scale, from the nanometre-scale organization of synaptic proteins to the macroscopic wiring of neuronal circuits. Because the synaptic electrochemical signal transmission that drives brain function ultimately relies on the organization of neuronal circuits, understanding brain function requires an understanding of the principles that determine hierarchical neuronal structure in living or intact organisms. Recent advances in fluorescence imaging now enable quantitative characterization of neuronal structure across length scales, ranging from single-molecule localization using super-resolution imaging to whole-brain imaging using light-sheet microscopy on cleared samples. These tools, together with correlative electron microscopy and magnetic resonance imaging at the nanoscopic and macroscopic scales, respectively, now facilitate our ability to probe brain structure across its full range of length scales with cellular and molecular specificity. As these imaging datasets become increasingly accessible to researchers, novel statistical and computational frameworks will play an increasing role in efforts to relate hierarchical brain structure to its function. In this perspective, we discuss several prominent experimental advances that are ushering in a new era of quantitative fluorescence-based imaging in neuroscience along with novel computational and statistical strategies that are helping to distil our understanding of complex brain structure. PMID:26855758

[Evaluation of cardiac tumors by multidetector computed tomography and magnetic resonance imaging].

PubMed

Mercado-Guzman, Marcela P; Meléndez-Ramírez, Gabriela; Castillo-Castellon, Francisco; Kimura-Hayama, Eric

Cardiac tumors, are a rare pathology (0.002-0.3%) in all age groups, however, they have a clinic importance, due the affected organ. They are classified in primary (benign or malignant) and secondary (metastasis) types. Among primary type, mixoma, is the most common benign tumor, and sarcoma represents most of the malignant injuries. Cardiac metastasis are more frequent than primary tumors. Clinic effects of cardiac tumors are unspecific and vary according their location, size and agresivity. The use of Multidetector Computed Tomography (MDCT) and Magnetic Resonance Imaging (MRI) assist on the location, sizing, anatomical relationships and the compromise of adyacents structures, besides, MRI is useful for tissue characterization of the tumor. Due to the previous reasons, studies based on noninvasive cardiovascular imaging, have an important role on the characterization of these lesions and the differential diagnosis among them. Copyright © 2016 Instituto Nacional de Cardiología Ignacio Chávez. Publicado por Masson Doyma México S.A. All rights reserved.

Analytical computation of three-dimensional synthetic seismograms by Modal Summation: method, validation and applications

NASA Astrophysics Data System (ADS)

La Mura, Cristina; Gholami, Vahid; Panza, Giuliano F.

2013-04-01

In order to enable realistic and reliable earthquake hazard assessment and reliable estimation of the ground motion response to an earthquake, three-dimensional velocity models have to be considered. The propagation of seismic waves in complex laterally varying 3D layered structures is a complicated process. Analytical solutions of the elastodynamic equations for such types of media are not known. The most common approaches to the formal description of seismic wavefields in such complex structures are methods based on direct numerical solutions of the elastodynamic equations, e.g. finite-difference, finite-element method, and approximate asymptotic methods. In this work, we present an innovative methodology for computing synthetic seismograms, complete of the main direct, refracted, converted phases and surface waves in three-dimensional anelastic models based on the combination of the Modal Summation technique with the Asymptotic Ray Theory in the framework of the WKBJ - approximation. The three - dimensional models are constructed using a set of vertically heterogeneous sections (1D structures) that are juxtaposed on a regular grid. The distribution of these sections in the grid is done in such a way to fulfill the requirement of weak lateral inhomogeneity in order to satisfy the condition of applicability of the WKBJ - approximation, i.e. the lateral gradient of the parameters characterizing the 1D structure has to be small with respect to the prevailing wavelength. The new method has been validated comparing synthetic seismograms with the records available of three different earthquakes in three different regions: Kanto basin (Japan) triggered by the 1990 Odawara earthquake Mw= 5.1, Romanian territory triggered by the 30 May 1990 Vrancea intermediate-depth earthquake Mw= 6.9 and Iranian territory affected by the 26 December 2003 Bam earthquake Mw= 6.6. Besides the advantage of being a useful tool for assessment of seismic hazard and seismic risk reduction, it is characterized by high efficiency, in fact, once the study region is identified and the 3D model is constructed, the computation, at each station, of the three components of the synthetic signal (displacement, velocity, and acceleration) takes less than 3 hours on a 2 GHz CPU.

Electron energy loss spectroscopy on semiconductor heterostructures for optoelectronics and photonics applications.

PubMed

Eljarrat, A; López-Conesa, L; Estradé, S; Peiró, F

2016-05-01

In this work, we present characterization methods for the analysis of nanometer-sized devices, based on silicon and III-V nitride semiconductor materials. These methods are devised in order to take advantage of the aberration corrected scanning transmission electron microscope, equipped with a monochromator. This set-up ensures the necessary high spatial and energy resolution for the characterization of the smallest structures. As with these experiments, we aim to obtain chemical and structural information, we use electron energy loss spectroscopy (EELS). The low-loss region of EELS is exploited, which features fundamental electronic properties of semiconductor materials and facilitates a high data throughput. We show how the detailed analysis of these spectra, using theoretical models and computational tools, can enhance the analytical power of EELS. In this sense, initially, results from the model-based fit of the plasmon peak are presented. Moreover, the application of multivariate analysis algorithms to low-loss EELS is explored. Finally, some physical limitations of the technique, such as spatial delocalization, are mentioned. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

Graph-based unsupervised segmentation algorithm for cultured neuronal networks' structure characterization and modeling.

PubMed

de Santos-Sierra, Daniel; Sendiña-Nadal, Irene; Leyva, Inmaculada; Almendral, Juan A; Ayali, Amir; Anava, Sarit; Sánchez-Ávila, Carmen; Boccaletti, Stefano

2015-06-01

Large scale phase-contrast images taken at high resolution through the life of a cultured neuronal network are analyzed by a graph-based unsupervised segmentation algorithm with a very low computational cost, scaling linearly with the image size. The processing automatically retrieves the whole network structure, an object whose mathematical representation is a matrix in which nodes are identified neurons or neurons' clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocytochemistry techniques, our non invasive measures entitle us to perform a longitudinal analysis during the maturation of a single culture. Such an analysis furnishes the way of individuating the main physical processes underlying the self-organization of the neurons' ensemble into a complex network, and drives the formulation of a phenomenological model yet able to describe qualitatively the overall scenario observed during the culture growth. © 2014 International Society for Advancement of Cytometry.

Evolutionary Models for Simple Biosystems

NASA Astrophysics Data System (ADS)

Bagnoli, Franco

The concept of evolutionary development of structures constituted a real revolution in biology: it was possible to understand how the very complex structures of life can arise in an out-of-equilibrium system. The investigation of such systems has shown that indeed, systems under a flux of energy or matter can self-organize into complex patterns, think for instance to Rayleigh-Bernard convection, Liesegang rings, patterns formed by granular systems under shear. Following this line, one could characterize life as a state of matter, characterized by the slow, continuous process that we call evolution. In this paper we try to identify the organizational level of life, that spans several orders of magnitude from the elementary constituents to whole ecosystems. Although similar structures can be found in other contexts like ideas (memes) in neural systems and self-replicating elements (computer viruses, worms, etc.) in computer systems, we shall concentrate on biological evolutionary structure, and try to put into evidence the role and the emergence of network structure in such systems.

Characterization of Unsteady Flow Structures Near Landing-Edge Slat. Part 2; 2D Computations

NASA Technical Reports Server (NTRS)

Khorrami, Mehdi; Choudhari, Meelan M.; Jenkins, Luther N.

2004-01-01

In our previous computational studies of a generic high-lift configuration, quasi-laminar (as opposed to fully turbulent) treatment of the slat cove region proved to be an effective approach for capturing the unsteady dynamics of the cove flow field. Combined with acoustic propagation via Ffowes Williams and Hawkings formulation, the quasi-laminar simulations captured some important features of the slat cove noise measured with microphone array techniques. However. a direct assessment of the computed cove flow field was not feasible due to the unavailability of off-surface flow measurements. To remedy this shortcoming, we have undertaken a combined experiment and computational study aimed at characterizing the flow structures and fluid mechanical processes within the slat cove region. Part I of this paper outlines the experimental aspects of this investigation focused on the 30P30N high-lift configuration; the present paper describes the accompanying computational results including a comparison between computation and experiment at various angles of attack. Even through predictions of the time-averaged flow field agree well with the measured data, the study indicates the need for further refinement of the zonal turbulence approach in order to capture the full dynamics of the cove's fluctuating flow field.

Analysis of thin-walled cylindrical composite shell structures subject to axial and bending loads: Concept development, analytical modeling and experimental verification

NASA Astrophysics Data System (ADS)

Mahadev, Sthanu

Continued research and development efforts devoted in recent years have generated novel avenues towards the advancement of efficient and effective, slender laminated fiber-reinforced composite members. Numerous studies have focused on the modeling and response characterization of composite structures with particular relevance to thin-walled cylindrical composite shells. This class of shell configurations is being actively explored to fully determine their mechanical efficacy as primary aerospace structural members. The proposed research is targeted towards formulating a composite shell theory based prognosis methodology that entails an elaborate analysis and investigation of thin-walled cylindrical shell type laminated composite configurations that are highly desirable in increasing number of mechanical and aerospace applications. The prime motivation to adopt this theory arises from its superior ability to generate simple yet viable closed-form analytical solution procedure to numerous geometrically intense, inherent curvature possessing composite structures. This analytical evaluative routine offers to acquire a first-hand insight on the primary mechanical characteristics that essentially govern the behavior of slender composite shells under typical static loading conditions. Current work exposes the robustness of this mathematical framework via demonstrating its potential towards the prediction of structural properties such as axial stiffness and bending stiffness respectively. Longitudinal ply-stress computations are investigated upon deriving the global stiffness matrix model for composite cylindrical tubes with circular cross-sections. Additionally, this work employs a finite element based numerical technique to substantiate the analytical results reported for cylindrically shaped circular composite tubes. Furthermore, this concept development is extended to the study of thin-walled, open cross-sectioned, curved laminated shells that are geometrically distinguished with respect to the circumferential arc angle, thickness-to-mean radius ratio and total laminate thickness. The potential of this methodology is challenged to analytically determine the location of the centroid. This precise location dictates the decoupling of extension-bending type deformational response in tension loaded composite structures. Upon the cross-validation of the centroidal point through the implementation of an ANSYS based finite element routine, influence of centroid is analytically examined under the application of a concentrated longitudinal tension and bending type loadings on a series of cylindrical shells characterized by three different symmetric-balanced stacking sequences. In-plane ply-stresses are computed and analyzed across the circumferential contour. An experimental investigation has been incorporated via designing an ad-hoc apparatus and test-up that accommodates the quantification of in-plane strains, computation of ply-stresses and addresses the physical characteristics for a set of auto-clave fabricated cylindrical shell articles. Consequently, this work is shown to essentially capture the mechanical aspects of cylindrical shells, thus facilitating structural engineers to design and manufacture viable structures.

General Multimechanism Reversible-Irreversible Time-Dependent Constitutive Deformation Model Being Developed

NASA Technical Reports Server (NTRS)

Saleeb, A. F.; Arnold, Steven M.

2001-01-01

Since most advanced material systems (for example metallic-, polymer-, and ceramic-based systems) being currently researched and evaluated are for high-temperature airframe and propulsion system applications, the required constitutive models must account for both reversible and irreversible time-dependent deformations. Furthermore, since an integral part of continuum-based computational methodologies (be they microscale- or macroscale-based) is an accurate and computationally efficient constitutive model to describe the deformation behavior of the materials of interest, extensive research efforts have been made over the years on the phenomenological representations of constitutive material behavior in the inelastic analysis of structures. From a more recent and comprehensive perspective, the NASA Glenn Research Center in conjunction with the University of Akron has emphasized concurrently addressing three important and related areas: that is, 1) Mathematical formulation; 2) Algorithmic developments for updating (integrating) the external (e.g., stress) and internal state variables; 3) Parameter estimation for characterizing the model. This concurrent perspective to constitutive modeling has enabled the overcoming of the two major obstacles to fully utilizing these sophisticated time-dependent (hereditary) constitutive models in practical engineering analysis. These obstacles are: 1) Lack of efficient and robust integration algorithms; 2) Difficulties associated with characterizing the large number of required material parameters, particularly when many of these parameters lack obvious or direct physical interpretations.

Correlation between structural and opto-electronic characteristics of crystalline Si microhole arrays for photonic light management

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

Sontheimer, Tobias, E-mail: tobias.sontheimer@helmholtz-berlin.de; Schnegg, Alexander; Lips, Klaus

2013-11-07

By employing electron paramagnetic resonance spectroscopy, transmission electron microscopy, and optical measurements, we systematically correlate the structural and optical properties with the deep-level defect characteristics of various tailored periodic Si microhole arrays, which are manufactured in an easily scalable and versatile process on nanoimprinted sol-gel coated glass. While tapered microhole arrays in a structured base layer are characterized by partly nanocrystalline features, poor electronic quality with a defect concentration of 10{sup 17} cm{sup −3} and a high optical sub-band gap absorption, planar polycrystalline Si layers perforated with periodic arrays of tapered microholes are composed of a compact crystalline structure and amore » defect concentration in the low 10{sup 16} cm{sup −3} regime. The low defect concentration is equivalent to the one in planar state-of-the-art solid phase crystallized Si films and correlates with a low optical sub-band gap absorption. By complementing the experimental characterization with 3-dimensional finite element simulations, we provide the basis for a computer-aided approach for the low-cost fabrication of novel high-quality structures on large areas featuring tailored opto-electronic properties.« less

Structure-functional prediction and analysis of cancer mutation effects in protein kinases.

PubMed

Dixit, Anshuman; Verkhivker, Gennady M

2014-01-01

A central goal of cancer research is to discover and characterize the functional effects of mutated genes that contribute to tumorigenesis. In this study, we provide a detailed structural classification and analysis of functional dynamics for members of protein kinase families that are known to harbor cancer mutations. We also present a systematic computational analysis that combines sequence and structure-based prediction models to characterize the effect of cancer mutations in protein kinases. We focus on the differential effects of activating point mutations that increase protein kinase activity and kinase-inactivating mutations that decrease activity. Mapping of cancer mutations onto the conformational mobility profiles of known crystal structures demonstrated that activating mutations could reduce a steric barrier for the movement from the basal "low" activity state to the "active" state. According to our analysis, the mechanism of activating mutations reflects a combined effect of partial destabilization of the kinase in its inactive state and a concomitant stabilization of its active-like form, which is likely to drive tumorigenesis at some level. Ultimately, the analysis of the evolutionary and structural features of the major cancer-causing mutational hotspot in kinases can also aid in the correlation of kinase mutation effects with clinical outcomes.

Causal Learning with Local Computations

ERIC Educational Resources Information Center

Fernbach, Philip M.; Sloman, Steven A.

2009-01-01

The authors proposed and tested a psychological theory of causal structure learning based on local computations. Local computations simplify complex learning problems via cues available on individual trials to update a single causal structure hypothesis. Structural inferences from local computations make minimal demands on memory, require…

Crystal structure characterization as well as theoretical study of spectroscopic properties of novel Schiff bases containing pyrazole group.

PubMed

Guo, Jia; Ren, Tiegang; Zhang, Jinglai; Li, Guihui; Li, Weijie; Yang, Lirong

2012-09-01

A series of novel Schiff bases containing pyrazole group were synthesized using 1-aryl-3-methyl-4-benzoyl-5-pyrazolone and phenylenediamine as the starting materials. All as-synthesized Schiff bases were characterized by means of NMR, FT-IR, and MS; and the molecular geometries of two Schiff bases as typical examples were determined by means of single crystal X-ray diffraction. In the meantime, the ultraviolet-visible light absorption spectra and fluorescent spectra of various as-synthesized products were also measured. Moreover, the B3LYP/6-1G(d,p) method was used for the optimization of the ground state geometry of the Schiff bases; and the spectroscopic properties of the products were computed and compared with corresponding experimental data based on cc-pVTZ basis set of TD-B3LYP method. It has been found that all as-synthesized Schiff bases show a remarkable absorption peak in a wavelength range of 270-370 nm; and their maximum emission peaks are around 344 nm and 332 nm, respectively. Copyright © 2012 Elsevier B.V. All rights reserved.

Resistive switching characteristics and mechanisms in silicon oxide memory devices

NASA Astrophysics Data System (ADS)

Chang, Yao-Feng; Fowler, Burt; Chen, Ying-Chen; Zhou, Fei; Wu, Xiaohan; Chen, Yen-Ting; Wang, Yanzhen; Xue, Fei; Lee, Jack C.

2016-05-01

Intrinsic unipolar SiOx-based resistance random access memories (ReRAM) characterization, switching mechanisms, and applications have been investigated. Device structures, material compositions, and electrical characteristics are identified that enable ReRAM cells with high ON/OFF ratio, low static power consumption, low switching power, and high readout-margin using complementary metal-oxide semiconductor transistor (CMOS)-compatible SiOx-based materials. These ideas are combined with the use of horizontal and vertical device structure designs, composition optimization, electrical control, and external factors to help understand resistive switching (RS) mechanisms. Measured temperature effects, pulse response, and carrier transport behaviors lead to compact models of RS mechanisms and energy band diagrams in order to aid the development of computer-aided design for ultralarge-v scale integration. This chapter presents a comprehensive investigation of SiOx-based RS characteristics and mechanisms for the post-CMOS device era.

Characterizing Bonding Patterns in Diradicals and Triradicals by Density-Based Wave Function Analysis: A Uniform Approach.

PubMed

Orms, Natalie; Rehn, Dirk R; Dreuw, Andreas; Krylov, Anna I

2018-02-13

Density-based wave function analysis enables unambiguous comparisons of the electronic structure computed by different methods and removes ambiguity of orbital choices. We use this tool to investigate the performance of different spin-flip methods for several prototypical diradicals and triradicals. In contrast to previous calibration studies that focused on energy gaps between high- and low spin-states, we focus on the properties of the underlying wave functions, such as the number of effectively unpaired electrons. Comparison of different density functional and wave function theory results provides insight into the performance of the different methods when applied to strongly correlated systems such as polyradicals. We show that canonical molecular orbitals for species like large copper-containing diradicals fail to correctly represent the underlying electronic structure due to highly non-Koopmans character, while density-based analysis of the same wave function delivers a clear picture of the bonding pattern.

Network analysis of named entity co-occurrences in written texts

NASA Astrophysics Data System (ADS)

Amancio, Diego Raphael

2016-06-01

The use of methods borrowed from statistics and physics to analyze written texts has allowed the discovery of unprecedent patterns of human behavior and cognition by establishing links between models features and language structure. While current models have been useful to unveil patterns via analysis of syntactical and semantical networks, only a few works have probed the relevance of investigating the structure arising from the relationship between relevant entities such as characters, locations and organizations. In this study, we represent entities appearing in the same context as a co-occurrence network, where links are established according to a null model based on random, shuffled texts. Computational simulations performed in novels revealed that the proposed model displays interesting topological features, such as the small world feature, characterized by high values of clustering coefficient. The effectiveness of our model was verified in a practical pattern recognition task in real networks. When compared with traditional word adjacency networks, our model displayed optimized results in identifying unknown references in texts. Because the proposed representation plays a complementary role in characterizing unstructured documents via topological analysis of named entities, we believe that it could be useful to improve the characterization of written texts (and related systems), specially if combined with traditional approaches based on statistical and deeper paradigms.

Fiber-based modeling of in situ ankle ligaments with consideration of progressive failure.

PubMed

Nie, Bingbing; Forman, Jason L; Panzer, Matthew B; Mait, Alexander R; Donlon, John-Paul; Kent, Richard W

2017-08-16

Ligament sprains account for a majority of injuries to the foot and ankle complex among athletic populations. The infeasibility of measuring the in situ response and load paths of individual ligaments has precluded a complete characterization of their mechanical behavior via experiment. In the present study a fiber-based modeling approach of in situ ankle ligaments was developed and validated for determining the heterogeneous force-elongation characteristics and the consequent injury patterns. Nine major ankle ligaments were modeled as bundles of discrete elements, corresponding functionally to the structure of collagen fibers. To incorporate the progressive nature of ligamentous injury, the limit strain at the occurrence of fiber failure was described by a distribution function ranging from 12% to 18% along the width of the insertion site. The model was validated by comparing the structural kinetic and kinematic response obtained experimentally and computationally under well-controlled foot rotations. The simulation results replicated the 6 degree-of-freedom bony motion and ligamentous injuries and, by implication, the in situ deformations of the ligaments. Gross stiffness of the whole ligament derived from the fibers was comparable to existing experimental data. The present modeling approach provides a biomechanically realistic, interpretable and computationally efficient way to characterize the in situ ligament slack, sequential and heterogeneous uncrimping of collagen fascicles and failure propagation as the external load is applied. Applications of this model include functional ankle joint mechanics, injury prevention and countermeasure design for athletes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Intraoperative brain tumor resection cavity characterization with conoscopic holography

NASA Astrophysics Data System (ADS)

Simpson, Amber L.; Burgner, Jessica; Chen, Ishita; Pheiffer, Thomas S.; Sun, Kay; Thompson, Reid C.; Webster, Robert J., III; Miga, Michael I.

2012-02-01

Brain shift compromises the accuracy of neurosurgical image-guided interventions if not corrected by either intraoperative imaging or computational modeling. The latter requires intraoperative sparse measurements for constraining and driving model-based compensation strategies. Conoscopic holography, an interferometric technique that measures the distance of a laser light illuminated surface point from a fixed laser source, was recently proposed for non-contact surface data acquisition in image-guided surgery and is used here for validation of our modeling strategies. In this contribution, we use this inexpensive, hand-held conoscopic holography device for intraoperative validation of our computational modeling approach to correcting for brain shift. Laser range scan, instrument swabbing, and conoscopic holography data sets were collected from two patients undergoing brain tumor resection therapy at Vanderbilt University Medical Center. The results of our study indicate that conoscopic holography is a promising method for surface acquisition since it requires no contact with delicate tissues and can characterize the extents of structures within confined spaces. We demonstrate that for two clinical cases, the acquired conoprobe points align with our model-updated images better than the uncorrected images lending further evidence that computational modeling approaches improve the accuracy of image-guided surgical interventions in the presence of soft tissue deformations.

Adiabatic quantum computing with spin qubits hosted by molecules.

PubMed

Yamamoto, Satoru; Nakazawa, Shigeaki; Sugisaki, Kenji; Sato, Kazunobu; Toyota, Kazuo; Shiomi, Daisuke; Takui, Takeji

2015-01-28

A molecular spin quantum computer (MSQC) requires electron spin qubits, which pulse-based electron spin/magnetic resonance (ESR/MR) techniques can afford to manipulate for implementing quantum gate operations in open shell molecular entities. Importantly, nuclear spins, which are topologically connected, particularly in organic molecular spin systems, are client qubits, while electron spins play a role of bus qubits. Here, we introduce the implementation for an adiabatic quantum algorithm, suggesting the possible utilization of molecular spins with optimized spin structures for MSQCs. We exemplify the utilization of an adiabatic factorization problem of 21, compared with the corresponding nuclear magnetic resonance (NMR) case. Two molecular spins are selected: one is a molecular spin composed of three exchange-coupled electrons as electron-only qubits and the other an electron-bus qubit with two client nuclear spin qubits. Their electronic spin structures are well characterized in terms of the quantum mechanical behaviour in the spin Hamiltonian. The implementation of adiabatic quantum computing/computation (AQC) has, for the first time, been achieved by establishing ESR/MR pulse sequences for effective spin Hamiltonians in a fully controlled manner of spin manipulation. The conquered pulse sequences have been compared with the NMR experiments and shown much faster CPU times corresponding to the interaction strength between the spins. Significant differences are shown in rotational operations and pulse intervals for ESR/MR operations. As a result, we suggest the advantages and possible utilization of the time-evolution based AQC approach for molecular spin quantum computers and molecular spin quantum simulators underlain by sophisticated ESR/MR pulsed spin technology.

Development and applications of two computational procedures for determining the vibration modes of structural systems. [aircraft structures - aerospaceplanes

NASA Technical Reports Server (NTRS)

Kvaternik, R. G.

1975-01-01

Two computational procedures for analyzing complex structural systems for their natural modes and frequencies of vibration are presented. Both procedures are based on a substructures methodology and both employ the finite-element stiffness method to model the constituent substructures. The first procedure is a direct method based on solving the eigenvalue problem associated with a finite-element representation of the complete structure. The second procedure is a component-mode synthesis scheme in which the vibration modes of the complete structure are synthesized from modes of substructures into which the structure is divided. The analytical basis of the methods contains a combination of features which enhance the generality of the procedures. The computational procedures exhibit a unique utilitarian character with respect to the versatility, computational convenience, and ease of computer implementation. The computational procedures were implemented in two special-purpose computer programs. The results of the application of these programs to several structural configurations are shown and comparisons are made with experiment.

Lytro camera technology: theory, algorithms, performance analysis

NASA Astrophysics Data System (ADS)

Georgiev, Todor; Yu, Zhan; Lumsdaine, Andrew; Goma, Sergio

2013-03-01

The Lytro camera is the first implementation of a plenoptic camera for the consumer market. We consider it a successful example of the miniaturization aided by the increase in computational power characterizing mobile computational photography. The plenoptic camera approach to radiance capture uses a microlens array as an imaging system focused on the focal plane of the main camera lens. This paper analyzes the performance of Lytro camera from a system level perspective, considering the Lytro camera as a black box, and uses our interpretation of Lytro image data saved by the camera. We present our findings based on our interpretation of Lytro camera file structure, image calibration and image rendering; in this context, artifacts and final image resolution are discussed.

Identification of family-specific residue packing motifs and their use for structure-based protein function prediction: I. Method development.

PubMed

Bandyopadhyay, Deepak; Huan, Jun; Prins, Jan; Snoeyink, Jack; Wang, Wei; Tropsha, Alexander

2009-11-01

Protein function prediction is one of the central problems in computational biology. We present a novel automated protein structure-based function prediction method using libraries of local residue packing patterns that are common to most proteins in a known functional family. Critical to this approach is the representation of a protein structure as a graph where residue vertices (residue name used as a vertex label) are connected by geometrical proximity edges. The approach employs two steps. First, it uses a fast subgraph mining algorithm to find all occurrences of family-specific labeled subgraphs for all well characterized protein structural and functional families. Second, it queries a new structure for occurrences of a set of motifs characteristic of a known family, using a graph index to speed up Ullman's subgraph isomorphism algorithm. The confidence of function inference from structure depends on the number of family-specific motifs found in the query structure compared with their distribution in a large non-redundant database of proteins. This method can assign a new structure to a specific functional family in cases where sequence alignments, sequence patterns, structural superposition and active site templates fail to provide accurate annotation.

Geometry-based ensembles: toward a structural characterization of the classification boundary.

PubMed

Pujol, Oriol; Masip, David

2009-06-01

This paper introduces a novel binary discriminative learning technique based on the approximation of the nonlinear decision boundary by a piecewise linear smooth additive model. The decision border is geometrically defined by means of the characterizing boundary points-points that belong to the optimal boundary under a certain notion of robustness. Based on these points, a set of locally robust linear classifiers is defined and assembled by means of a Tikhonov regularized optimization procedure in an additive model to create a final lambda-smooth decision rule. As a result, a very simple and robust classifier with a strong geometrical meaning and nonlinear behavior is obtained. The simplicity of the method allows its extension to cope with some of today's machine learning challenges, such as online learning, large-scale learning or parallelization, with linear computational complexity. We validate our approach on the UCI database, comparing with several state-of-the-art classification techniques. Finally, we apply our technique in online and large-scale scenarios and in six real-life computer vision and pattern recognition problems: gender recognition based on face images, intravascular ultrasound tissue classification, speed traffic sign detection, Chagas' disease myocardial damage severity detection, old musical scores clef classification, and action recognition using 3D accelerometer data from a wearable device. The results are promising and this paper opens a line of research that deserves further attention.

Nonlinear optical and G-Quadruplex DNA stabilization properties of novel mixed ligand copper(II) complexes and coordination polymers: Synthesis, structural characterization and computational studies

NASA Astrophysics Data System (ADS)

Rajasekhar, Bathula; Bodavarapu, Navya; Sridevi, M.; Thamizhselvi, G.; RizhaNazar, K.; Padmanaban, R.; Swu, Toka

2018-03-01

The present study reports the synthesis and evaluation of nonlinear optical property and G-Quadruplex DNA Stabilization of five novel copper(II) mixed ligand complexes. They were synthesized from copper(II) salt, 2,5- and 2,3- pyridinedicarboxylic acid, diethylenetriamine and amide based ligand (AL). The crystal structure of these complexes were determined through X-ray diffraction and supported by ESI-MAS, NMR, UV-Vis and FT-IR spectroscopic methods. Their nonlinear optical property was studied using Gaussian09 computer program. For structural optimization and nonlinear optical property, density functional theory (DFT) based B3LYP method was used with LANL2DZ basis set for metal ion and 6-31G∗ for C,H,N,O and Cl atoms. The present work reveals that pre-polarized Complex-2 showed higher β value (29.59 × 10-30e.s.u) as compared to that of neutral complex-1 (β = 0.276 × 10-30e.s.u.) which may be due to greater advantage of polarizability. Complex-2 is expected to be a potential material for optoelectronic and photonic technologies. Docking studies using AutodockVina revealed that complex-2 has higher binding energy for both G-Quadruplex DNA (-8.7 kcal/mol) and duplex DNA (-10.1 kcal/mol). It was also observed that structure plays an important role in binding efficiency.

Effect of different types of surfactants on the microstructure of methyltrimethoxysilane-derived silica aerogels: A combined experimental and computational approach.

PubMed

Vareda, João P; Maximiano, Pedro; Cunha, Luís P; Ferreira, André F; Simões, Pedro N; Durães, Luísa

2018-02-15

Surfactants interfere with sol-gel particle/pore growth, influencing the structure and properties of silica aerogels. Their ability to induce microscopic changes in the aerogel's structure may be useful to improve/control the thermal insulation performance of aerogels. The influence of different types of surfactants (anionic, cationic and non-ionic) on the microstructural arrangement and macroscopic properties of methyltrimethoxysilane (MTMS)-based aerogels was evaluated for the first time, using an experimental and computational comparative approach. Molecular dynamics simulations were performed based on two representative silica molecular structures derived from MTMS, while the experimentally-obtained silica aerogels were characterized in terms of chemical/structural/mechanical/thermal insulation properties. The use of both hexadecyltrimethylammonium bromide (CTAB) and sodium dodecylsulfate (SDS) led to a decrease in bulk density, thermal conductivity and average pore size of the aerogels, with notorious increase of their flexibility. The observed changes were due to microstructural arrangements, as evidenced by scanning electron microscopy (SEM). However, the non-ionic surfactant, Pluronic F-127, did not have a positive impact on the desired properties. Globally, the simulation results support the experimental findings, suggesting differentiated microstructural changes induced by the use of cationic or anionic surfactants. The addition of CTAB and SDS generally resulted in smaller or larger silica aggregates, respectively. Copyright © 2017 Elsevier Inc. All rights reserved.

Biophysical and computational characterization of vandetanib-lysozyme interaction

NASA Astrophysics Data System (ADS)

Kabir, Md. Zahirul; Hamzah, Nur Aziean Binti; Ghani, Hamidah; Mohamad, Saharuddin B.; Alias, Zazali; Tayyab, Saad

2018-01-01

Interaction of an anticancer drug, vandetanib (VDB) with a ligand transporter, lysozyme (LYZ) was explored using multispectroscopic techniques, such as fluorescence, absorption and circular dichroism along with computational analysis. Fluorescence data and absorption results confirmed VDB-LYZ complexation. VDB-induced quenching was characterized as static quenching based on inverse correlation of KSV with temperature as well as kq values. The complex was characterized by the weak binding constant (Ka = 4.96-3.14 × 103 M-1). Thermodynamic data (ΔS = + 12.82 J mol-1 K-1; ΔH = - 16.73 kJ mol-1) of VDB-LYZ interaction revealed participation of hydrophobic and van der Waals forces along with hydrogen bonds in VDB-LYZ complexation. Microenvironmental perturbations around tryptophan and tyrosine residues as well as secondary and tertiary structural alterations in LYZ upon addition of VDB were evident from the 3-D fluorescence, far- and near-UV CD spectral analyses, respectively. Interestingly, addition of VDB to LYZ significantly increased protein's thermostability. Molecular docking results suggested the location of VDB binding site near the LYZ active site while molecular dynamics simulation results suggested stability of VDB-LYZ complex. Presence of Mg2+, Ba2+ and Zn2+ was found to interfere with VDB-LYZ interaction.

Characterization of mechanical properties of pericardium tissue using planar biaxial tension and flexural deformation.

PubMed

Murdock, Kyle; Martin, Caitlin; Sun, Wei

2018-01-01

Flexure is an important mode of deformation for native and bioprosthetic heart valves. However, mechanical characterization of bioprosthetic leaflet materials has been done primarily through planar tensile testing. In this study, an integrated experimental and computational cantilever beam bending test was performed to characterize the flexural properties of glutaraldehyde-treated bovine and porcine pericardium of different thicknesses. A strain-invariant based structural constitutive model was used to model the pericardial mechanical behavior quantified through the bending tests of this study and the planar biaxial tests previously performed. The model parameters were optimized through an inverse finite element (FE) procedure in order to describe both sets of experimental data. The optimized material properties were implemented in FE simulations of transcatheter aortic valve (TAV) deformation. It was observed that porcine pericardium TAV leaflets experienced significantly more flexure than bovine when subjected to opening pressurization, and that the flexure may be overestimated using a constitutive model derived from purely planar tensile experimental data. Thus, modeling of a combination of flexural and biaxial tensile testing data may be necessary to more accurately describe the mechanical properties of pericardium, and to computationally investigate bioprosthetic leaflet function and design. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Computer-Based Approach for Deriving and Measuring Individual and Team Knowledge Structure from Essay Questions

ERIC Educational Resources Information Center

Clariana, Roy B.; Wallace, Patricia

2007-01-01

This proof-of-concept investigation describes a computer-based approach for deriving the knowledge structure of individuals and of groups from their written essays, and considers the convergent criterion-related validity of the computer-based scores relative to human rater essay scores and multiple-choice test scores. After completing a…

Challenges in structural approaches to cell modeling.

PubMed

Im, Wonpil; Liang, Jie; Olson, Arthur; Zhou, Huan-Xiang; Vajda, Sandor; Vakser, Ilya A

2016-07-31

Computational modeling is essential for structural characterization of biomolecular mechanisms across the broad spectrum of scales. Adequate understanding of biomolecular mechanisms inherently involves our ability to model them. Structural modeling of individual biomolecules and their interactions has been rapidly progressing. However, in terms of the broader picture, the focus is shifting toward larger systems, up to the level of a cell. Such modeling involves a more dynamic and realistic representation of the interactomes in vivo, in a crowded cellular environment, as well as membranes and membrane proteins, and other cellular components. Structural modeling of a cell complements computational approaches to cellular mechanisms based on differential equations, graph models, and other techniques to model biological networks, imaging data, etc. Structural modeling along with other computational and experimental approaches will provide a fundamental understanding of life at the molecular level and lead to important applications to biology and medicine. A cross section of diverse approaches presented in this review illustrates the developing shift from the structural modeling of individual molecules to that of cell biology. Studies in several related areas are covered: biological networks; automated construction of three-dimensional cell models using experimental data; modeling of protein complexes; prediction of non-specific and transient protein interactions; thermodynamic and kinetic effects of crowding; cellular membrane modeling; and modeling of chromosomes. The review presents an expert opinion on the current state-of-the-art in these various aspects of structural modeling in cellular biology, and the prospects of future developments in this emerging field. Copyright © 2016 Elsevier Ltd. All rights reserved.

HOTCFGM-1D: A Coupled Higher-Order Theory for Cylindrical Structural Components with Through-Thickness Functionally Graded Microstructures

NASA Technical Reports Server (NTRS)

Pindera, Marek-Jerzy; Aboudi, Jacob

1998-01-01

The objective of this three-year project was to develop and deliver to NASA Lewis one-dimensional and two-dimensional higher-order theories, and related computer codes, for the analysis, optimization and design of cylindrical functionally graded materials/structural components for use in advanced aircraft engines (e.g., combustor linings, rotor disks, heat shields, blisk blades). To satisfy this objective, a quasi one-dimensional version of the higher-order theory, HOTCFGM-1D, and four computer codes based on this theory, for the analysis, design and optimization of cylindrical structural components functionally graded in the radial direction were developed. The theory is applicable to thin multi-phased composite shell/cylinders subjected to macroscopically axisymmetric thermomechanical and inertial loading applied uniformly along the axial direction such that the overall deformation is characterized by a constant average axial strain. The reinforcement phases are uniformly distributed in the axial and circumferential directions, and arbitrarily distributed in the radial direction, thereby allowing functional grading of the internal reinforcement in this direction.

Quantitative Examination of Corrosion Damage by Means of Thermal Response Measurements

NASA Technical Reports Server (NTRS)

Rajic, Nik

1998-01-01

Two computational methods are presented that enable a characterization of corrosion damage to be performed from thermal response measurements derived from a standard flash thermographic inspection. The first is based upon a one dimensional analytical solution to the heat diffusion equation and presumes the lateral extent of damage is large compared to the residual structural thickness, such that lateral heat diffusion effects can be considered insignificant. The second proposed method, based on a finite element optimization scheme, addresses the more general case where these conditions are not met. Results from an experimental application are given to illustrate the precision, robustness and practical efficacy of both methods.

Perspective: Structural fluctuation of protein and Anfinsen's thermodynamic hypothesis

NASA Astrophysics Data System (ADS)

Hirata, Fumio; Sugita, Masatake; Yoshida, Masasuke; Akasaka, Kazuyuki

2018-01-01

The thermodynamics hypothesis, casually referred to as "Anfinsen's dogma," is described theoretically in terms of a concept of the structural fluctuation of protein or the first moment (average structure) and the second moment (variance and covariance) of the structural distribution. The new theoretical concept views the unfolding and refolding processes of protein as a shift of the structural distribution induced by a thermodynamic perturbation, with the variance-covariance matrix varying. Based on the theoretical concept, a method to characterize the mechanism of folding (or unfolding) is proposed. The transition state, if any, between two stable states is interpreted as a gap in the distribution, which is created due to an extensive reorganization of hydrogen bonds among back-bone atoms of protein and with water molecules in the course of conformational change. Further perspective to applying the theory to the computer-aided drug design, and to the material science, is briefly discussed.

First- and second-order sensitivity analysis of linear and nonlinear structures

NASA Technical Reports Server (NTRS)

Haftka, R. T.; Mroz, Z.

1986-01-01

This paper employs the principle of virtual work to derive sensitivity derivatives of structural response with respect to stiffness parameters using both direct and adjoint approaches. The computations required are based on additional load conditions characterized by imposed initial strains, body forces, or surface tractions. As such, they are equally applicable to numerical or analytical solution techniques. The relative efficiency of various approaches for calculating first and second derivatives is assessed. It is shown that for the evaluation of second derivatives the most efficient approach is one that makes use of both the first-order sensitivities and adjoint vectors. Two example problems are used for demonstrating the various approaches.

On the representation matrices of the spin permutation group. [for atomic and molecular electronic structures

NASA Technical Reports Server (NTRS)

Wilson, S.

1977-01-01

A method is presented for the determination of the representation matrices of the spin permutation group (symmetric group), a detailed knowledge of these matrices being required in the study of the electronic structure of atoms and molecules. The method is characterized by the use of two different coupling schemes. Unlike the Yamanouchi spin algebraic scheme, the method is not recursive. The matrices for the fundamental transpositions can be written down directly in one of the two bases. The method results in a computationally significant reduction in the number of matrix elements that have to be stored when compared with, say, the standard Young tableaux group theoretical approach.

Aeroelastic Modeling of a Nozzle Startup Transient

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Zhao, Xiang; Zhang, Sijun; Chen, Yen-Sen

2014-01-01

Lateral nozzle forces are known to cause severe structural damage to any new rocket engine in development during test. While three-dimensional, transient, turbulent, chemically reacting computational fluid dynamics methodology has been demonstrated to capture major side load physics with rigid nozzles, hot-fire tests often show nozzle structure deformation during major side load events, leading to structural damages if structural strengthening measures were not taken. The modeling picture is incomplete without the capability to address the two-way responses between the structure and fluid. The objective of this study is to develop a tightly coupled aeroelastic modeling algorithm by implementing the necessary structural dynamics component into an anchored computational fluid dynamics methodology. The computational fluid dynamics component is based on an unstructured-grid, pressure-based computational fluid dynamics formulation, while the computational structural dynamics component is developed under the framework of modal analysis. Transient aeroelastic nozzle startup analyses at sea level were performed, and the computed transient nozzle fluid-structure interaction physics presented,

Applications of NMR and computational methodologies to study protein dynamics.

PubMed

Narayanan, Chitra; Bafna, Khushboo; Roux, Louise D; Agarwal, Pratul K; Doucet, Nicolas

2017-08-15

Overwhelming evidence now illustrates the defining role of atomic-scale protein flexibility in biological events such as allostery, cell signaling, and enzyme catalysis. Over the years, spin relaxation nuclear magnetic resonance (NMR) has provided significant insights on the structural motions occurring on multiple time frames over the course of a protein life span. The present review article aims to illustrate to the broader community how this technique continues to shape many areas of protein science and engineering, in addition to being an indispensable tool for studying atomic-scale motions and functional characterization. Continuing developments in underlying NMR technology alongside software and hardware developments for complementary computational approaches now enable methodologies to routinely provide spatial directionality and structural representations traditionally harder to achieve solely using NMR spectroscopy. In addition to its well-established role in structural elucidation, we present recent examples that illustrate the combined power of selective isotope labeling, relaxation dispersion experiments, chemical shift analyses, and computational approaches for the characterization of conformational sub-states in proteins and enzymes. Copyright © 2017 Elsevier Inc. All rights reserved.

Factorization and the synthesis of optimal feedback kernels for differential-delay systems

NASA Technical Reports Server (NTRS)

Milman, Mark M.; Scheid, Robert E.

1987-01-01

A combination of ideas from the theories of operator Riccati equations and Volterra factorizations leads to the derivation of a novel, relatively simple set of hyperbolic equations which characterize the optimal feedback kernel for the finite-time regulator problem for autonomous differential-delay systems. Analysis of these equations elucidates the underlying structure of the feedback kernel and leads to the development of fast and accurate numerical methods for its computation. Unlike traditional formulations based on the operator Riccati equation, the gain is characterized by means of classical solutions of the derived set of equations. This leads to the development of approximation schemes which are analogous to what has been accomplished for systems of ordinary differential equations with given initial conditions.

Template-Based Modeling of Protein-RNA Interactions.

PubMed

Zheng, Jinfang; Kundrotas, Petras J; Vakser, Ilya A; Liu, Shiyong

2016-09-01

Protein-RNA complexes formed by specific recognition between RNA and RNA-binding proteins play an important role in biological processes. More than a thousand of such proteins in human are curated and many novel RNA-binding proteins are to be discovered. Due to limitations of experimental approaches, computational techniques are needed for characterization of protein-RNA interactions. Although much progress has been made, adequate methodologies reliably providing atomic resolution structural details are still lacking. Although protein-RNA free docking approaches proved to be useful, in general, the template-based approaches provide higher quality of predictions. Templates are key to building a high quality model. Sequence/structure relationships were studied based on a representative set of binary protein-RNA complexes from PDB. Several approaches were tested for pairwise target/template alignment. The analysis revealed a transition point between random and correct binding modes. The results showed that structural alignment is better than sequence alignment in identifying good templates, suitable for generating protein-RNA complexes close to the native structure, and outperforms free docking, successfully predicting complexes where the free docking fails, including cases of significant conformational change upon binding. A template-based protein-RNA interaction modeling protocol PRIME was developed and benchmarked on a representative set of complexes.

Spatially Characterizing Effective Timber Supply

NASA Technical Reports Server (NTRS)

Berry, J. K.; Sailor, J.

1982-01-01

The structure of a computer-oriented cartographic model for assessing roundwood supply for generation of base load electricity is discussed. The model provides an analytical procedure for coupling spatial information of harvesting economics and owner willingness to sell stumpages. Supply is characterized in terms of standing timber; of accessibility considering various harvesting and hauling factors; and of availability as affected by ownership and residential patterns. Factors governing accessibility to timber include effective harvesting distance to haulic roads as modified by barriers and slopes. Haul distance is expressed in units that take into account the relative ease of travel along various road types to a central processing facility. Areas of accessible timber are grouped into spatial units, termed 'timbersheds', of common access to particular haul road segments that belong to unique 'transport zones'. Timber availability considerations include size of ownership parcels, housing density and excluded areas. The analysis techniques are demonstrated for a cartographic data base in western Massachusetts.

Developing advanced X-ray scattering methods combined with crystallography and computation.

PubMed

Perry, J Jefferson P; Tainer, John A

2013-03-01

The extensive use of small angle X-ray scattering (SAXS) over the last few years is rapidly providing new insights into protein interactions, complex formation and conformational states in solution. This SAXS methodology allows for detailed biophysical quantification of samples of interest. Initial analyses provide a judgment of sample quality, revealing the potential presence of aggregation, the overall extent of folding or disorder, the radius of gyration, maximum particle dimensions and oligomerization state. Structural characterizations include ab initio approaches from SAXS data alone, and when combined with previously determined crystal/NMR, atomistic modeling can further enhance structural solutions and assess validity. This combination can provide definitions of architectures, spatial organizations of protein domains within a complex, including those not determined by crystallography or NMR, as well as defining key conformational states of a protein interaction. SAXS is not generally constrained by macromolecule size, and the rapid collection of data in a 96-well plate format provides methods to screen sample conditions. This includes screening for co-factors, substrates, differing protein or nucleotide partners or small molecule inhibitors, to more fully characterize the variations within assembly states and key conformational changes. Such analyses may be useful for screening constructs and conditions to determine those most likely to promote crystal growth of a complex under study. Moreover, these high throughput structural determinations can be leveraged to define how polymorphisms affect assembly formations and activities. This is in addition to potentially providing architectural characterizations of complexes and interactions for systems biology-based research, and distinctions in assemblies and interactions in comparative genomics. Thus, SAXS combined with crystallography/NMR and computation provides a unique set of tools that should be considered as being part of one's repertoire of biophysical analyses, when conducting characterizations of protein and other macromolecular interactions. Copyright © 2013 Elsevier Inc. All rights reserved.

ANN expert system screening for illicit amphetamines using molecular descriptors

NASA Astrophysics Data System (ADS)

Gosav, S.; Praisler, M.; Dorohoi, D. O.

2007-05-01

The goal of this study was to develop and an artificial neural network (ANN) based on computed descriptors, which would be able to classify the molecular structures of potential illicit amphetamines and to derive their biological activity according to the similarity of their molecular structure with amphetamines of known toxicity. The system is necessary for testing new molecular structures for epidemiological, clinical, and forensic purposes. It was built using a database formed by 146 compounds representing drugs of abuse (mainly central stimulants, hallucinogens, sympathomimetic amines, narcotics and other potent analgesics), precursors, or derivatized counterparts. Their molecular structures were characterized by computing three types of descriptors: 38 constitutional descriptors (CDs), 69 topological descriptors (TDs) and 160 3D-MoRSE descriptors (3DDs). An ANN system was built for each category of variables. All three networks (CD-NN, TD-NN and 3DD-NN) were trained to distinguish between stimulant amphetamines, hallucinogenic amphetamines, and nonamphetamines. A selection of variables was performed when necessary. The efficiency with which each network identifies the class identity of an unknown sample was evaluated by calculating several figures of merit. The results of the comparative analysis are presented.

Computational design of d-peptide inhibitors of hepatitis delta antigen dimerization

NASA Astrophysics Data System (ADS)

Elkin, Carl D.; Zuccola, Harmon J.; Hogle, James M.; Joseph-McCarthy, Diane

2000-11-01

Hepatitis delta virus (HDV) encodes a single polypeptide called hepatitis delta antigen (DAg). Dimerization of DAg is required for viral replication. The structure of the dimerization region, residues 12 to 60, consists of an anti-parallel coiled coil [Zuccola et al., Structure, 6 (1998) 821]. Multiple Copy Simultaneous Searches (MCSS) of the hydrophobic core region formed by the bend in the helix of one monomer of this structure were carried out for many diverse functional groups. Six critical interaction sites were identified. The Protein Data Bank was searched for backbone templates to use in the subsequent design process by matching to these sites. A 14 residue helix expected to bind to the d-isomer of the target structure was selected as the template. Over 200 000 mutant sequences of this peptide were generated based on the MCSS results. A secondary structure prediction algorithm was used to screen all sequences, and in general only those that were predicted to be highly helical were retained. Approximately 100 of these 14-mers were model built as d-peptides and docked with the l-isomer of the target monomer. Based on calculated interaction energies, predicted helicity, and intrahelical salt bridge patterns, a small number of peptides were selected as the most promising candidates. The ligand design approach presented here is the computational analogue of mirror image phage display. The results have been used to characterize the interactions responsible for formation of this model anti-parallel coiled coil and to suggest potential ligands to disrupt it.

Computational characterization of ordered nanostructured surfaces

NASA Astrophysics Data System (ADS)

Mohieddin Abukhdeir, Nasser

2016-08-01

A vital and challenging task for materials researchers is to determine relationships between material characteristics and desired properties. While the measurement and assessment of material properties can be complex, quantitatively characterizing their structure is frequently a more challenging task. This issue is magnified for materials researchers in the areas of nanoscience and nanotechnology, where material structure is further complicated by phenomena such as self-assembly, collective behavior, and measurement uncertainty. Recent progress has been made in this area for both self-assembled and nanostructured surfaces due to increasing accessibility of imaging techniques at the nanoscale. In this context, recent advances in nanomaterial surface structure characterization are reviewed including the development of new theory and image processing methods.

Tertiary structure-based analysis of microRNA–target interactions

PubMed Central

Gan, Hin Hark; Gunsalus, Kristin C.

2013-01-01

Current computational analysis of microRNA interactions is based largely on primary and secondary structure analysis. Computationally efficient tertiary structure-based methods are needed to enable more realistic modeling of the molecular interactions underlying miRNA-mediated translational repression. We incorporate algorithms for predicting duplex RNA structures, ionic strength effects, duplex entropy and free energy, and docking of duplex–Argonaute protein complexes into a pipeline to model and predict miRNA–target duplex binding energies. To ensure modeling accuracy and computational efficiency, we use an all-atom description of RNA and a continuum description of ionic interactions using the Poisson–Boltzmann equation. Our method predicts the conformations of two constructs of Caenorhabditis elegans let-7 miRNA–target duplexes to an accuracy of ∼3.8 Å root mean square distance of their NMR structures. We also show that the computed duplex formation enthalpies, entropies, and free energies for eight miRNA–target duplexes agree with titration calorimetry data. Analysis of duplex–Argonaute docking shows that structural distortions arising from single-base-pair mismatches in the seed region influence the activity of the complex by destabilizing both duplex hybridization and its association with Argonaute. Collectively, these results demonstrate that tertiary structure-based modeling of miRNA interactions can reveal structural mechanisms not accessible with current secondary structure-based methods. PMID:23417009

Causal learning with local computations.

PubMed

Fernbach, Philip M; Sloman, Steven A

2009-05-01

The authors proposed and tested a psychological theory of causal structure learning based on local computations. Local computations simplify complex learning problems via cues available on individual trials to update a single causal structure hypothesis. Structural inferences from local computations make minimal demands on memory, require relatively small amounts of data, and need not respect normative prescriptions as inferences that are principled locally may violate those principles when combined. Over a series of 3 experiments, the authors found (a) systematic inferences from small amounts of data; (b) systematic inference of extraneous causal links; (c) influence of data presentation order on inferences; and (d) error reduction through pretraining. Without pretraining, a model based on local computations fitted data better than a Bayesian structural inference model. The data suggest that local computations serve as a heuristic for learning causal structure. Copyright 2009 APA, all rights reserved.

Development of a Cloud Computing-Based Pier Type Port Structure Stability Evaluation Platform Using Fiber Bragg Grating Sensors.

PubMed

Jo, Byung Wan; Jo, Jun Ho; Khan, Rana Muhammad Asad; Kim, Jung Hoon; Lee, Yun Sung

2018-05-23

Structure Health Monitoring is a topic of great interest in port structures due to the ageing of structures and the limitations of evaluating structures. This paper presents a cloud computing-based stability evaluation platform for a pier type port structure using Fiber Bragg Grating (FBG) sensors in a system consisting of a FBG strain sensor, FBG displacement gauge, FBG angle meter, gateway, and cloud computing-based web server. The sensors were installed on core components of the structure and measurements were taken to evaluate the structures. The measurement values were transmitted to the web server via the gateway to analyze and visualize them. All data were analyzed and visualized in the web server to evaluate the structure based on the safety evaluation index (SEI). The stability evaluation platform for pier type port structures involves the efficient monitoring of the structures which can be carried out easily anytime and anywhere by converging new technologies such as cloud computing and FBG sensors. In addition, the platform has been successfully implemented at “Maryang Harbor” situated in Maryang-Meyon of Korea to test its durability.

Automated eddy current analysis of materials

NASA Technical Reports Server (NTRS)

Workman, Gary L.

1990-01-01

This research effort focused on the use of eddy current techniques for characterizing flaws in graphite-based filament-wound cylindrical structures. A major emphasis was on incorporating artificial intelligence techniques into the signal analysis portion of the inspection process. Developing an eddy current scanning system using a commercial robot for inspecting graphite structures (and others) has been a goal in the overall concept and is essential for the final implementation for expert system interpretation. Manual scans, as performed in the preliminary work here, do not provide sufficiently reproducible eddy current signatures to be easily built into a real time expert system. The expert systems approach to eddy current signal analysis requires that a suitable knowledge base exist in which correct decisions as to the nature of the flaw can be performed. In eddy current or any other expert systems used to analyze signals in real time in a production environment, it is important to simplify computational procedures as much as possible. For that reason, we have chosen to use the measured resistance and reactance values for the preliminary aspects of this work. A simple computation, such as phase angle of the signal, is certainly within the real time processing capability of the computer system. In the work described here, there is a balance between physical measurements and finite element calculations of those measurements. The goal is to evolve into the most cost effective procedures for maintaining the correctness of the knowledge base.

A hybrid computational-experimental approach for automated crystal structure solution

NASA Astrophysics Data System (ADS)

Meredig, Bryce; Wolverton, C.

2013-02-01

Crystal structure solution from diffraction experiments is one of the most fundamental tasks in materials science, chemistry, physics and geology. Unfortunately, numerous factors render this process labour intensive and error prone. Experimental conditions, such as high pressure or structural metastability, often complicate characterization. Furthermore, many materials of great modern interest, such as batteries and hydrogen storage media, contain light elements such as Li and H that only weakly scatter X-rays. Finally, structural refinements generally require significant human input and intuition, as they rely on good initial guesses for the target structure. To address these many challenges, we demonstrate a new hybrid approach, first-principles-assisted structure solution (FPASS), which combines experimental diffraction data, statistical symmetry information and first-principles-based algorithmic optimization to automatically solve crystal structures. We demonstrate the broad utility of FPASS to clarify four important crystal structure debates: the hydrogen storage candidates MgNH and NH3BH3; Li2O2, relevant to Li-air batteries; and high-pressure silane, SiH4.

Fabrication, characterization, and heuristic trade space exploration of magnetically actuated Miura-Ori origami structures

NASA Astrophysics Data System (ADS)

Cowan, Brett; von Lockette, Paris R.

2017-04-01

The authors develop magnetically actuated Miura-Ori structures through observation, experiment, and computation using an initially heuristic strategy followed by trade space visualization and optimization. The work is novel, especially within origami engineering, in that beyond final target shape approximation, Miura-Ori structures in this work are additionally evaluated for the shape approximation while folding and for their efficient use of their embedded actuators. The structures consisted of neodymium magnets placed on the panels of silicone elastomer substrates cast in the Miura-Ori folding pattern. Initially four configurations, arrangements of magnets on the panels, were selected based on heuristic arguments that (1) maximized the amount of magnetic torque applied to the creases and (2) reduced the number of magnets needed to affect all creases in the pattern. The results of experimental and computational performance metrics were used in a weighted sum model to predict the optimum configuration, which was then fabricated and experimentally characterized for comparison to the initial prototypes. As expected, optimization of magnet placement and orientation was effective at increasing the degree of theoretical useful work. Somewhat unexpectedly, however, trade space results showed that even after optimization, the configuration with the most number of magnets was least effective, per magnet, at directing its actuation to the structure’s creases. Overall, though the winning configuration experimentally outperformed its initial, non-optimal counterparts, results showed that the choice of optimum configuration was heavily dependent on the weighting factors. These results highlight both the ability of the Miura-Ori to be actuated with external magnetic stimuli, the effectiveness of a heuristic design approach that focuses on the actuation mechanism, and the need to address path-dependent metrics in assessing performance in origami folding structures.

Modeling, estimation and identification methods for static shape determination of flexible structures. [for large space structure design

NASA Technical Reports Server (NTRS)

Rodriguez, G.; Scheid, R. E., Jr.

1986-01-01

This paper outlines methods for modeling, identification and estimation for static determination of flexible structures. The shape estimation schemes are based on structural models specified by (possibly interconnected) elliptic partial differential equations. The identification techniques provide approximate knowledge of parameters in elliptic systems. The techniques are based on the method of maximum-likelihood that finds parameter values such that the likelihood functional associated with the system model is maximized. The estimation methods are obtained by means of a function-space approach that seeks to obtain the conditional mean of the state given the data and a white noise characterization of model errors. The solutions are obtained in a batch-processing mode in which all the data is processed simultaneously. After methods for computing the optimal estimates are developed, an analysis of the second-order statistics of the estimates and of the related estimation error is conducted. In addition to outlining the above theoretical results, the paper presents typical flexible structure simulations illustrating performance of the shape determination methods.

A strategy for reducing turnaround time in design optimization using a distributed computer system

NASA Technical Reports Server (NTRS)

Young, Katherine C.; Padula, Sharon L.; Rogers, James L.

1988-01-01

There is a need to explore methods for reducing lengthly computer turnaround or clock time associated with engineering design problems. Different strategies can be employed to reduce this turnaround time. One strategy is to run validated analysis software on a network of existing smaller computers so that portions of the computation can be done in parallel. This paper focuses on the implementation of this method using two types of problems. The first type is a traditional structural design optimization problem, which is characterized by a simple data flow and a complicated analysis. The second type of problem uses an existing computer program designed to study multilevel optimization techniques. This problem is characterized by complicated data flow and a simple analysis. The paper shows that distributed computing can be a viable means for reducing computational turnaround time for engineering design problems that lend themselves to decomposition. Parallel computing can be accomplished with a minimal cost in terms of hardware and software.

Development of an Aeroelastic Modeling Capability for Transient Nozzle Side Load Analysis

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Zhao, Xiang; Zhang, Sijun; Chen, Yen-Sen

2013-01-01

Lateral nozzle forces are known to cause severe structural damage to any new rocket engine in development during test. While three-dimensional, transient, turbulent, chemically reacting computational fluid dynamics methodology has been demonstrated to capture major side load physics with rigid nozzles, hot-fire tests often show nozzle structure deformation during major side load events, leading to structural damages if structural strengthening measures were not taken. The modeling picture is incomplete without the capability to address the two-way responses between the structure and fluid. The objective of this study is to develop a coupled aeroelastic modeling capability by implementing the necessary structural dynamics component into an anchored computational fluid dynamics methodology. The computational fluid dynamics component is based on an unstructured-grid, pressure-based computational fluid dynamics formulation, while the computational structural dynamics component is developed in the framework of modal analysis. Transient aeroelastic nozzle startup analyses of the Block I Space Shuttle Main Engine at sea level were performed. The computed results from the aeroelastic nozzle modeling are presented.

Design component method for sensitivity analysis of built-up structures

NASA Technical Reports Server (NTRS)

Choi, Kyung K.; Seong, Hwai G.

1986-01-01

A 'design component method' that provides a unified and systematic organization of design sensitivity analysis for built-up structures is developed and implemented. Both conventional design variables, such as thickness and cross-sectional area, and shape design variables of components of built-up structures are considered. It is shown that design of components of built-up structures can be characterized and system design sensitivity expressions obtained by simply adding contributions from each component. The method leads to a systematic organization of computations for design sensitivity analysis that is similar to the way in which computations are organized within a finite element code.

Keto-enol tautomerism of (E)-2-[(3,4-dimethylphenylimino)methyl]-4-nitrophenol: Synthesis, X-ray, FT-IR, UV-Vis, NMR and quantum chemical characterizations

NASA Astrophysics Data System (ADS)

Özek Yıldırım, Arzu; Yıldırım, M. Hakkı; Albayrak Kaştaş, Çiǧdem

2017-01-01

(E)-2-((3,4-dimethylphenylimino)methyl)-4-nitrophenol, which is a new Schiff base compound, was synthesized and characterized by experimental and computational methods. Molecular geometry, harmonic oscillator model of aromaticity (HOMA) indices, intra- and inter-molecular interactions in the crystal structure were determined by using single crystal X-ray diffraction technique. The optimized structures, which are obtained by Gaussian and Slater type orbitals, were compared to experimental structures to determine how much correlation is found between the experimental and the calculated properties. Intramolecular and hyperconjugative interactions of bonds have been found by Natural Bond Orbital analysis. The experimental infrared spectrum of the compound has been analyzed in detail by the calculated infrared spectra and Potential Energy Distribution analysis. To find out about the correlation between the solvent polarity and the enol-keto equilibrium, experimental UV-Visible spectra of the compound were obtained in benzene, CHCl3, EtOH and DMSO solvents. In these solvents, the UV-Vis spectra and relaxed potential energy surface scan (PES) calculations have been performed to get more insight into the equilibrium dynamics. Solvent effects in UV-Vis and PES calculations have been taken into account by using Polarizable Continuum Modelling method. 1H and 13C NMR spectra of the compound (in DMSO) were analyzed. The computational study of nonlinear optical properties shows that the compound can be used for the development of nonlinear optical materials.

New approaches to high-throughput structure characterization of SH3 complexes: the example of Myosin-3 and Myosin-5 SH3 domains from S. cerevisiae.

PubMed

Musi, Valeria; Birdsall, Berry; Fernandez-Ballester, Gregorio; Guerrini, Remo; Salvatori, Severo; Serrano, Luis; Pastore, Annalisa

2006-04-01

SH3 domains are small protein modules that are involved in protein-protein interactions in several essential metabolic pathways. The availability of the complete genome and the limited number of clearly identifiable SH3 domains make the yeast Saccharomyces cerevisae an ideal proteomic-based model system to investigate the structural rules dictating the SH3-mediated protein interactions and to develop new tools to assist these studies. In the present work, we have determined the solution structure of the SH3 domain from Myo3 and modeled by homology that of the highly homologous Myo5, two myosins implicated in actin polymerization. We have then implemented an integrated approach that makes use of experimental and computational methods to characterize their binding properties. While accommodating their targets in the classical groove, the two domains have selectivity in both orientation and sequence specificity of the target peptides. From our study, we propose a consensus sequence that may provide a useful guideline to identify new natural partners and suggest a strategy of more general applicability that may be of use in other structural proteomic studies.

Mapping the Small Molecule Interactome by Mass Spectrometry.

PubMed

Flaxman, Hope A; Woo, Christina M

2018-01-16

Mapping small molecule interactions throughout the proteome provides the critical structural basis for functional analysis of their impact on biochemistry. However, translation of mass spectrometry-based proteomics methods to directly profile the interaction between a small molecule and the whole proteome is challenging because of the substoichiometric nature of many interactions, the diversity of covalent and noncovalent interactions involved, and the subsequent computational complexity associated with their spectral assignment. Recent advances in chemical proteomics have begun fill this gap to provide a structural basis for the breadth of small molecule-protein interactions in the whole proteome. Innovations enabling direct characterization of the small molecule interactome include faster, more sensitive instrumentation coupled to chemical conjugation, enrichment, and labeling methods that facilitate detection and assignment. These methods have started to measure molecular interaction hotspots due to inherent differences in local amino acid reactivity and binding affinity throughout the proteome. Measurement of the small molecule interactome is producing structural insights and methods for probing and engineering protein biochemistry. Direct structural characterization of the small molecule interactome is a rapidly emerging area pushing new frontiers in biochemistry at the interface of small molecules and the proteome.

Probing RNA Native Conformational Ensembles with Structural Constraints.

PubMed

Fonseca, Rasmus; van den Bedem, Henry; Bernauer, Julie

2016-05-01

Noncoding ribonucleic acids (RNA) play a critical role in a wide variety of cellular processes, ranging from regulating gene expression to post-translational modification and protein synthesis. Their activity is modulated by highly dynamic exchanges between three-dimensional conformational substates, which are difficult to characterize experimentally and computationally. Here, we present an innovative, entirely kinematic computational procedure to efficiently explore the native ensemble of RNA molecules. Our procedure projects degrees of freedom onto a subspace of conformation space defined by distance constraints in the tertiary structure. The dimensionality reduction enables efficient exploration of conformational space. We show that the conformational distributions obtained with our method broadly sample the conformational landscape observed in NMR experiments. Compared to normal mode analysis-based exploration, our procedure diffuses faster through the experimental ensemble while also accessing conformational substates to greater precision. Our results suggest that conformational sampling with a highly reduced but fully atomistic representation of noncoding RNA expresses key features of their dynamic nature.

Computer Modeling of the Structure and Spectra of Fluorescent Proteins

PubMed Central

Grigorenko, B.L.; Savitsky, A.P.

2009-01-01

Fluorescent proteins from the family of green fluorescent proteins are intensively used as biomarkers in living systems. The chromophore group based on the hydroxybenzylidene-imidazoline molecule, which is formed in nature from three amino-acid residues inside the protein globule and well shielded from external media, is responsible for light absorption and fluorescence. Along with the intense experimental studies of the properties of fluorescent proteins and their chromophores by biochemical, X-ray, and spectroscopic tools, in recent years, computer modeling has been used to characterize their properties and spectra. We present in this review the most interesting results of the molecular modeling of the structural parameters and optical and vibrational spectra of the chromophorecontaining domains of fluorescent proteins by methods of quantum chemistry, molecular dynamics, and combined quantum-mechanical-molecular-mechanical approaches. The main emphasis is on the correlation of theoretical and experimental data and on the predictive power of modeling, which may be useful for creating new, efficient biomarkers. PMID:22649601

Characterization of biomechanical properties of cells through dielectrophoresis-based cell stretching and actin cytoskeleton modeling.

PubMed

Bai, Guohua; Li, Ying; Chu, Henry K; Wang, Kaiqun; Tan, Qiulin; Xiong, Jijun; Sun, Dong

2017-04-04

Cytoskeleton is a highly dynamic network that helps to maintain the rigidity of a cell, and the mechanical properties of a cell are closely related to many cellular functions. This paper presents a new method to probe and characterize cell mechanical properties through dielectrophoresis (DEP)-based cell stretching manipulation and actin cytoskeleton modeling. Leukemia NB4 cells were used as cell line, and changes in their biological properties were examined after chemotherapy treatment with doxorubicin (DOX). DEP-integrated microfluidic chip was utilized as a low-cost and efficient tool to study the deformability of cells. DEP forces used in cell stretching were first evaluated through computer simulation, and the results were compared with modeling equations and with the results of optical stretching (OT) experiments. Structural parameters were then extracted by fitting the experimental data into the actin cytoskeleton model, and the underlying mechanical properties of the cells were subsequently characterized. The DEP forces generated under different voltage inputs were calculated and the results from different approaches demonstrate good approximations to the force estimation. Both DEP and OT stretching experiments confirmed that DOX-treated NB4 cells were stiffer than the untreated cells. The structural parameters extracted from the model and the confocal images indicated significant change in actin network after DOX treatment. The proposed DEP method combined with actin cytoskeleton modeling is a simple engineering tool to characterize the mechanical properties of cells.

Characterization of Viscoelastic Materials Through an Active Mixer by Direct-Ink Writing

NASA Astrophysics Data System (ADS)

Drake, Eric

The goal of this thesis is two-fold: First, to determine mixing effectiveness of an active mixer attachment to a three-dimensional (3D) printer by characterizing actively-mixed, three-dimensionally printed silicone elastomers. Second, to understand mechanical properties of a printed lattice structure with varying geometry and composition. Ober et al defines mixing effectiveness as a measureable quantity characterized by two key variables: (i) a dimensionless impeller parameter (O ) that depends on mixer geometry as well as Peclet number (Pe) and (ii) a coefficient of variation (COV) that describes the mixer effectiveness based upon image intensity. The first objective utilizes tungsten tracer particles distributed throughout a batch of Dow Corning SE1700 (two parts silicone) - ink "A". Ink "B" is made from pure SE1700. Using the in-site active mixer, both ink "A" and "B" coalesce to form a hybrid ink just before extrusion. Two samples of varying mixer speeds and composition ratios are printed and analyzed by microcomputed tomography (MicroCT). A continuous stirred tank reactor (CSTR) model is applied to better understand mixing behavior. Results are then compared with computer models to verify the hypothesis. Data suggests good mixing for the sample with higher impeller speed. A Radial Distrubtion Function (RDF) macro is used to provide further qualitative analysis of mixing efficiency. The second objective of this thesis utilized three-dimensionally printed samples of varying geometry and composition to ascertain mechanical properties. Samples were printed using SE1700 provided by Lawrence Livermore National Laboratory with a face-centered tetragonal (FCT) structure. Hardness testing is conducted using a Shore OO durometer guided by a computer-controlled, three-axis translation stage to provide precise movements. Data is collected across an 'x-y' plane of the specimen. To explain the data, a simply supported beam model is applied to a single unit cell which yields basic structural behavior per cell. Characterizing the sample as a whole requires a more rigorous approach and non-trivial complexities due to varying geometries and compositions exist. The data demonstrates a uniform change in hardness as a function of position. Additionally, the data indicates periodicities in the lattice structure.

Algorithms and software used in selecting structure of machine-training cluster based on neurocomputers

NASA Astrophysics Data System (ADS)

Romanchuk, V. A.; Lukashenko, V. V.

2018-05-01

The technique of functioning of a control system by a computing cluster based on neurocomputers is proposed. Particular attention is paid to the method of choosing the structure of the computing cluster due to the fact that the existing methods are not effective because of a specialized hardware base - neurocomputers, which are highly parallel computer devices with an architecture different from the von Neumann architecture. A developed algorithm for choosing the computational structure of a cloud cluster is described, starting from the direction of data transfer in the flow control graph of the program and its adjacency matrix.

Investigation of Thermal Effects of Photocoagulation on Retinal Tissue Using Fine-Motion-Sensitive Dynamic Optical Coherence Tomography.

PubMed

Kurokawa, Kazuhiro; Makita, Shuichi; Yasuno, Yoshiaki

2016-01-01

To enable an objective evaluation of photocoagulation, we characterize thermal tissue changes induced by laser irradiation with different laser parameters using optical coherence tomography (OCT). Spectral-domain OCT with a newly developed image processing method was used to monitor the thermal changes of ex vivo porcine retina. A sequence of OCT B-scans was obtained at the same retinal position simultaneously with the photocoagulation. Cross-sectional tissue displacement maps with respect to an OCT image taken before laser irradiation were computed for images taken before, during, and after laser irradiation, by using a correlation-based custom algorithm. Cross-sectional correlation maps (OCT correlation maps) were also computed from an OCT image taken before laser irradiation as a base-line to visualize alterations of tissue microstructure induced by laser irradiation. By systematically controlling laser power and exposure times, tissue displacements and structural changes of 200 retinal regions of 10 porcine eyes were characterized. Thermal tissue changes were characterized by B-scan images, OCT correlation maps, and tissue displacement maps. Larger tissue deformation was induced with higher laser power and shorter exposure time, while the same total laser energy (10 mJ) was applied. The measured tissue displacements revealed the complicated dynamics of tissue displacements. Three types of dynamics were observed; lateral expansion, lateral constriction, and a type showing more complicated dynamics. The results demonstrated the ability of this OCT-based method to evaluate retinal changes induced by laser irradiation. This evaluation could lead to further understanding of thermal effects, and increasing reproducibility of photocoagulation therapy.

High-efficiency AlGaAs-GaAs Cassegrainian concentrator cells

NASA Technical Reports Server (NTRS)

Werthen, J. G.; Hamaker, H. C.; Virshup, G. F.; Lewis, C. R.; Ford, C. W.

1985-01-01

AlGaAs-GaAs heteroface space concentrator solar cells have been fabricated by metalorganic chemical vapor deposition. AMO efficiencies as high as 21.1% have been observed both for p-n and np structures under concentration (90 to 100X) at 25 C. Both cell structures are characterized by high quantum efficiencies and their performances are close to those predicted by a realistic computer model. In agreement with the computer model, the n-p cell exhibits a higher short-circuit current density.

X-ray coherent scattering tomography of textured material (Conference Presentation)

NASA Astrophysics Data System (ADS)

Zhu, Zheyuan; Pang, Shuo

2017-05-01

Small-angle X-ray scattering (SAXS) measures the signature of angular-dependent coherently scattered X-rays, which contains richer information in material composition and structure compared to conventional absorption-based computed tomography. SAXS image reconstruction method of a 2 or 3 dimensional object based on computed tomography, termed as coherent scattering computed tomography (CSCT), enables the detection of spatially-resolved, material-specific isotropic scattering signature inside an extended object, and provides improved contrast for medical diagnosis, security screening, and material characterization applications. However, traditional CSCT methods assumes materials are fine powders or amorphous, and possess isotropic scattering profiles, which is not generally true for all materials. Anisotropic scatters cannot be captured using conventional CSCT method and result in reconstruction errors. To obtain correct information from the sample, we designed new imaging strategy which incorporates extra degree of detector motion into X-ray scattering tomography for the detection of anisotropic scattered photons from a series of two-dimensional intensity measurements. Using a table-top, narrow-band X-ray source and a panel detector, we demonstrate the anisotropic scattering profile captured from an extended object and the reconstruction of a three-dimensional object. For materials possessing a well-organized crystalline structure with certain symmetry, the scatter texture is more predictable. We will also discuss the compressive schemes and implementation of data acquisition to improve the collection efficiency and accelerate the imaging process.

Structural, Linguistic and Topic Variables in Verbal and Computational Problems in Elementary Mathematics.

ERIC Educational Resources Information Center

Beardslee, Edward C.; Jerman, Max E.

Five structural, four linguistic and twelve topic variables are used in regression analyses on results of a 50-item achievement test. The test items are related to 12 topics from the third-grade mathematics curriculum. The items reflect one of two cases of the structural variable, cognitive level; the two levels are characterized, inductive…

L-shaped benzimidazole fluorophores: synthesis, characterization and optical response to bases, acids and anions.

PubMed

Lirag, Rio Carlo; Le, Ha T M; Miljanić, Ognjen Š

2013-05-14

Nine L-shaped benzimidazole fluorophores have been synthesized, computationally evaluated and spectroscopically characterized. These "half-cruciform" fluorophores respond to bases, acids and anions through changes in fluorescence that vary from moderate to dramatic.

An Adaptive Evaluation Structure for Computer-Based Instruction.

ERIC Educational Resources Information Center

Welsh, William A.

Adaptive Evaluation Structure (AES) is a set of linked computer programs designed to increase the effectiveness of interactive computer-assisted instruction at the college level. The package has four major features, the first of which is based on a prior cognitive inventory and on the accuracy and pace of student responses. AES adjusts materials…

Protein binding hot spots prediction from sequence only by a new ensemble learning method.

PubMed

Hu, Shan-Shan; Chen, Peng; Wang, Bing; Li, Jinyan

2017-10-01

Hot spots are interfacial core areas of binding proteins, which have been applied as targets in drug design. Experimental methods are costly in both time and expense to locate hot spot areas. Recently, in-silicon computational methods have been widely used for hot spot prediction through sequence or structure characterization. As the structural information of proteins is not always solved, and thus hot spot identification from amino acid sequences only is more useful for real-life applications. This work proposes a new sequence-based model that combines physicochemical features with the relative accessible surface area of amino acid sequences for hot spot prediction. The model consists of 83 classifiers involving the IBk (Instance-based k means) algorithm, where instances are encoded by important properties extracted from a total of 544 properties in the AAindex1 (Amino Acid Index) database. Then top-performance classifiers are selected to form an ensemble by a majority voting technique. The ensemble classifier outperforms the state-of-the-art computational methods, yielding an F1 score of 0.80 on the benchmark binding interface database (BID) test set. http://www2.ahu.edu.cn/pchen/web/HotspotEC.htm .

Computational design and experimental verification of a symmetric protein homodimer.

PubMed

Mou, Yun; Huang, Po-Ssu; Hsu, Fang-Ciao; Huang, Shing-Jong; Mayo, Stephen L

2015-08-25

Homodimers are the most common type of protein assembly in nature and have distinct features compared with heterodimers and higher order oligomers. Understanding homodimer interactions at the atomic level is critical both for elucidating their biological mechanisms of action and for accurate modeling of complexes of unknown structure. Computation-based design of novel protein-protein interfaces can serve as a bottom-up method to further our understanding of protein interactions. Previous studies have demonstrated that the de novo design of homodimers can be achieved to atomic-level accuracy by β-strand assembly or through metal-mediated interactions. Here, we report the design and experimental characterization of a α-helix-mediated homodimer with C2 symmetry based on a monomeric Drosophila engrailed homeodomain scaffold. A solution NMR structure shows that the homodimer exhibits parallel helical packing similar to the design model. Because the mutations leading to dimer formation resulted in poor thermostability of the system, design success was facilitated by the introduction of independent thermostabilizing mutations into the scaffold. This two-step design approach, function and stabilization, is likely to be generally applicable, especially if the desired scaffold is of low thermostability.

Multi-dimensional upwinding-based implicit LES for the vorticity transport equations

NASA Astrophysics Data System (ADS)

Foti, Daniel; Duraisamy, Karthik

2017-11-01

Complex turbulent flows such as rotorcraft and wind turbine wakes are characterized by the presence of strong coherent structures that can be compactly described by vorticity variables. The vorticity-velocity formulation of the incompressible Navier-Stokes equations is employed to increase numerical efficiency. Compared to the traditional velocity-pressure formulation, high order numerical methods and sub-grid scale models for the vorticity transport equation (VTE) have not been fully investigated. Consistent treatment of the convection and stretching terms also needs to be addressed. Our belief is that, by carefully designing sharp gradient-capturing numerical schemes, coherent structures can be more efficiently captured using the vorticity-velocity formulation. In this work, a multidimensional upwind approach for the VTE is developed using the generalized Riemann problem-based scheme devised by Parish et al. (Computers & Fluids, 2016). The algorithm obtains high resolution by augmenting the upwind fluxes with transverse and normal direction corrections. The approach is investigated with several canonical vortex-dominated flows including isolated and interacting vortices and turbulent flows. The capability of the technique to represent sub-grid scale effects is also assessed. Navy contract titled ``Turbulence Modelling Across Disparate Length Scales for Naval Computational Fluid Dynamics Applications,'' through Continuum Dynamics, Inc.

ClustENM: ENM-Based Sampling of Essential Conformational Space at Full Atomic Resolution

PubMed Central

Kurkcuoglu, Zeynep; Bahar, Ivet; Doruker, Pemra

2016-01-01

Accurate sampling of conformational space and, in particular, the transitions between functional substates has been a challenge in molecular dynamic (MD) simulations of large biomolecular systems. We developed an Elastic Network Model (ENM)-based computational method, ClustENM, for sampling large conformational changes of biomolecules with various sizes and oligomerization states. ClustENM is an iterative method that combines ENM with energy minimization and clustering steps. It is an unbiased technique, which requires only an initial structure as input, and no information about the target conformation. To test the performance of ClustENM, we applied it to six biomolecular systems: adenylate kinase (AK), calmodulin, p38 MAP kinase, HIV-1 reverse transcriptase (RT), triosephosphate isomerase (TIM), and the 70S ribosomal complex. The generated ensembles of conformers determined at atomic resolution show good agreement with experimental data (979 structures resolved by X-ray and/or NMR) and encompass the subspaces covered in independent MD simulations for TIM, p38, and RT. ClustENM emerges as a computationally efficient tool for characterizing the conformational space of large systems at atomic detail, in addition to generating a representative ensemble of conformers that can be advantageously used in simulating substrate/ligand-binding events. PMID:27494296

Plant Identification Based on Leaf Midrib Cross-Section Images Using Fractal Descriptors.

PubMed

da Silva, Núbia Rosa; Florindo, João Batista; Gómez, María Cecilia; Rossatto, Davi Rodrigo; Kolb, Rosana Marta; Bruno, Odemir Martinez

2015-01-01

The correct identification of plants is a common necessity not only to researchers but also to the lay public. Recently, computational methods have been employed to facilitate this task, however, there are few studies front of the wide diversity of plants occurring in the world. This study proposes to analyse images obtained from cross-sections of leaf midrib using fractal descriptors. These descriptors are obtained from the fractal dimension of the object computed at a range of scales. In this way, they provide rich information regarding the spatial distribution of the analysed structure and, as a consequence, they measure the multiscale morphology of the object of interest. In Biology, such morphology is of great importance because it is related to evolutionary aspects and is successfully employed to characterize and discriminate among different biological structures. Here, the fractal descriptors are used to identify the species of plants based on the image of their leaves. A large number of samples are examined, being 606 leaf samples of 50 species from Brazilian flora. The results are compared to other imaging methods in the literature and demonstrate that fractal descriptors are precise and reliable in the taxonomic process of plant species identification.

Quantitative characterization of the carbon/carbon composites components based on video of polarized light microscope.

PubMed

Li, Yixian; Qi, Lehua; Song, Yongshan; Chao, Xujiang

2017-06-01

The components of carbon/carbon (C/C) composites have significant influence on the thermal and mechanical properties, so a quantitative characterization of component is necessary to study the microstructure of C/C composites, and further to improve the macroscopic properties of C/C composites. Considering the extinction crosses of the pyrocarbon matrix have significant moving features, the polarized light microscope (PLM) video is used to characterize C/C composites quantitatively because it contains sufficiently dynamic and structure information. Then the optical flow method is introduced to compute the optical flow field between the adjacent frames, and segment the components of C/C composites from PLM image by image processing. Meanwhile the matrix with different textures is re-segmented by the length difference of motion vectors, and then the component fraction of each component and extinction angle of pyrocarbon matrix are calculated directly. Finally, the C/C composites are successfully characterized from three aspects of carbon fiber, pyrocarbon, and pores by a series of image processing operators based on PLM video, and the errors of component fractions are less than 15%. © 2017 Wiley Periodicals, Inc.

Automated selection of stabilizing mutations in designed and natural proteins.

PubMed

Borgo, Benjamin; Havranek, James J

2012-01-31

The ability to engineer novel protein folds, conformations, and enzymatic activities offers enormous potential for the development of new protein therapeutics and biocatalysts. However, many de novo and redesigned proteins exhibit poor hydrophobic packing in their predicted structures, leading to instability or insolubility. The general utility of rational, structure-based design would greatly benefit from an improved ability to generate well-packed conformations. Here we present an automated protocol within the RosettaDesign framework that can identify and improve poorly packed protein cores by selecting a series of stabilizing point mutations. We apply our method to previously characterized designed proteins that exhibited a decrease in stability after a full computational redesign. We further demonstrate the ability of our method to improve the thermostability of a well-behaved native protein. In each instance, biophysical characterization reveals that we were able to stabilize the original proteins against chemical and thermal denaturation. We believe our method will be a valuable tool for both improving upon designed proteins and conferring increased stability upon native proteins.

Automated selection of stabilizing mutations in designed and natural proteins

PubMed Central

Borgo, Benjamin; Havranek, James J.

2012-01-01

The ability to engineer novel protein folds, conformations, and enzymatic activities offers enormous potential for the development of new protein therapeutics and biocatalysts. However, many de novo and redesigned proteins exhibit poor hydrophobic packing in their predicted structures, leading to instability or insolubility. The general utility of rational, structure-based design would greatly benefit from an improved ability to generate well-packed conformations. Here we present an automated protocol within the RosettaDesign framework that can identify and improve poorly packed protein cores by selecting a series of stabilizing point mutations. We apply our method to previously characterized designed proteins that exhibited a decrease in stability after a full computational redesign. We further demonstrate the ability of our method to improve the thermostability of a well-behaved native protein. In each instance, biophysical characterization reveals that we were able to stabilize the original proteins against chemical and thermal denaturation. We believe our method will be a valuable tool for both improving upon designed proteins and conferring increased stability upon native proteins. PMID:22307603

Energetics and Structural Characterization of the large-scale Functional Motion of Adenylate Kinase

PubMed Central

Formoso, Elena; Limongelli, Vittorio; Parrinello, Michele

2015-01-01

Adenylate Kinase (AK) is a signal transducing protein that regulates cellular energy homeostasis balancing between different conformations. An alteration of its activity can lead to severe pathologies such as heart failure, cancer and neurodegenerative diseases. A comprehensive elucidation of the large-scale conformational motions that rule the functional mechanism of this enzyme is of great value to guide rationally the development of new medications. Here using a metadynamics-based computational protocol we elucidate the thermodynamics and structural properties underlying the AK functional transitions. The free energy estimation of the conformational motions of the enzyme allows characterizing the sequence of events that regulate its action. We reveal the atomistic details of the most relevant enzyme states, identifying residues such as Arg119 and Lys13, which play a key role during the conformational transitions and represent druggable spots to design enzyme inhibitors. Our study offers tools that open new areas of investigation on large-scale motion in proteins. PMID:25672826

Energetics and Structural Characterization of the large-scale Functional Motion of Adenylate Kinase

NASA Astrophysics Data System (ADS)

Formoso, Elena; Limongelli, Vittorio; Parrinello, Michele

2015-02-01

Adenylate Kinase (AK) is a signal transducing protein that regulates cellular energy homeostasis balancing between different conformations. An alteration of its activity can lead to severe pathologies such as heart failure, cancer and neurodegenerative diseases. A comprehensive elucidation of the large-scale conformational motions that rule the functional mechanism of this enzyme is of great value to guide rationally the development of new medications. Here using a metadynamics-based computational protocol we elucidate the thermodynamics and structural properties underlying the AK functional transitions. The free energy estimation of the conformational motions of the enzyme allows characterizing the sequence of events that regulate its action. We reveal the atomistic details of the most relevant enzyme states, identifying residues such as Arg119 and Lys13, which play a key role during the conformational transitions and represent druggable spots to design enzyme inhibitors. Our study offers tools that open new areas of investigation on large-scale motion in proteins.

Experimental study and numerical simulation on the structural and mechanical properties of Typha leaves through multimodal microscopy approaches.

PubMed

Liu, Jingjing; Zhang, Zhihui; Yu, Zhenglei; Liang, Yunhong; Li, Xiujuan; Ren, Luquan

2018-01-01

The Typha leaf, with special multi-level structure, low density and excellent mechanical properties, is an ideal bionic prototype utilized for lightweight design. In order to further study the relationship between the structure and mechanical properties, the three-dimensional macroscopic morphology of Typha leaves was characterized by micro computed tomography (Micro-CT) and its internal microstructure was observed by scanning electron microscopy (SEM). The combination of experimental and computational research was carried out in this paper, to reveal and verify the effect of multi-level structure on the mechanical properties. A universal testing machine and a self-developed mechanical testing apparatus with high precision and low load were used to measure the mechanical properties of the axial compression and lateral bending of the leaves, respectively. Three models with different internal structures were established based on the above-mentioned three-dimensional morphologies. The result demonstrated that the structure of partitions and diaphragms within the Typha leaf could form a reinforcement ribs structure which could provide multiple load paths and make the process of compression and bending difficult. The further nonlinear finite element analysis through LS-DYNA proved that internal structure could improve the ability of the models to resist compression and deformation. The investigation can be the reference for lightweight thin-walled structure design and inspire the application of the bionic structural materials. Copyright © 2017 Elsevier Ltd. All rights reserved.

Discovering Coherent Structures Using Local Causal States

NASA Astrophysics Data System (ADS)

Rupe, Adam; Crutchfield, James P.; Kashinath, Karthik; Prabhat, Mr.

2017-11-01

Coherent structures were introduced in the study of fluid dynamics and were initially defined as regions characterized by high levels of coherent vorticity, i.e. regions where instantaneously space and phase correlated vorticity are high. In a more general spatiotemporal setting, coherent structures can be seen as localized broken symmetries which persist in time. Building off the computational mechanics framework, which integrates tools from computation and information theory to capture pattern and structure in nonlinear dynamical systems, we introduce a theory of coherent structures, in the more general sense. Central to computational mechanics is the causal equivalence relation, and a local spatiotemporal generalization of it is used to construct the local causal states, which are utilized to uncover a system's spatiotemporal symmetries. Coherent structures are then identified as persistent, localized deviations from these symmetries. We illustrate how novel patterns and structures can be discovered in cellular automata and outline the path from them to laminar, transitional and turbulent flows. Funded by Intel through the Big Data Center at LBNL and the IPCC at UC Davis.

Computational structure analysis of biomacromolecule complexes by interface geometry.

PubMed

Mahdavi, Sedigheh; Salehzadeh-Yazdi, Ali; Mohades, Ali; Masoudi-Nejad, Ali

2013-12-01

The ability to analyze and compare protein-nucleic acid and protein-protein interaction interface has critical importance in understanding the biological function and essential processes occurring in the cells. Since high-resolution three-dimensional (3D) structures of biomacromolecule complexes are available, computational characterizing of the interface geometry become an important research topic in the field of molecular biology. In this study, the interfaces of a set of 180 protein-nucleic acid and protein-protein complexes are computed to understand the principles of their interactions. The weighted Voronoi diagram of the atoms and the Alpha complex has provided an accurate description of the interface atoms. Our method is implemented in the presence and absence of water molecules. A comparison among the three types of interaction interfaces show that RNA-protein complexes have the largest size of an interface. The results show a high correlation coefficient between our method and the PISA server in the presence and absence of water molecules in the Voronoi model and the traditional model based on solvent accessibility and the high validation parameters in comparison to the classical model. Copyright © 2013 Elsevier Ltd. All rights reserved.

Estimation and Identifiability of Model Parameters in Human Nociceptive Processing Using Yes-No Detection Responses to Electrocutaneous Stimulation.

PubMed

Yang, Huan; Meijer, Hil G E; Buitenweg, Jan R; van Gils, Stephan A

2016-01-01

Healthy or pathological states of nociceptive subsystems determine different stimulus-response relations measured from quantitative sensory testing. In turn, stimulus-response measurements may be used to assess these states. In a recently developed computational model, six model parameters characterize activation of nerve endings and spinal neurons. However, both model nonlinearity and limited information in yes-no detection responses to electrocutaneous stimuli challenge to estimate model parameters. Here, we address the question whether and how one can overcome these difficulties for reliable parameter estimation. First, we fit the computational model to experimental stimulus-response pairs by maximizing the likelihood. To evaluate the balance between model fit and complexity, i.e., the number of model parameters, we evaluate the Bayesian Information Criterion. We find that the computational model is better than a conventional logistic model regarding the balance. Second, our theoretical analysis suggests to vary the pulse width among applied stimuli as a necessary condition to prevent structural non-identifiability. In addition, the numerically implemented profile likelihood approach reveals structural and practical non-identifiability. Our model-based approach with integration of psychophysical measurements can be useful for a reliable assessment of states of the nociceptive system.

On the interaction structure of linear multi-input feedback control systems. M.S. Thesis; [problem solving, lattices (mathematics)

NASA Technical Reports Server (NTRS)

Wong, P. K.

1975-01-01

The closely-related problems of designing reliable feedback stabilization strategy and coordinating decentralized feedbacks are considered. Two approaches are taken. A geometric characterization of the structure of control interaction (and its dual) was first attempted and a concept of structural homomorphism developed based on the idea of 'similarity' of interaction pattern. The idea of finding classes of individual feedback maps that do not 'interfere' with the stabilizing action of each other was developed by identifying the structural properties of nondestabilizing and LQ-optimal feedback maps. Some known stability properties of LQ-feedback were generalized and some partial solutions were provided to the reliable stabilization and decentralized feedback coordination problems. A concept of coordination parametrization was introduced, and a scheme for classifying different modes of decentralization (information, control law computation, on-line control implementation) in control systems was developed.

Mitochondrial network complexity emerges from fission/fusion dynamics.

PubMed

Zamponi, Nahuel; Zamponi, Emiliano; Cannas, Sergio A; Billoni, Orlando V; Helguera, Pablo R; Chialvo, Dante R

2018-01-10

Mitochondrial networks exhibit a variety of complex behaviors, including coordinated cell-wide oscillations of energy states as well as a phase transition (depolarization) in response to oxidative stress. Since functional and structural properties are often interwinded, here we characterized the structure of mitochondrial networks in mouse embryonic fibroblasts using network tools and percolation theory. Subsequently we perturbed the system either by promoting the fusion of mitochondrial segments or by inducing mitochondrial fission. Quantitative analysis of mitochondrial clusters revealed that structural parameters of healthy mitochondria laid in between the extremes of highly fragmented and completely fusioned networks. We confirmed our results by contrasting our empirical findings with the predictions of a recently described computational model of mitochondrial network emergence based on fission-fusion kinetics. Altogether these results offer not only an objective methodology to parametrize the complexity of this organelle but also support the idea that mitochondrial networks behave as critical systems and undergo structural phase transitions.

Pre- and Post-Processing Tools to Create and Characterize Particle-Based Composite Model Structures

DTIC Science & Technology

2017-11-01

ARL-TR-8213 ● NOV 2017 US Army Research Laboratory Pre- and Post -Processing Tools to Create and Characterize Particle-Based...ARL-TR-8213 ● NOV 2017 US Army Research Laboratory Pre- and Post -Processing Tools to Create and Characterize Particle-Based Composite...AND SUBTITLE Pre- and Post -Processing Tools to Create and Characterize Particle-Based Composite Model Structures 5a. CONTRACT NUMBER 5b. GRANT

An assisted navigation training framework based on judgment theory using sparse and discrete human-machine interfaces.

PubMed

Lopes, Ana C; Nunes, Urbano

2009-01-01

This paper aims to present a new framework to train people with severe motor disabilities steering an assisted mobile robot (AMR), such as a powered wheelchair. Users with high level of motor disabilities are not able to use standard HMIs, which provide a continuous command signal (e. g. standard joystick). For this reason HMIs providing a small set of simple commands, which are sparse and discrete in time must be used (e. g. scanning interface, or brain computer interface), making very difficult to steer the AMR. In this sense, the assisted navigation training framework (ANTF) is designed to train users driving the AMR, in indoor structured environments, using this type of HMIs. Additionally it provides user characterization on steering the robot, which will later be used to adapt the AMR navigation system to human competence steering the AMR. A rule-based lens (RBL) model is used to characterize users on driving the AMR. Individual judgment performance choosing the best manoeuvres is modeled using a genetic-based policy capturing (GBPC) technique characterized to infer non-compensatory judgment strategies from human decision data. Three user models, at three different learning stages, using the RBL paradigm, are presented.

The electronic structure of Au25 clusters: between discrete and continuous

NASA Astrophysics Data System (ADS)

Katsiev, Khabiboulakh; Lozova, Nataliya; Wang, Lu; Sai Krishna, Katla; Li, Ruipeng; Mei, Wai-Ning; Skrabalak, Sara E.; Kumar, Challa S. S. R.; Losovyj, Yaroslav

2016-08-01

Here, an approach based on synchrotron resonant photoemission is employed to explore the transition between quantization and hybridization of the electronic structure in atomically precise ligand-stabilized nanoparticles. While the presence of ligands maintains quantization in Au25 clusters, their removal renders increased hybridization of the electronic states in the vicinity of the Fermi level. These observations are supported by DFT studies.Here, an approach based on synchrotron resonant photoemission is employed to explore the transition between quantization and hybridization of the electronic structure in atomically precise ligand-stabilized nanoparticles. While the presence of ligands maintains quantization in Au25 clusters, their removal renders increased hybridization of the electronic states in the vicinity of the Fermi level. These observations are supported by DFT studies. Electronic supplementary information (ESI) available: Experimental details including chemicals, sample preparation, and characterization methods. Computation techniques, SV-AUC, GIWAXS, XPS, UPS, MALDI-TOF, ESI data of Au25 clusters. See DOI: 10.1039/c6nr02374f

New fluorescent azo-Schiff base Cu(II) and Zn(II) metal chelates; spectral, structural, electrochemical, photoluminescence and computational studies

NASA Astrophysics Data System (ADS)

Purtas, Fatih; Sayin, Koray; Ceyhan, Gokhan; Kose, Muhammet; Kurtoglu, Mukerrem

2017-06-01

A new Schiff base containing azo chromophore group obtained by condensation of 2-hydroxy-4-[(E)-phenyldiazenyl]benzaldehyde with 3,4-dimethylaniline (HL) are used for the syntheses of new copper(II) and zinc(II) chelates, [Cu(L)2], and [Zn(L)2], and characterized by physico-chemical and spectroscopic methods such as 1H and 13C NMR, IR, UV.-Vis. and elemental analyses. The solid state structure of the ligand was characterized by single crystal X-ray diffraction study. X-ray diffraction data was then used to calculate the harmonic oscillator model of aromaticity (HOMA) indexes for the rings so as to investigate of enol-imine and keto-amine tautomeric forms in the solid state. The phenol ring C10-C15 shows a considerable deviation from the aromaticity with HOMA value of 0.837 suggesting the shift towards the keto-amine tautomeric form in the solid state. The analytical data show that the metal to ligand ratio in the chelates was found to be 1:2. Theoretical calculations of the possible isomers of the ligand and two metal complexes are performed by using B3LYP method. Electrochemical and photoluminescence properties of the synthesized azo-Schiff bases were also investigated.

Structure-Functional Prediction and Analysis of Cancer Mutation Effects in Protein Kinases

PubMed Central

Dixit, Anshuman; Verkhivker, Gennady M.

2014-01-01

A central goal of cancer research is to discover and characterize the functional effects of mutated genes that contribute to tumorigenesis. In this study, we provide a detailed structural classification and analysis of functional dynamics for members of protein kinase families that are known to harbor cancer mutations. We also present a systematic computational analysis that combines sequence and structure-based prediction models to characterize the effect of cancer mutations in protein kinases. We focus on the differential effects of activating point mutations that increase protein kinase activity and kinase-inactivating mutations that decrease activity. Mapping of cancer mutations onto the conformational mobility profiles of known crystal structures demonstrated that activating mutations could reduce a steric barrier for the movement from the basal “low” activity state to the “active” state. According to our analysis, the mechanism of activating mutations reflects a combined effect of partial destabilization of the kinase in its inactive state and a concomitant stabilization of its active-like form, which is likely to drive tumorigenesis at some level. Ultimately, the analysis of the evolutionary and structural features of the major cancer-causing mutational hotspot in kinases can also aid in the correlation of kinase mutation effects with clinical outcomes. PMID:24817905

Color reproduction system based on color appearance model and gamut mapping

NASA Astrophysics Data System (ADS)

Cheng, Fang-Hsuan; Yang, Chih-Yuan

2000-06-01

By the progress of computer, computer peripherals such as color monitor and printer are often used to generate color image. However, cross media color reproduction by human perception is usually different. Basically, the influence factors are device calibration and characterization, viewing condition, device gamut and human psychology. In this thesis, a color reproduction system based on color appearance model and gamut mapping is proposed. It consists of four parts; device characterization, color management technique, color appearance model and gamut mapping.

ARIANNA: A research environment for neuroimaging studies in autism spectrum disorders.

PubMed

Retico, Alessandra; Arezzini, Silvia; Bosco, Paolo; Calderoni, Sara; Ciampa, Alberto; Coscetti, Simone; Cuomo, Stefano; De Santis, Luca; Fabiani, Dario; Fantacci, Maria Evelina; Giuliano, Alessia; Mazzoni, Enrico; Mercatali, Pietro; Miscali, Giovanni; Pardini, Massimiliano; Prosperi, Margherita; Romano, Francesco; Tamburini, Elena; Tosetti, Michela; Muratori, Filippo

2017-08-01

The complexity and heterogeneity of Autism Spectrum Disorders (ASD) require the implementation of dedicated analysis techniques to obtain the maximum from the interrelationship among many variables that describe affected individuals, spanning from clinical phenotypic characterization and genetic profile to structural and functional brain images. The ARIANNA project has developed a collaborative interdisciplinary research environment that is easily accessible to the community of researchers working on ASD (https://arianna.pi.infn.it). The main goals of the project are: to analyze neuroimaging data acquired in multiple sites with multivariate approaches based on machine learning; to detect structural and functional brain characteristics that allow the distinguishing of individuals with ASD from control subjects; to identify neuroimaging-based criteria to stratify the population with ASD to support the future development of personalized treatments. Secure data handling and storage are guaranteed within the project, as well as the access to fast grid/cloud-based computational resources. This paper outlines the web-based architecture, the computing infrastructure and the collaborative analysis workflows at the basis of the ARIANNA interdisciplinary working environment. It also demonstrates the full functionality of the research platform. The availability of this innovative working environment for analyzing clinical and neuroimaging information of individuals with ASD is expected to support researchers in disentangling complex data thus facilitating their interpretation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Current capabilities for simulating the extreme distortion of thin structures subjected to severe impacts

NASA Technical Reports Server (NTRS)

Key, Samuel W.

1993-01-01

The explicit transient dynamics technology in use today for simulating the impact and subsequent transient dynamic response of a structure has its origins in the 'hydrocodes' dating back to the late 1940's. The growth in capability in explicit transient dynamics technology parallels the growth in speed and size of digital computers. Computer software for simulating the explicit transient dynamic response of a structure is characterized by algorithms that use a large number of small steps. In explicit transient dynamics software there is a significant emphasis on speed and simplicity. The finite element technology used to generate the spatial discretization of a structure is based on a compromise between completeness of the representation for the physical processes modelled and speed in execution. That is, since it is expected in every calculation that the deformation will be finite and the material will be strained beyond the elastic range, the geometry and the associated gradient operators must be reconstructed, as well as complex stress-strain models evaluated at every time step. As a result, finite elements derived for explicit transient dynamics software use the simplest and barest constructions possible for computational efficiency while retaining an essential representation of the physical behavior. The best example of this technology is the four-node bending quadrilateral derived by Belytschko, Lin and Tsay. Today, the speed, memory capacity and availability of computer hardware allows a number of the previously used algorithms to be 'improved.' That is, it is possible with today's computing hardware to modify many of the standard algorithms to improve their representation of the physical process at the expense of added complexity and computational effort. The purpose is to review a number of these algorithms and identify the improvements possible. In many instances, both the older, faster version of the algorithm and the improved and somewhat slower version of the algorithm are found implemented together in software. Specifically, the following seven algorithmic items are examined: the invariant time derivatives of stress used in material models expressed in rate form; incremental objectivity and strain used in the numerical integration of the material models; the use of one-point element integration versus mean quadrature; shell elements used to represent the behavior of thin structural components; beam elements based on stress-resultant plasticity versus cross-section integration; the fidelity of elastic-plastic material models in their representation of ductile metals; and the use of Courant subcycling to reduce computational effort.

Bending of an Infinite beam on a base with two parameters in the absence of a part of the base

NASA Astrophysics Data System (ADS)

Aleksandrovskiy, Maxim; Zaharova, Lidiya

2018-03-01

Currently, in connection with the rapid development of high-rise construction and the improvement of joint operation of high-rise structures and bases models, the questions connected with the use of various calculation methods become topical. The rigor of analytical methods is capable of more detailed and accurate characterization of the structures behavior, which will affect the reliability of objects and can lead to a reduction in their cost. In the article, a model with two parameters is used as a computational model of the base that can effectively take into account the distributive properties of the base by varying the coefficient reflecting the shift parameter. The paper constructs the effective analytical solution of the problem of a beam of infinite length interacting with a two-parameter voided base. Using the Fourier integral equations, the original differential equation is reduced to the Fredholm integral equation of the second kind with a degenerate kernel, and all the integrals are solved analytically and explicitly, which leads to an increase in the accuracy of the computations in comparison with the approximate methods. The paper consider the solution of the problem of a beam loaded with a concentrated force applied at the point of origin with a fixed value of the length of the dip section. The paper gives the analysis of the obtained results values for various parameters of coefficient taking into account cohesion of the ground.

Internal structures of scaffold-free 3D cell cultures visualized by synchrotron radiation-based micro-computed tomography

NASA Astrophysics Data System (ADS)

Saldamli, Belma; Herzen, Julia; Beckmann, Felix; Tübel, Jutta; Schauwecker, Johannes; Burgkart, Rainer; Jürgens, Philipp; Zeilhofer, Hans-Florian; Sader, Robert; Müller, Bert

2008-08-01

Recently the importance of the third dimension in cell biology has been better understood, resulting in a re-orientation towards three-dimensional (3D) cultivation. Yet adequate tools for their morphological characterization have to be established. Synchrotron radiation-based micro computed tomography (SRμCT) allows visualizing such biological systems with almost isotropic micrometer resolution, non-destructively. We have applied SRμCT for studying the internal morphology of human osteoblast-derived, scaffold-free 3D cultures, termed histoids. Primary human osteoblasts, isolated from femoral neck spongy bone, were grown as 2D culture in non-mineralizing osteogenic medium until a rather thick, multi-cellular membrane was formed. This delicate system was intentionally released to randomly fold itself. The folded cell cultures were grown to histoids of cubic milli- or centimeter size in various combinations of mineralizing and non-mineralizing osteogenic medium for a total period of minimum 56 weeks. The SRμCT-measurements were performed in the absorption contrast mode at the beamlines BW 2 and W 2 (HASYLAB at DESY, Hamburg, Germany), operated by the GKSS-Research Center. To investigate the entire volume of interest several scans were performed under identical conditions and registered to obtain one single dataset of each sample. The histoids grown under different conditions exhibit similar external morphology of globular or ovoid shape. The SRμCT-examination revealed the distinctly different morphological structures inside the histoids. One obtains details of the histoids that permit to identify and select the most promising slices for subsequent histological characterization.

Impact design methods for ceramic components in gas turbine engines

NASA Technical Reports Server (NTRS)

Song, J.; Cuccio, J.; Kington, H.

1991-01-01

Methods currently under development to design ceramic turbine components with improved impact resistance are presented. Two different modes of impact damage are identified and characterized, i.e., structural damage and local damage. The entire computation is incorporated into the EPIC computer code. Model capability is demonstrated by simulating instrumented plate impact and particle impact tests.

Mitigating component performance variation

DOEpatents

Gara, Alan G.; Sylvester, Steve S.; Eastep, Jonathan M.; Nagappan, Ramkumar; Cantalupo, Christopher M.

2018-01-09

Apparatus and methods may provide for characterizing a plurality of similar components of a distributed computing system based on a maximum safe operation level associated with each component and storing characterization data in a database and allocating non-uniform power to each similar component based at least in part on the characterization data in the database to substantially equalize performance of the components.

Multidisciplinary tailoring of hot composite structures

NASA Technical Reports Server (NTRS)

Singhal, Surendra N.; Chamis, Christos C.

1993-01-01

A computational simulation procedure is described for multidisciplinary analysis and tailoring of layered multi-material hot composite engine structural components subjected to simultaneous multiple discipline-specific thermal, structural, vibration, and acoustic loads. The effect of aggressive environments is also simulated. The simulation is based on a three-dimensional finite element analysis technique in conjunction with structural mechanics codes, thermal/acoustic analysis methods, and tailoring procedures. The integrated multidisciplinary simulation procedure is general-purpose including the coupled effects of nonlinearities in structure geometry, material, loading, and environmental complexities. The composite material behavior is assessed at all composite scales, i.e., laminate/ply/constituents (fiber/matrix), via a nonlinear material characterization hygro-thermo-mechanical model. Sample tailoring cases exhibiting nonlinear material/loading/environmental behavior of aircraft engine fan blades, are presented. The various multidisciplinary loads lead to different tailored designs, even those competing with each other, as in the case of minimum material cost versus minimum structure weight and in the case of minimum vibration frequency versus minimum acoustic noise.

Adaptive Crack Modeling with Interface Solid Elements for Plain and Fiber Reinforced Concrete Structures.

PubMed

Zhan, Yijian; Meschke, Günther

2017-07-08

The effective analysis of the nonlinear behavior of cement-based engineering structures not only demands physically-reliable models, but also computationally-efficient algorithms. Based on a continuum interface element formulation that is suitable to capture complex cracking phenomena in concrete materials and structures, an adaptive mesh processing technique is proposed for computational simulations of plain and fiber-reinforced concrete structures to progressively disintegrate the initial finite element mesh and to add degenerated solid elements into the interfacial gaps. In comparison with the implementation where the entire mesh is processed prior to the computation, the proposed adaptive cracking model allows simulating the failure behavior of plain and fiber-reinforced concrete structures with remarkably reduced computational expense.

Adaptive Crack Modeling with Interface Solid Elements for Plain and Fiber Reinforced Concrete Structures

PubMed Central

Zhan, Yijian

2017-01-01

The effective analysis of the nonlinear behavior of cement-based engineering structures not only demands physically-reliable models, but also computationally-efficient algorithms. Based on a continuum interface element formulation that is suitable to capture complex cracking phenomena in concrete materials and structures, an adaptive mesh processing technique is proposed for computational simulations of plain and fiber-reinforced concrete structures to progressively disintegrate the initial finite element mesh and to add degenerated solid elements into the interfacial gaps. In comparison with the implementation where the entire mesh is processed prior to the computation, the proposed adaptive cracking model allows simulating the failure behavior of plain and fiber-reinforced concrete structures with remarkably reduced computational expense. PMID:28773130

Offdiagonal complexity: A computationally quick complexity measure for graphs and networks

NASA Astrophysics Data System (ADS)

Claussen, Jens Christian

2007-02-01

A vast variety of biological, social, and economical networks shows topologies drastically differing from random graphs; yet the quantitative characterization remains unsatisfactory from a conceptual point of view. Motivated from the discussion of small scale-free networks, a biased link distribution entropy is defined, which takes an extremum for a power-law distribution. This approach is extended to the node-node link cross-distribution, whose nondiagonal elements characterize the graph structure beyond link distribution, cluster coefficient and average path length. From here a simple (and computationally cheap) complexity measure can be defined. This offdiagonal complexity (OdC) is proposed as a novel measure to characterize the complexity of an undirected graph, or network. While both for regular lattices and fully connected networks OdC is zero, it takes a moderately low value for a random graph and shows high values for apparently complex structures as scale-free networks and hierarchical trees. The OdC approach is applied to the Helicobacter pylori protein interaction network and randomly rewired surrogates.

Signal decomposition for surrogate modeling of a constrained ultrasonic design space

NASA Astrophysics Data System (ADS)

Homa, Laura; Sparkman, Daniel; Wertz, John; Welter, John; Aldrin, John C.

2018-04-01

The U.S. Air Force seeks to improve the methods and measures by which the lifecycle of composite structures are managed. Nondestructive evaluation of damage - particularly internal damage resulting from impact - represents a significant input to that improvement. Conventional ultrasound can detect this damage; however, full 3D characterization has not been demonstrated. A proposed approach for robust characterization uses model-based inversion through fitting of simulated results to experimental data. One challenge with this approach is the high computational expense of the forward model to simulate the ultrasonic B-scans for each damage scenario. A potential solution is to construct a surrogate model using a subset of simulated ultrasonic scans built using a highly accurate, computationally expensive forward model. However, the dimensionality of these simulated B-scans makes interpolating between them a difficult and potentially infeasible problem. Thus, we propose using the chirplet decomposition to reduce the dimensionality of the data, and allow for interpolation in the chirplet parameter space. By applying the chirplet decomposition, we are able to extract the salient features in the data and construct a surrogate forward model.

An information driven strategy to support multidisciplinary design

NASA Technical Reports Server (NTRS)

Rangan, Ravi M.; Fulton, Robert E.

1990-01-01

The design of complex engineering systems such as aircraft, automobiles, and computers is primarily a cooperative multidisciplinary design process involving interactions between several design agents. The common thread underlying this multidisciplinary design activity is the information exchange between the various groups and disciplines. The integrating component in such environments is the common data and the dependencies that exist between such data. This may be contrasted to classical multidisciplinary analyses problems where there is coupling between distinct design parameters. For example, they may be expressed as mathematically coupled relationships between aerodynamic and structural interactions in aircraft structures, between thermal and structural interactions in nuclear plants, and between control considerations and structural interactions in flexible robots. These relationships provide analytical based frameworks leading to optimization problem formulations. However, in multidisciplinary design problems, information based interactions become more critical. Many times, the relationships between different design parameters are not amenable to analytical characterization. Under such circumstances, information based interactions will provide the best integration paradigm, i.e., there is a need to model the data entities and their dependencies between design parameters originating from different design agents. The modeling of such data interactions and dependencies forms the basis for integrating the various design agents.

1-Pentyl-3-(4-methoxy-1-naphthoyl)indole and 2-(2-methoxy-phenyl)-1-(1-pentyl-1 H-indol-3-yl)-ethanone: X-ray structures and computational studies

NASA Astrophysics Data System (ADS)

Nycz, Jacek E.; Malecki, Grzegorz; Zawiazalec, Marcin; Pazdziorek, Tadeusz; Skop, Patrycja

2010-12-01

1-Pentyl-3-(4-methoxy-1-naphthoyl)indole (shortly named JWH-081) ( 1) and 2-(2-methoxy-phenyl)-1-(1-pentyl-1 H-indol-3-yl)-ethanone (shortly named JWH-250) ( 2), are examples of cannabinoids which were characterized by FTIR, UV-Vis, multinuclear NMR spectroscopy and single crystal X-ray diffraction method. The geometries of the studied compounds were optimized in singlet states using the density functional theory (DFT) method with B3LYP functional. Electronic spectra were calculated by TDDFT method. In general, the predicted bond lengths and angles are in a good agreement with the values based on the X-ray crystal structure data.

Part-whole reasoning in medical ontologies revisited--introducing SEP triplets into classification-based description logics.

PubMed

Schulz, S; Romacker, M; Hahn, U

1998-01-01

The development of powerful and comprehensive medical ontologies that support formal reasoning on a large scale is one of the key requirements for clinical computing in the next millennium. Taxonomic medical knowledge, a major portion of these ontologies, is mainly characterized by generalization and part-whole relations between concepts. While reasoning in generalization hierarchies is quite well understood, no fully conclusive mechanism as yet exists for part-whole reasoning. The approach we take emulates part-whole reasoning via classification-based reasoning using SEP triplets, a special data structure for encoding part-whole relations that is fully embedded in the formal framework of standard description logics.

Part-whole reasoning in medical ontologies revisited--introducing SEP triplets into classification-based description logics.

PubMed Central

Schulz, S.; Romacker, M.; Hahn, U.

1998-01-01

The development of powerful and comprehensive medical ontologies that support formal reasoning on a large scale is one of the key requirements for clinical computing in the next millennium. Taxonomic medical knowledge, a major portion of these ontologies, is mainly characterized by generalization and part-whole relations between concepts. While reasoning in generalization hierarchies is quite well understood, no fully conclusive mechanism as yet exists for part-whole reasoning. The approach we take emulates part-whole reasoning via classification-based reasoning using SEP triplets, a special data structure for encoding part-whole relations that is fully embedded in the formal framework of standard description logics. Images Figure 3 PMID:9929335

TAOI B- Computational Microstructural Optimization Design Tool for High Temperature Structural Materials

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

Mishra, Rajiv; Charit, Indrajit

2015-02-28

The objectives of this research were two-fold: (a) develop a methodology for microstructural optimization of alloys - genetic algorithm approach for alloy microstructural optimization using theoretical models based on fundamental micro-mechanisms, and (b) develop a new computationally designed Ni-Cr alloy for coal-fired power plant applications. The broader outcome of these objectives is expected to be creation of an integrated approach for ‘structural materials by microstructural design’. Three alloy systems were considered for computational optimization and validation, (i) Ni-20Cr (wt.%) base alloy using only solid solution strengthening, (ii) nano-Y2O3 containing Ni-20Cr-1.2Y2O3 (wt.%) alloy for dispersion strengthening and (iii) a sub-micron Al2O3more » for composite strengthening, Ni-20Cr-1.2Y2O3-5.0Al2O3 (wt.%). The specimens were synthesized by mechanical alloying and consolidated using spark plasma sintering. Detailed microstructural characterization was done along with initial mechanical properties to validate the computational prediction. A key target property is to have creep rate of 1x10-9 s-1 at 100 MPa and 800oC. The initial results were quite promising and require additional quantification of strengthening contributions from dislocation-particle attractive interaction and load transfer. The observed creep rate was in order of 10-9 s-1 for longer time creep test of Ni-20Cr -1.2Y2O3-5Al2O3, lending support to the overall approach pursued in this project.« less

Rational selection of structurally diverse natural product scaffolds with favorable ADME properties for drug discovery.

PubMed

Samiulla, D S; Vaidyanathan, V V; Arun, P C; Balan, G; Blaze, M; Bondre, S; Chandrasekhar, G; Gadakh, A; Kumar, R; Kharvi, G; Kim, H O; Kumar, S; Malikayil, J A; Moger, M; Mone, M K; Nagarjuna, P; Ogbu, C; Pendhalkar, D; Rao, A V S Raja; Rao, G Venkateshwar; Sarma, V K; Shaik, S; Sharma, G V R; Singh, S; Sreedhar, C; Sonawane, R; Timmanna, U; Hardy, L W

2005-01-01

Natural product analogs are significant sources for therapeutic agents. To capitalize efficiently on the effective features of naturally occurring substances, a natural product-based library production platform has been devised at Aurigene for drug lead discovery. This approach combines the attractive biological and physicochemical properties of natural product scaffolds, provided by eons of natural selection, with the chemical diversity available from parallel synthetic methods. Virtual property analysis, using computational methods described here, guides the selection of a set of natural product scaffolds that are both structurally diverse and likely to have favorable pharmacokinetic properties. The experimental characterization of several in vitro ADME properties of twenty of these scaffolds, and of a small set of designed congeners based upon one scaffold, is also described. These data confirm that most of the scaffolds and the designed library members have properties favorable to their utilization for creating libraries of lead-like molecules.

Application of the Ugi reaction with multiple amino acid-derived components: synthesis and conformational evaluation of piperazine-based minimalist peptidomimetics.

PubMed

Stucchi, Mattia; Cairati, Silvia; Cetin-Atalay, Rengul; Christodoulou, Michael S; Grazioso, Giovanni; Pescitelli, Gennaro; Silvani, Alessandra; Yildirim, Deniz Cansen; Lesma, Giordano

2015-05-07

The concurrent employment of α-amino acid-derived chiral components such as aldehydes and α-isocyanoacetates, in a sequential Ugi reaction/cyclization two-step strategy, opens the door to the synthesis of three structurally distinct piperazine-based scaffolds, characterized by the presence of L-Ala and/or L-Phe-derived side chains and bearing appropriate functionalities to be easily applied in peptide chemistry. By means of computational studies, these scaffolds have been demonstrated to act as minimalist peptidomimetics, able to mimic a well defined range of peptide secondary structures and therefore potentially useful for the synthesis of small-molecule PPI modulators. Preliminary biological evaluation of two different resistant hepatocellular carcinoma cellular lines, for which differentiation versus resistance ability seem to be strongly correlated with well defined types of PPIs, has revealed a promising antiproliferative activity for selected compounds.

COMPUTER PREDICTION OF BIOLOGICAL ACTIVITY OF DIMETHYL-N-(BENZOYL)AMIDOPHOSPHATE AND DIMETHYL-N-(PHENYLSULFONYL)AMIDOPHOSPHATE, EVALUATION OF THEIR CYTOTOXIC ACTIVITY AGAINST LEUKEMIC CELLS IN VITRO.

PubMed

Grynyuk, I I; Prylutska, S V; Kariaka, N S; Sliva, T Yu; Moroz, O V; Franskevych, D V; Amirkhanov, V M; Matyshevska, O P; Slobodyanik, M S

2015-01-01

Structural analogues of β-diketones--dimethyl-N-(benzoyl)amidophosphate (HCP) and dimethyl-N-(phenylsulfonyl)amidophosphate (HSP) were synthesized and identified by the methods of IR, 1H and 31P NMR spectroscopy. Screening of biological activity and calculation of physicochemical parameters of HCP and HSP compounds were done with the use of PASS and ACD/Labs computer programs. A wide range of biological activity of synthesized compounds, antitumor activity in particular, has been found. Calculations of the bioavailability criteria indicate that the investigated compounds have no deviations from Lipinski's rules. HCP compound is characterized by a high lipophilicity at physiological pH as compared to HSP. It was found that cytotoxic effect of the studied compounds on the leukemic L1210 cells was of time- and dose-dependent character. HCP is characterized by more pronounced and early cytotoxic effects as compared to HSP. It was shown that 2.5 mM HCP increased ROS production 3 times in the early period of incubation, and decreased cell viability by 40% after 48 h, and by 66%--after 72 h. Based on the computer calculation and undertaken research, HCP was selected for target chemical modifications and enhancement of its antitumor effect.

Conformational Analysis of Drug Molecules: A Practical Exercise in the Medicinal Chemistry Course

ERIC Educational Resources Information Center

Yuriev, Elizabeth; Chalmers, David; Capuano, Ben

2009-01-01

Medicinal chemistry is a specialized, scientific discipline. Computational chemistry and structure-based drug design constitute important themes in the education of medicinal chemists. This problem-based task is associated with structure-based drug design lectures. It requires students to use computational techniques to investigate conformational…

SInCRe—structural interactome computational resource for Mycobacterium tuberculosis

PubMed Central

Metri, Rahul; Hariharaputran, Sridhar; Ramakrishnan, Gayatri; Anand, Praveen; Raghavender, Upadhyayula S.; Ochoa-Montaño, Bernardo; Higueruelo, Alicia P.; Sowdhamini, Ramanathan; Chandra, Nagasuma R.; Blundell, Tom L.; Srinivasan, Narayanaswamy

2015-01-01

We have developed an integrated database for Mycobacterium tuberculosis H37Rv (Mtb) that collates information on protein sequences, domain assignments, functional annotation and 3D structural information along with protein–protein and protein–small molecule interactions. SInCRe (Structural Interactome Computational Resource) is developed out of CamBan (Cambridge and Bangalore) collaboration. The motivation for development of this database is to provide an integrated platform to allow easily access and interpretation of data and results obtained by all the groups in CamBan in the field of Mtb informatics. In-house algorithms and databases developed independently by various academic groups in CamBan are used to generate Mtb-specific datasets and are integrated in this database to provide a structural dimension to studies on tuberculosis. The SInCRe database readily provides information on identification of functional domains, genome-scale modelling of structures of Mtb proteins and characterization of the small-molecule binding sites within Mtb. The resource also provides structure-based function annotation, information on small-molecule binders including FDA (Food and Drug Administration)-approved drugs, protein–protein interactions (PPIs) and natural compounds that bind to pathogen proteins potentially and result in weakening or elimination of host–pathogen protein–protein interactions. Together they provide prerequisites for identification of off-target binding. Database URL: http://proline.biochem.iisc.ernet.in/sincre PMID:26130660

Uncertainty quantification and validation of 3D lattice scaffolds for computer-aided biomedical applications.

PubMed

Gorguluarslan, Recep M; Choi, Seung-Kyum; Saldana, Christopher J

2017-07-01

A methodology is proposed for uncertainty quantification and validation to accurately predict the mechanical response of lattice structures used in the design of scaffolds. Effective structural properties of the scaffolds are characterized using a developed multi-level stochastic upscaling process that propagates the quantified uncertainties at strut level to the lattice structure level. To obtain realistic simulation models for the stochastic upscaling process and minimize the experimental cost, high-resolution finite element models of individual struts were reconstructed from the micro-CT scan images of lattice structures which are fabricated by selective laser melting. The upscaling method facilitates the process of determining homogenized strut properties to reduce the computational cost of the detailed simulation model for the scaffold. Bayesian Information Criterion is utilized to quantify the uncertainties with parametric distributions based on the statistical data obtained from the reconstructed strut models. A systematic validation approach that can minimize the experimental cost is also developed to assess the predictive capability of the stochastic upscaling method used at the strut level and lattice structure level. In comparison with physical compression test results, the proposed methodology of linking the uncertainty quantification with the multi-level stochastic upscaling method enabled an accurate prediction of the elastic behavior of the lattice structure with minimal experimental cost by accounting for the uncertainties induced by the additive manufacturing process. Copyright © 2017 Elsevier Ltd. All rights reserved.

Integrating structure-based and ligand-based approaches for computational drug design.

PubMed

Wilson, Gregory L; Lill, Markus A

2011-04-01

Methods utilized in computer-aided drug design can be classified into two major categories: structure based and ligand based, using information on the structure of the protein or on the biological and physicochemical properties of bound ligands, respectively. In recent years there has been a trend towards integrating these two methods in order to enhance the reliability and efficiency of computer-aided drug-design approaches by combining information from both the ligand and the protein. This trend resulted in a variety of methods that include: pseudoreceptor methods, pharmacophore methods, fingerprint methods and approaches integrating docking with similarity-based methods. In this article, we will describe the concepts behind each method and selected applications.

Synthesis, spectroscopic and computational characterization of the tautomerism of pyrazoline derivatives from chalcones

NASA Astrophysics Data System (ADS)

Miguel, Fábio Balbino; Dantas, Juliana Arantes; Amorim, Stefany; Andrade, Gustavo F. S.; Costa, Luiz Antônio Sodré; Couri, Mara Rubia Costa

2016-01-01

In the present study a series of novel pyrazolines derivatives has been synthesized, and their structures assigned on the basis of FT-Raman, 1H and 13C NMR spectral data and computational DFT calculations. A joint computational study using B3LYP/6-311G(2d,2p) density functional theory and FT-Raman investigation on the tautomerism of 3-(4-substituted-phenyl)-4,5-dihydro-5-(4-substituted-phenyl)pyrazole-1-carbothioamide and 3-(4-substituted-phenyl)-4,5-dihydro-5-(4-substituted-phenyl)pyrazole-1-carboxamide are presented. The structures were characterized as a minimum in the potential energy surface using DFT. The calculated Raman and NMR spectra were of such remarkable agreement to the experimental results that the equilibrium between tautomeric forms has been discussed in detail. Our study suggests the existence of tautomers, the carboxamide/carbothioamide group may tautomerize, in the solid state or in solution. Thermodynamic data calculated suggests that the R(Cdbnd S)NH2 and R(Cdbnd O)NH2 species are more stable than the R(Cdbnd NH)SH and R(Cdbnd NH)OH species. Additionally, results found for the 1H NMR shifting, pointed out to which structure is present.

A Molecular–Structure Hypothesis

PubMed Central

Boeyens, Jan C. A.

2010-01-01

The self-similar symmetry that occurs between atomic nuclei, biological growth structures, the solar system, globular clusters and spiral galaxies suggests that a similar pattern should characterize atomic and molecular structures. This possibility is explored in terms of the current molecular structure-hypothesis and its extension into four-dimensional space-time. It is concluded that a quantum molecule only has structure in four dimensions and that classical (Newtonian) structure, which occurs in three dimensions, cannot be simulated by quantum-chemical computation. PMID:21151437

Advanced applications of scatterometry based optical metrology

NASA Astrophysics Data System (ADS)

Dixit, Dhairya; Keller, Nick; Kagalwala, Taher; Recchia, Fiona; Lifshitz, Yevgeny; Elia, Alexander; Todi, Vinit; Fronheiser, Jody; Vaid, Alok

2017-03-01

The semiconductor industry continues to drive patterning solutions that enable devices with higher memory storage capacity, faster computing performance, and lower cost per transistor. These developments in the field of semiconductor manufacturing along with the overall minimization of the size of transistors require continuous development of metrology tools used for characterization of these complex 3D device architectures. Optical scatterometry or optical critical dimension (OCD) is one of the most prevalent inline metrology techniques in semiconductor manufacturing because it is a quick, precise and non-destructive metrology technique. However, at present OCD is predominantly used to measure the feature dimensions such as line-width, height, side-wall angle, etc. of the patterned nano structures. Use of optical scatterometry for characterizing defects such as pitch-walking, overlay, line edge roughness, etc. is fairly limited. Inspection of process induced abnormalities is a fundamental part of process yield improvement. It provides process engineers with important information about process errors, and consequently helps optimize materials and process parameters. Scatterometry is an averaging technique and extending it to measure the position of local process induced defectivity and feature-to-feature variation is extremely challenging. This report is an overview of applications and benefits of using optical scatterometry for characterizing defects such as pitch-walking, overlay and fin bending for advanced technology nodes beyond 7nm. Currently, the optical scatterometry is based on conventional spectroscopic ellipsometry and spectroscopic reflectometry measurements, but generalized ellipsometry or Mueller matrix spectroscopic ellipsometry data provides important, additional information about complex structures that exhibit anisotropy and depolarization effects. In addition the symmetry-antisymmetry properties associated with Mueller matrix (MM) elements provide an excellent means of measuring asymmetry present in the structure. The useful additional information as well as symmetry-antisymmetry properties of MM elements is used to characterize fin bending, overlay defects and design improvements in the OCD test structures are used to boost OCDs' sensitivity to pitch-walking. In addition, the validity of the OCD based results is established by comparing the results to the top down critical dimensionscanning electron microscope (CD-SEM) and cross-sectional transmission electron microscope (TEM) images.

Molecular Dynamics Study of the Structure, Flexibility, and Hydrophilicity of PETIM Dendrimers: A Comparison with PAMAM Dendrimers.

PubMed

Kanchi, Subbarao; Suresh, Gorle; Priyakumar, U Deva; Ayappa, K G; Maiti, Prabal K

2015-10-15

A new class of dendrimers, the poly(propyl ether imine) (PETIM) dendrimer, has been shown to be a novel hyperbranched polymer having potential applications as a drug delivery vehicle. Structure and dynamics of the amine terminated PETIM dendrimer and their changes with respect to the dendrimer generation are poorly understood. Since most drugs are hydrophobic in nature, the extent of hydrophobicity of the dendrimer core is related to its drug encapsulation and retention efficacy. In this study, we carry out fully atomistic molecular dynamics (MD) simulations to characterize the structure of PETIM (G2-G6) dendrimers in salt solution as a function of dendrimer generation at different protonation levels. Structural properties such as radius of gyration (Rg), radial density distribution, aspect ratio, and asphericity are calculated. In order to assess the hydrophilicity of the dendrimer, we compute the number of bound water molecules in the interior of dendrimer as well as the number of dendrimer-water hydrogen bonds. We conclude that PETIM dendrimers have relatively greater hydrophobicity and flexibility when compared with their extensively investigated PAMAM counterparts. Hence PETIM dendrimers are expected to have stronger interactions with lipid membranes as well as improved drug encapsulation and retention properties when compared with PAMAM dendrimers. We compute the root-mean-square fluctuation of dendrimers as well as their entropy to quantify the flexibility of the dendrimer. Finally we note that structural and solvation properties computed using force field parameters derived based on the CHARMM general purpose force field were in good quantitative agreement with those obtained using the generalized Amber force field (GAFF).

Preliminary Design of a Consultation Knowledge-Based System for the Minimization of Distortion in Welded Structures

DTIC Science & Technology

1989-02-01

which capture the knowledge of such experts. These Expert Systems, or Knowledge-Based Systems’, differ from the usual computer programming techniques...their applications in the fields of structural design and welding is reviewed. 5.1 Introduction Expert Systems, or KBES, are computer programs using Al...procedurally constructed as conventional computer programs usually are; * The knowledge base of such systems is executable, unlike databases 3 "Ill

A matrix of heterobimetallic complexes for interrogation of hydrogen evolution reaction electrocatalysts.

PubMed

Ghosh, Pokhraj; Ding, Shengda; Chupik, Rachel B; Quiroz, Manuel; Hsieh, Chung-Hung; Bhuvanesh, Nattami; Hall, Michael B; Darensbourg, Marcetta Y

2017-12-01

Experimental and computational studies address key questions in a structure-function analysis of bioinspired electrocatalysts for the HER. Combinations of NiN 2 S 2 or [(NO)Fe]N 2 S 2 as donors to (η 5 -C 5 H 5 )Fe(CO) + or [Fe(NO) 2 ] +/0 generate a series of four bimetallics, gradually "softened" by increasing nitrosylation, from 0 to 3, by the non-innocent NO ligands. The nitrosylated NiFe complexes are isolated and structurally characterized in two redox levels, demonstrating required features of electrocatalysis. Computational modeling of experimental structures and likely transient intermediates that connect the electrochemical events find roles for electron delocalization by NO, as well as Fe-S bond dissociation that produce a terminal thiolate as pendant base well positioned to facilitate proton uptake and transfer. Dihydrogen formation is via proton/hydride coupling by internal S-H + ··· - H-Fe units of the "harder" bimetallic arrangements with more localized electron density, while softer units convert H - ···H - via reductive elimination from two Fe-H deriving from the highly delocalized, doubly reduced [Fe 2 (NO) 3 ] - derivative. Computational studies also account for the inactivity of a Ni 2 Fe complex resulting from entanglement of added H + in a pinched -S δ - ···H + ··· δ - S- arrangement.

An objective and reproducible landform and topography description approach based on digital terrain analysis used for soil profile site characteristics

NASA Astrophysics Data System (ADS)

Gruber, Fabian E.; Baruck, Jasmin; Hastik, Richard; Geitner, Clemens

2015-04-01

All major soil description and classification systems, including the World Reference Base (WRB) and the German Soil description guidelines (KA5), require the characterization of landform and topography for soil profile sites. This is commonly done at more than one scale, for instance at macro-, meso- and micro scale. However, inherent when humans perform such a task, different surveyors will reach different conclusions due to their subjective perception of landscape structure, based on their individual mind-model of soil-landscape structure, emphasizing different aspects and scales of the landscape. In this study we apply a work-flow using the GRASS GIS extension module r.geomorphon to make use of high resolution digital elevation models (DEMs) to characterize the landform elements and topography of soil profile sites at different scales, and compare the results with a large number of soil profile site descriptions performed during the course of forestry surveys in South and North Tyrol (Italy and Austria, respectively). The r.geomorphon extension module for the open source geographic information system GRASS GIS applies a pattern recognition algorithm to delineate landform elements based on an input DEM. For each raster cell it computes and characterizes the visible neighborhood using line-of-sight calculations and then applies a lookup-table to classify the raster cell into one of ten landform elements (flat, peak, ridge, shoulder, slope, spur, hollow, footslope, valley and pit). The input parameter search radius (L) represents the maximum number of pixels for line-of-sight calculation, resulting in landforms larger than L to be split into landform components. The use of these visibility calculations makes this landform delineation approach suitable for comparison with the landform descriptions of soil surveyors, as their spatial perception of the landscape surrounding a soil profile site certainly influences their classification of the landform on which the profile is situated (aided by additional information such as topographic maps and aerial images). Variation of the L-value furthermore presents the opportunity to mimic the different scales at which surveyors describe soil profile locations. We first illustrate the use of r.geomorphon for site descriptions using exemplary artificial elevation profiles resembling typic catenas at different scales (L-values). We then compare the results of a landform element map computed with r.geomorphon to the relief descriptions in the test dataset. We link the surveyors' landform classification to the computed landform elements. Using a multi-scale approach we characterize raster cell locations in a way similar to the micro-, meso- and macroscale definitions used in soil survey, resulting in so-called geomorphon-signatures, such as "pit (meso-scale) located on a ridge (macro-scale)". We investigate which ranges of L-values best represent the different observation-scales as noted by soil surveyors and discuss the impacts of using a large dataset of profile location descriptions performed by different surveyors. Issues that arise are possible individual differences in landscape structure perception, but also questions regarding the accuracy of position and resulting topographic measurements in soil profile site description.

CSM research: Methods and application studies

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.

1989-01-01

Computational mechanics is that discipline of applied science and engineering devoted to the study of physical phenomena by means of computational methods based on mathematical modeling and simulation, utilizing digital computers. The discipline combines theoretical and applied mechanics, approximation theory, numerical analysis, and computer science. Computational mechanics has had a major impact on engineering analysis and design. When applied to structural mechanics, the discipline is referred to herein as computational structural mechanics. Complex structures being considered by NASA for the 1990's include composite primary aircraft structures and the space station. These structures will be much more difficult to analyze than today's structures and necessitate a major upgrade in computerized structural analysis technology. NASA has initiated a research activity in structural analysis called Computational Structural Mechanics (CSM). The broad objective of the CSM activity is to develop advanced structural analysis technology that will exploit modern and emerging computers, such as those with vector and/or parallel processing capabilities. Here, the current research directions for the Methods and Application Studies Team of the Langley CSM activity are described.

Molecular Dynamics Simulations and Structural Analysis of Giardia duodenalis 14-3-3 Protein-Protein Interactions.

PubMed

Cau, Ylenia; Fiorillo, Annarita; Mori, Mattia; Ilari, Andrea; Botta, Maurizo; Lalle, Marco

2015-12-28

Giardiasis is a gastrointestinal diarrheal illness caused by the protozoan parasite Giardia duodenalis, which affects annually over 200 million people worldwide. The limited antigiardial drug arsenal and the emergence of clinical cases refractory to standard treatments dictate the need for new chemotherapeutics. The 14-3-3 family of regulatory proteins, extensively involved in protein-protein interactions (PPIs) with pSer/pThr clients, represents a highly promising target. Despite homology with human counterparts, the single 14-3-3 of G. duodenalis (g14-3-3) is characterized by a constitutive phosphorylation in a region critical for target binding, thus affecting the function and the conformation of g14-3-3/clients interaction. However, to approach the design of specific small molecule modulators of g14-3-3 PPIs, structural elucidations are required. Here, we present a detailed computational and crystallographic study exploring the implications of g14-3-3 phosphorylation on protein structure and target binding. Self-Guided Langevin Dynamics and classical molecular dynamics simulations show that phosphorylation affects locally and globally g14-3-3 conformation, inducing a structural rearrangement more suitable for target binding. Profitable features for g14-3-3/clients interaction were highlighted using a hydrophobicity-based descriptor to characterize g14-3-3 client peptides. Finally, the X-ray structure of g14-3-3 in complex with a mode-1 prototype phosphopeptide was solved and combined with structure-based simulations to identify molecular features relevant for clients binding to g14-3-3. The data presented herein provide a further and structural understanding of g14-3-3 features and set the basis for drug design studies.

Preliminary characterization of the oral microbiota of Chinese adults with and without gingivitis

PubMed Central

2011-01-01

Background Microbial communities inhabiting human mouth are associated with oral health and disease. Previous studies have indicated the general prevalence of adult gingivitis in China to be high. The aim of this study was to characterize in depth the oral microbiota of Chinese adults with or without gingivitis, by defining the microbial phylogenetic diversity and community-structure using highly paralleled pyrosequencing. Methods Six non-smoking Chinese, three with and three without gingivitis (age range 21-39 years, 4 females and 2 males) were enrolled in the present cross-sectional study. Gingival parameters of inflammation and bleeding on probing were characterized by a clinician using the Mazza Gingival Index (MGI). Plaque (sampled separately from four different oral sites) and salivary samples were obtained from each subject. Sequences and relative abundance of the bacterial 16 S rDNA PCR-amplicons were determined via pyrosequencing that produced 400 bp-long reads. The sequence data were analyzed via a computational pipeline customized for human oral microbiome analyses. Furthermore, the relative abundances of selected microbial groups were validated using quantitative PCR. Results The oral microbiomes from gingivitis and healthy subjects could be distinguished based on the distinct community structures of plaque microbiomes, but not the salivary microbiomes. Contributions of community members to community structure divergence were statistically accessed at the phylum, genus and species-like levels. Eight predominant taxa were found associated with gingivitis: TM7, Leptotrichia, Selenomonas, Streptococcus, Veillonella, Prevotella, Lautropia, and Haemophilus. Furthermore, 98 species-level OTUs were identified to be gingivitis-associated, which provided microbial features of gingivitis at a species resolution. Finally, for the two selected genera Streptococcus and Fusobacterium, Real-Time PCR based quantification of relative bacterial abundance validated the pyrosequencing-based results. Conclusions This methods study suggests that oral samples from this patient population of gingivitis can be characterized via plaque microbiome by pyrosequencing the 16 S rDNA genes. Further studies that characterize serial samples from subjects (longitudinal study design) with a larger population size may provide insight into the temporal and ecological features of oral microbial communities in clinically-defined states of gingivitis. PMID:22152152

Characterizing bonding patterns in diradicals and triradicals by density-based wave function analysis: A uniform approach

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

Orms, Natalie; Rehn, Dirk; Dreuw, Andreas

Density-based wave function analysis enables unambiguous comparisons of electronic structure computed by different methods and removes ambiguity of orbital choices. Here, we use this tool to investigate the performance of different spin-flip methods for several prototypical diradicals and triradicals. In contrast to previous calibration studies that focused on energy gaps between high and low spin-states, we focus on the properties of the underlying wave functions, such as the number of effectively unpaired electrons. Comparison of different density functional and wave function theory results provides insight into the performance of the different methods when applied to strongly correlated systems such asmore » polyradicals. We also show that canonical molecular orbitals for species like large copper-containing diradicals fail to correctly represent the underlying electronic structure due to highly non-Koopmans character, while density-based analysis of the same wave function delivers a clear picture of bonding pattern.« less

Characterizing bonding patterns in diradicals and triradicals by density-based wave function analysis: A uniform approach

DOE PAGES

Orms, Natalie; Rehn, Dirk; Dreuw, Andreas; ...

2017-12-21

Density-based wave function analysis enables unambiguous comparisons of electronic structure computed by different methods and removes ambiguity of orbital choices. Here, we use this tool to investigate the performance of different spin-flip methods for several prototypical diradicals and triradicals. In contrast to previous calibration studies that focused on energy gaps between high and low spin-states, we focus on the properties of the underlying wave functions, such as the number of effectively unpaired electrons. Comparison of different density functional and wave function theory results provides insight into the performance of the different methods when applied to strongly correlated systems such asmore » polyradicals. We also show that canonical molecular orbitals for species like large copper-containing diradicals fail to correctly represent the underlying electronic structure due to highly non-Koopmans character, while density-based analysis of the same wave function delivers a clear picture of bonding pattern.« less

Comparison of measured temperatures, thermal stresses and creep residues with predictions on a built-up titanium structure

NASA Technical Reports Server (NTRS)

Jenkins, Jerald M.

1987-01-01

Temperature, thermal stresses, and residual creep stresses were studied by comparing laboratory values measured on a built-up titanium structure with values calculated from finite-element models. Several such models were used to examine the relationship between computational thermal stresses and thermal stresses measured on a built-up structure. Element suitability, element density, and computational temperature discrepancies were studied to determine their impact on measured and calculated thermal stress. The optimum number of elements is established from a balance between element density and suitable safety margins, such that the answer is acceptably safe yet is economical from a computational viewpoint. It is noted that situations exist where relatively small excursions of calculated temperatures from measured values result in far more than proportional increases in thermal stress values. Measured residual stresses due to creep significantly exceeded the values computed by the piecewise linear elastic strain analogy approach. The most important element in the computation is the correct definition of the creep law. Computational methodology advances in predicting residual stresses due to creep require significantly more viscoelastic material characterization.

Template-Based Modeling of Protein-RNA Interactions

PubMed Central

Zheng, Jinfang; Kundrotas, Petras J.; Vakser, Ilya A.

2016-01-01

Protein-RNA complexes formed by specific recognition between RNA and RNA-binding proteins play an important role in biological processes. More than a thousand of such proteins in human are curated and many novel RNA-binding proteins are to be discovered. Due to limitations of experimental approaches, computational techniques are needed for characterization of protein-RNA interactions. Although much progress has been made, adequate methodologies reliably providing atomic resolution structural details are still lacking. Although protein-RNA free docking approaches proved to be useful, in general, the template-based approaches provide higher quality of predictions. Templates are key to building a high quality model. Sequence/structure relationships were studied based on a representative set of binary protein-RNA complexes from PDB. Several approaches were tested for pairwise target/template alignment. The analysis revealed a transition point between random and correct binding modes. The results showed that structural alignment is better than sequence alignment in identifying good templates, suitable for generating protein-RNA complexes close to the native structure, and outperforms free docking, successfully predicting complexes where the free docking fails, including cases of significant conformational change upon binding. A template-based protein-RNA interaction modeling protocol PRIME was developed and benchmarked on a representative set of complexes. PMID:27662342

Computational identification of novel biochemical systems involved in oxidation, glycosylation and other complex modifications of bases in DNA.

PubMed

Iyer, Lakshminarayan M; Zhang, Dapeng; Burroughs, A Maxwell; Aravind, L

2013-09-01

Discovery of the TET/JBP family of dioxygenases that modify bases in DNA has sparked considerable interest in novel DNA base modifications and their biological roles. Using sensitive sequence and structure analyses combined with contextual information from comparative genomics, we computationally characterize over 12 novel biochemical systems for DNA modifications. We predict previously unidentified enzymes, such as the kinetoplastid J-base generating glycosyltransferase (and its homolog GREB1), the catalytic specificity of bacteriophage TET/JBP proteins and their role in complex DNA base modifications. We also predict the enzymes involved in synthesis of hypermodified bases such as alpha-glutamylthymine and alpha-putrescinylthymine that have remained enigmatic for several decades. Moreover, the current analysis suggests that bacteriophages and certain nucleo-cytoplasmic large DNA viruses contain an unexpectedly diverse range of DNA modification systems, in addition to those using previously characterized enzymes such as Dam, Dcm, TET/JBP, pyrimidine hydroxymethylases, Mom and glycosyltransferases. These include enzymes generating modified bases such as deazaguanines related to queuine and archaeosine, pyrimidines comparable with lysidine, those derived using modified S-adenosyl methionine derivatives and those using TET/JBP-generated hydroxymethyl pyrimidines as biosynthetic starting points. We present evidence that some of these modification systems are also widely dispersed across prokaryotes and certain eukaryotes such as basidiomycetes, chlorophyte and stramenopile alga, where they could serve as novel epigenetic marks for regulation or discrimination of self from non-self DNA. Our study extends the role of the PUA-like fold domains in recognition of modified nucleic acids and predicts versions of the ASCH and EVE domains to be novel 'readers' of modified bases in DNA. These results open opportunities for the investigation of the biology of these systems and their use in biotechnology.

Computational identification of novel biochemical systems involved in oxidation, glycosylation and other complex modifications of bases in DNA

PubMed Central

Iyer, Lakshminarayan M.; Zhang, Dapeng; Maxwell Burroughs, A.; Aravind, L.

2013-01-01

Discovery of the TET/JBP family of dioxygenases that modify bases in DNA has sparked considerable interest in novel DNA base modifications and their biological roles. Using sensitive sequence and structure analyses combined with contextual information from comparative genomics, we computationally characterize over 12 novel biochemical systems for DNA modifications. We predict previously unidentified enzymes, such as the kinetoplastid J-base generating glycosyltransferase (and its homolog GREB1), the catalytic specificity of bacteriophage TET/JBP proteins and their role in complex DNA base modifications. We also predict the enzymes involved in synthesis of hypermodified bases such as alpha-glutamylthymine and alpha-putrescinylthymine that have remained enigmatic for several decades. Moreover, the current analysis suggests that bacteriophages and certain nucleo-cytoplasmic large DNA viruses contain an unexpectedly diverse range of DNA modification systems, in addition to those using previously characterized enzymes such as Dam, Dcm, TET/JBP, pyrimidine hydroxymethylases, Mom and glycosyltransferases. These include enzymes generating modified bases such as deazaguanines related to queuine and archaeosine, pyrimidines comparable with lysidine, those derived using modified S-adenosyl methionine derivatives and those using TET/JBP-generated hydroxymethyl pyrimidines as biosynthetic starting points. We present evidence that some of these modification systems are also widely dispersed across prokaryotes and certain eukaryotes such as basidiomycetes, chlorophyte and stramenopile alga, where they could serve as novel epigenetic marks for regulation or discrimination of self from non-self DNA. Our study extends the role of the PUA-like fold domains in recognition of modified nucleic acids and predicts versions of the ASCH and EVE domains to be novel ‘readers’ of modified bases in DNA. These results open opportunities for the investigation of the biology of these systems and their use in biotechnology. PMID:23814188

A linear programming approach to reconstructing subcellular structures from confocal images for automated generation of representative 3D cellular models.

PubMed

Wood, Scott T; Dean, Brian C; Dean, Delphine

2013-04-01

This paper presents a novel computer vision algorithm to analyze 3D stacks of confocal images of fluorescently stained single cells. The goal of the algorithm is to create representative in silico model structures that can be imported into finite element analysis software for mechanical characterization. Segmentation of cell and nucleus boundaries is accomplished via standard thresholding methods. Using novel linear programming methods, a representative actin stress fiber network is generated by computing a linear superposition of fibers having minimum discrepancy compared with an experimental 3D confocal image. Qualitative validation is performed through analysis of seven 3D confocal image stacks of adherent vascular smooth muscle cells (VSMCs) grown in 2D culture. The presented method is able to automatically generate 3D geometries of the cell's boundary, nucleus, and representative F-actin network based on standard cell microscopy data. These geometries can be used for direct importation and implementation in structural finite element models for analysis of the mechanics of a single cell to potentially speed discoveries in the fields of regenerative medicine, mechanobiology, and drug discovery. Copyright © 2012 Elsevier B.V. All rights reserved.

Computational characterization of chromatin domain boundary-associated genomic elements

PubMed Central

Hong, Seungpyo

2017-01-01

Abstract Topologically associated domains (TADs) are 3D genomic structures with high internal interactions that play important roles in genome compaction and gene regulation. Their genomic locations and their association with CCCTC-binding factor (CTCF)-binding sites and transcription start sites (TSSs) were recently reported. However, the relationship between TADs and other genomic elements has not been systematically evaluated. This was addressed in the present study, with a focus on the enrichment of these genomic elements and their ability to predict the TAD boundary region. We found that consensus CTCF-binding sites were strongly associated with TAD boundaries as well as with the transcription factors (TFs) Zinc finger protein (ZNF)143 and Yin Yang (YY)1. TAD boundary-associated genomic elements include DNase I-hypersensitive sites, H3K36 trimethylation, TSSs, RNA polymerase II, and TFs such as Specificity protein 1, ZNF274 and SIX homeobox 5. Computational modeling with these genomic elements suggests that they have distinct roles in TAD boundary formation. We propose a structural model of TAD boundaries based on these findings that provides a basis for studying the mechanism of chromatin structure formation and gene regulation. PMID:28977568

Context based computational analysis and characterization of ARS consensus sequences (ACS) of Saccharomyces cerevisiae genome.

PubMed

Singh, Vinod Kumar; Krishnamachari, Annangarachari

2016-09-01

Genome-wide experimental studies in Saccharomyces cerevisiae reveal that autonomous replicating sequence (ARS) requires an essential consensus sequence (ACS) for replication activity. Computational studies identified thousands of ACS like patterns in the genome. However, only a few hundreds of these sites act as replicating sites and the rest are considered as dormant or evolving sites. In a bid to understand the sequence makeup of replication sites, a content and context-based analysis was performed on a set of replicating ACS sequences that binds to origin-recognition complex (ORC) denoted as ORC-ACS and non-replicating ACS sequences (nrACS), that are not bound by ORC. In this study, DNA properties such as base composition, correlation, sequence dependent thermodynamic and DNA structural profiles, and their positions have been considered for characterizing ORC-ACS and nrACS. Analysis reveals that ORC-ACS depict marked differences in nucleotide composition and context features in its vicinity compared to nrACS. Interestingly, an A-rich motif was also discovered in ORC-ACS sequences within its nucleosome-free region. Profound changes in the conformational features, such as DNA helical twist, inclination angle and stacking energy between ORC-ACS and nrACS were observed. Distribution of ACS motifs in the non-coding segments points to the locations of ORC-ACS which are found far away from the adjacent gene start position compared to nrACS thereby enabling an accessible environment for ORC-proteins. Our attempt is novel in considering the contextual view of ACS and its flanking region along with nucleosome positioning in the S. cerevisiae genome and may be useful for any computational prediction scheme.

Validation of finite element computations for the quantitative prediction of underwater noise from impact pile driving.

PubMed

Zampolli, Mario; Nijhof, Marten J J; de Jong, Christ A F; Ainslie, Michael A; Jansen, Erwin H W; Quesson, Benoit A J

2013-01-01

The acoustic radiation from a pile being driven into the sediment by a sequence of hammer strikes is studied with a linear, axisymmetric, structural acoustic frequency domain finite element model. Each hammer strike results in an impulsive sound that is emitted from the pile and then propagated in the shallow water waveguide. Measurements from accelerometers mounted on the head of a test pile and from hydrophones deployed in the water are used to validate the model results. Transfer functions between the force input at the top of the anvil and field quantities, such as acceleration components in the structure or pressure in the fluid, are computed with the model. These transfer functions are validated using accelerometer or hydrophone measurements to infer the structural forcing. A modeled hammer forcing pulse is used in the successive step to produce quantitative predictions of sound exposure at the hydrophones. The comparison between the model and the measurements shows that, although several simplifying assumptions were made, useful predictions of noise levels based on linear structural acoustic models are possible. In the final part of the paper, the model is used to characterize the pile as an acoustic radiator by analyzing the flow of acoustic energy.

Carbon fiber counting. [aircraft structures

NASA Technical Reports Server (NTRS)

Pride, R. A.

1980-01-01

A method was developed for characterizing the number and lengths of carbon fibers accidentally released by the burning of composite portions of civil aircraft structure in a jet fuel fire after an accident. Representative samplings of carbon fibers collected on transparent sticky film were counted from photographic enlargements with a computer aided technique which also provided fiber lengths.

Accurate structural and spectroscopic characterization of prebiotic molecules: The neutral and cationic acetyl cyanide and their related species.

PubMed

Bellili, A; Linguerri, R; Hochlaf, M; Puzzarini, C

2015-11-14

In an effort to provide an accurate structural and spectroscopic characterization of acetyl cyanide, its two enolic isomers and the corresponding cationic species, state-of-the-art computational methods, and approaches have been employed. The coupled-cluster theory including single and double excitations together with a perturbative treatment of triples has been used as starting point in composite schemes accounting for extrapolation to the complete basis-set limit as well as core-valence correlation effects to determine highly accurate molecular structures, fundamental vibrational frequencies, and rotational parameters. The available experimental data for acetyl cyanide allowed us to assess the reliability of our computations: structural, energetic, and spectroscopic properties have been obtained with an overall accuracy of about, or better than, 0.001 Å, 2 kcal/mol, 1-10 MHz, and 11 cm(-1) for bond distances, adiabatic ionization potentials, rotational constants, and fundamental vibrational frequencies, respectively. We are therefore confident that the highly accurate spectroscopic data provided herein can be useful for guiding future experimental investigations and/or astronomical observations.

Docking-based modeling of protein-protein interfaces for extensive structural and functional characterization of missense mutations.

PubMed

Barradas-Bautista, Didier; Fernández-Recio, Juan

2017-01-01

Next-generation sequencing (NGS) technologies are providing genomic information for an increasing number of healthy individuals and patient populations. In the context of the large amount of generated genomic data that is being generated, understanding the effect of disease-related mutations at molecular level can contribute to close the gap between genotype and phenotype and thus improve prevention, diagnosis or treatment of a pathological condition. In order to fully characterize the effect of a pathological mutation and have useful information for prediction purposes, it is important first to identify whether the mutation is located at a protein-binding interface, and second to understand the effect on the binding affinity of the affected interaction/s. Computational methods, such as protein docking are currently used to complement experimental efforts and could help to build the human structural interactome. Here we have extended the original pyDockNIP method to predict the location of disease-associated nsSNPs at protein-protein interfaces, when there is no available structure for the protein-protein complex. We have applied this approach to the pathological interaction networks of six diseases with low structural data on PPIs. This approach can almost double the number of nsSNPs that can be characterized and identify edgetic effects in many nsSNPs that were previously unknown. This can help to annotate and interpret genomic data from large-scale population studies, and to achieve a better understanding of disease at molecular level.

Docking-based modeling of protein-protein interfaces for extensive structural and functional characterization of missense mutations

PubMed Central

2017-01-01

Next-generation sequencing (NGS) technologies are providing genomic information for an increasing number of healthy individuals and patient populations. In the context of the large amount of generated genomic data that is being generated, understanding the effect of disease-related mutations at molecular level can contribute to close the gap between genotype and phenotype and thus improve prevention, diagnosis or treatment of a pathological condition. In order to fully characterize the effect of a pathological mutation and have useful information for prediction purposes, it is important first to identify whether the mutation is located at a protein-binding interface, and second to understand the effect on the binding affinity of the affected interaction/s. Computational methods, such as protein docking are currently used to complement experimental efforts and could help to build the human structural interactome. Here we have extended the original pyDockNIP method to predict the location of disease-associated nsSNPs at protein-protein interfaces, when there is no available structure for the protein-protein complex. We have applied this approach to the pathological interaction networks of six diseases with low structural data on PPIs. This approach can almost double the number of nsSNPs that can be characterized and identify edgetic effects in many nsSNPs that were previously unknown. This can help to annotate and interpret genomic data from large-scale population studies, and to achieve a better understanding of disease at molecular level. PMID:28841721

Computer-Based Methods for Thermodynamic Analysis of Materials Processing.

DTIC Science & Technology

1983-11-30

metallic alloys (12,13), silicides (14),and oxynitride * . systems (15). - . 2. Thermochemical System Employed to Characterize Binary Ill-V Phase Diagrams The...reference to Figure I shows that the stable form of RbF is the sodium chloride S form. Table I shows that OGH -oS -RFRFLS-RFRFLM-12866-.381T J/g.at. (5...KF, BF=(I/3)8aF LF-(I/4)LaF3V PF-(113)PbF 2 S- Sodium Chloride Structures Stable form of NF, KE, RE and (;F L-Liquid, M-Stable form of ZF, KeStable form

Stepwise Bay Annulation of Indigo for the Synthesis of Desymmetrized Electron Acceptors and Donor–Acceptor Constructs

DOE PAGES

Kolaczkowski, Matthew A.; He, Bo; Liu, Yi

2016-10-10

In this work, a selective stepwise annulation of indigo has been demonstrated as a means of providing both monoannulated and differentially double-annulated indigo derivatives. Disparate substitution of the electron accepting bay-annulated indigo system allows for fine control over both the electronic properties as well as donor-acceptor structural architectures. Optical and electronic properties were characterized computationally as well as through UV-vis absorption spectroscopy and cyclic voltammetry. Finally, this straightforward method provides a modular approach for the design of indigo-based materials with tailored optoelectronic properties.

THE FUTURE OF COMPUTER-BASED TOXICITY PREDICTION: MECHANISM-BASED MODELS VS. INFORMATION MINING APPROACHES

EPA Science Inventory

The Future of Computer-Based Toxicity Prediction:
Mechanism-Based Models vs. Information Mining Approaches

When we speak of computer-based toxicity prediction, we are generally referring to a broad array of approaches which rely primarily upon chemical structure ...

In-Situ X-ray Tomography Observation of Structure Evolution in 1,3,5-Triamino-2,4,6-Trinitrobenzene Based Polymer Bonded Explosive (TATB-PBX) under Thermo-Mechanical Loading.

PubMed

Yuan, Zeng-Nian; Chen, Hua; Li, Jing-Ming; Dai, Bin; Zhang, Wei-Bin

2018-05-04

In order to study the fracture behavior and structure evolution of 1,3,5-Triamino-2,4,6-Trinitrobenzene (TATB)-based polymer bonded explosive in thermal-mechanical loading, in-situ studies were performed on X-ray computed tomography system using quasi-static Brazilian test. The experiment temperature was set from −20 °C to 70 °C. Three-dimensional morphology of cracks at different temperatures was obtained through digital image process. The various fracture modes were compared by scanning electron microscopy. Fracture degree and complexity were defined to quantitatively characterize the different types of fractures. Fractal dimension was used to characterize the roughness of the crack surface. The displacement field of particles in polymer bonded explosive (PBX) was used to analyze the interior structure evolution during the process of thermal-mechanical loading. It was found that the brittleness of PBX reduced, the fracture got more tortuous, and the crack surface got smoother as the temperature rose. At lower temperatures, especially lower than glass transition temperature of binders, there were slipping and shear among particles, and particles tended to displace and disperse; while at higher temperatures, especially above the glass transition temperature of binders, there was reorganization of particles and particles tended to merge, disperse, and reduce sizes, rather than displacing.

Introducing etch kernels for efficient pattern sampling and etch bias prediction

NASA Astrophysics Data System (ADS)

Weisbuch, François; Lutich, Andrey; Schatz, Jirka

2018-01-01

Successful patterning requires good control of the photolithography and etch processes. While compact litho models, mainly based on rigorous physics, can predict very well the contours printed in photoresist, pure empirical etch models are less accurate and more unstable. Compact etch models are based on geometrical kernels to compute the litho-etch biases that measure the distance between litho and etch contours. The definition of the kernels, as well as the choice of calibration patterns, is critical to get a robust etch model. This work proposes to define a set of independent and anisotropic etch kernels-"internal, external, curvature, Gaussian, z_profile"-designed to represent the finest details of the resist geometry to characterize precisely the etch bias at any point along a resist contour. By evaluating the etch kernels on various structures, it is possible to map their etch signatures in a multidimensional space and analyze them to find an optimal sampling of structures. The etch kernels evaluated on these structures were combined with experimental etch bias derived from scanning electron microscope contours to train artificial neural networks to predict etch bias. The method applied to contact and line/space layers shows an improvement in etch model prediction accuracy over standard etch model. This work emphasizes the importance of the etch kernel definition to characterize and predict complex etch effects.

Towards quantitative classification of folded proteins in terms of elementary functions.

PubMed

Hu, Shuangwei; Krokhotin, Andrei; Niemi, Antti J; Peng, Xubiao

2011-04-01

A comparative classification scheme provides a good basis for several approaches to understand proteins, including prediction of relations between their structure and biological function. But it remains a challenge to combine a classification scheme that describes a protein starting from its well-organized secondary structures and often involves direct human involvement, with an atomary-level physics-based approach where a protein is fundamentally nothing more than an ensemble of mutually interacting carbon, hydrogen, oxygen, and nitrogen atoms. In order to bridge these two complementary approaches to proteins, conceptually novel tools need to be introduced. Here we explain how an approach toward geometric characterization of entire folded proteins can be based on a single explicit elementary function that is familiar from nonlinear physical systems where it is known as the kink soliton. Our approach enables the conversion of hierarchical structural information into a quantitative form that allows for a folded protein to be characterized in terms of a small number of global parameters that are in principle computable from atomary-level considerations. As an example we describe in detail how the native fold of the myoglobin 1M6C emerges from a combination of kink solitons with a very high atomary-level accuracy. We also verify that our approach describes longer loops and loops connecting α helices with β strands, with the same overall accuracy. ©2011 American Physical Society

Real-Time Ligand Binding Pocket Database Search Using Local Surface Descriptors

PubMed Central

Chikhi, Rayan; Sael, Lee; Kihara, Daisuke

2010-01-01

Due to the increasing number of structures of unknown function accumulated by ongoing structural genomics projects, there is an urgent need for computational methods for characterizing protein tertiary structures. As functions of many of these proteins are not easily predicted by conventional sequence database searches, a legitimate strategy is to utilize structure information in function characterization. Of a particular interest is prediction of ligand binding to a protein, as ligand molecule recognition is a major part of molecular function of proteins. Predicting whether a ligand molecule binds a protein is a complex problem due to the physical nature of protein-ligand interactions and the flexibility of both binding sites and ligand molecules. However, geometric and physicochemical complementarity is observed between the ligand and its binding site in many cases. Therefore, ligand molecules which bind to a local surface site in a protein can be predicted by finding similar local pockets of known binding ligands in the structure database. Here, we present two representations of ligand binding pockets and utilize them for ligand binding prediction by pocket shape comparison. These representations are based on mapping of surface properties of binding pockets, which are compactly described either by the two dimensional pseudo-Zernike moments or the 3D Zernike descriptors. These compact representations allow a fast real-time pocket searching against a database. Thorough benchmark study employing two different datasets show that our representations are competitive with the other existing methods. Limitations and potentials of the shape-based methods as well as possible improvements are discussed. PMID:20455259

Real-time ligand binding pocket database search using local surface descriptors.

PubMed

Chikhi, Rayan; Sael, Lee; Kihara, Daisuke

2010-07-01

Because of the increasing number of structures of unknown function accumulated by ongoing structural genomics projects, there is an urgent need for computational methods for characterizing protein tertiary structures. As functions of many of these proteins are not easily predicted by conventional sequence database searches, a legitimate strategy is to utilize structure information in function characterization. Of particular interest is prediction of ligand binding to a protein, as ligand molecule recognition is a major part of molecular function of proteins. Predicting whether a ligand molecule binds a protein is a complex problem due to the physical nature of protein-ligand interactions and the flexibility of both binding sites and ligand molecules. However, geometric and physicochemical complementarity is observed between the ligand and its binding site in many cases. Therefore, ligand molecules which bind to a local surface site in a protein can be predicted by finding similar local pockets of known binding ligands in the structure database. Here, we present two representations of ligand binding pockets and utilize them for ligand binding prediction by pocket shape comparison. These representations are based on mapping of surface properties of binding pockets, which are compactly described either by the two-dimensional pseudo-Zernike moments or the three-dimensional Zernike descriptors. These compact representations allow a fast real-time pocket searching against a database. Thorough benchmark studies employing two different datasets show that our representations are competitive with the other existing methods. Limitations and potentials of the shape-based methods as well as possible improvements are discussed.

Development of an Aeroelastic Modeling Capability for Transient Nozzle Side Load Analysis

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Zhao, Xiang; Zhang, Sijun; Chen, Yen-Sen

2013-01-01

Lateral nozzle forces are known to cause severe structural damage to any new rocket engine in development. Currently there is no fully coupled computational tool to analyze this fluid/structure interaction process. The objective of this study was to develop a fully coupled aeroelastic modeling capability to describe the fluid/structure interaction process during the transient nozzle operations. The aeroelastic model composes of three components: the computational fluid dynamics component based on an unstructured-grid, pressure-based computational fluid dynamics formulation, the computational structural dynamics component developed in the framework of modal analysis, and the fluid-structural interface component. The developed aeroelastic model was applied to the transient nozzle startup process of the Space Shuttle Main Engine at sea level. The computed nozzle side loads and the axial nozzle wall pressure profiles from the aeroelastic nozzle are compared with those of the published rigid nozzle results, and the impact of the fluid/structure interaction on nozzle side loads is interrogated and presented.

Computational materials chemistry for carbon capture using porous materials

NASA Astrophysics Data System (ADS)

Sharma, Abhishek; Huang, Runhong; Malani, Ateeque; Babarao, Ravichandar

2017-11-01

Control over carbon dioxide (CO2) release is extremely important to decrease its hazardous effects on the environment such as global warming, ocean acidification, etc. For CO2 capture and storage at industrial point sources, nanoporous materials offer an energetically viable and economically feasible approach compared to chemisorption in amines. There is a growing need to design and synthesize new nanoporous materials with enhanced capability for carbon capture. Computational materials chemistry offers tools to screen and design cost-effective materials for CO2 separation and storage, and it is less time consuming compared to trial and error experimental synthesis. It also provides a guide to synthesize new materials with better properties for real world applications. In this review, we briefly highlight the various carbon capture technologies and the need of computational materials design for carbon capture. This review discusses the commonly used computational chemistry-based simulation methods for structural characterization and prediction of thermodynamic properties of adsorbed gases in porous materials. Finally, simulation studies reported on various potential porous materials, such as zeolites, porous carbon, metal organic frameworks (MOFs) and covalent organic frameworks (COFs), for CO2 capture are discussed.

Comparing DNA damage-processing pathways by computer analysis of chromosome painting data.

PubMed

Levy, Dan; Vazquez, Mariel; Cornforth, Michael; Loucas, Bradford; Sachs, Rainer K; Arsuaga, Javier

2004-01-01

Chromosome aberrations are large-scale illegitimate rearrangements of the genome. They are indicative of DNA damage and informative about damage processing pathways. Despite extensive investigations over many years, the mechanisms underlying aberration formation remain controversial. New experimental assays such as multiplex fluorescent in situ hybridyzation (mFISH) allow combinatorial "painting" of chromosomes and are promising for elucidating aberration formation mechanisms. Recently observed mFISH aberration patterns are so complex that computer and graph-theoretical methods are needed for their full analysis. An important part of the analysis is decomposing a chromosome rearrangement process into "cycles." A cycle of order n, characterized formally by the cyclic graph with 2n vertices, indicates that n chromatin breaks take part in a single irreducible reaction. We here describe algorithms for computing cycle structures from experimentally observed or computer-simulated mFISH aberration patterns. We show that analyzing cycles quantitatively can distinguish between different aberration formation mechanisms. In particular, we show that homology-based mechanisms do not generate the large number of complex aberrations, involving higher-order cycles, observed in irradiated human lymphocytes.

Quantitative Characterization of Molecular Similarity Spaces: Tools for Computational Toxicology

DTIC Science & Technology

2000-01-20

numbers for hydrogen-filled molecular structure, hydrogen-suppressed molecular structure, and van der Waals volume. Van der Waals...relative covalent radii Geometrical Vw van der Waals volume 3DW 3-D Wiener number for the hydrogen-suppressed geometric distance matrix...molecular structure, and van der Waals volume. Van der Waals volume, Vw (Bondi 1964). was calculated using Sybyl 6.1 from Tripos As- sociates. Inc

K-Partite RNA Secondary Structures

NASA Astrophysics Data System (ADS)

Jiang, Minghui; Tejada, Pedro J.; Lasisi, Ramoni O.; Cheng, Shanhong; Fechser, D. Scott

RNA secondary structure prediction is a fundamental problem in structural bioinformatics. The prediction problem is difficult because RNA secondary structures may contain pseudoknots formed by crossing base pairs. We introduce k-partite secondary structures as a simple classification of RNA secondary structures with pseudoknots. An RNA secondary structure is k-partite if it is the union of k pseudoknot-free sub-structures. Most known RNA secondary structures are either bipartite or tripartite. We show that there exists a constant number k such that any secondary structure can be modified into a k-partite secondary structure with approximately the same free energy. This offers a partial explanation of the prevalence of k-partite secondary structures with small k. We give a complete characterization of the computational complexities of recognizing k-partite secondary structures for all k ≥ 2, and show that this recognition problem is essentially the same as the k-colorability problem on circle graphs. We present two simple heuristics, iterated peeling and first-fit packing, for finding k-partite RNA secondary structures. For maximizing the number of base pair stackings, our iterated peeling heuristic achieves a constant approximation ratio of at most k for 2 ≤ k ≤ 5, and at most frac6{1-(1-6/k)^k} le frac6{1-e^{-6}} < 6.01491 for k ≥ 6. Experiment on sequences from PseudoBase shows that our first-fit packing heuristic outperforms the leading method HotKnots in predicting RNA secondary structures with pseudoknots. Source code, data set, and experimental results are available at http://www.cs.usu.edu/ mjiang/rna/kpartite/.

Exploring the Structure of Spatial Representations

PubMed Central

Madl, Tamas; Franklin, Stan; Chen, Ke; Trappl, Robert; Montaldi, Daniela

2016-01-01

It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these ‘cognitive maps’ are not well understood. We propose that the structure of the representations of navigation space arises from clustering within individual psychological spaces, i.e. from a process that groups together objects that are close in these spaces. Building on the ideas of representational geometry and similarity-based representations in cognitive science, we formulate methods for learning dissimilarity functions (metrics) characterizing participants’ psychological spaces. We show that these learned metrics, together with a probabilistic model of clustering based on the Bayesian cognition paradigm, allow prediction of participants’ cognitive map structures in advance. Apart from insights into spatial representation learning in human cognition, these methods could facilitate novel computational tools capable of using human-like spatial concepts. We also compare several features influencing spatial memory structure, including spatial distance, visual similarity and functional similarity, and report strong correlations between these dimensions and the grouping probability in participants’ spatial representations, providing further support for clustering in spatial memory. PMID:27347681

3D-SURFER 2.0: web platform for real-time search and characterization of protein surfaces.

PubMed

Xiong, Yi; Esquivel-Rodriguez, Juan; Sael, Lee; Kihara, Daisuke

2014-01-01

The increasing number of uncharacterized protein structures necessitates the development of computational approaches for function annotation using the protein tertiary structures. Protein structure database search is the basis of any structure-based functional elucidation of proteins. 3D-SURFER is a web platform for real-time protein surface comparison of a given protein structure against the entire PDB using 3D Zernike descriptors. It can smoothly navigate the protein structure space in real-time from one query structure to another. A major new feature of Release 2.0 is the ability to compare the protein surface of a single chain, a single domain, or a single complex against databases of protein chains, domains, complexes, or a combination of all three in the latest PDB. Additionally, two types of protein structures can now be compared: all-atom-surface and backbone-atom-surface. The server can also accept a batch job for a large number of database searches. Pockets in protein surfaces can be identified by VisGrid and LIGSITE (csc) . The server is available at http://kiharalab.org/3d-surfer/.

Introducing anisotropic Minkowski functionals and quantitative anisotropy measures for local structure analysis in biomedical imaging

NASA Astrophysics Data System (ADS)

Wismüller, Axel; De, Titas; Lochmüller, Eva; Eckstein, Felix; Nagarajan, Mahesh B.

2013-03-01

The ability of Minkowski Functionals to characterize local structure in different biological tissue types has been demonstrated in a variety of medical image processing tasks. We introduce anisotropic Minkowski Functionals (AMFs) as a novel variant that captures the inherent anisotropy of the underlying gray-level structures. To quantify the anisotropy characterized by our approach, we further introduce a method to compute a quantitative measure motivated by a technique utilized in MR diffusion tensor imaging, namely fractional anisotropy. We showcase the applicability of our method in the research context of characterizing the local structure properties of trabecular bone micro-architecture in the proximal femur as visualized on multi-detector CT. To this end, AMFs were computed locally for each pixel of ROIs extracted from the head, neck and trochanter regions. Fractional anisotropy was then used to quantify the local anisotropy of the trabecular structures found in these ROIs and to compare its distribution in different anatomical regions. Our results suggest a significantly greater concentration of anisotropic trabecular structures in the head and neck regions when compared to the trochanter region (p < 10-4). We also evaluated the ability of such AMFs to predict bone strength in the femoral head of proximal femur specimens obtained from 50 donors. Our results suggest that such AMFs, when used in conjunction with multi-regression models, can outperform more conventional features such as BMD in predicting failure load. We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding directional attributes of local structure, which may be useful in a wide scope of biomedical imaging applications.

Introducing Anisotropic Minkowski Functionals and Quantitative Anisotropy Measures for Local Structure Analysis in Biomedical Imaging

PubMed Central

Wismüller, Axel; De, Titas; Lochmüller, Eva; Eckstein, Felix; Nagarajan, Mahesh B.

2017-01-01

The ability of Minkowski Functionals to characterize local structure in different biological tissue types has been demonstrated in a variety of medical image processing tasks. We introduce anisotropic Minkowski Functionals (AMFs) as a novel variant that captures the inherent anisotropy of the underlying gray-level structures. To quantify the anisotropy characterized by our approach, we further introduce a method to compute a quantitative measure motivated by a technique utilized in MR diffusion tensor imaging, namely fractional anisotropy. We showcase the applicability of our method in the research context of characterizing the local structure properties of trabecular bone micro-architecture in the proximal femur as visualized on multi-detector CT. To this end, AMFs were computed locally for each pixel of ROIs extracted from the head, neck and trochanter regions. Fractional anisotropy was then used to quantify the local anisotropy of the trabecular structures found in these ROIs and to compare its distribution in different anatomical regions. Our results suggest a significantly greater concentration of anisotropic trabecular structures in the head and neck regions when compared to the trochanter region (p < 10−4). We also evaluated the ability of such AMFs to predict bone strength in the femoral head of proximal femur specimens obtained from 50 donors. Our results suggest that such AMFs, when used in conjunction with multi-regression models, can outperform more conventional features such as BMD in predicting failure load. We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding directional attributes of local structure, which may be useful in a wide scope of biomedical imaging applications. PMID:29170580

X-ray micro computed tomography characterization of cellular SiC foams for their applications in chemical engineering

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

Ou, Xiaoxia

Open-cell SiC foams clearly are promising materials for continuous-flow chemical applications such as heterogeneous catalysis and distillation. X-ray micro computed tomography characterization of cellular β-SiC foams at a spatial voxel size of 13.6{sup 3} μm{sup 3} and the interpretation of morphological properties of SiC open-cell foams with implications to their transport properties are presented. Static liquid hold-up in SiC foams was investigated through in-situ draining experiments for the first time using the μ-CT technique providing thorough 3D information about the amount and distribution of liquid hold-up inside the foam. This will enable better modeling and design of structured reactors basedmore » on SiC foams in the future. In order to see more practical uses, μ-CT data of cellular foams must be exploited to optimize the design of the morphology of foams for a specific application. - Highlights: •Characterization of SiC foams using novel X-ray micro computed tomography. •Interpretation of structural properties of SiC foams regarding to their transport properties. •Static liquid hold-up analysis of SiC foams through in-situ draining experiments.« less

Computer graphics application in the engineering design integration system

NASA Technical Reports Server (NTRS)

Glatt, C. R.; Abel, R. W.; Hirsch, G. N.; Alford, G. E.; Colquitt, W. N.; Stewart, W. A.

1975-01-01

The computer graphics aspect of the Engineering Design Integration (EDIN) system and its application to design problems were discussed. Three basic types of computer graphics may be used with the EDIN system for the evaluation of aerospace vehicles preliminary designs: offline graphics systems using vellum-inking or photographic processes, online graphics systems characterized by direct coupled low cost storage tube terminals with limited interactive capabilities, and a minicomputer based refresh terminal offering highly interactive capabilities. The offline line systems are characterized by high quality (resolution better than 0.254 mm) and slow turnaround (one to four days). The online systems are characterized by low cost, instant visualization of the computer results, slow line speed (300 BAUD), poor hard copy, and the early limitations on vector graphic input capabilities. The recent acquisition of the Adage 330 Graphic Display system has greatly enhanced the potential for interactive computer aided design.

Rotational and Infrared Spectroscopy of Ethanimine: A Route toward Its Astrophysical and Planetary Detection

NASA Astrophysics Data System (ADS)

Melli, Alessio; Melosso, Mattia; Tasinato, Nicola; Bosi, Giulio; Spada, Lorenzo; Bloino, Julien; Mendolicchio, Marco; Dore, Luca; Barone, Vincenzo; Puzzarini, Cristina

2018-03-01

Ethanimine, a possible precursor of amino acids, is considered an important prebiotic molecule and thus may play important roles in the formation of biological building blocks in the interstellar medium. In addition, its identification in Titan’s atmosphere would be important for understanding the abiotic synthesis of organic species. An accurate computational characterization of the molecular structure, energetics, and spectroscopic properties of the E and Z isomers of ethanimine, CH3CHNH, has been carried out by means of a composite scheme based on coupled-cluster techniques, which also account for extrapolation to the complete basis-set limit and core-valence correlation correction, combined with density functional theory for the treatment of vibrational anharmonic effects. By combining the computational results with new millimeter-wave measurements up to 300 GHz, the rotational spectrum of both isomers can be accurately predicted up to 500 GHz. Furthermore, our computations allowed us to revise the infrared spectrum of both E- and Z-CH3CHNH, thus predicting all fundamental bands with high accuracy.

Towards cortex sized artificial neural systems.

PubMed

Johansson, Christopher; Lansner, Anders

2007-01-01

We propose, implement, and discuss an abstract model of the mammalian neocortex. This model is instantiated with a sparse recurrently connected neural network that has spiking leaky integrator units and continuous Hebbian learning. First we study the structure, modularization, and size of neocortex, and then we describe a generic computational model of the cortical circuitry. A characterizing feature of the model is that it is based on the modularization of neocortex into hypercolumns and minicolumns. Both a floating- and fixed-point arithmetic implementation of the model are presented along with simulation results. We conclude that an implementation on a cluster computer is not communication but computation bounded. A mouse and rat cortex sized version of our model executes in 44% and 23% of real-time respectively. Further, an instance of the model with 1.6 x 10(6) units and 2 x 10(11) connections performed noise reduction and pattern completion. These implementations represent the current frontier of large-scale abstract neural network simulations in terms of network size and running speed.

Noise facilitation in associative memories of exponential capacity.

PubMed

Karbasi, Amin; Salavati, Amir Hesam; Shokrollahi, Amin; Varshney, Lav R

2014-11-01

Recent advances in associative memory design through structured pattern sets and graph-based inference algorithms have allowed reliable learning and recall of an exponential number of patterns that satisfy certain subspace constraints. Although these designs correct external errors in recall, they assume neurons that compute noiselessly, in contrast to the highly variable neurons in brain regions thought to operate associatively, such as hippocampus and olfactory cortex. Here we consider associative memories with boundedly noisy internal computations and analytically characterize performance. As long as the internal noise level is below a specified threshold, the error probability in the recall phase can be made exceedingly small. More surprising, we show that internal noise improves the performance of the recall phase while the pattern retrieval capacity remains intact: the number of stored patterns does not reduce with noise (up to a threshold). Computational experiments lend additional support to our theoretical analysis. This work suggests a functional benefit to noisy neurons in biological neuronal networks.

Computer-Based Indexing on a Small Scale: Bibliography.

ERIC Educational Resources Information Center

Douglas, Kimberly; Wismer, Don

The 131 references on small scale computer-based indexing cited in this bibliography are subdivided as follows: general, general (computer), index structure, microforms, specific systems, KWIC KWAC KWOC, and thesauri. (RAA)

Computational solvation analysis of biomolecules in aqueous ionic liquid mixtures : From large flexible proteins to small rigid drugs.

PubMed

Zeindlhofer, Veronika; Schröder, Christian

2018-06-01

Based on their tunable properties, ionic liquids attracted significant interest to replace conventional, organic solvents in biomolecular applications. Following a Gartner cycle, the expectations on this new class of solvents dropped after the initial hype due to the high viscosity, hydrolysis, and toxicity problems as well as their high cost. Since not all possible combinations of cations and anions can be tested experimentally, fundamental knowledge on the interaction of the ionic liquid ions with water and with biomolecules is mandatory to optimize the solvation behavior, the biodegradability, and the costs of the ionic liquid. Here, we report on current computational approaches to characterize the impact of the ionic liquid ions on the structure and dynamics of the biomolecule and its solvation layer to explore the full potential of ionic liquids.

Characterization and reconstruction of 3D stochastic microstructures via supervised learning.

PubMed

Bostanabad, R; Chen, W; Apley, D W

2016-12-01

The need for computational characterization and reconstruction of volumetric maps of stochastic microstructures for understanding the role of material structure in the processing-structure-property chain has been highlighted in the literature. Recently, a promising characterization and reconstruction approach has been developed where the essential idea is to convert the digitized microstructure image into an appropriate training dataset to learn the stochastic nature of the morphology by fitting a supervised learning model to the dataset. This compact model can subsequently be used to efficiently reconstruct as many statistically equivalent microstructure samples as desired. The goal of this paper is to build upon the developed approach in three major directions by: (1) extending the approach to characterize 3D stochastic microstructures and efficiently reconstruct 3D samples, (2) improving the performance of the approach by incorporating user-defined predictors into the supervised learning model, and (3) addressing potential computational issues by introducing a reduced model which can perform as effectively as the full model. We test the extended approach on three examples and show that the spatial dependencies, as evaluated via various measures, are well preserved in the reconstructed samples. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

Discrete Molecular Dynamics Can Predict Helical Prestructured Motifs in Disordered Proteins

PubMed Central

Han, Kyou-Hoon; Dokholyan, Nikolay V.; Tompa, Péter; Kalmár, Lajos; Hegedűs, Tamás

2014-01-01

Intrinsically disordered proteins (IDPs) lack a stable tertiary structure, but their short binding regions termed Pre-Structured Motifs (PreSMo) can form transient secondary structure elements in solution. Although disordered proteins are crucial in many biological processes and designing strategies to modulate their function is highly important, both experimental and computational tools to describe their conformational ensembles and the initial steps of folding are sparse. Here we report that discrete molecular dynamics (DMD) simulations combined with replica exchange (RX) method efficiently samples the conformational space and detects regions populating α-helical conformational states in disordered protein regions. While the available computational methods predict secondary structural propensities in IDPs based on the observation of protein-protein interactions, our ab initio method rests on physical principles of protein folding and dynamics. We show that RX-DMD predicts α-PreSMos with high confidence confirmed by comparison to experimental NMR data. Moreover, the method also can dissect α-PreSMos in close vicinity to each other and indicate helix stability. Importantly, simulations with disordered regions forming helices in X-ray structures of complexes indicate that a preformed helix is frequently the binding element itself, while in other cases it may have a role in initiating the binding process. Our results indicate that RX-DMD provides a breakthrough in the structural and dynamical characterization of disordered proteins by generating the structural ensembles of IDPs even when experimental data are not available. PMID:24763499

On the use of log-transformation vs. nonlinear regression for analyzing biological power laws.

PubMed

Xiao, Xiao; White, Ethan P; Hooten, Mevin B; Durham, Susan L

2011-10-01

Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain.

A new mixed-ligand copper(II) complex of (E)-N";-(2-hydroxybenzylidene) acetohydrazide: Synthesis, characterization, NLO behavior, DFT calculation and biological activities

NASA Astrophysics Data System (ADS)

Yousef Ebrahimipour, S.; Sheikhshoaie, Iran; Crochet, Aurelien; Khaleghi, Moj; Fromm, Katharina M.

2014-08-01

A tridentate hydrazone Schiff base ligand, (E)-N";-(2-hydroxybenzylidene)acetohydrazide [HL], and its mixed-ligand Cu(II) complex [CuL(phen)], have been synthesized and characterized by elemental analyses, FT-IR, molar conductivity, UV-Vis spectroscopy. The structure of the complex has been determined by X-ray diffraction. This complex has square pyramidal geometry and the positions around central atom are occupied with donor atoms of Schiff base ligand and two nitrogens of 1,10-phenanthroline. Computational studies of compounds were performed by using DFT calculations. The linear polarizabilities and first hyperpolarizabilities of the studied molecules indicate that these compounds can be good candidates of nonlinear optical materials. It is in accordance with experimental data. In addition, invitro antimicrobial results show that these compounds specially [CuL(phen)] have great potential of antibacterial activity against Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, Listeria monocytogenes bacteria and antifungal activity against Candida Albicans in comparison to some standard drugs.

Spectrum of the Laplace-Beltrami operator and the phase structure of causal dynamical triangulations

NASA Astrophysics Data System (ADS)

Clemente, Giuseppe; D'Elia, Massimo

2018-06-01

We propose a new method to characterize the different phases observed in the nonperturbative numerical approach to quantum gravity known as causal dynamical triangulations. The method is based on the analysis of the eigenvalues and the eigenvectors of the Laplace-Beltrami operator computed on the triangulations: it generalizes previous works based on the analysis of diffusive processes and proves capable of providing more detailed information on the geometric properties of the triangulations. In particular, we apply the method to the analysis of spatial slices, showing that the different phases can be characterized by a new order parameter related to the presence or absence of a gap in the spectrum of the Laplace-Beltrami operator, and deriving an effective dimensionality of the slices at the different scales. We also propose quantities derived from the spectrum that could be used to monitor the running to the continuum limit around a suitable critical point in the phase diagram, if any is found.

Synthesis, spectroscopic characterization and computational chemical study of 5-cyano-2-thiouracil derivatives as potential antimicrobial agents

NASA Astrophysics Data System (ADS)

Rizk, Sameh A.; El-Naggar, Abeer M.; El-Badawy, Azza A.

2018-03-01

A series of 5-cyano-2-thiouracil derivatives, containing diverse hydrophobic groups in the 2-, 4- and 6-positions, were synthesized through one pot reaction of thiophene 2-carboxaldehyde, ethylcyanoacetate and thiourea using classic reflux-based method as well as microwave-assisted methods. Such prepared compounds were reacted with different electrophilic reagents to synthesize potent anti-microbial agents, e.g. 1,3,4-thiadiazinopyrimidine, hydrazide and triazolopyrimidine derivatives (compounds 4a-e, 9 and 10-12) respectively. The density functional theory (DFT) was then applied to explore the structural and electronic characteristics of these materials. It is found that compound 12 exhibited the highest antibacterial and antifungal activity against C. Albicans showing six-fold increasing biological affinity compared to that of Colitrimazole drug with MIC values 7.8 and 49 μg/mL, respectively. All the synthesized compounds have been characterized based on their elemental analyses and spectral data. Such compounds can be submitted to in vivo antimicrobial studies in future works.

Computational aeroelasticity using a pressure-based solver

NASA Astrophysics Data System (ADS)

Kamakoti, Ramji

A computational methodology for performing fluid-structure interaction computations for three-dimensional elastic wing geometries is presented. The flow solver used is based on an unsteady Reynolds-Averaged Navier-Stokes (RANS) model. A well validated k-ε turbulence model with wall function treatment for near wall region was used to perform turbulent flow calculations. Relative merits of alternative flow solvers were investigated. The predictor-corrector-based Pressure Implicit Splitting of Operators (PISO) algorithm was found to be computationally economic for unsteady flow computations. Wing structure was modeled using Bernoulli-Euler beam theory. A fully implicit time-marching scheme (using the Newmark integration method) was used to integrate the equations of motion for structure. Bilinear interpolation and linear extrapolation techniques were used to transfer necessary information between fluid and structure solvers. Geometry deformation was accounted for by using a moving boundary module. The moving grid capability was based on a master/slave concept and transfinite interpolation techniques. Since computations were performed on a moving mesh system, the geometric conservation law must be preserved. This is achieved by appropriately evaluating the Jacobian values associated with each cell. Accurate computation of contravariant velocities for unsteady flows using the momentum interpolation method on collocated, curvilinear grids was also addressed. Flutter computations were performed for the AGARD 445.6 wing at subsonic, transonic and supersonic Mach numbers. Unsteady computations were performed at various dynamic pressures to predict the flutter boundary. Results showed favorable agreement of experiment and previous numerical results. The computational methodology exhibited capabilities to predict both qualitative and quantitative features of aeroelasticity.

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

PubMed

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

2015-11-01

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

Materials discovery guided by data-driven insights

NASA Astrophysics Data System (ADS)

Klintenberg, Mattias

As the computational power continues to grow systematic computational exploration has become an important tool for materials discovery. In this presentation the Electronic Structure Project (ESP/ELSA) will be discussed and a number of examples presented that show some of the capabilities of a data-driven methodology for guiding materials discovery. These examples include topological insulators, detector materials and 2D materials. ESP/ELSA is an initiative that dates back to 2001 and today contain many tens of thousands of materials that have been investigated using a robust and high accuracy electronic structure method (all-electron FP-LMTO) thus providing basic materials first-principles data for most inorganic compounds that have been structurally characterized. The web-site containing the ESP/ELSA data has as of today been accessed from more than 4,000 unique computers from all around the world.

Computational Analysis of Residue Interaction Networks and Coevolutionary Relationships in the Hsp70 Chaperones: A Community-Hopping Model of Allosteric Regulation and Communication

PubMed Central

Stetz, Gabrielle; Verkhivker, Gennady M.

2017-01-01

Allosteric interactions in the Hsp70 proteins are linked with their regulatory mechanisms and cellular functions. Despite significant progress in structural and functional characterization of the Hsp70 proteins fundamental questions concerning modularity of the allosteric interaction networks and hierarchy of signaling pathways in the Hsp70 chaperones remained largely unexplored and poorly understood. In this work, we proposed an integrated computational strategy that combined atomistic and coarse-grained simulations with coevolutionary analysis and network modeling of the residue interactions. A novel aspect of this work is the incorporation of dynamic residue correlations and coevolutionary residue dependencies in the construction of allosteric interaction networks and signaling pathways. We found that functional sites involved in allosteric regulation of Hsp70 may be characterized by structural stability, proximity to global hinge centers and local structural environment that is enriched by highly coevolving flexible residues. These specific characteristics may be necessary for regulation of allosteric structural transitions and could distinguish regulatory sites from nonfunctional conserved residues. The observed confluence of dynamics correlations and coevolutionary residue couplings with global networking features may determine modular organization of allosteric interactions and dictate localization of key mediating sites. Community analysis of the residue interaction networks revealed that concerted rearrangements of local interacting modules at the inter-domain interface may be responsible for global structural changes and a population shift in the DnaK chaperone. The inter-domain communities in the Hsp70 structures harbor the majority of regulatory residues involved in allosteric signaling, suggesting that these sites could be integral to the network organization and coordination of structural changes. Using a network-based formalism of allostery, we introduced a community-hopping model of allosteric communication. Atomistic reconstruction of signaling pathways in the DnaK structures captured a direction-specific mechanism and molecular details of signal transmission that are fully consistent with the mutagenesis experiments. The results of our study reconciled structural and functional experiments from a network-centric perspective by showing that global properties of the residue interaction networks and coevolutionary signatures may be linked with specificity and diversity of allosteric regulation mechanisms. PMID:28095400

Computational Analysis of Residue Interaction Networks and Coevolutionary Relationships in the Hsp70 Chaperones: A Community-Hopping Model of Allosteric Regulation and Communication.

PubMed

Stetz, Gabrielle; Verkhivker, Gennady M

2017-01-01

Allosteric interactions in the Hsp70 proteins are linked with their regulatory mechanisms and cellular functions. Despite significant progress in structural and functional characterization of the Hsp70 proteins fundamental questions concerning modularity of the allosteric interaction networks and hierarchy of signaling pathways in the Hsp70 chaperones remained largely unexplored and poorly understood. In this work, we proposed an integrated computational strategy that combined atomistic and coarse-grained simulations with coevolutionary analysis and network modeling of the residue interactions. A novel aspect of this work is the incorporation of dynamic residue correlations and coevolutionary residue dependencies in the construction of allosteric interaction networks and signaling pathways. We found that functional sites involved in allosteric regulation of Hsp70 may be characterized by structural stability, proximity to global hinge centers and local structural environment that is enriched by highly coevolving flexible residues. These specific characteristics may be necessary for regulation of allosteric structural transitions and could distinguish regulatory sites from nonfunctional conserved residues. The observed confluence of dynamics correlations and coevolutionary residue couplings with global networking features may determine modular organization of allosteric interactions and dictate localization of key mediating sites. Community analysis of the residue interaction networks revealed that concerted rearrangements of local interacting modules at the inter-domain interface may be responsible for global structural changes and a population shift in the DnaK chaperone. The inter-domain communities in the Hsp70 structures harbor the majority of regulatory residues involved in allosteric signaling, suggesting that these sites could be integral to the network organization and coordination of structural changes. Using a network-based formalism of allostery, we introduced a community-hopping model of allosteric communication. Atomistic reconstruction of signaling pathways in the DnaK structures captured a direction-specific mechanism and molecular details of signal transmission that are fully consistent with the mutagenesis experiments. The results of our study reconciled structural and functional experiments from a network-centric perspective by showing that global properties of the residue interaction networks and coevolutionary signatures may be linked with specificity and diversity of allosteric regulation mechanisms.

Theoretical, Experimental, and Computational Evaluation of Several Vane-Type Slow-Wave Structures

NASA Technical Reports Server (NTRS)

Wallett, Thomas M.; Qureshi, A. Haq

1994-01-01

Several types of periodic vane slow-wave structures were fabricated. The dispersion characteristics were found by theoretical analysis, experimental testing, and computer simulation using the MAFIA code. Computer-generated characteristics agreed to approximately within 2 percent of the experimental characteristics for all structures. The theoretical characteristics, however, deviated increasingly as the width to height ratio became smaller. Interaction impedances were also computed based on the experimental and computer-generated resonance frequency shifts due to the introduction of a perturbing dielectric rod.

Analysis of HD 73045 light curve data

NASA Astrophysics Data System (ADS)

Das, Mrinal Kanti; Bhatraju, Naveen Kumar; Joshi, Santosh

2018-04-01

In this work we analyzed the Kepler light curve data of HD 73045. The raw data has been smoothened using standard filters. The power spectrum has been obtained by using a fast Fourier transform routine. It shows the presence of more than one period. In order to take care of any non-stationary behavior, we carried out a wavelet analysis to obtain the wavelet power spectrum. In addition, to identify the scale invariant structure, the data has been analyzed using a multifractal detrended fluctuation analysis. Further to characterize the diversity of embedded patterns in the HD 73045 flux time series, we computed various entropy-based complexity measures e.g. sample entropy, spectral entropy and permutation entropy. The presence of periodic structure in the time series was further analyzed using the visibility network and horizontal visibility network model of the time series. The degree distributions in the two network models confirm such structures.

Structured light imaging system for structural and optical characterization of 3D tissue-simulating phantoms

NASA Astrophysics Data System (ADS)

Liu, Songde; Smith, Zach; Xu, Ronald X.

2016-10-01

There is a pressing need for a phantom standard to calibrate medical optical devices. However, 3D printing of tissue-simulating phantom standard is challenged by lacking of appropriate methods to characterize and reproduce surface topography and optical properties accurately. We have developed a structured light imaging system to characterize surface topography and optical properties (absorption coefficient and reduced scattering coefficient) of 3D tissue-simulating phantoms. The system consisted of a hyperspectral light source, a digital light projector (DLP), a CMOS camera, two polarizers, a rotational stage, a translation stage, a motion controller, and a personal computer. Tissue-simulating phantoms with different structural and optical properties were characterized by the proposed imaging system and validated by a standard integrating sphere system. The experimental results showed that the proposed system was able to achieve pixel-level optical properties with a percentage error of less than 11% for absorption coefficient and less than 7% for reduced scattering coefficient for phantoms without surface curvature. In the meanwhile, 3D topographic profile of the phantom can be effectively reconstructed with an accuracy of less than 1% deviation error. Our study demonstrated that the proposed structured light imaging system has the potential to characterize structural profile and optical properties of 3D tissue-simulating phantoms.

Modeling Flow in Porous Media with Double Porosity/Permeability.

NASA Astrophysics Data System (ADS)

Seyed Joodat, S. H.; Nakshatrala, K. B.; Ballarini, R.

2016-12-01

Although several continuum models are available to study the flow of fluids in porous media with two pore-networks [1], they lack a firm theoretical basis. In this poster presentation, we will present a mathematical model with firm thermodynamic basis and a robust computational framework for studying flow in porous media that exhibit double porosity/permeability. The mathematical model will be derived by appealing to the maximization of rate of dissipation hypothesis, which ensures that the model is in accord with the second law of thermodynamics. We will also present important properties that the solutions under the model satisfy, along with an analytical solution procedure based on the Green's function method. On the computational front, a stabilized mixed finite element formulation will be derived based on the variational multi-scale formalism. The equal-order interpolation, which is computationally the most convenient, is stable under this formulation. The performance of this formulation will be demonstrated using patch tests, numerical convergence study, and representative problems. It will be shown that the pressure and velocity profiles under the double porosity/permeability model are qualitatively and quantitatively different from the corresponding ones under the classical Darcy equations. Finally, it will be illustrated that the surface pore-structure is not sufficient in characterizing the flow through a complex porous medium, which pitches a case for using advanced characterization tools like micro-CT. References [1] G. I. Barenblatt, I. P. Zheltov, and I. N. Kochina, "Basic concepts in the theory of seepage of homogeneous liquids in fissured rocks [strata]," Journal of Applied Mathematics and Mechanics, vol. 24, pp. 1286-1303, 1960.

Ab-initio and DFT methodologies for computing hyperpolarizabilities and susceptibilities of highly conjugated organic compounds for nonlinear optical applications

NASA Astrophysics Data System (ADS)

Karakas, A.; Karakaya, M.; Ceylan, Y.; El Kouari, Y.; Taboukhat, S.; Boughaleb, Y.; Sofiani, Z.

2016-06-01

In this talk, after a short introduction on the methodologies used for computing dipole polarizability (α), second and third-order hyperpolarizability and susceptibility; the results of theoretical studies performed on density functional theory (DFT) and ab-initio quantum mechanical calculations of nonlinear optical (NLO) properties for a few selected organic compounds and polymers will be explained. The electric dipole moments (μ) and dispersion-free first hyperpolarizabilities (β) for a family of azo-azulenes and a styrylquinolinium dye have been determined by DFT at B3LYP level. To reveal the frequency-dependent NLO behavior, the dynamic α, second hyperpolarizabilities (γ), second (χ(2)) and third-order (χ(3)) susceptibilites have been evaluated using time-dependent HartreeFock (TDHF) procedure. To provide an insight into the third-order NLO phenomena of a series of pyrrolo-tetrathiafulvalene-based molecules and pushpull azobenzene polymers, two-photon absorption (TPA) characterizations have been also investigated by means of TDHF. All computed results of the examined compounds are compared with their previous experimental findings and the measured data for similar structures in the literature. The one-photon absorption (OPA) characterizations of the title molecules have been theoretically obtained by configuration interaction (CI) method. The highest occupied molecular orbitals (HOMO), the lowest unoccupied molecular orbitals (LUMO) and the HOMO-LUMO band gaps have been revealed by DFT at B3LYP level for azo-azulenes, styrylquinolinium dye, push-pull azobenzene polymers and by parametrization method 6 (PM6) for pyrrolo-tetrathiafulvalene-based molecules.

Polynuclear Aromatic Hydrocarbons with Curved Surfaces: Buckyballs

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

Sygula, Andrzej

The discovery of a new allotropic form of elemental carbon – the fullerenes – and subsequently other novel forms of elemental carbon with pyramidalized surfaces, most notably single-walled and multi-walled carbon nanotubes, introduced a novel structural motif to the polycyclic aromatic hydrocarbons (PAHs) with nonplanar surfaces. Our research program supported by BES DOE grant DE-FG02-04ER15514 has dealt with the synthesis, structural studies, and chemistry of the novel curved-surface PAHs with carbon frameworks structurally related to fullerenes. They are referred to as “buckybowls”. We prepared several new buckybowls and, even more importantly, developed the efficient, gram-scale synthetic methodologies for the preparationmore » of small buckybowls, most notably corannulene (C20H10) and its derivatives. In addition, the employment of the corannulene-based synthons previously developed in our laboratory led to a number of highly nonplanar molecular architectures with two or more corannulene subunits with a potential for the applications as novel materials in separation sciences, nanoelectronics, photovoltaics and catalysis. In collaboration with Professor Angelici (Iowa State) we prepared and characterized several transition metal complexes of corannulene, providing the first structural characterization of η6 metal complexes of buckybowls by a single crystal X-ray diffraction. In addition to the definitive structural characterization of the complexes we demonstrated that the (η6-C6Me6)Ru2+ unit in some relatively stable complexes activate the corannulene ligand to react with proper nucleophiles suggesting that such complexex may be used in catalysis. (Section C). We have explored the efficiency of the dispersion-based interactions of curved-surface conjugated carbon networks by high-level computational models. We showed that the curvature of such networks does not reduce the van der Waals attractions as compared to the planar systems of similar size. We than concentrated on the design, synthesis and testing of the previously unknown molecular receptors with corannulene pincers which are capable of forming the strong ball-and-socket inclusion complexes with fullerenes in solution and in the solid state. Buckycatcher I (a molecular receptor with two corannulene pincers preorganized on a tetrabensocyclooctatetraene tether) inclusion complexes with fullerenes provided the first experimental evidence for the importance of concave-convex π – π interactions in the supramolecular chemistry of fullerene carbon cages with buckybowls. C60@Buckycatcher I has become the prototypical supramolecular system formed by the relatively weak (on the atom-to-atom bases) and has been extensively used by the computational community to test the quality of the theoretical models. In addition, Buckycatcher I shows an exceptional ability to adopt other guest molecules and several its inclusion complexes and/or solvates have been structurally characterized. These unusual structures show the potential of the buckycatchers to be tested as novel organic materials. “Intelligent design” of molecular receptors with corannulene receptors using computational approach allowing for a priori prediction of their binding potentials led to the preparation of other buckycatchers. Both bi- and tridentate corannulene pincers were tested and two of the bidentate receptors (Buckycatchers II and III) exhibited the outstanding affinity toward fullerenes, significantly exciding Buckycatcher I performance. Careful tailoring of the tethers resulted in the optimization of binding energies of the receptors with guest carbon cages and in the reduction of the entropy/solvation penalties. Practical preparation of dicorannulenopentacene opens a new avenue for the synthesis of a pool of bis-corannulene receptors possessing polar groups on their dibenzobarrelene tether. The polar “anchors” can be used to attach these efficient fullerene receptors to solid supports in order to modify their surfaces with the potential applications in separation sciences, catalysis and photovoltaic materials. additionally, the presence of such groups will improve the solubility of the receptors in polar solvents, expanding the scope of their supramolecular chemistry in solutions. Rigorous studies of thermodynamics of host-guest association of molecular clips and tweezers in organic solvents with C60/C70 inclusion complexes with Buckycatcher I as a model system have provided a full set of thermodynamical data including ΔG, ΔH, and –TΔS, for the formation of the inclusion complexes over a range of temperatures and in several solvents. Both 1H NMR and Isothermal Calorimetry (ITC) titrations provide virtually identical association constants, confirming the reliability of the results. WE have shown that thermodynamics of the host-guest complex formation is more complicated than anticipated and proposed by the existing computational models. These data are of premium importance for the testing of the computational solvation models and for a deeper understanding of the supramolecular interactions in organic solvents.« less

Insights into Hydrate Formation and Stability of Morphinanes from a Combination of Experimental and Computational Approaches

PubMed Central

2014-01-01

Morphine, codeine, and ethylmorphine are important drug compounds whose free bases and hydrochloride salts form stable hydrates. These compounds were used to systematically investigate the influence of the type of functional groups, the role of water molecules, and the Cl– counterion on molecular aggregation and solid state properties. Five new crystal structures have been determined. Additionally, structure models for anhydrous ethylmorphine and morphine hydrochloride dihydrate, two phases existing only in a very limited humidity range, are proposed on the basis of computational dehydration modeling. These match the experimental powder X-ray diffraction patterns and the structural information derived from infrared spectroscopy. All 12 structurally characterized morphinane forms (including structures from the Cambridge Structural Database) crystallize in the orthorhombic space group P212121. Hydrate formation results in higher dimensional hydrogen bond networks. The salt structures of the different compounds exhibit only little structural variation. Anhydrous polymorphs were detected for all compounds except ethylmorphine (one anhydrate) and its hydrochloride salt (no anhydrate). Morphine HCl forms a trihydrate and dihydrate. Differential scanning and isothermal calorimetry were employed to estimate the heat of the hydrate ↔ anhydrate phase transformations, indicating an enthalpic stabilization of the respective hydrate of 5.7 to 25.6 kJ mol–1 relative to the most stable anhydrate. These results are in qualitative agreement with static 0 K lattice energy calculations for all systems except morphine hydrochloride, showing the need for further improvements in quantitative thermodynamic prediction of hydrates having water···water interactions. Thus, the combination of a variety of experimental techniques, covering temperature- and moisture-dependent stability, and computational modeling allowed us to generate sufficient kinetic, thermodynamic and structural information to understand the principles of hydrate formation of the model compounds. This approach also led to the detection of several new crystal forms of the investigated morphinanes. PMID:25036525

Visualization and prediction of supercritical CO 2 distribution in sandstones during drainage: An in situ synchrotron X-ray micro-computed tomography study

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

Voltolini, Marco; Kwon, Tae-Hyuk; Ajo-Franklin, Jonathan

Pore-scale distribution of supercritical CO 2 (scCO 2) exerts significant control on a variety of key hydrologic as well as geochemical processes, including residual trapping and dissolution. Despite such importance, only a small number of experiments have directly characterized the three-dimensional distribution of scCO 2 in geologic materials during the invasion (drainage) process. Here, we present a study which couples dynamic high-resolution synchrotron X-ray micro-computed tomography imaging of a scCO 2/brine system at in situ pressure/temperature conditions with quantitative pore-scale modeling to allow direct validation of a pore-scale description of scCO2 distribution. The experiment combines high-speed synchrotron radiography with tomographymore » to characterize the brine saturated sample, the scCO 2 breakthrough process, and the partially saturated state of a sandstone sample from the Domengine Formation, a regionally extensive unit within the Sacramento Basin (California, USA). The availability of a 3D dataset allowed us to examine correlations between grains and pores morphometric parameters and the actual distribution of scCO 2 in the sample, including the examination of the role of small-scale sedimentary structure on CO2 distribution. The segmented scCO 2/brine volume was also used to validate a simple computational model based on the local thickness concept, able to accurately simulate the distribution of scCO 2 after drainage. The same method was also used to simulate Hg capillary pressure curves with satisfactory results when compared to the measured ones. Finally, this predictive approach, requiring only a tomographic scan of the dry sample, proved to be an effective route for studying processes related to CO 2 invasion structure in geological samples at the pore scale.« less

Visualization and prediction of supercritical CO 2 distribution in sandstones during drainage: An in situ synchrotron X-ray micro-computed tomography study

DOE PAGES

Voltolini, Marco; Kwon, Tae-Hyuk; Ajo-Franklin, Jonathan

2017-10-21

Pore-scale distribution of supercritical CO 2 (scCO 2) exerts significant control on a variety of key hydrologic as well as geochemical processes, including residual trapping and dissolution. Despite such importance, only a small number of experiments have directly characterized the three-dimensional distribution of scCO 2 in geologic materials during the invasion (drainage) process. Here, we present a study which couples dynamic high-resolution synchrotron X-ray micro-computed tomography imaging of a scCO 2/brine system at in situ pressure/temperature conditions with quantitative pore-scale modeling to allow direct validation of a pore-scale description of scCO2 distribution. The experiment combines high-speed synchrotron radiography with tomographymore » to characterize the brine saturated sample, the scCO 2 breakthrough process, and the partially saturated state of a sandstone sample from the Domengine Formation, a regionally extensive unit within the Sacramento Basin (California, USA). The availability of a 3D dataset allowed us to examine correlations between grains and pores morphometric parameters and the actual distribution of scCO 2 in the sample, including the examination of the role of small-scale sedimentary structure on CO2 distribution. The segmented scCO 2/brine volume was also used to validate a simple computational model based on the local thickness concept, able to accurately simulate the distribution of scCO 2 after drainage. The same method was also used to simulate Hg capillary pressure curves with satisfactory results when compared to the measured ones. Finally, this predictive approach, requiring only a tomographic scan of the dry sample, proved to be an effective route for studying processes related to CO 2 invasion structure in geological samples at the pore scale.« less

Common and Distant Structural Characteristics of Feruloyl Esterase Families from Aspergillus oryzae

PubMed Central

Udatha, D. B. R. K. Gupta; Mapelli, Valeria; Panagiotou, Gianni; Olsson, Lisbeth

2012-01-01

Background Feruloyl esterases (FAEs) are important biomass degrading accessory enzymes due to their capability of cleaving the ester links between hemicellulose and pectin to aromatic compounds of lignin, thus enhancing the accessibility of plant tissues to cellulolytic and hemicellulolytic enzymes. FAEs have gained increased attention in the area of biocatalytic transformations for the synthesis of value added compounds with medicinal and nutritional applications. Following the increasing attention on these enzymes, a novel descriptor based classification system has been proposed for FAEs resulting into 12 distinct families and pharmacophore models for three FAE sub-families have been developed. Methodology/Principal Findings The feruloylome of Aspergillus oryzae contains 13 predicted FAEs belonging to six sub-families based on our recently developed descriptor-based classification system. The three-dimensional structures of the 13 FAEs were modeled for structural analysis of the feruloylome. The three genes coding for three enzymes, viz., A.O.2, A.O.8 and A.O.10 from the feruloylome of A. oryzae, representing sub-families with unknown functional features, were heterologously expressed in Pichia pastoris, characterized for substrate specificity and structural characterization through CD spectroscopy. Common feature-based pharamacophore models were developed according to substrate specificity characteristics of the three enzymes. The active site residues were identified for the three expressed FAEs by determining the titration curves of amino acid residues as a function of the pH by applying molecular simulations. Conclusions/Significance Our findings on the structure-function relationships and substrate specificity of the FAEs of A. oryzae will be instrumental for further understanding of the FAE families in the novel classification system. The developed pharmacophore models could be applied for virtual screening of compound databases for short listing the putative substrates prior to docking studies or for post-processing docking results to remove false positives. Our study exemplifies how computational predictions can complement to the information obtained through experimental methods. PMID:22745763

Common and distant structural characteristics of feruloyl esterase families from Aspergillus oryzae.

PubMed

Udatha, D B R K Gupta; Mapelli, Valeria; Panagiotou, Gianni; Olsson, Lisbeth

2012-01-01

Feruloyl esterases (FAEs) are important biomass degrading accessory enzymes due to their capability of cleaving the ester links between hemicellulose and pectin to aromatic compounds of lignin, thus enhancing the accessibility of plant tissues to cellulolytic and hemicellulolytic enzymes. FAEs have gained increased attention in the area of biocatalytic transformations for the synthesis of value added compounds with medicinal and nutritional applications. Following the increasing attention on these enzymes, a novel descriptor based classification system has been proposed for FAEs resulting into 12 distinct families and pharmacophore models for three FAE sub-families have been developed. The feruloylome of Aspergillus oryzae contains 13 predicted FAEs belonging to six sub-families based on our recently developed descriptor-based classification system. The three-dimensional structures of the 13 FAEs were modeled for structural analysis of the feruloylome. The three genes coding for three enzymes, viz., A.O.2, A.O.8 and A.O.10 from the feruloylome of A. oryzae, representing sub-families with unknown functional features, were heterologously expressed in Pichia pastoris, characterized for substrate specificity and structural characterization through CD spectroscopy. Common feature-based pharamacophore models were developed according to substrate specificity characteristics of the three enzymes. The active site residues were identified for the three expressed FAEs by determining the titration curves of amino acid residues as a function of the pH by applying molecular simulations. Our findings on the structure-function relationships and substrate specificity of the FAEs of A. oryzae will be instrumental for further understanding of the FAE families in the novel classification system. The developed pharmacophore models could be applied for virtual screening of compound databases for short listing the putative substrates prior to docking studies or for post-processing docking results to remove false positives. Our study exemplifies how computational predictions can complement to the information obtained through experimental methods.

Optical Metrology for Directed Self-assembly Patterning Using Mueller Matrix Spectroscopic Ellipsometry Based Scatterometry

NASA Astrophysics Data System (ADS)

Dixit, Dhairya J.

The semiconductor industry continues to drive patterning solutions that enable devices with higher memory storage capacity, faster computing performance, lower cost per transistors, and higher transistor density. These developments in the field of semiconductor manufacturing along with the overall minimization of the size of transistors require cutting-edge metrology tools for characterization. Directed self-assembly (DSA) patterning process can be used to fabricate nanoscale line-space patterns and contact holes via thermodynamically driven micro-phase separation of block copolymer (BCP) films with boundary constraints from guiding templates. Its main advantages are high pattern resolution (~10 nm), high throughput, no requirement of a high-resolution mask, and compatibility with standard fab-equipment and processes. Although research into DSA patterning has demonstrated a high potential as a nanoscale patterning process, there are critical challenges that must be overcome before transferring DSA into high volume manufacturing, including achievement of low defect density and high process stability. For this, advances in critical dimension (CD) and overlay measurement as well as rapid defect characterization are required. Both scatterometry and critical dimension-scanning electron microscopy (CD-SEM) are routinely used for inline dimensional metrology. CD-SEM inspection is limited, as it does not easily provide detailed line-shape information, whereas scatterometry has the capability of measuring important feature dimensions including: line-width, line-shape, sidewall-angle, and thickness of the patterned samples quickly and non-destructively. The present work describes the application of Mueller matrix spectroscopic ellipsometry (MMSE) based scatterometry to optically characterize DSA patterned line- space grating and contact hole structures fabricated with phase-separated polystyrene-b-polymethylmethacrylate (PS-b-PMMA) at various integration steps of BCP DSA based patterning process. This work focuses on understanding the efficacy of MMSE base scatterometry for characterizing complex DSA structures. For example, the use of symmetry-antisymmetry properties associated with Mueller matrix (MM) elements to understand the topography of the periodic nanostructures and measure defectivity. Simulations (the forward problem approach of scatterometry) are used to investigate MM elements' sensitivity to changes in DSA structure such as one vs. two contact hole patterns and predict sensitivity to dimensional changes. A regression-based approach is used to extract feature shape parameters of the DSA structures by fitting simulated optical spectra to experimental optical spectra. Detection of the DSA defects is a key to reducing defect density for eventual manufacturability and production use of DSA process. Simulations of optical models of structures containing defects are used to evaluate the sensitivity of MM elements to DSA defects. This study describes the application of MMSE to determine the DSA pattern defectivity via spectral comparisons based on optical anisotropy and depolarization. The use of depolarization and optical anisotropy for characterization of experimental MMSE data is a very recent development in scatterometry. In addition, reconstructed scatterometry models are used to calculate line edge roughness in 28 nm pitch Si fins fabricated using DSA patterning process.

NMR crystallography of 2-acylamino-6-[1 H]-pyridones: Solid-state NMR, GIPAW computational, and single crystal X-ray diffraction studies

NASA Astrophysics Data System (ADS)

Ośmiałowski, Borys; Kolehmainen, Erkki; Ikonen, Satu; Ahonen, Kari; Löfman, Miika

2011-12-01

2-Acylamino-6-[1 H]-pyridones [acyl = RCO, where R = methyl ( 1), ethyl ( 2), iso-propyl ( 3), tert-butyl ( 4), and 1-adamantyl ( 5)] have been synthesized and characterized by NMR spectroscopy. From three congeners, 2, 3 and 5, also single crystal X-ray structures have been solved. For these derivatives GIPAW calculations acts as a "bridge" between solid-state NMR data and calculated chemical shifts based on X-ray determined geometry. In crystals all three compounds exist as pyridone tautomers possessing similar six-membered ring structure stabilized by intramolecular C dbnd O⋯HN hydrogen bond. Theoretical GIPAW calculated and experimental 13C and 15N CPMAS NMR shifts are in excellent agreement with each other.

Life's attractors : understanding developmental systems through reverse engineering and in silico evolution.

PubMed

Jaeger, Johannes; Crombach, Anton

2012-01-01

We propose an approach to evolutionary systems biology which is based on reverse engineering of gene regulatory networks and in silico evolutionary simulations. We infer regulatory parameters for gene networks by fitting computational models to quantitative expression data. This allows us to characterize the regulatory structure and dynamical repertoire of evolving gene regulatory networks with a reasonable amount of experimental and computational effort. We use the resulting network models to identify those regulatory interactions that are conserved, and those that have diverged between different species. Moreover, we use the models obtained by data fitting as starting points for simulations of evolutionary transitions between species. These simulations enable us to investigate whether such transitions are random, or whether they show stereotypical series of regulatory changes which depend on the structure and dynamical repertoire of an evolving network. Finally, we present a case study-the gap gene network in dipterans (flies, midges, and mosquitoes)-to illustrate the practical application of the proposed methodology, and to highlight the kind of biological insights that can be gained by this approach.

Anomalous columnar order of charged colloidal platelets

NASA Astrophysics Data System (ADS)

Morales-Anda, L.; Wensink, H. H.; Galindo, A.; Gil-Villegas, A.

2012-01-01

Monte Carlo computer simulations are carried out for a model system of like-charged colloidal platelets in the isothermal-isobaric ensemble (NpT). The aim is to elucidate the role of electrostatic interactions on the structure of synthetic clay systems at high particle densities. Short-range repulsions between particles are described by a suitable hard-core model representing a discotic particle. This potential is supplemented with an electrostatic potential based on a Yukawa model for the screened Coulombic potential between infinitely thin disklike macro-ions. The particle aspect-ratio and electrostatic parameters were chosen to mimic an aqueous dispersion of thin, like-charged, rigid colloidal platelets at finite salt concentration. An examination of the fluid phase diagram reveals a marked shift in the isotropic-nematic transition compared to the hard cut-sphere reference system. Several statistical functions, such as the pair correlation function for the center-of-mass coordinates and structure factor, are obtained to characterize the structural organization of the platelets phases. At low salinity and high osmotic pressure we observe anomalous hexagonal columnar structures characterized by interpenetrating columns with a typical intercolumnar distance corresponding to about half of that of a regular columnar phase. Increasing the ionic strength leads to the formation of glassy, disordered structures consisting of compact clusters of platelets stacked into finite-sized columns. These so-called "nematic columnar" structures have been recently observed in systems of charge-stabilized gibbsite platelets. Our findings are corroborated by an analysis of the static structure factor from a simple density functional theory.

Homogenization in micro-magneto-mechanics

NASA Astrophysics Data System (ADS)

Sridhar, A.; Keip, M.-A.; Miehe, C.

2016-07-01

Ferromagnetic materials are characterized by a heterogeneous micro-structure that can be altered by external magnetic and mechanical stimuli. The understanding and the description of the micro-structure evolution is of particular importance for the design and the analysis of smart materials with magneto-mechanical coupling. The macroscopic response of the material results from complex magneto-mechanical interactions occurring on smaller length scales, which are driven by magnetization reorientation and associated magnetic domain wall motions. The aim of this work is to directly base the description of the macroscopic magneto-mechanical material behavior on the micro-magnetic domain evolution. This will be realized by the incorporation of a ferromagnetic phase-field formulation into a macroscopic Boltzmann continuum by the use of computational homogenization. The transition conditions between the two scales are obtained via rigorous exploitation of rate-type and incremental variational principles, which incorporate an extended version of the classical Hill-Mandel macro-homogeneity condition covering the phase field on the micro-scale. An efficient two-scale computational scenario is developed based on an operator splitting scheme that includes a predictor for the magnetization on the micro-scale. Two- and three-dimensional numerical simulations demonstrate the performance of the method. They investigate micro-magnetic domain evolution driven by macroscopic fields as well as the associated overall hysteretic response of ferromagnetic solids.

Failure analysis of fuel cell electrodes using three-dimensional multi-length scale X-ray computed tomography

NASA Astrophysics Data System (ADS)

Pokhrel, A.; El Hannach, M.; Orfino, F. P.; Dutta, M.; Kjeang, E.

2016-10-01

X-ray computed tomography (XCT), a non-destructive technique, is proposed for three-dimensional, multi-length scale characterization of complex failure modes in fuel cell electrodes. Comparative tomography data sets are acquired for a conditioned beginning of life (BOL) and a degraded end of life (EOL) membrane electrode assembly subjected to cathode degradation by voltage cycling. Micro length scale analysis shows a five-fold increase in crack size and 57% thickness reduction in the EOL cathode catalyst layer, indicating widespread action of carbon corrosion. Complementary nano length scale analysis shows a significant reduction in porosity, increased pore size, and dramatically reduced effective diffusivity within the remaining porous structure of the catalyst layer at EOL. Collapsing of the structure is evident from the combination of thinning and reduced porosity, as uniquely determined by the multi-length scale approach. Additionally, a novel image processing based technique developed for nano scale segregation of pore, ionomer, and Pt/C dominated voxels shows an increase in ionomer volume fraction, Pt/C agglomerates, and severe carbon corrosion at the catalyst layer/membrane interface at EOL. In summary, XCT based multi-length scale analysis enables detailed information needed for comprehensive understanding of the complex failure modes observed in fuel cell electrodes.

Computational design of a Diels-Alderase from a thermophilic esterase: the importance of dynamics

NASA Astrophysics Data System (ADS)

Linder, Mats; Johansson, Adam Johannes; Olsson, Tjelvar S. G.; Liebeschuetz, John; Brinck, Tore

2012-09-01

A novel computational Diels-Alderase design, based on a relatively rare form of carboxylesterase from Geobacillus stearothermophilus, is presented and theoretically evaluated. The structure was found by mining the PDB for a suitable oxyanion hole-containing structure, followed by a combinatorial approach to find suitable substrates and rational mutations. Four lead designs were selected and thoroughly modeled to obtain realistic estimates of substrate binding and prearrangement. Molecular dynamics simulations and DFT calculations were used to optimize and estimate binding affinity and activation energies. A large quantum chemical model was used to capture the salient interactions in the crucial transition state (TS). Our quantitative estimation of kinetic parameters was validated against four experimentally characterized Diels-Alderases with good results. The final designs in this work are predicted to have rate enhancements of ≈103-106 and high predicted proficiencies. This work emphasizes the importance of considering protein dynamics in the design approach, and provides a quantitative estimate of the how the TS stabilization observed in most de novo and redesigned enzymes is decreased compared to a minimal, `ideal' model. The presented design is highly interesting for further optimization and applications since it is based on a thermophilic enzyme ( T opt = 70 °C).

First-principles modeling of biological systems and structure-based drug-design.

PubMed

Sgrignani, Jacopo; Magistrato, Alessandra

2013-03-01

Molecular modeling techniques play a relevant role in drug design providing detailed information at atomistic level on the structural, dynamical, mechanistic and electronic properties of biological systems involved in diseases' onset, integrating and supporting commonly used experimental approaches. These information are often not accessible to the experimental techniques taken singularly, but are of crucial importance for drug design. Due to the enormous increase of the computer power in the last decades, quantum mechanical (QM) or first-principles-based methods have become often used to address biological issues of pharmaceutical relevance, providing relevant information for drug design. Due to their complexity and their size, biological systems are often investigated by means of a mixed quantum-classical (QM/MM) approach, which treats at an accurate QM level a limited chemically relevant portion of the system and at the molecular mechanics (MM) level the remaining of the biomolecule and its environment. This method provides a good compromise between computational cost and accuracy, allowing to characterize the properties of the biological system and the (free) energy landscape of the process in study with the accuracy of a QM description. In this review, after a brief introduction of QM and QM/MM methods, we will discuss few representative examples, taken from our work, of the application of these methods in the study of metallo-enzymes of pharmaceutical interest, of metal-containing anticancer drugs targeting the DNA as well as of neurodegenerative diseases. The information obtained from these studies may provide the basis for a rationale structure-based drug design of new and more efficient inhibitors or drugs.

Three-dimensional representations of salt-dome margins at four active strategic petroleum reserve sites.

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

Rautman, Christopher Arthur; Stein, Joshua S.

2003-01-01

Existing paper-based site characterization models of salt domes at the four active U.S. Strategic Petroleum Reserve sites have been converted to digital format and visualized using modern computer software. The four sites are the Bayou Choctaw dome in Iberville Parish, Louisiana; the Big Hill dome in Jefferson County, Texas; the Bryan Mound dome in Brazoria County, Texas; and the West Hackberry dome in Cameron Parish, Louisiana. A new modeling algorithm has been developed to overcome limitations of many standard geological modeling software packages in order to deal with structurally overhanging salt margins that are typical of many salt domes. Thismore » algorithm, and the implementing computer program, make use of the existing interpretive modeling conducted manually using professional geological judgement and presented in two dimensions in the original site characterization reports as structure contour maps on the top of salt. The algorithm makes use of concepts of finite-element meshes of general engineering usage. Although the specific implementation of the algorithm described in this report and the resulting output files are tailored to the modeling and visualization software used to construct the figures contained herein, the algorithm itself is generic and other implementations and output formats are possible. The graphical visualizations of the salt domes at the four Strategic Petroleum Reserve sites are believed to be major improvements over the previously available two-dimensional representations of the domes via conventional geologic drawings (cross sections and contour maps). Additionally, the numerical mesh files produced by this modeling activity are available for import into and display by other software routines. The mesh data are not explicitly tabulated in this report; however an electronic version in simple ASCII format is included on a PC-based compact disk.« less

Synthesis, characterization and theoretical study in gaseous and solid phases of the imine 4-Acetyl-N-(4-methoxybenzylidene)aniline

NASA Astrophysics Data System (ADS)

Batista, J. F. N.; Cruz, J. W.; Doriguetto, A. C.; Torres, C.; de Almeida, E. T.; Camps, I.

2017-11-01

In the present paper we describe the synthesis and characterization of the Schiff's base or imine 4-Acetyl-N-(4-methoxybenzylidene)aniline (1), which provided experimental support for the theoretical calculations. The imine was characterized by infrared spectroscopy and single crystal XRD techniques. The computational studies were performed using the density functional theory (DFT) for the gaseous and solid phases. As similar compounds already shown biological activity, the pharmacokinetic properties of (1) were evaluated. Our results shown that (1), in its gaseous form, it is electronically stable and has pharmacological drug like properties. Due to its structural similarity with commercial drugs, it is a promise candidate to act as a nonsteroidal anti-inflammatory and to treat dementia, sleep disorders, alcohol dependence, and psychosis. From the solid state calculations we obtain that (1) is a low gap semiconductor and can act as an absorber for electromagnetic radiations with energy greater that ∼ 0.9eV .

G-LoSA for Prediction of Protein-Ligand Binding Sites and Structures.

PubMed

Lee, Hui Sun; Im, Wonpil

2017-01-01

Recent advances in high-throughput structure determination and computational protein structure prediction have significantly enriched the universe of protein structure. However, there is still a large gap between the number of available protein structures and that of proteins with annotated function in high accuracy. Computational structure-based protein function prediction has emerged to reduce this knowledge gap. The identification of a ligand binding site and its structure is critical to the determination of a protein's molecular function. We present a computational methodology for predicting small molecule ligand binding site and ligand structure using G-LoSA, our protein local structure alignment and similarity measurement tool. All the computational procedures described here can be easily implemented using G-LoSA Toolkit, a package of standalone software programs and preprocessed PDB structure libraries. G-LoSA and G-LoSA Toolkit are freely available to academic users at http://compbio.lehigh.edu/GLoSA . We also illustrate a case study to show the potential of our template-based approach harnessing G-LoSA for protein function prediction.

Efficient Characterization of Protein Cavities within Molecular Simulation Trajectories: trj_cavity.

PubMed

Paramo, Teresa; East, Alexandra; Garzón, Diana; Ulmschneider, Martin B; Bond, Peter J

2014-05-13

Protein cavities and tunnels are critical in determining phenomena such as ligand binding, molecular transport, and enzyme catalysis. Molecular dynamics (MD) simulations enable the exploration of the flexibility and conformational plasticity of protein cavities, extending the information available from static experimental structures relevant to, for example, drug design. Here, we present a new tool (trj_cavity) implemented within the GROMACS ( www.gromacs.org ) framework for the rapid identification and characterization of cavities detected within MD trajectories. trj_cavity is optimized for usability and computational efficiency and is applicable to the time-dependent analysis of any cavity topology, and optional specialized descriptors can be used to characterize, for example, protein channels. Its novel grid-based algorithm performs an efficient neighbor search whose calculation time is linear with system size, and a comparison of performance with other widely used cavity analysis programs reveals an orders-of-magnitude improvement in the computational cost. To demonstrate its potential for revealing novel mechanistic insights, trj_cavity has been used to analyze long-time scale simulation trajectories for three diverse protein cavity systems. This has helped to reveal, respectively, the lipid binding mechanism in the deep hydrophobic cavity of a soluble mite-allergen protein, Der p 2; a means for shuttling carbohydrates between the surface-exposed substrate-binding and catalytic pockets of a multidomain, membrane-proximal pullulanase, PulA; and the structural basis for selectivity in the transmembrane pore of a voltage-gated sodium channel (NavMs), embedded within a lipid bilayer environment. trj_cavity is available for download under an open-source license ( http://sourceforge.net/projects/trjcavity ). A simplified, GROMACS-independent version may also be compiled.

Equivalent model construction for a non-linear dynamic system based on an element-wise stiffness evaluation procedure and reduced analysis of the equivalent system

NASA Astrophysics Data System (ADS)

Kim, Euiyoung; Cho, Maenghyo

2017-11-01

In most non-linear analyses, the construction of a system matrix uses a large amount of computation time, comparable to the computation time required by the solving process. If the process for computing non-linear internal force matrices is substituted with an effective equivalent model that enables the bypass of numerical integrations and assembly processes used in matrix construction, efficiency can be greatly enhanced. A stiffness evaluation procedure (STEP) establishes non-linear internal force models using polynomial formulations of displacements. To efficiently identify an equivalent model, the method has evolved such that it is based on a reduced-order system. The reduction process, however, makes the equivalent model difficult to parameterize, which significantly affects the efficiency of the optimization process. In this paper, therefore, a new STEP, E-STEP, is proposed. Based on the element-wise nature of the finite element model, the stiffness evaluation is carried out element-by-element in the full domain. Since the unit of computation for the stiffness evaluation is restricted by element size, and since the computation is independent, the equivalent model can be constructed efficiently in parallel, even in the full domain. Due to the element-wise nature of the construction procedure, the equivalent E-STEP model is easily characterized by design parameters. Various reduced-order modeling techniques can be applied to the equivalent system in a manner similar to how they are applied in the original system. The reduced-order model based on E-STEP is successfully demonstrated for the dynamic analyses of non-linear structural finite element systems under varying design parameters.

Overview of the LINCS architecture

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

Fletcher, J.G.; Watson, R.W.

1982-01-13

Computing at the Lawrence Livermore National Laboratory (LLNL) has evolved over the past 15 years with a computer network based resource sharing environment. The increasing use of low cost and high performance micro, mini and midi computers and commercially available local networking systems will accelerate this trend. Further, even the large scale computer systems, on which much of the LLNL scientific computing depends, are evolving into multiprocessor systems. It is our belief that the most cost effective use of this environment will depend on the development of application systems structured into cooperating concurrent program modules (processes) distributed appropriately over differentmore » nodes of the environment. A node is defined as one or more processors with a local (shared) high speed memory. Given the latter view, the environment can be characterized as consisting of: multiple nodes communicating over noisy channels with arbitrary delays and throughput, heterogenous base resources and information encodings, no single administration controlling all resources, distributed system state, and no uniform time base. The system design problem is - how to turn the heterogeneous base hardware/firmware/software resources of this environment into a coherent set of resources that facilitate development of cost effective, reliable, and human engineered applications. We believe the answer lies in developing a layered, communication oriented distributed system architecture; layered and modular to support ease of understanding, reconfiguration, extensibility, and hiding of implementation or nonessential local details; communication oriented because that is a central feature of the environment. The Livermore Interactive Network Communication System (LINCS) is a hierarchical architecture designed to meet the above needs. While having characteristics in common with other architectures, it differs in several respects.« less

Cloud-Based NoSQL Open Database of Pulmonary Nodules for Computer-Aided Lung Cancer Diagnosis and Reproducible Research.

PubMed

Ferreira Junior, José Raniery; Oliveira, Marcelo Costa; de Azevedo-Marques, Paulo Mazzoncini

2016-12-01

Lung cancer is the leading cause of cancer-related deaths in the world, and its main manifestation is pulmonary nodules. Detection and classification of pulmonary nodules are challenging tasks that must be done by qualified specialists, but image interpretation errors make those tasks difficult. In order to aid radiologists on those hard tasks, it is important to integrate the computer-based tools with the lesion detection, pathology diagnosis, and image interpretation processes. However, computer-aided diagnosis research faces the problem of not having enough shared medical reference data for the development, testing, and evaluation of computational methods for diagnosis. In order to minimize this problem, this paper presents a public nonrelational document-oriented cloud-based database of pulmonary nodules characterized by 3D texture attributes, identified by experienced radiologists and classified in nine different subjective characteristics by the same specialists. Our goal with the development of this database is to improve computer-aided lung cancer diagnosis and pulmonary nodule detection and classification research through the deployment of this database in a cloud Database as a Service framework. Pulmonary nodule data was provided by the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI), image descriptors were acquired by a volumetric texture analysis, and database schema was developed using a document-oriented Not only Structured Query Language (NoSQL) approach. The proposed database is now with 379 exams, 838 nodules, and 8237 images, 4029 of them are CT scans and 4208 manually segmented nodules, and it is allocated in a MongoDB instance on a cloud infrastructure.

The pKa Cooperative: A Collaborative Effort to Advance Structure-Based Calculations of pKa values and Electrostatic Effects in Proteins

PubMed Central

Nielsen, Jens E.; Gunner, M. R.; Bertrand García-Moreno, E.

2012-01-01

The pKa Cooperative http://www.pkacoop.org was organized to advance development of accurate and useful computational methods for structure-based calculation of pKa values and electrostatic energy in proteins. The Cooperative brings together laboratories with expertise and interest in theoretical, computational and experimental studies of protein electrostatics. To improve structure-based energy calculations it is necessary to better understand the physical character and molecular determinants of electrostatic effects. The Cooperative thus intends to foment experimental research into fundamental aspects of proteins that depend on electrostatic interactions. It will maintain a depository for experimental data useful for critical assessment of methods for structure-based electrostatics calculations. To help guide the development of computational methods the Cooperative will organize blind prediction exercises. As a first step, computational laboratories were invited to reproduce an unpublished set of experimental pKa values of acidic and basic residues introduced in the interior of staphylococcal nuclease by site-directed mutagenesis. The pKa values of these groups are unique and challenging to simulate owing to the large magnitude of their shifts relative to normal pKa values in water. Many computational methods were tested in this 1st Blind Prediction Challenge and critical assessment exercise. A workshop was organized in the Telluride Science Research Center to assess objectively the performance of many computational methods tested on this one extensive dataset. This volume of PROTEINS: Structure, Function, and Bioinformatics introduces the pKa Cooperative, presents reports submitted by participants in the blind prediction challenge, and highlights some of the problems in structure-based calculations identified during this exercise. PMID:22002877

Assessment of scaffold porosity: the new route of micro-CT.

PubMed

Bertoldi, Serena; Farè, Silvia; Tanzi, Maria Cristina

2011-01-01

A complete morphologic characterization of porous scaffolds for tissue engineering application is fundamental, as the architectural parameters, in particular porosity, strongly affect the mechanical and biological performance of the structures. Therefore, appropriate techniques for this purpose need to be selected. Several techniques for the assessment of scaffold porosity have been proposed, including Scanning Electron Microscopy observation, mercury and liquid extrusion porosimetry, gas pycnometry, and capillary flow porometry. Each of these techniques has several drawbacks and, a combination of different techniques is often required so as to achieve an in depth study of the morphologic properties of the scaffold. A single technique is often limited and suitable only for the assessment of a specific parameter. To overcome this limit, the most attractive option would be a single nondestructive technique, yet capable of providing a comprehensive set of data. It appears that micro-computed tomography (micro-CT) can potentially fulfill this role. Initially developed to characterize the 3D trabecular microarchitecture of bone, its use has been recently exploited by researchers for the morphologic characterization of porous biomaterials, as it enables obtaining a full assessment of the porous structures both in terms of pore size and interconnected porosity. This review aims to explore the use of micro-CT in scaffold characterization, comparing it with other previously developed techniques; we also focus on the contribution of this innovative tool to the development of scaffold-based tissue engineering application.

Images as drivers of progress in cardiac computational modelling

PubMed Central

Lamata, Pablo; Casero, Ramón; Carapella, Valentina; Niederer, Steve A.; Bishop, Martin J.; Schneider, Jürgen E.; Kohl, Peter; Grau, Vicente

2014-01-01

Computational models have become a fundamental tool in cardiac research. Models are evolving to cover multiple scales and physical mechanisms. They are moving towards mechanistic descriptions of personalised structure and function, including effects of natural variability. These developments are underpinned to a large extent by advances in imaging technologies. This article reviews how novel imaging technologies, or the innovative use and extension of established ones, integrate with computational models and drive novel insights into cardiac biophysics. In terms of structural characterization, we discuss how imaging is allowing a wide range of scales to be considered, from cellular levels to whole organs. We analyse how the evolution from structural to functional imaging is opening new avenues for computational models, and in this respect we review methods for measurement of electrical activity, mechanics and flow. Finally, we consider ways in which combined imaging and modelling research is likely to continue advancing cardiac research, and identify some of the main challenges that remain to be solved. PMID:25117497

Virtual fragment preparation for computational fragment-based drug design.

PubMed

Ludington, Jennifer L

2015-01-01

Fragment-based drug design (FBDD) has become an important component of the drug discovery process. The use of fragments can accelerate both the search for a hit molecule and the development of that hit into a lead molecule for clinical testing. In addition to experimental methodologies for FBDD such as NMR and X-ray Crystallography screens, computational techniques are playing an increasingly important role. The success of the computational simulations is due in large part to how the database of virtual fragments is prepared. In order to prepare the fragments appropriately it is necessary to understand how FBDD differs from other approaches and the issues inherent in building up molecules from smaller fragment pieces. The ultimate goal of these calculations is to link two or more simulated fragments into a molecule that has an experimental binding affinity consistent with the additive predicted binding affinities of the virtual fragments. Computationally predicting binding affinities is a complex process, with many opportunities for introducing error. Therefore, care should be taken with the fragment preparation procedure to avoid introducing additional inaccuracies.This chapter is focused on the preparation process used to create a virtual fragment database. Several key issues of fragment preparation which affect the accuracy of binding affinity predictions are discussed. The first issue is the selection of the two-dimensional atomic structure of the virtual fragment. Although the particular usage of the fragment can affect this choice (i.e., whether the fragment will be used for calibration, binding site characterization, hit identification, or lead optimization), general factors such as synthetic accessibility, size, and flexibility are major considerations in selecting the 2D structure. Other aspects of preparing the virtual fragments for simulation are the generation of three-dimensional conformations and the assignment of the associated atomic point charges.

Medical image computing for computer-supported diagnostics and therapy. Advances and perspectives.

PubMed

Handels, H; Ehrhardt, J

2009-01-01

Medical image computing has become one of the most challenging fields in medical informatics. In image-based diagnostics of the future software assistance will become more and more important, and image analysis systems integrating advanced image computing methods are needed to extract quantitative image parameters to characterize the state and changes of image structures of interest (e.g. tumors, organs, vessels, bones etc.) in a reproducible and objective way. Furthermore, in the field of software-assisted and navigated surgery medical image computing methods play a key role and have opened up new perspectives for patient treatment. However, further developments are needed to increase the grade of automation, accuracy, reproducibility and robustness. Moreover, the systems developed have to be integrated into the clinical workflow. For the development of advanced image computing systems methods of different scientific fields have to be adapted and used in combination. The principal methodologies in medical image computing are the following: image segmentation, image registration, image analysis for quantification and computer assisted image interpretation, modeling and simulation as well as visualization and virtual reality. Especially, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients and will gain importance in diagnostic and therapy of the future. From a methodical point of view the authors identify the following future trends and perspectives in medical image computing: development of optimized application-specific systems and integration into the clinical workflow, enhanced computational models for image analysis and virtual reality training systems, integration of different image computing methods, further integration of multimodal image data and biosignals and advanced methods for 4D medical image computing. The development of image analysis systems for diagnostic support or operation planning is a complex interdisciplinary process. Image computing methods enable new insights into the patient's image data and have the future potential to improve medical diagnostics and patient treatment.

Synthesis, spectroscopic and computational characterization of the tautomerism of pyrazoline derivatives from chalcones.

PubMed

Miguel, Fábio Balbino; Dantas, Juliana Arantes; Amorim, Stefany; Andrade, Gustavo F S; Costa, Luiz Antônio Sodré; Couri, Mara Rubia Costa

2016-01-05

In the present study a series of novel pyrazolines derivatives has been synthesized, and their structures assigned on the basis of FT-Raman, (1)H and (13)C NMR spectral data and computational DFT calculations. A joint computational study using B3LYP/6-311G(2d,2p) density functional theory and FT-Raman investigation on the tautomerism of 3-(4-substituted-phenyl)-4,5-dihydro-5-(4-substituted-phenyl)pyrazole-1-carbothioamide and 3-(4-substituted-phenyl)-4,5-dihydro-5-(4-substituted-phenyl)pyrazole-1-carboxamide are presented. The structures were characterized as a minimum in the potential energy surface using DFT. The calculated Raman and NMR spectra were of such remarkable agreement to the experimental results that the equilibrium between tautomeric forms has been discussed in detail. Our study suggests the existence of tautomers, the carboxamide/carbothioamide group may tautomerize, in the solid state or in solution. Thermodynamic data calculated suggests that the R(CS)NH2 and R(CO)NH2 species are more stable than the R(CNH)SH and R(CNH)OH species. Additionally, results found for the (1)H NMR shifting, pointed out to which structure is present. Copyright © 2015 Elsevier B.V. All rights reserved.

Characterization of microgravity effects on bone structure and strength using fractal analysis

NASA Technical Reports Server (NTRS)

Acharya, Raj S.; Shackelford, Linda

1995-01-01

The effect of micro-gravity on the musculoskeletal system has been well studied. Significant changes in bone and muscle have been shown after long term space flight. Similar changes have been demonstrated due to bed rest. Bone demineralization is particularly profound in weight bearing bones. Much of the current techniques to monitor bone condition use bone mass measurements. However, bone mass measurements are not reliable to distinguish Osteoporotic and Normal subjects. It has been shown that the overlap between normals and osteoporosis is found for all of the bone mass measurement technologies: single and dual photon absorptiometry, quantitative computed tomography and direct measurement of bone area/volume on biopsy as well as radiogrammetry. A similar discordance is noted in the fact that it has not been regularly possible to find the expected correlation between severity of osteoporosis and degree of bone loss. Structural parameters such as trabecular connectivity have been proposed as features for assessing bone conditions. In this report, we use fractal analysis to characterize bone structure. We show that the fractal dimension computed with MRI images and X-Ray images of the patella are the same. Preliminary experimental results show that the fractal dimension computed from MRI images of vertebrae of human subjects before bedrest is higher than during bedrest.

Porosity characterization of fiber-reinforced ceramic matrix composite using synchrotron X-ray computed tomography

NASA Astrophysics Data System (ADS)

Zou, C.; Marrow, T. J.; Reinhard, C.; Li, B.; Zhang, C.; Wang, S.

2016-03-01

The pore structure and porosity of a continuous fiber reinforced ceramic matrix composite has been characterized using high-resolution synchrotron X-ray computed tomography (XCT). Segmentation of the reconstructed tomograph images reveals different types of pores within the composite, the inter-fiber bundle open pores displaying a "node-bond" geometry, and the intra-fiber bundle isolated micropores showing a piping shape. The 3D morphology of the pores is resolved and each pore is labeled. The quantitative filtering of the pores measures a total porosity 8.9% for the composite, amid which there is about 7.1~ 9.3% closed micropores.

Study and characterization of a MEMS micromirror device

NASA Astrophysics Data System (ADS)

Furlong, Cosme; Pryputniewicz, Ryszard J.

2004-08-01

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

A comparative approach for the investigation of biological information processing: An examination of the structure and function of computer hard drives and DNA

PubMed Central

2010-01-01

Background The robust storage, updating and utilization of information are necessary for the maintenance and perpetuation of dynamic systems. These systems can exist as constructs of metal-oxide semiconductors and silicon, as in a digital computer, or in the "wetware" of organic compounds, proteins and nucleic acids that make up biological organisms. We propose that there are essential functional properties of centralized information-processing systems; for digital computers these properties reside in the computer's hard drive, and for eukaryotic cells they are manifest in the DNA and associated structures. Methods Presented herein is a descriptive framework that compares DNA and its associated proteins and sub-nuclear structure with the structure and function of the computer hard drive. We identify four essential properties of information for a centralized storage and processing system: (1) orthogonal uniqueness, (2) low level formatting, (3) high level formatting and (4) translation of stored to usable form. The corresponding aspects of the DNA complex and a computer hard drive are categorized using this classification. This is intended to demonstrate a functional equivalence between the components of the two systems, and thus the systems themselves. Results Both the DNA complex and the computer hard drive contain components that fulfill the essential properties of a centralized information storage and processing system. The functional equivalence of these components provides insight into both the design process of engineered systems and the evolved solutions addressing similar system requirements. However, there are points where the comparison breaks down, particularly when there are externally imposed information-organizing structures on the computer hard drive. A specific example of this is the imposition of the File Allocation Table (FAT) during high level formatting of the computer hard drive and the subsequent loading of an operating system (OS). Biological systems do not have an external source for a map of their stored information or for an operational instruction set; rather, they must contain an organizational template conserved within their intra-nuclear architecture that "manipulates" the laws of chemistry and physics into a highly robust instruction set. We propose that the epigenetic structure of the intra-nuclear environment and the non-coding RNA may play the roles of a Biological File Allocation Table (BFAT) and biological operating system (Bio-OS) in eukaryotic cells. Conclusions The comparison of functional and structural characteristics of the DNA complex and the computer hard drive leads to a new descriptive paradigm that identifies the DNA as a dynamic storage system of biological information. This system is embodied in an autonomous operating system that inductively follows organizational structures, data hierarchy and executable operations that are well understood in the computer science industry. Characterizing the "DNA hard drive" in this fashion can lead to insights arising from discrepancies in the descriptive framework, particularly with respect to positing the role of epigenetic processes in an information-processing context. Further expansions arising from this comparison include the view of cells as parallel computing machines and a new approach towards characterizing cellular control systems. PMID:20092652

A comparative approach for the investigation of biological information processing: an examination of the structure and function of computer hard drives and DNA.

PubMed

D'Onofrio, David J; An, Gary

2010-01-21

The robust storage, updating and utilization of information are necessary for the maintenance and perpetuation of dynamic systems. These systems can exist as constructs of metal-oxide semiconductors and silicon, as in a digital computer, or in the "wetware" of organic compounds, proteins and nucleic acids that make up biological organisms. We propose that there are essential functional properties of centralized information-processing systems; for digital computers these properties reside in the computer's hard drive, and for eukaryotic cells they are manifest in the DNA and associated structures. Presented herein is a descriptive framework that compares DNA and its associated proteins and sub-nuclear structure with the structure and function of the computer hard drive. We identify four essential properties of information for a centralized storage and processing system: (1) orthogonal uniqueness, (2) low level formatting, (3) high level formatting and (4) translation of stored to usable form. The corresponding aspects of the DNA complex and a computer hard drive are categorized using this classification. This is intended to demonstrate a functional equivalence between the components of the two systems, and thus the systems themselves. Both the DNA complex and the computer hard drive contain components that fulfill the essential properties of a centralized information storage and processing system. The functional equivalence of these components provides insight into both the design process of engineered systems and the evolved solutions addressing similar system requirements. However, there are points where the comparison breaks down, particularly when there are externally imposed information-organizing structures on the computer hard drive. A specific example of this is the imposition of the File Allocation Table (FAT) during high level formatting of the computer hard drive and the subsequent loading of an operating system (OS). Biological systems do not have an external source for a map of their stored information or for an operational instruction set; rather, they must contain an organizational template conserved within their intra-nuclear architecture that "manipulates" the laws of chemistry and physics into a highly robust instruction set. We propose that the epigenetic structure of the intra-nuclear environment and the non-coding RNA may play the roles of a Biological File Allocation Table (BFAT) and biological operating system (Bio-OS) in eukaryotic cells. The comparison of functional and structural characteristics of the DNA complex and the computer hard drive leads to a new descriptive paradigm that identifies the DNA as a dynamic storage system of biological information. This system is embodied in an autonomous operating system that inductively follows organizational structures, data hierarchy and executable operations that are well understood in the computer science industry. Characterizing the "DNA hard drive" in this fashion can lead to insights arising from discrepancies in the descriptive framework, particularly with respect to positing the role of epigenetic processes in an information-processing context. Further expansions arising from this comparison include the view of cells as parallel computing machines and a new approach towards characterizing cellular control systems.

Characterization of rhenium compounds obtained by electrochemical synthesis after aging process

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

Vargas-Uscategui, Alejandro, E-mail: avargasuscat@ing.uchile.cl; Mosquera, Edgar; López-Encarnación, Juan M.

2014-12-15

The proper identification of the molecular nature of the aged rhenium compound obtained by means of electrodeposition from an alkaline aqueous electrolyte was determined. Chemical, structural and vibrational experimental characterization of the aged Re compound showed agreement with quantum-computations, thereby allowing the unambiguous identification of the Re compound as H(ReO{sub 4})H{sub 2}O. - Graphical abstract: Rhenium oxides were electrodeposited on a copper surface and after environmental aging was formed the H(ReO{sub 4})H{sub 2}O compound. The characterization of the synthesized material was made through the comparison of experimental evidence with quantum mechanical computations carried out by means of density functional theorymore » (DFT). - Highlights: • Aged rhenium compound obtained by means of electrodeposition was studied. • The study was made by combining experimental and DFT-computational information. • The aged electrodeposited material is consistent with the H(ReO{sub 4})H{sub 2}O compound.« less

Myoglobin structure and function: A multiweek biochemistry laboratory project.

PubMed

Silverstein, Todd P; Kirk, Sarah R; Meyer, Scott C; Holman, Karen L McFarlane

2015-01-01

We have developed a multiweek laboratory project in which students isolate myoglobin and characterize its structure, function, and redox state. The important laboratory techniques covered in this project include size-exclusion chromatography, electrophoresis, spectrophotometric titration, and FTIR spectroscopy. Regarding protein structure, students work with computer modeling and visualization of myoglobin and its homologues, after which they spectroscopically characterize its thermal denaturation. Students also study protein function (ligand binding equilibrium) and are instructed on topics in data analysis (calibration curves, nonlinear vs. linear regression). This upper division biochemistry laboratory project is a challenging and rewarding one that not only exposes students to a wide variety of important biochemical laboratory techniques but also ties those techniques together to work with a single readily available and easily characterized protein, myoglobin. © 2015 International Union of Biochemistry and Molecular Biology.

Climate Modeling Computing Needs Assessment

NASA Astrophysics Data System (ADS)

Petraska, K. E.; McCabe, J. D.

2011-12-01

This paper discusses early findings of an assessment of computing needs for NASA science, engineering and flight communities. The purpose of this assessment is to document a comprehensive set of computing needs that will allow us to better evaluate whether our computing assets are adequately structured to meet evolving demand. The early results are interesting, already pointing out improvements we can make today to get more out of the computing capacity we have, as well as potential game changing innovations for the future in how we apply information technology to science computing. Our objective is to learn how to leverage our resources in the best way possible to do more science for less money. Our approach in this assessment is threefold: Development of use case studies for science workflows; Creating a taxonomy and structure for describing science computing requirements; and characterizing agency computing, analysis, and visualization resources. As projects evolve, science data sets increase in a number of ways: in size, scope, timelines, complexity, and fidelity. Generating, processing, moving, and analyzing these data sets places distinct and discernable requirements on underlying computing, analysis, storage, and visualization systems. The initial focus group for this assessment is the Earth Science modeling community within NASA's Science Mission Directorate (SMD). As the assessment evolves, this focus will expand to other science communities across the agency. We will discuss our use cases, our framework for requirements and our characterizations, as well as our interview process, what we learned and how we plan to improve our materials after using them in the first round of interviews in the Earth Science Modeling community. We will describe our plans for how to expand this assessment, first into the Earth Science data analysis and remote sensing communities, and then throughout the full community of science, engineering and flight at NASA.

Characterization of SNPs in the dopamine-β-hydroxylase gene providing new insights into its structure-function relationship.

PubMed

Punchaichira, Toyanji Joseph; Dey, Sanjay Kumar; Mukhopadhyay, Anirban; Kundu, Suman; Thelma, B K

2017-07-01

Dopamine-β-hydroxylase (DBH, EC 1.14.17.1), an oxido-reductase that catalyses the conversion of dopamine to norepinephrine, is largely expressed in sympathetic neurons and adrenal medulla. Several regulatory and structural variants in DBH associated with various neuropsychiatric, cardiovascular diseases and a few that may determine enzyme activity have also been identified. Due to paucity of studies on functional characterization of DBH variants, its structure-function relationship is poorly understood. The purpose of the study was to characterize five non-synonymous (ns) variants that were prioritized either based on previous association studies or Sorting Tolerant From Intolerant (SIFT) algorithm. The DBH ORF with wild type (WT) and site-directed mutagenized variants were transfected into HEK293 cells to generate transient and stable lines expressing these variant enzymes. Activity was determined by UPLC-PDA and corresponding quantity by MRM HR on a TripleTOF 5600 MS respectively of spent media from stable cell lines. Homospecific activity computed for the WT and variant proteins showed a marginal decrease in A318S, W544S and R549C variants. In transient cell lines, differential secretion was observed in the case of L317P, W544S and R549C. Secretory defect in L317P was confirmed by localization in ER. R549C exhibited both decreased homospecific activity and differential secretion. Of note, all the variants were seen to be destabilizing based on in silico folding analysis and molecular dynamics (MD) simulation, lending support to our experimental observations. These novel genotype-phenotype correlations in this gene of considerable pharmacological relevance have implications for dopamine-related disorders.

The signaling petri net-based simulator: a non-parametric strategy for characterizing the dynamics of cell-specific signaling networks.

PubMed

Ruths, Derek; Muller, Melissa; Tseng, Jen-Te; Nakhleh, Luay; Ram, Prahlad T

2008-02-29

Reconstructing cellular signaling networks and understanding how they work are major endeavors in cell biology. The scale and complexity of these networks, however, render their analysis using experimental biology approaches alone very challenging. As a result, computational methods have been developed and combined with experimental biology approaches, producing powerful tools for the analysis of these networks. These computational methods mostly fall on either end of a spectrum of model parameterization. On one end is a class of structural network analysis methods; these typically use the network connectivity alone to generate hypotheses about global properties. On the other end is a class of dynamic network analysis methods; these use, in addition to the connectivity, kinetic parameters of the biochemical reactions to predict the network's dynamic behavior. These predictions provide detailed insights into the properties that determine aspects of the network's structure and behavior. However, the difficulty of obtaining numerical values of kinetic parameters is widely recognized to limit the applicability of this latter class of methods. Several researchers have observed that the connectivity of a network alone can provide significant insights into its dynamics. Motivated by this fundamental observation, we present the signaling Petri net, a non-parametric model of cellular signaling networks, and the signaling Petri net-based simulator, a Petri net execution strategy for characterizing the dynamics of signal flow through a signaling network using token distribution and sampling. The result is a very fast method, which can analyze large-scale networks, and provide insights into the trends of molecules' activity-levels in response to an external stimulus, based solely on the network's connectivity. We have implemented the signaling Petri net-based simulator in the PathwayOracle toolkit, which is publicly available at http://bioinfo.cs.rice.edu/pathwayoracle. Using this method, we studied a MAPK1,2 and AKT signaling network downstream from EGFR in two breast tumor cell lines. We analyzed, both experimentally and computationally, the activity level of several molecules in response to a targeted manipulation of TSC2 and mTOR-Raptor. The results from our method agreed with experimental results in greater than 90% of the cases considered, and in those where they did not agree, our approach provided valuable insights into discrepancies between known network connectivities and experimental observations.

The Signaling Petri Net-Based Simulator: A Non-Parametric Strategy for Characterizing the Dynamics of Cell-Specific Signaling Networks

PubMed Central

Ruths, Derek; Muller, Melissa; Tseng, Jen-Te; Nakhleh, Luay; Ram, Prahlad T.

2008-01-01

Reconstructing cellular signaling networks and understanding how they work are major endeavors in cell biology. The scale and complexity of these networks, however, render their analysis using experimental biology approaches alone very challenging. As a result, computational methods have been developed and combined with experimental biology approaches, producing powerful tools for the analysis of these networks. These computational methods mostly fall on either end of a spectrum of model parameterization. On one end is a class of structural network analysis methods; these typically use the network connectivity alone to generate hypotheses about global properties. On the other end is a class of dynamic network analysis methods; these use, in addition to the connectivity, kinetic parameters of the biochemical reactions to predict the network's dynamic behavior. These predictions provide detailed insights into the properties that determine aspects of the network's structure and behavior. However, the difficulty of obtaining numerical values of kinetic parameters is widely recognized to limit the applicability of this latter class of methods. Several researchers have observed that the connectivity of a network alone can provide significant insights into its dynamics. Motivated by this fundamental observation, we present the signaling Petri net, a non-parametric model of cellular signaling networks, and the signaling Petri net-based simulator, a Petri net execution strategy for characterizing the dynamics of signal flow through a signaling network using token distribution and sampling. The result is a very fast method, which can analyze large-scale networks, and provide insights into the trends of molecules' activity-levels in response to an external stimulus, based solely on the network's connectivity. We have implemented the signaling Petri net-based simulator in the PathwayOracle toolkit, which is publicly available at http://bioinfo.cs.rice.edu/pathwayoracle. Using this method, we studied a MAPK1,2 and AKT signaling network downstream from EGFR in two breast tumor cell lines. We analyzed, both experimentally and computationally, the activity level of several molecules in response to a targeted manipulation of TSC2 and mTOR-Raptor. The results from our method agreed with experimental results in greater than 90% of the cases considered, and in those where they did not agree, our approach provided valuable insights into discrepancies between known network connectivities and experimental observations. PMID:18463702

Integrative Inferences on Pattern Geometries of Grapes Grown under Water Stress and Their Resulting Wines.

PubMed

Hsieh, Fushing; Hsueh, Chih-Hsin; Heitkamp, Constantin; Matthews, Mark

2016-01-01

Multiple datasets of two consecutive vintages of replicated grape and wines from six different deficit irrigation regimes are characterized and compared. The process consists of four temporal-ordered signature phases: harvest field data, juice composition, wine composition before bottling and bottled wine. A new computing paradigm and an integrative inferential platform are developed for discovering phase-to-phase pattern geometries for such characterization and comparison purposes. Each phase is manifested by a distinct set of features, which are measurable upon phase-specific entities subject to the common set of irrigation regimes. Throughout the four phases, this compilation of data from irrigation regimes with subsamples is termed a space of media-nodes, on which measurements of phase-specific features were recoded. All of these collectively constitute a bipartite network of data, which is then normalized and binary coded. For these serial bipartite networks, we first quantify patterns that characterize individual phases by means of a new computing paradigm called "Data Mechanics". This computational technique extracts a coupling geometry which captures and reveals interacting dependence among and between media-nodes and feature-nodes in forms of hierarchical block sub-matrices. As one of the principal discoveries, the holistic year-factor persistently surfaces as the most inferential factor in classifying all media-nodes throughout all phases. This could be deemed either surprising in its over-arching dominance or obvious based on popular belief. We formulate and test pattern-based hypotheses that confirm such fundamental patterns. We also attempt to elucidate the driving force underlying the phase-evolution in winemaking via a newly developed partial coupling geometry, which is designed to integrate two coupling geometries. Such partial coupling geometries are confirmed to bear causal and predictive implications. All pattern inferences are performed with respect to a profile of energy distributions sampled from network bootstrapping ensembles conforming to block-structures specified by corresponding hypotheses.

Integrative Inferences on Pattern Geometries of Grapes Grown under Water Stress and Their Resulting Wines

PubMed Central

Hsieh, Fushing; Hsueh, Chih-Hsin; Heitkamp, Constantin; Matthews, Mark

2016-01-01

Multiple datasets of two consecutive vintages of replicated grape and wines from six different deficit irrigation regimes are characterized and compared. The process consists of four temporal-ordered signature phases: harvest field data, juice composition, wine composition before bottling and bottled wine. A new computing paradigm and an integrative inferential platform are developed for discovering phase-to-phase pattern geometries for such characterization and comparison purposes. Each phase is manifested by a distinct set of features, which are measurable upon phase-specific entities subject to the common set of irrigation regimes. Throughout the four phases, this compilation of data from irrigation regimes with subsamples is termed a space of media-nodes, on which measurements of phase-specific features were recoded. All of these collectively constitute a bipartite network of data, which is then normalized and binary coded. For these serial bipartite networks, we first quantify patterns that characterize individual phases by means of a new computing paradigm called “Data Mechanics”. This computational technique extracts a coupling geometry which captures and reveals interacting dependence among and between media-nodes and feature-nodes in forms of hierarchical block sub-matrices. As one of the principal discoveries, the holistic year-factor persistently surfaces as the most inferential factor in classifying all media-nodes throughout all phases. This could be deemed either surprising in its over-arching dominance or obvious based on popular belief. We formulate and test pattern-based hypotheses that confirm such fundamental patterns. We also attempt to elucidate the driving force underlying the phase-evolution in winemaking via a newly developed partial coupling geometry, which is designed to integrate two coupling geometries. Such partial coupling geometries are confirmed to bear causal and predictive implications. All pattern inferences are performed with respect to a profile of energy distributions sampled from network bootstrapping ensembles conforming to block-structures specified by corresponding hypotheses. PMID:27508416

Unit cell-based computer-aided manufacturing system for tissue engineering.

PubMed

Kang, Hyun-Wook; Park, Jeong Hun; Kang, Tae-Yun; Seol, Young-Joon; Cho, Dong-Woo

2012-03-01

Scaffolds play an important role in the regeneration of artificial tissues or organs. A scaffold is a porous structure with a micro-scale inner architecture in the range of several to several hundreds of micrometers. Therefore, computer-aided construction of scaffolds should provide sophisticated functionality for porous structure design and a tool path generation strategy that can achieve micro-scale architecture. In this study, a new unit cell-based computer-aided manufacturing (CAM) system was developed for the automated design and fabrication of a porous structure with micro-scale inner architecture that can be applied to composite tissue regeneration. The CAM system was developed by first defining a data structure for the computing process of a unit cell representing a single pore structure. Next, an algorithm and software were developed and applied to construct porous structures with a single or multiple pore design using solid freeform fabrication technology and a 3D tooth/spine computer-aided design model. We showed that this system is quite feasible for the design and fabrication of a scaffold for tissue engineering.

Computational investigation of the human SOD1 mutant, Cys146Arg, that directs familial amyotrophic lateral sclerosis.

PubMed

Srinivasan, E; Rajasekaran, R

2017-07-25

The genetic substitution mutation of Cys146Arg in the SOD1 protein is predominantly found in the Japanese population suffering from familial amyotrophic lateral sclerosis (FALS). A complete study of the biophysical aspects of this particular missense mutation through conformational analysis and producing free energy landscapes could provide an insight into the pathogenic mechanism of ALS disease. In this study, we utilized general molecular dynamics simulations along with computational predictions to assess the structural characterization of the protein as well as the conformational preferences of monomeric wild type and mutant SOD1. Our static analysis, accomplished through multiple programs, predicted the deleterious and destabilizing effect of mutant SOD1. Subsequently, comparative molecular dynamic studies performed on the wild type and mutant SOD1 indicated a loss in the protein conformational stability and flexibility. We observed the mutational consequences not only in local but also in long-range variations in the structural properties of the SOD1 protein. Long-range intramolecular protein interactions decrease upon mutation, resulting in less compact structures in the mutant protein rather than in the wild type, suggesting that the mutant structures are less stable than the wild type SOD1. We also presented the free energy landscape to study the collective motion of protein conformations through principal component analysis for the wild type and mutant SOD1. Overall, the study assisted in revealing the cause of the structural destabilization and protein misfolding via structural characterization, secondary structure composition and free energy landscapes. Hence, the computational framework in our study provides a valuable direction for the search for the cure against fatal FALS.

Analysis of the structure and dynamics of human serum albumin.

PubMed

Guizado, T R Cuya

2014-10-01

Human serum albumin (HSA) is a biologically relevant protein that binds a variety of drugs and other small molecules. No less than 50 structures are deposited in the RCSB Protein Data Bank (PDB). Based on these structures, we first performed a clustering analysis. Despite the diversity of ligands, only two well defined conformations are detected, with a deviation of 0.46 nm between the average structures of the two clusters, while deviations within each cluster are smaller than 0.08 nm. Those two conformations are representative of the apoprotein and the HSA-myristate complex already identified in previous literature. Considering the structures within each cluster as a representative sample of the dynamical states of the corresponding conformation, we scrutinize the structural and dynamical differences between both conformations. Analysis of the fluctuations within each cluster set reveals that domain II is the most rigid one and better matches both structures. Then, taking this domain as reference, we show that the structural difference between both conformations can be expressed in terms of twist and hinge motions of domains I and III, respectively. We also characterize the dynamical difference between conformations by computing correlations and principal components for each set of dynamical states. The two conformations display different collective motions. The results are compared with those obtained from the trajectories of short molecular dynamics simulations, giving consistent outcomes. Let us remark that, beyond the relevance of the results for the structural and dynamical characterization of HAS conformations, the present methodology could be extended to other proteins in the PDB archive.

Vibration-based monitoring and diagnostics using compressive sensing

NASA Astrophysics Data System (ADS)

Ganesan, Vaahini; Das, Tuhin; Rahnavard, Nazanin; Kauffman, Jeffrey L.

2017-04-01

Vibration data from mechanical systems carry important information that is useful for characterization and diagnosis. Standard approaches rely on continually streaming data at a fixed sampling frequency. For applications involving continuous monitoring, such as Structural Health Monitoring (SHM), such approaches result in high volume data and rely on sensors being powered for prolonged durations. Furthermore, for spatial resolution, structures are instrumented with a large array of sensors. This paper shows that both volume of data and number of sensors can be reduced significantly by applying Compressive Sensing (CS) in vibration monitoring applications. The reduction is achieved by using random sampling and capitalizing on the sparsity of vibration signals in the frequency domain. Preliminary experimental results validating CS-based frequency recovery are also provided. By exploiting the sparsity of mode shapes, CS can also enable efficient spatial reconstruction using fewer spatially distributed sensors. CS can thereby reduce the cost and power requirement of sensing as well as streamline data storage and processing in monitoring applications. In well-instrumented structures, CS can enable continued monitoring in case of sensor or computational failures.

Synthesis, characterization and computational studies of 3-{(E)-[(2-hydroxyphenyl)imino]methyl}benzene-1,2-diol and molecular structure of its zwitterionic form

NASA Astrophysics Data System (ADS)

Ezeorah, Julius Chigozie; Ossai, Valentine; Obasi, Lawrence Nnamdi; Elzagheid, Mohamed I.; Rhyman, Lydia; Lutter, Michael; Jurkschat, Klaus; Dege, Necmi; Ramasami, Ponnadurai

2018-01-01

The Schiff base 3-{(E)-[(2-hydroxyphenyl)imino]methyl}benzene-1,2-diol was synthesized by the condensation of 2,3-dihydroxybenzaldehyde and 2-aminophenol in water at room temperature. The crystal was grown using two solvents (dry methanol and 60% methanol). The compound was characterized using elemental microanalysis, IR, NMR, UV spectroscopies and single-crystal X-ray diffraction crystallography. The X-ray structure reveals that the Schiff base crystallizes as a methanol solvate in dry methanol with triclinic crystal system, space group P-1 and Z = 2 in the unit cell and as a non-methanol solvate in 60% methanol with triclinic crystal system, space group P-1 and Z = 4 in the unit cell. The compound showed absorption bands at 272, 389, 473 and 602 nm in DMSO. These bands were assigned as π → π ∗, n → π∗ and n-σ∗ transitions. The 473 and 602 nm bands in DMSO reveal that the compound exists in tautomeric forms. The presence of N-H, C-O and Cdbnd N stretching vibrations in the IR spectrum indicates that the compound is zwitterionic in the solid state. This study was supplemented using density functional theory method.

Year 2 Report: Protein Function Prediction Platform

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

Zhou, C E

2012-04-27

Upon completion of our second year of development in a 3-year development cycle, we have completed a prototype protein structure-function annotation and function prediction system: Protein Function Prediction (PFP) platform (v.0.5). We have met our milestones for Years 1 and 2 and are positioned to continue development in completion of our original statement of work, or a reasonable modification thereof, in service to DTRA Programs involved in diagnostics and medical countermeasures research and development. The PFP platform is a multi-scale computational modeling system for protein structure-function annotation and function prediction. As of this writing, PFP is the only existing fullymore » automated, high-throughput, multi-scale modeling, whole-proteome annotation platform, and represents a significant advance in the field of genome annotation (Fig. 1). PFP modules perform protein functional annotations at the sequence, systems biology, protein structure, and atomistic levels of biological complexity (Fig. 2). Because these approaches provide orthogonal means of characterizing proteins and suggesting protein function, PFP processing maximizes the protein functional information that can currently be gained by computational means. Comprehensive annotation of pathogen genomes is essential for bio-defense applications in pathogen characterization, threat assessment, and medical countermeasure design and development in that it can short-cut the time and effort required to select and characterize protein biomarkers.« less

Characterization of porous glass fiber-reinforced composite (FRC) implant structures: porosity and mechanical properties.

PubMed

Ylä-Soininmäki, Anne; Moritz, Niko; Lassila, Lippo V J; Peltola, Matti; Aro, Hannu T; Vallittu, Pekka K

2013-12-01

The aim of this study was to characterize the microstructure and mechanical properties of porous fiber-reinforced composites (FRC). Implants made of the FRC structures are intended for cranial applications. The FRC specimens were prepared by impregnating E-glass fiber sheet with non-resorbable bifunctional bis-phenyl glycidyl dimethacrylate and triethylene glycol dimethacrylate resin matrix. Four groups of porous FRC specimens were prepared with a different amount of resin matrix. Control group contained specimens of fibers, which were bound together with sizing only. Microstructure of the specimens was analyzed using a micro computed tomography (micro-CT) based method. Mechanical properties of the specimens were measured with a tensile test. The amount of resin matrix in the specimens had an effect on the microstructure. Total porosity was 59.5 % (median) in the group with the lowest resin content and 11.2 % (median) in the group with the highest resin content. In control group, total porosity was 94.2 % (median). Correlations with resin content were obtained for all micro-CT based parameters except TbPf. The tensile strength of the composites was 21.3 MPa (median) in the group with the highest resin content and 43.4 MPa (median) in the group with the highest resin content. The tensile strength in control group was 18.9 MPa (median). There were strong correlations between the tensile strength of the specimens and most of the micro-CT based parameters. This experiment suggests that porous FRC structures may have the potential for use in implants for cranial bone reconstructions, provided further relevant in vitro and in vivo tests are performed.

Synthesis and characterization of antifouling poly(N-acryloylaminoethoxyethanol) with ultralow protein adsorption and cell attachment.

PubMed

Chen, Hong; Zhang, Mingzhen; Yang, Jintao; Zhao, Chao; Hu, Rundong; Chen, Qiang; Chang, Yung; Zheng, Jie

2014-09-02

Rational design of effective antifouling polymers is challenging but important for many fundamental and applied applications. Herein we synthesize and characterize an N-acryloylaminoethoxyethanol (AAEE) monomer, which integrates three hydrophilic groups of hydroxyl, amide, and ethylene glycol in the same material. AAEE monomers were further grafted and polymerized on gold substrates to form polyAAEE brushes with well-controlled thickness via surface-initiated atomic transfer radical polymerization (SI-ATRP), with particular attention to a better understanding of the molecular structure-antifouling property relationship of hydroxyl-acrylic-based polymers. The surface hydrophilicity and antifouling properties of polyAAEE brushes as a function of film thickness are studied by combined experimental and computational methods including surface plasmon resonance (SPR) sensors, atomic force microscopy (AFM), cell adhesion assay, and molecular dynamics (MD) simulations. With the optimal polymer film thicknesses (∼10-40 nm), polyAAEE-grafted surfaces can effectively resist protein adsorption from single-protein solutions and undiluted human blood plasma and serum to a nonfouling level (i.e., <0.3 ng/cm(2)). The polyAAEE brushes also highly resist mammalian cell attachment up to 3 days. MD simulations confirm that the integration of three hydrophilic groups induce a stronger and closer hydration layer around polyAAEE, revealing a positive relationship between surface hydration and antifouling properties. The molecular structure-antifouling properties relationship of a series of hydroxyl-acrylic-based polymers is also discussed. This work hopefully provides a promising structural motif for the design of new effective antifouling materials beyond traditional ethylene glycol-based antifouling materials.

Characterizing Crowd Participation and Productivity of Foldit Through Web Scraping

DTIC Science & Technology

2016-03-01

Berkeley Open Infrastructure for Network Computing CDF Cumulative Distribution Function CPU Central Processing Unit CSSG Crowdsourced Serious Game...computers at once can create a similar capacity. According to Anderson [6], principal investigator for the Berkeley Open Infrastructure for Network...extraterrestrial life. From this project, a software-based distributed computing platform called the Berkeley Open Infrastructure for Network Computing

Characterization of real-time computers

NASA Technical Reports Server (NTRS)

Shin, K. G.; Krishna, C. M.

1984-01-01

A real-time system consists of a computer controller and controlled processes. Despite the synergistic relationship between these two components, they have been traditionally designed and analyzed independently of and separately from each other; namely, computer controllers by computer scientists/engineers and controlled processes by control scientists. As a remedy for this problem, in this report real-time computers are characterized by performance measures based on computer controller response time that are: (1) congruent to the real-time applications, (2) able to offer an objective comparison of rival computer systems, and (3) experimentally measurable/determinable. These measures, unlike others, provide the real-time computer controller with a natural link to controlled processes. In order to demonstrate their utility and power, these measures are first determined for example controlled processes on the basis of control performance functionals. They are then used for two important real-time multiprocessor design applications - the number-power tradeoff and fault-masking and synchronization.

A 3D Model for Eddy Current Inspection in Aeronautics: Application to Riveted Structures

NASA Astrophysics Data System (ADS)

Paillard, S.; Pichenot, G.; Lambert, M.; Voillaume, H.; Dominguez, N.

2007-03-01

Eddy current technique is currently an operational tool used for fastener inspection which is an important issue for the maintenance of aircraft structures. The industry calls for faster, more sensitive and reliable NDT techniques for the detection and characterization of potential flaws nearby rivet. In order to reduce the development time and to optimize the design and the performances assessment of an inspection procedure, the CEA and EADS have started a collaborative work aiming at extending the modeling features of the CIVA non destructive simulation plat-form in order to handle the configuration of a layered planar structure with a rivet and an embedded flaw nearby. Therefore, an approach based on the Volume Integral Method using the Green dyadic formalism which greatly increases computation efficiency has been developed. The first step, modeling the rivet without flaw as a hole in a multi-stratified structure, has been reached and validated in several configurations with experimental data.

Structure-based view on [PSI(+)] prion properties.

PubMed

Bondarev, Stanislav A; Zhouravleva, Galina A; Belousov, Mikhail V; Kajava, Andrey V

2015-01-01

Yeast [PSI(+)] prion is one of the most suitable and well characterized system for the investigation of the prion phenomenon. However, until recently, the lack of data on the 3D arrangement of Sup35p prion fibrils hindered progress in this area. The recent arrival in this field of new experimental techniques led to the parallel and in-register superpleated β-structure as a consensus model for Sup35p fibrils. Here, we analyzed the effect of amino acid substitutions of the Sup35 protein through the prism of this structural model. Application of a newly developed computational approach, called ArchCandy, gives us a better understanding of the effect caused by mutations on the fibril forming potential of Sup35 protein. This bioinformatics tool can be used for the design of new mutations with desired modification of prion properties. Thus, we provide examples of how today, having progress toward elucidation of the structural arrangement of Sup35p fibrils, researchers can advance more efficiently to a better understanding of prion [PSI(+)] stability and propagation.

Application of a Probalistic Sizing Methodology for Ceramic Structures

NASA Astrophysics Data System (ADS)

Rancurel, Michael; Behar-Lafenetre, Stephanie; Cornillon, Laurence; Leroy, Francois-Henri; Coe, Graham; Laine, Benoit

2012-07-01

Ceramics are increasingly used in the space industry to take advantage of their stability and high specific stiffness properties. Their brittle behaviour often leads to size them by increasing the safety factors that are applied on the maximum stresses. It induces to oversize the structures. This is inconsistent with the major driver in space architecture, the mass criteria. This paper presents a methodology to size ceramic structures based on their failure probability. Thanks to failure tests on samples, the Weibull law which characterizes the strength distribution of the material is obtained. A-value (Q0.0195%) and B-value (Q0.195%) are then assessed to take into account the limited number of samples. A knocked-down Weibull law that interpolates the A- & B- values is also obtained. Thanks to these two laws, a most-likely and a knocked- down prediction of failure probability are computed for complex ceramic structures. The application of this methodology and its validation by test is reported in the paper.

Sepsis reconsidered: Identifying novel metrics for behavioral landscape characterization with a high-performance computing implementation of an agent-based model.

PubMed

Cockrell, Chase; An, Gary

2017-10-07

Sepsis affects nearly 1 million people in the United States per year, has a mortality rate of 28-50% and requires more than $20 billion a year in hospital costs. Over a quarter century of research has not yielded a single reliable diagnostic test or a directed therapeutic agent for sepsis. Central to this insufficiency is the fact that sepsis remains a clinical/physiological diagnosis representing a multitude of molecularly heterogeneous pathological trajectories. Advances in computational capabilities offered by High Performance Computing (HPC) platforms call for an evolution in the investigation of sepsis to attempt to define the boundaries of traditional research (bench, clinical and computational) through the use of computational proxy models. We present a novel investigatory and analytical approach, derived from how HPC resources and simulation are used in the physical sciences, to identify the epistemic boundary conditions of the study of clinical sepsis via the use of a proxy agent-based model of systemic inflammation. Current predictive models for sepsis use correlative methods that are limited by patient heterogeneity and data sparseness. We address this issue by using an HPC version of a system-level validated agent-based model of sepsis, the Innate Immune Response ABM (IIRBM), as a proxy system in order to identify boundary conditions for the possible behavioral space for sepsis. We then apply advanced analysis derived from the study of Random Dynamical Systems (RDS) to identify novel means for characterizing system behavior and providing insight into the tractability of traditional investigatory methods. The behavior space of the IIRABM was examined by simulating over 70 million sepsis patients for up to 90 days in a sweep across the following parameters: cardio-respiratory-metabolic resilience; microbial invasiveness; microbial toxigenesis; and degree of nosocomial exposure. In addition to using established methods for describing parameter space, we developed two novel methods for characterizing the behavior of a RDS: Probabilistic Basins of Attraction (PBoA) and Stochastic Trajectory Analysis (STA). Computationally generated behavioral landscapes demonstrated attractor structures around stochastic regions of behavior that could be described in a complementary fashion through use of PBoA and STA. The stochasticity of the boundaries of the attractors highlights the challenge for correlative attempts to characterize and classify clinical sepsis. HPC simulations of models like the IIRABM can be used to generate approximations of the behavior space of sepsis to both establish "boundaries of futility" with respect to existing investigatory approaches and apply system engineering principles to investigate the general dynamic properties of sepsis to provide a pathway for developing control strategies. The issues that bedevil the study and treatment of sepsis, namely clinical data sparseness and inadequate experimental sampling of system behavior space, are fundamental to nearly all biomedical research, manifesting in the "Crisis of Reproducibility" at all levels. HPC-augmented simulation-based research offers an investigatory strategy more consistent with that seen in the physical sciences (which combine experiment, theory and simulation), and an opportunity to utilize the leading advances in HPC, namely deep machine learning and evolutionary computing, to form the basis of an iterative scientific process to meet the full promise of Precision Medicine (right drug, right patient, right time). Copyright © 2017. Published by Elsevier Ltd.

Parameter retrieval of chiral metamaterials based on the state-space approach.

PubMed

Zarifi, Davoud; Soleimani, Mohammad; Abdolali, Ali

2013-08-01

This paper deals with the introduction of an approach for the electromagnetic characterization of homogeneous chiral layers. The proposed method is based on the state-space approach and properties of a 4×4 state transition matrix. Based on this, first, the forward problem analysis through the state-space method is reviewed and properties of the state transition matrix of a chiral layer are presented and proved as two theorems. The formulation of a proposed electromagnetic characterization method is then presented. In this method, scattering data for a linearly polarized plane wave incident normally on a homogeneous chiral slab are combined with properties of a state transition matrix and provide a powerful characterization method. The main difference with respect to other well-established retrieval procedures based on the use of the scattering parameters relies on the direct computation of the transfer matrix of the slab as opposed to the conventional calculation of the propagation constant and impedance of the modes supported by the medium. The proposed approach allows avoiding nonlinearity of the problem but requires getting enough equations to fulfill the task which was provided by considering some properties of the state transition matrix. To demonstrate the applicability and validity of the method, the constitutive parameters of two well-known dispersive chiral metamaterial structures at microwave frequencies are retrieved. The results show that the proposed method is robust and reliable.

Computer-Based Training: Capitalizing on Lessons Learned

ERIC Educational Resources Information Center

Bedwell, Wendy L.; Salas, Eduardo

2010-01-01

Computer-based training (CBT) is a methodology for providing systematic, structured learning; a useful tool when properly designed. CBT has seen a resurgence given the serious games movement, which is at the forefront of integrating primarily entertainment computer-based games into education and training. This effort represents a multidisciplinary…

Kinematics of the New Madrid seismic zone, central United States, based on stepover models

USGS Publications Warehouse

Pratt, Thomas L.

2012-01-01

Seismicity in the New Madrid seismic zone (NMSZ) of the central United States is generally attributed to a stepover structure in which the Reelfoot thrust fault transfers slip between parallel strike-slip faults. However, some arms of the seismic zone do not fit this simple model. Comparison of the NMSZ with an analog sandbox model of a restraining stepover structure explains all of the arms of seismicity as only part of the extensive pattern of faults that characterizes stepover structures. Computer models show that the stepover structure may form because differences in the trends of lower crustal shearing and inherited upper crustal faults make a step between en echelon fault segments the easiest path for slip in the upper crust. The models predict that the modern seismicity occurs only on a subset of the faults in the New Madrid stepover structure, that only the southern part of the stepover structure ruptured in the A.D. 1811–1812 earthquakes, and that the stepover formed because the trends of older faults are not the same as the current direction of shearing.

A comparative study between experimental results and numerical predictions of multi-wall structural response to hypervelocity impact

NASA Technical Reports Server (NTRS)

Schonberg, William P.; Peck, Jeffrey A.

1992-01-01

Over the last three decades, multiwall structures have been analyzed extensively, primarily through experiment, as a means of increasing the protection afforded to spacecraft structure. However, as structural configurations become more varied, the number of tests required to characterize their response increases dramatically. As an alternative, numerical modeling of high-speed impact phenomena is often being used to predict the response of a variety of structural systems under impact loading conditions. This paper presents the results of a preliminary numerical/experimental investigation of the hypervelocity impact response of multiwall structures. The results of experimental high-speed impact tests are compared against the predictions of the HULL hydrodynamic computer code. It is shown that the hypervelocity impact response characteristics of a specific system cannot be accurately predicted from a limited number of HULL code impact simulations. However, if a wide range of impact loadings conditions are considered, then the ballistic limit curve of the system based on the entire series of numerical simulations can be used as a relatively accurate indication of actual system response.

A demonstrative model of a lunar base simulation on a personal computer

NASA Technical Reports Server (NTRS)

1985-01-01

The initial demonstration model of a lunar base simulation is described. This initial model was developed on the personal computer level to demonstrate feasibility and technique before proceeding to a larger computer-based model. Lotus Symphony Version 1.1 software was used to base the demonstration model on an personal computer with an MS-DOS operating system. The personal computer-based model determined the applicability of lunar base modeling techniques developed at an LSPI/NASA workshop. In addition, the personnal computer-based demonstration model defined a modeling structure that could be employed on a larger, more comprehensive VAX-based lunar base simulation. Refinement of this personal computer model and the development of a VAX-based model is planned in the near future.

A Self-Instructional Approach To the Teaching of Enzymology Involving Computer-Based Sequence Analysis and Molecular Modelling.

ERIC Educational Resources Information Center

Attwood, Paul V.

1997-01-01

Describes a self-instructional assignment approach to the teaching of advanced enzymology. Presents an assignment that offers a means of teaching enzymology to students that exposes them to modern computer-based techniques of analyzing protein structure and relates structure to enzyme function. (JRH)

Graph characterization via Ihara coefficients.

PubMed

Ren, Peng; Wilson, Richard C; Hancock, Edwin R

2011-02-01

The novel contributions of this paper are twofold. First, we demonstrate how to characterize unweighted graphs in a permutation-invariant manner using the polynomial coefficients from the Ihara zeta function, i.e., the Ihara coefficients. Second, we generalize the definition of the Ihara coefficients to edge-weighted graphs. For an unweighted graph, the Ihara zeta function is the reciprocal of a quasi characteristic polynomial of the adjacency matrix of the associated oriented line graph. Since the Ihara zeta function has poles that give rise to infinities, the most convenient numerically stable representation is to work with the coefficients of the quasi characteristic polynomial. Moreover, the polynomial coefficients are invariant to vertex order permutations and also convey information concerning the cycle structure of the graph. To generalize the representation to edge-weighted graphs, we make use of the reduced Bartholdi zeta function. We prove that the computation of the Ihara coefficients for unweighted graphs is a special case of our proposed method for unit edge weights. We also present a spectral analysis of the Ihara coefficients and indicate their advantages over other graph spectral methods. We apply the proposed graph characterization method to capturing graph-class structure and clustering graphs. Experimental results reveal that the Ihara coefficients are more effective than methods based on Laplacian spectra.

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

Hattrick-Simpers, Jason R.; Gregoire, John M.; Kusne, A. Gilad

With their ability to rapidly elucidate composition-structure-property relationships, high-throughput experimental studies have revolutionized how materials are discovered, optimized, and commercialized. It is now possible to synthesize and characterize high-throughput libraries that systematically address thousands of individual cuts of fabrication parameter space. An unresolved issue remains transforming structural characterization data into phase mappings. This difficulty is related to the complex information present in diffraction and spectroscopic data and its variation with composition and processing. Here, we review the field of automated phase diagram attribution and discuss the impact that emerging computational approaches will have in the generation of phase diagrams andmore » beyond.« less

Computational methods and software systems for dynamics and control of large space structures

NASA Technical Reports Server (NTRS)

Park, K. C.; Felippa, C. A.; Farhat, C.; Pramono, E.

1990-01-01

Two key areas of crucial importance to the computer-based simulation of large space structures are discussed. The first area involves multibody dynamics (MBD) of flexible space structures, with applications directed to deployment, construction, and maneuvering. The second area deals with advanced software systems, with emphasis on parallel processing. The latest research thrust in the second area involves massively parallel computers.

High-resolution mapping of bifurcations in nonlinear biochemical circuits

NASA Astrophysics Data System (ADS)

Genot, A. J.; Baccouche, A.; Sieskind, R.; Aubert-Kato, N.; Bredeche, N.; Bartolo, J. F.; Taly, V.; Fujii, T.; Rondelez, Y.

2016-08-01

Analog molecular circuits can exploit the nonlinear nature of biochemical reaction networks to compute low-precision outputs with fewer resources than digital circuits. This analog computation is similar to that employed by gene-regulation networks. Although digital systems have a tractable link between structure and function, the nonlinear and continuous nature of analog circuits yields an intricate functional landscape, which makes their design counter-intuitive, their characterization laborious and their analysis delicate. Here, using droplet-based microfluidics, we map with high resolution and dimensionality the bifurcation diagrams of two synthetic, out-of-equilibrium and nonlinear programs: a bistable DNA switch and a predator-prey DNA oscillator. The diagrams delineate where function is optimal, dynamics bifurcates and models fail. Inverse problem solving on these large-scale data sets indicates interference from enzymatic coupling. Additionally, data mining exposes the presence of rare, stochastically bursting oscillators near deterministic bifurcations.

Space station data system analysis/architecture study. Task 2: Options development DR-5. Volume 1: Technology options

NASA Technical Reports Server (NTRS)

1985-01-01

The second task in the Space Station Data System (SSDS) Analysis/Architecture Study is the development of an information base that will support the conduct of trade studies and provide sufficient data to make key design/programmatic decisions. This volume identifies the preferred options in the technology category and characterizes these options with respect to performance attributes, constraints, cost, and risk. The technology category includes advanced materials, processes, and techniques that can be used to enhance the implementation of SSDS design structures. The specific areas discussed are mass storage, including space and round on-line storage and off-line storage; man/machine interface; data processing hardware, including flight computers and advanced/fault tolerant computer architectures; and software, including data compression algorithms, on-board high level languages, and software tools. Also discussed are artificial intelligence applications and hard-wire communications.

Unconventional Hamilton-type variational principle in phase space and symplectic algorithm

NASA Astrophysics Data System (ADS)

Luo, En; Huang, Weijiang; Zhang, Hexin

2003-06-01

By a novel approach proposed by Luo, the unconventional Hamilton-type variational principle in phase space for elastodynamics of multidegree-of-freedom system is established in this paper. It not only can fully characterize the initial-value problem of this dynamic, but also has a natural symplectic structure. Based on this variational principle, a symplectic algorithm which is called a symplectic time-subdomain method is proposed. A non-difference scheme is constructed by applying Lagrange interpolation polynomial to the time subdomain. Furthermore, it is also proved that the presented symplectic algorithm is an unconditionally stable one. From the results of the two numerical examples of different types, it can be seen that the accuracy and the computational efficiency of the new method excel obviously those of widely used Wilson-θ and Newmark-β methods. Therefore, this new algorithm is a highly efficient one with better computational performance.

Quantitative Pulmonary Imaging Using Computed Tomography and Magnetic Resonance Imaging

PubMed Central

Washko, George R.; Parraga, Grace; Coxson, Harvey O.

2011-01-01

Measurements of lung function, including spirometry and body plethesmography, are easy to perform and are the current clinical standard for assessing disease severity. However, these lung functional techniques do not adequately explain the observed variability in clinical manifestations of disease and offer little insight into the relationship of lung structure and function. Lung imaging and the image based assessment of lung disease has matured to the extent that it is common for clinical, epidemiologic, and genetic investigation to have a component dedicated to image analysis. There are several exciting imaging modalities currently being used for the non-invasive study of lung anatomy and function. In this review we will focus on two of them, x-ray computed tomography and magnetic resonance imaging. Following a brief introduction of each method we detail some of the most recent work being done to characterize smoking-related lung disease and the clinical applications of such knowledge. PMID:22142490

Analysis of STM images with pure and CO-functionalized tips: A first-principles and experimental study

NASA Astrophysics Data System (ADS)

Gustafsson, Alexander; Okabayashi, Norio; Peronio, Angelo; Giessibl, Franz J.; Paulsson, Magnus

2017-08-01

We describe a first-principles method to calculate scanning tunneling microscopy (STM) images, and compare the results to well-characterized experiments combining STM with atomic force microscopy (AFM). The theory is based on density functional theory with a localized basis set, where the wave functions in the vacuum gap are computed by propagating the localized-basis wave functions into the gap using a real-space grid. Constant-height STM images are computed using Bardeen's approximation method, including averaging over the reciprocal space. We consider copper adatoms and single CO molecules adsorbed on Cu(111), scanned with a single-atom copper tip with and without CO functionalization. The calculated images agree with state-of-the-art experiments, where the atomic structure of the tip apex is determined by AFM. The comparison further allows for detailed interpretation of the STM images.

Computed tomographic analysis of calvarial hyperostosis in captive lions.

PubMed

Gross-Tsubery, Ruth; Chai, Orit; Shilo, Yael; Miara, Limor; Horowitz, Igal H; Shmueli, Ayelet; Aizenberg, Itzhak; Hoffman, Chen; Reifen, Ram; Shamir, Merav H

2010-01-01

Osseous malformations in the skull and cervical vertebrae of lions in captivity are believed to be caused by hypovitaminosis A. These often lead to severe neurologic abnormalities and may result in death. We describe the characterization of these abnormalities based on computed tomography (CT). CT images of two affected and three healthy lions were compared with define the normal anatomy of the skull and cervical vertebrae and provide information regarding the aforementioned osseous malformations. Because bone structure is influenced by various factors other than the aforementioned disease, all values were divided by the skull width that was not affected. The calculated ratios were compared and the most pronounced abnormalities in the affected lions were, narrowing of the foramen magnum, thickening of the tentorium osseus cerebelli and thickening of the dorsal arch of the atlas. CT is useful for detection of the calvarial abnormalities in lions and may be useful in further defining this syndrome.

Simulation Based Exploration of Critical Zone Dynamics in Intensively Managed Landscapes

NASA Astrophysics Data System (ADS)

Kumar, P.

2017-12-01

The advent of high-resolution measurements of topographic and (vertical) vegetation features using areal LiDAR are enabling us to resolve micro-scale ( 1m) landscape structural characteristics over large areas. Availability of hyperspectral measurements is further augmenting these LiDAR data by enabling the biogeochemical characterization of vegetation and soils at unprecedented spatial resolutions ( 1-10m). Such data have opened up novel opportunities for modeling Critical Zone processes and exploring questions that were not possible before. We show how an integrated 3-D model at 1m grid resolution can enable us to resolve micro-topographic and ecological dynamics and their control on hydrologic and biogeochemical processes over large areas. We address the computational challenge of such detailed modeling by exploiting hybrid CPU and GPU computing technologies. We show results of moisture, biogeochemical, and vegetation dynamics from studies in the Critical Zone Observatory for Intensively managed Landscapes (IMLCZO) in the Midwestern United States.

Characterization of structural connections for multicomponent systems

NASA Technical Reports Server (NTRS)

Lawrence, Charles; Huckelbridge, Arthur A.

1988-01-01

This study explores combining Component Mode Synthesis methods for coupling structural components with Parameter Identification procedures for improving the analytical modeling of the connections. Improvements in the connection stiffness and damping properties are computed in terms of physical parameters so that the physical characteristics of the connections can be better understood, in addition to providing improved input for the system model.

Toward a Unified Sub-symbolic Computational Theory of Cognition

PubMed Central

Butz, Martin V.

2016-01-01

This paper proposes how various disciplinary theories of cognition may be combined into a unifying, sub-symbolic, computational theory of cognition. The following theories are considered for integration: psychological theories, including the theory of event coding, event segmentation theory, the theory of anticipatory behavioral control, and concept development; artificial intelligence and machine learning theories, including reinforcement learning and generative artificial neural networks; and theories from theoretical and computational neuroscience, including predictive coding and free energy-based inference. In the light of such a potential unification, it is discussed how abstract cognitive, conceptualized knowledge and understanding may be learned from actively gathered sensorimotor experiences. The unification rests on the free energy-based inference principle, which essentially implies that the brain builds a predictive, generative model of its environment. Neural activity-oriented inference causes the continuous adaptation of the currently active predictive encodings. Neural structure-oriented inference causes the longer term adaptation of the developing generative model as a whole. Finally, active inference strives for maintaining internal homeostasis, causing goal-directed motor behavior. To learn abstract, hierarchical encodings, however, it is proposed that free energy-based inference needs to be enhanced with structural priors, which bias cognitive development toward the formation of particular, behaviorally suitable encoding structures. As a result, it is hypothesized how abstract concepts can develop from, and thus how they are structured by and grounded in, sensorimotor experiences. Moreover, it is sketched-out how symbol-like thought can be generated by a temporarily active set of predictive encodings, which constitute a distributed neural attractor in the form of an interactive free-energy minimum. The activated, interactive network attractor essentially characterizes the semantics of a concept or a concept composition, such as an actual or imagined situation in our environment. Temporal successions of attractors then encode unfolding semantics, which may be generated by a behavioral or mental interaction with an actual or imagined situation in our environment. Implications, further predictions, possible verification, and falsifications, as well as potential enhancements into a fully spelled-out unified theory of cognition are discussed at the end of the paper. PMID:27445895

RNA secondary structure prediction using soft computing.

PubMed

Ray, Shubhra Sankar; Pal, Sankar K

2013-01-01

Prediction of RNA structure is invaluable in creating new drugs and understanding genetic diseases. Several deterministic algorithms and soft computing-based techniques have been developed for more than a decade to determine the structure from a known RNA sequence. Soft computing gained importance with the need to get approximate solutions for RNA sequences by considering the issues related with kinetic effects, cotranscriptional folding, and estimation of certain energy parameters. A brief description of some of the soft computing-based techniques, developed for RNA secondary structure prediction, is presented along with their relevance. The basic concepts of RNA and its different structural elements like helix, bulge, hairpin loop, internal loop, and multiloop are described. These are followed by different methodologies, employing genetic algorithms, artificial neural networks, and fuzzy logic. The role of various metaheuristics, like simulated annealing, particle swarm optimization, ant colony optimization, and tabu search is also discussed. A relative comparison among different techniques, in predicting 12 known RNA secondary structures, is presented, as an example. Future challenging issues are then mentioned.

Hafnium transistor process design for neural interfacing.

PubMed

Parent, David W; Basham, Eric J

2009-01-01

A design methodology is presented that uses 1-D process simulations of Metal Insulator Semiconductor (MIS) structures to design the threshold voltage of hafnium oxide based transistors used for neural recording. The methodology is comprised of 1-D analytical equations for threshold voltage specification, and doping profiles, and 1-D MIS Technical Computer Aided Design (TCAD) to design a process to implement a specific threshold voltage, which minimized simulation time. The process was then verified with a 2-D process/electrical TCAD simulation. Hafnium oxide films (HfO) were grown and characterized for dielectric constant and fixed oxide charge for various annealing temperatures, two important design variables in threshold voltage design.

Efficient decentralized consensus protocols

NASA Technical Reports Server (NTRS)

Lakshman, T. V.; Agrawala, A. K.

1986-01-01

Decentralized consensus protocols are characterized by successive rounds of message interchanges. Protocols which achieve a consensus in one round of message interchange require O(N-squared) messages, where N is the number of participants. In this paper, a communication scheme, based on finite projective planes, which requires only O(N sq rt N) messages for each round is presented. Using this communication scheme, decentralized consensus protocols which achieve a consensus within two rounds of message interchange are developed. The protocols are symmetric, and the communication scheme does not impose any hierarchical structure. The scheme is illustrated using blocking and nonblocking commit protocols, decentralized extrema finding, and computation of the sum function.

Low oxidation state aluminum-containing cluster anions: Cp{sup ∗}Al{sub n}H{sup −}, n = 1–3

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

Zhang, Xinxing; Ganteför, Gerd; Bowen, Kit, E-mail: AKandalam@wcupa.edu, E-mail: kbowen@jhu.edu

Three new, low oxidation state, aluminum-containing cluster anions, Cp*Al{sub n}H{sup −}, n = 1–3, were prepared via reactions between aluminum hydride cluster anions, Al{sub n}H{sub m}{sup −}, and Cp*H ligands. These were characterized by mass spectrometry, anion photoelectron spectroscopy, and density functional theory based calculations. Agreement between the experimentally and theoretically determined vertical detachment energies and adiabatic detachment energies validated the computed geometrical structures. Reactions between aluminum hydride cluster anions and ligands provide a new avenue for discovering low oxidation state, ligated aluminum clusters.

Computational Materials Science and Chemistry: Accelerating Discovery and Innovation through Simulation-Based Engineering and Science

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

Crabtree, George; Glotzer, Sharon; McCurdy, Bill

This report is based on a SC Workshop on Computational Materials Science and Chemistry for Innovation on July 26-27, 2010, to assess the potential of state-of-the-art computer simulations to accelerate understanding and discovery in materials science and chemistry, with a focus on potential impacts in energy technologies and innovation. The urgent demand for new energy technologies has greatly exceeded the capabilities of today's materials and chemical processes. To convert sunlight to fuel, efficiently store energy, or enable a new generation of energy production and utilization technologies requires the development of new materials and processes of unprecedented functionality and performance. Newmore » materials and processes are critical pacing elements for progress in advanced energy systems and virtually all industrial technologies. Over the past two decades, the United States has developed and deployed the world's most powerful collection of tools for the synthesis, processing, characterization, and simulation and modeling of materials and chemical systems at the nanoscale, dimensions of a few atoms to a few hundred atoms across. These tools, which include world-leading x-ray and neutron sources, nanoscale science facilities, and high-performance computers, provide an unprecedented view of the atomic-scale structure and dynamics of materials and the molecular-scale basis of chemical processes. For the first time in history, we are able to synthesize, characterize, and model materials and chemical behavior at the length scale where this behavior is controlled. This ability is transformational for the discovery process and, as a result, confers a significant competitive advantage. Perhaps the most spectacular increase in capability has been demonstrated in high performance computing. Over the past decade, computational power has increased by a factor of a million due to advances in hardware and software. This rate of improvement, which shows no sign of abating, has enabled the development of computer simulations and models of unprecedented fidelity. We are at the threshold of a new era where the integrated synthesis, characterization, and modeling of complex materials and chemical processes will transform our ability to understand and design new materials and chemistries with predictive power. In turn, this predictive capability will transform technological innovation by accelerating the development and deployment of new materials and processes in products and manufacturing. Harnessing the potential of computational science and engineering for the discovery and development of materials and chemical processes is essential to maintaining leadership in these foundational fields that underpin energy technologies and industrial competitiveness. Capitalizing on the opportunities presented by simulation-based engineering and science in materials and chemistry will require an integration of experimental capabilities with theoretical and computational modeling; the development of a robust and sustainable infrastructure to support the development and deployment of advanced computational models; and the assembly of a community of scientists and engineers to implement this integration and infrastructure. This community must extend to industry, where incorporating predictive materials science and chemistry into design tools can accelerate the product development cycle and drive economic competitiveness. The confluence of new theories, new materials synthesis capabilities, and new computer platforms has created an unprecedented opportunity to implement a "materials-by-design" paradigm with wide-ranging benefits in technological innovation and scientific discovery. The Workshop on Computational Materials Science and Chemistry for Innovation was convened in Bethesda, Maryland, on July 26-27, 2010. Sponsored by the Department of Energy (DOE) Offices of Advanced Scientific Computing Research and Basic Energy Sciences, the workshop brought together 160 experts in materials science, chemistry, and computational science representing more than 65 universities, laboratories, and industries, and four agencies. The workshop examined seven foundational challenge areas in materials science and chemistry: materials for extreme conditions, self-assembly, light harvesting, chemical reactions, designer fluids, thin films and interfaces, and electronic structure. Each of these challenge areas is critical to the development of advanced energy systems, and each can be accelerated by the integrated application of predictive capability with theory and experiment. The workshop concluded that emerging capabilities in predictive modeling and simulation have the potential to revolutionize the development of new materials and chemical processes. Coupled with world-leading materials characterization and nanoscale science facilities, this predictive capability provides the foundation for an innovation ecosystem that can accelerate the discovery, development, and deployment of new technologies, including advanced energy systems. Delivering on the promise of this innovation ecosystem requires the following: Integration of synthesis, processing, characterization, theory, and simulation and modeling. Many of the newly established Energy Frontier Research Centers and Energy Hubs are exploiting this integration. Achieving/strengthening predictive capability in foundational challenge areas. Predictive capability in the seven foundational challenge areas described in this report is critical to the development of advanced energy technologies. Developing validated computational approaches that span vast differences in time and length scales. This fundamental computational challenge crosscuts all of the foundational challenge areas. Similarly challenging is coupling of analytical data from multiple instruments and techniques that are required to link these length and time scales. Experimental validation and quantification of uncertainty in simulation and modeling. Uncertainty quantification becomes increasingly challenging as simulations become more complex. Robust and sustainable computational infrastructure, including software and applications. For modeling and simulation, software equals infrastructure. To validate the computational tools, software is critical infrastructure that effectively translates huge arrays of experimental data into useful scientific understanding. An integrated approach for managing this infrastructure is essential. Efficient transfer and incorporation of simulation-based engineering and science in industry. Strategies for bridging the gap between research and industrial applications and for widespread industry adoption of integrated computational materials engineering are needed.« less

Computational 3D structures of drug-targeting proteins in the 2009-H1N1 influenza A virus

NASA Astrophysics Data System (ADS)

Du, Qi-Shi; Wang, Shu-Qing; Huang, Ri-Bo; Chou, Kuo-Chen

2010-01-01

The neuraminidase (NA) and M2 proton channel of influenza virus are the drug-targeting proteins, based on which several drugs were developed. However these once powerful drugs encountered drug-resistant problem to the H5N1 and H1N1 flu. To address this problem, the computational 3D structures of NA and M2 proteins of 2009-H1N1 influenza virus were built using the molecular modeling technique and computational chemistry method. Based on the models the structure features of NA and M2 proteins were analyzed, the docking structures of drug-protein complexes were computed, and the residue mutations were annotated. The results may help to solve the drug-resistant problem and stimulate designing more effective drugs against 2009-H1N1 influenza pandemic.

Analogs of methyllycaconitine as novel noncompetitive inhibitors of nicotinic receptors: pharmacological characterization, computational modeling, and pharmacophore development.

PubMed

McKay, Dennis B; Chang, Cheng; González-Cestari, Tatiana F; McKay, Susan B; El-Hajj, Raed A; Bryant, Darrell L; Zhu, Michael X; Swaan, Peter W; Arason, Kristjan M; Pulipaka, Aravinda B; Orac, Crina M; Bergmeier, Stephen C

2007-05-01

As a novel approach to drug discovery involving neuronal nicotinic acetylcholine receptors (nAChRs), our laboratory targeted nonagonist binding sites (i.e., noncompetitive binding sites, negative allosteric binding sites) located on nAChRs. Cultured bovine adrenal cells were used as neuronal models to investigate interactions of 67 analogs of methyllycaconitine (MLA) on native alpha3beta4* nAChRs. The availability of large numbers of structurally related molecules presents a unique opportunity for the development of pharmacophore models for noncompetitive binding sites. Our MLA analogs inhibited nicotine-mediated functional activation of both native and recombinant alpha3beta4* nAChRs with a wide range of IC(50) values (0.9-115 microM). These analogs had little or no inhibitory effects on agonist binding to native or recombinant nAChRs, supporting noncompetitive inhibitory activity. Based on these data, two highly predictive 3D quantitative structure-activity relationship (comparative molecular field analysis and comparative molecular similarity index analysis) models were generated. These computational models were successfully validated and provided insights into the molecular interactions of MLA analogs with nAChRs. In addition, a pharmacophore model was constructed to analyze and visualize the binding requirements to the analog binding site. The pharmacophore model was subsequently applied to search structurally diverse molecular databases to prospectively identify novel inhibitors. The rapid identification of eight molecules from database mining and our successful demonstration of in vitro inhibitory activity support the utility of these computational models as novel tools for the efficient retrieval of inhibitors. These results demonstrate the effectiveness of computational modeling and pharmacophore development, which may lead to the identification of new therapeutic drugs that target novel sites on nAChRs.

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

Larson, Natalie M.; Zok, Frank W.

One route for producing fiber-reinforced ceramic-matrix composites entails repeated impregnation and pyrolysis of a preceramic polymer in a fiber preform. The process relies crucially on the development of networks of contiguous cracks during pyrolysis, thereby allowing further impregnation to attain nearly-full densification. The present study employs in-situ x-ray computed tomography (XCT) to reveal in three dimensions the evolution of matrix structure during pyrolysis of a SiC-based preceramic polymer to 1200 °C. Observations are used to guide the development of a taxonomy of crack geometries and crack structures and to identify the temporal sequence of their formation. A quantitative analysis ismore » employed to characterize effects of local microstructural dimensions on the conditions required to form cracks of various types. Complementary measurements of gas evolution and mass loss of the preceramic polymer during pyrolysis as well as changes in mass density and Young's modulus provide context for the physical changes revealed by XCT. Furthermore, the findings provide a foundation for future development of physics-based models to guide composite fabrication processes.« less

High-Yield Growth and Characterization of ⟨100⟩ InP p-n Diode Nanowires.

PubMed

Cavalli, Alessandro; Wang, Jia; Esmaeil Zadeh, Iman; Reimer, Michael E; Verheijen, Marcel A; Soini, Martin; Plissard, Sebastien R; Zwiller, Val; Haverkort, Jos E M; Bakkers, Erik P A M

2016-05-11

Semiconductor nanowires are nanoscale structures holding promise in many fields such as optoelectronics, quantum computing, and thermoelectrics. Nanowires are usually grown vertically on (111)-oriented substrates, while (100) is the standard in semiconductor technology. The ability to grow and to control impurity doping of ⟨100⟩ nanowires is crucial for integration. Here, we discuss doping of single-crystalline ⟨100⟩ nanowires, and the structural and optoelectronic properties of p-n junctions based on ⟨100⟩ InP nanowires. We describe a novel approach to achieve low resistance electrical contacts to nanowires via a gradual interface based on p-doped InAsP. As a first demonstration in optoelectronic devices, we realize a single nanowire light emitting diode in a ⟨100⟩-oriented InP nanowire p-n junction. To obtain high vertical yield, which is necessary for future applications, we investigate the effect of the introduction of dopants on the nanowire growth.

Parallel computation of genome-scale RNA secondary structure to detect structural constraints on human genome.

PubMed

Kawaguchi, Risa; Kiryu, Hisanori

2016-05-06

RNA secondary structure around splice sites is known to assist normal splicing by promoting spliceosome recognition. However, analyzing the structural properties of entire intronic regions or pre-mRNA sequences has been difficult hitherto, owing to serious experimental and computational limitations, such as low read coverage and numerical problems. Our novel software, "ParasoR", is designed to run on a computer cluster and enables the exact computation of various structural features of long RNA sequences under the constraint of maximal base-pairing distance. ParasoR divides dynamic programming (DP) matrices into smaller pieces, such that each piece can be computed by a separate computer node without losing the connectivity information between the pieces. ParasoR directly computes the ratios of DP variables to avoid the reduction of numerical precision caused by the cancellation of a large number of Boltzmann factors. The structural preferences of mRNAs computed by ParasoR shows a high concordance with those determined by high-throughput sequencing analyses. Using ParasoR, we investigated the global structural preferences of transcribed regions in the human genome. A genome-wide folding simulation indicated that transcribed regions are significantly more structural than intergenic regions after removing repeat sequences and k-mer frequency bias. In particular, we observed a highly significant preference for base pairing over entire intronic regions as compared to their antisense sequences, as well as to intergenic regions. A comparison between pre-mRNAs and mRNAs showed that coding regions become more accessible after splicing, indicating constraints for translational efficiency. Such changes are correlated with gene expression levels, as well as GC content, and are enriched among genes associated with cytoskeleton and kinase functions. We have shown that ParasoR is very useful for analyzing the structural properties of long RNA sequences such as mRNAs, pre-mRNAs, and long non-coding RNAs whose lengths can be more than a million bases in the human genome. In our analyses, transcribed regions including introns are indicated to be subject to various types of structural constraints that cannot be explained from simple sequence composition biases. ParasoR is freely available at https://github.com/carushi/ParasoR .

Computational and Statistical Analyses of Amino Acid Usage and Physico-Chemical Properties of the Twelve Late Embryogenesis Abundant Protein Classes

PubMed Central

Jaspard, Emmanuel; Macherel, David; Hunault, Gilles

2012-01-01

Late Embryogenesis Abundant Proteins (LEAPs) are ubiquitous proteins expected to play major roles in desiccation tolerance. Little is known about their structure - function relationships because of the scarcity of 3-D structures for LEAPs. The previous building of LEAPdb, a database dedicated to LEAPs from plants and other organisms, led to the classification of 710 LEAPs into 12 non-overlapping classes with distinct properties. Using this resource, numerous physico-chemical properties of LEAPs and amino acid usage by LEAPs have been computed and statistically analyzed, revealing distinctive features for each class. This unprecedented analysis allowed a rigorous characterization of the 12 LEAP classes, which differed also in multiple structural and physico-chemical features. Although most LEAPs can be predicted as intrinsically disordered proteins, the analysis indicates that LEAP class 7 (PF03168) and probably LEAP class 11 (PF04927) are natively folded proteins. This study thus provides a detailed description of the structural properties of this protein family opening the path toward further LEAP structure - function analysis. Finally, since each LEAP class can be clearly characterized by a unique set of physico-chemical properties, this will allow development of software to predict proteins as LEAPs. PMID:22615859

GPU-accelerated computing for Lagrangian coherent structures of multi-body gravitational regimes

NASA Astrophysics Data System (ADS)

Lin, Mingpei; Xu, Ming; Fu, Xiaoyu

2017-04-01

Based on a well-established theoretical foundation, Lagrangian Coherent Structures (LCSs) have elicited widespread research on the intrinsic structures of dynamical systems in many fields, including the field of astrodynamics. Although the application of LCSs in dynamical problems seems straightforward theoretically, its associated computational cost is prohibitive. We propose a block decomposition algorithm developed on Compute Unified Device Architecture (CUDA) platform for the computation of the LCSs of multi-body gravitational regimes. In order to take advantage of GPU's outstanding computing properties, such as Shared Memory, Constant Memory, and Zero-Copy, the algorithm utilizes a block decomposition strategy to facilitate computation of finite-time Lyapunov exponent (FTLE) fields of arbitrary size and timespan. Simulation results demonstrate that this GPU-based algorithm can satisfy double-precision accuracy requirements and greatly decrease the time needed to calculate final results, increasing speed by approximately 13 times. Additionally, this algorithm can be generalized to various large-scale computing problems, such as particle filters, constellation design, and Monte-Carlo simulation.

Impact of geometrical properties on permeability and fluid phase distribution in porous media

NASA Astrophysics Data System (ADS)

Lehmann, P.; Berchtold, M.; Ahrenholz, B.; Tölke, J.; Kaestner, A.; Krafczyk, M.; Flühler, H.; Künsch, H. R.

2008-09-01

To predict fluid phase distribution in porous media, the effect of geometric properties on flow processes must be understood. In this study, we analyze the effect of volume, surface, curvature and connectivity (the four Minkowski functionals) on the hydraulic conductivity and the water retention curve. For that purpose, we generated 12 artificial structures with 800 3 voxels (the units of a 3D image) and compared them with a scanned sand sample of the same size. The structures were generated with a Boolean model based on a random distribution of overlapping ellipsoids whose size and shape were chosen to fulfill the criteria of the measured functionals. The pore structure of sand material was mapped with X-rays from synchrotrons. To analyze the effect of geometry on water flow and fluid distribution we carried out three types of analysis: Firstly, we computed geometrical properties like chord length, distance from the solids, pore size distribution and the Minkowski functionals as a function of pore size. Secondly, the fluid phase distribution as a function of the applied pressure was calculated with a morphological pore network model. Thirdly, the permeability was determined using a state-of-the-art lattice-Boltzmann method. For the simulated structure with the true Minkowski functionals the pores were larger and the computed air-entry value of the artificial medium was reduced to 85% of the value obtained from the scanned sample. The computed permeability for the geometry with the four fitted Minkowski functionals was equal to the permeability of the scanned image. The permeability was much more sensitive to the volume and surface than to curvature and connectivity of the medium. We conclude that the Minkowski functionals are not sufficient to characterize the geometrical properties of a porous structure that are relevant for the distribution of two fluid phases. Depending on the procedure to generate artificial structures with predefined Minkowski functionals, structures differing in pore size distribution can be obtained.

Chemical graphs, molecular matrices and topological indices in chemoinformatics and quantitative structure-activity relationships.

PubMed

Ivanciuc, Ovidiu

2013-06-01

Chemical and molecular graphs have fundamental applications in chemoinformatics, quantitative structureproperty relationships (QSPR), quantitative structure-activity relationships (QSAR), virtual screening of chemical libraries, and computational drug design. Chemoinformatics applications of graphs include chemical structure representation and coding, database search and retrieval, and physicochemical property prediction. QSPR, QSAR and virtual screening are based on the structure-property principle, which states that the physicochemical and biological properties of chemical compounds can be predicted from their chemical structure. Such structure-property correlations are usually developed from topological indices and fingerprints computed from the molecular graph and from molecular descriptors computed from the three-dimensional chemical structure. We present here a selection of the most important graph descriptors and topological indices, including molecular matrices, graph spectra, spectral moments, graph polynomials, and vertex topological indices. These graph descriptors are used to define several topological indices based on molecular connectivity, graph distance, reciprocal distance, distance-degree, distance-valency, spectra, polynomials, and information theory concepts. The molecular descriptors and topological indices can be developed with a more general approach, based on molecular graph operators, which define a family of graph indices related by a common formula. Graph descriptors and topological indices for molecules containing heteroatoms and multiple bonds are computed with weighting schemes based on atomic properties, such as the atomic number, covalent radius, or electronegativity. The correlation in QSPR and QSAR models can be improved by optimizing some parameters in the formula of topological indices, as demonstrated for structural descriptors based on atomic connectivity and graph distance.

Hierarchical nonlinear behavior of hot composite structures

NASA Technical Reports Server (NTRS)

Murthy, P. L. N.; Chamis, C. C.; Singhal, S. N.

1993-01-01

Hierarchical computational procedures are described to simulate the multiple scale thermal/mechanical behavior of high temperature metal matrix composites (HT-MMC) in the following three broad areas: (1) behavior of HT-MMC's from micromechanics to laminate via METCAN (Metal Matrix Composite Analyzer), (2) tailoring of HT-MMC behavior for optimum specific performance via MMLT (Metal Matrix Laminate Tailoring), and (3) HT-MMC structural response for hot structural components via HITCAN (High Temperature Composite Analyzer). Representative results from each area are presented to illustrate the effectiveness of computational simulation procedures and accompanying computer codes. The sample case results show that METCAN can be used to simulate material behavior such as the entire creep span; MMLT can be used to concurrently tailor the fabrication process and the interphase layer for optimum performance such as minimum residual stresses; and HITCAN can be used to predict the structural behavior such as the deformed shape due to component fabrication. These codes constitute virtual portable desk-top test laboratories for characterizing HT-MMC laminates, tailoring the fabrication process, and qualifying structural components made from them.

Synthesis, spectroscopy and computational studies of some biologically important hydroxyhaloquinolines and their novel derivatives

NASA Astrophysics Data System (ADS)

Malecki, Grzegorz; Nycz, Jacek E.; Ryrych, Ewa; Ponikiewski, Lukasz; Nowak, Maria; Kusz, Joachim; Pikies, Jerzy

2010-04-01

A series crystalline compounds of methyl and phosphinyl derivatives of 2-methylquinolin-8-ol ( 1a) and related 5,7-dichloro-2-methylquinolin-8-ol ( 1b) were quantitatively prepared and characterized by microanalysis, IR, UV-vis and multinuclear NMR spectroscopy. Five of them have been characterized by single crystal X-ray diffraction method. The known compounds, 8-methoxy-2-methylquinoline ( 2a) and 8-methoxyquinoline ( 2d), were synthesised by a new route. NMR solution spectra at ambient temperature, showed readily diagnostic H-1 and C-13 signals from methyl groups. The geometries of the studied compounds were optimized in singlet states using the density functional theory (DFT) method with B3LYP functional. In general, the predicted bond lengths and angles are in a good agreement with the values based on the X-ray crystal structure data. Electronic spectra were calculated by TDDFT method.

The mouse cortico-striatal projectome

PubMed Central

Hintiryan, Houri; Foster, Nicholas N.; Bowman, Ian; Bay, Maxwell; Song, Monica Y.; Gou, Lin; Yamashita, Seita; Bienkowski, Michael S.; Zingg, Brian; Zhu, Muye; Yang, X. William; Shih, Jean C.; Toga, Arthur W.; Dong, Hong-Wei

2017-01-01

Different cortical areas are organized into distinct intra-cortical subnetworks. How descending pathways from the entire cortex interact subcortically as a network remains unclear. Here, we report an open-access comprehensive mesoscale cortico-striatal projectome—a detailed connectivity projection map from the entire cerebral cortex to the dorsal striatum or caudoputamen (CP) in rodents. Based on these projections, we use novel computational neuroanatomical tools to identify 29 distinct functional striatal domains. Further, we characterize different cortico-striatal networks and how they reconfigure across the rostral-caudal extent of the CP. The workflow was also applied to select cortico-striatal connections in two different mouse models of disconnection syndromes to demonstrate its utility in characterizing circuitry-specific connectopathies. Together, this work provides the structural basis for studying the functional diversity of the dorsal striatum and disruptions of cortico-basal ganglia networks across a broad range of disorders. PMID:27322419

Analytic studies of local-severe-storm observables by satellites

NASA Technical Reports Server (NTRS)

Dergarabedian, P.; Fendell, F.

1977-01-01

Attention is concentrated on the exceptionally violet whirlwind, often characterized by a fairly vertical axis of rotation. For a cylindrical polar coordinate system with axis coincident with the axis of rotation, the secondary flow involves the radial and axial velocity components. The thesis advanced is, first, that a violent whirlwind is characterized by swirl speeds relative to the axis of rotation on the order of 90 m/s, with 100 m/s being close to an upper bound. This estimate is based on interpretation of funnel-cloud shape (which also suggests properties of the radial profile of swirl, as well as the maximum magnitude); an error assessment of the funnel-cloud interpretation procedure is developed. Second, computation of ground-level pressure deficits achievable from typical tornado-spawning ambients by idealized thermohydrostatic processes suggests that a two-cell structure is required to sustain such large speeds.

Using quantum process tomography to characterize decoherence in an analog electronic device

NASA Astrophysics Data System (ADS)

Ostrove, Corey; La Cour, Brian; Lanham, Andrew; Ott, Granville

The mathematical structure of a universal gate-based quantum computer can be emulated faithfully on a classical electronic device using analog signals to represent a multi-qubit state. We describe a prototype device capable of performing a programmable sequence of single-qubit and controlled two-qubit gate operations on a pair of voltage signals representing the real and imaginary parts of a two-qubit quantum state. Analog filters and true-RMS voltage measurements are used to perform unitary and measurement gate operations. We characterize the degradation of the represented quantum state with successive gate operations by formally performing quantum process tomography to estimate the equivalent decoherence channel. Experimental measurements indicate that the performance of the device may be accurately modeled as an equivalent quantum operation closely resembling a depolarizing channel with a fidelity of over 99%. This work was supported by the Office of Naval Research under Grant No. N00014-14-1-0323.

Flexibility and rigidity of cross-linked Straight Fibrils under axial motion constraints.

PubMed

Nagy Kem, Gyula

2016-09-01

The Straight Fibrils are stiff rod-like filaments and play a significant role in cellular processes as structural stability and intracellular transport. Introducing a 3D mechanical model for the motion of braced cylindrical fibrils under axial motion constraint; we provide some mechanism and a graph theoretical model for fibril structures and give the characterization of the flexibility and the rigidity of this bar-and-joint spatial framework. The connectedness and the circuit of the bracing graph characterize the flexibility of these structures. In this paper, we focus on the kinematical properties of hierarchical levels of fibrils and evaluate the number of the bracing elements for the rigidity and its computational complexity. The presented model is a good characterization of the frameworks of bio-fibrils such as microtubules, cellulose, which inspired this work. Copyright © 2016 Elsevier Ltd. All rights reserved.

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences

PubMed Central

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns. PMID:26147887

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences.

PubMed

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.

Media effects in modulating the conformational equilibrium of a model compound for tumor necrosis factor converting enzyme inhibition

NASA Astrophysics Data System (ADS)

Banchelli, Martina; Guardiani, Carlo; Sandberg, Robert B.; Menichetti, Stefano; Procacci, Piero; Caminati, Gabriella

2015-07-01

Small-molecule inhibitors of Tumor Necrosis Factor α Converting Enzyme (TACE) are a promising therapeutic tool for Rheumatoid Arthritis, Multiple Sclerosis and other autoimmune diseases. Here we report on an extensive chemical-physical analysis of the media effects in modulating the conformational landscape of MBET306, the common scaffold and a synthetic precursor of a family of recently discovered tartrate-based TACE inhibitors. The structural features of this molecule with potential pharmaceutical applications have been disclosed by interpreting extensive photophysical measurements in various solvents with the aid of enhanced sampling molecular dynamics simulations and time dependent density functional calculations. Using a combination of experimental and computational techniques, the paper provides a general protocol for studying the structure in solution of molecular systems characterized by the existence of conformational metastable states.

Computational design and multivariate optimization of an electrochemical metoprolol sensor based on molecular imprinting in combination with carbon nanotubes.

PubMed

Nezhadali, Azizollah; Mojarrab, Maliheh

2016-06-14

This work describes the development of an electrochemical sensor based on a new molecularly imprinted polymer for detection of metoprolol (MTP) at ultra-trace level. The polypyrrole (PPy) was electrochemically synthesized on the tip of a pencil graphite electrode (PGE) which modified whit functionalized multi-walled carbon nanotubes (MWCNTs). The fabrication process of the sensor was characterized by cyclic voltammetry (CV) and the measurement process was carried out by differential pulse voltammetry (DPV). A computational approach was used to screening functional monomers and polymerization solvent for rational design of molecularly imprinted polymer (MIP). Based on computational results, pyrrole and water were selected as functional monomer and polymerization solvent, respectively. Several significant parameters controlling the performance of the MIP sensor were examined and optimized using multivariate optimization methods such as Plackett-Burman design (PBD) and central composite design (CCD). Under the selected optimal conditions, MIP sensor was showed a linear range from 0.06 to 490 μmol L(-1) MTP, a limit of detection of 2.88 nmol L(-1), a highly reproducible response (RSD 3.9%) and a good selectivity in the presence of structurally related molecules. Furthermore, the applicability of the method was successfully tested with determination of MTP in real samples (tablet, and serum). Copyright © 2016 Elsevier B.V. All rights reserved.

Parameters Free Computational Characterization of Defects in Transition Metal Oxides with Diffusion Quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Santana, Juan A.; Krogel, Jaron T.; Kent, Paul R.; Reboredo, Fernando

Materials based on transition metal oxides (TMO's) are among the most challenging systems for computational characterization. Reliable and practical computations are possible by directly solving the many-body problem for TMO's with quantum Monte Carlo (QMC) methods. These methods are very computationally intensive, but recent developments in algorithms and computational infrastructures have enabled their application to real materials. We will show our efforts on the application of the diffusion quantum Monte Carlo (DMC) method to study the formation of defects in binary and ternary TMO and heterostructures of TMO. We will also outline current limitations in hardware and algorithms. This work is supported by the Materials Sciences & Engineering Division of the Office of Basic Energy Sciences, U.S. Department of Energy (DOE).

Thai Language Sentence Similarity Computation Based on Syntactic Structure and Semantic Vector

NASA Astrophysics Data System (ADS)

Wang, Hongbin; Feng, Yinhan; Cheng, Liang

2018-03-01

Sentence similarity computation plays an increasingly important role in text mining, Web page retrieval, machine translation, speech recognition and question answering systems. Thai language as a kind of resources scarce language, it is not like Chinese language with HowNet and CiLin resources. So the Thai sentence similarity research faces some challenges. In order to solve this problem of the Thai language sentence similarity computation. This paper proposes a novel method to compute the similarity of Thai language sentence based on syntactic structure and semantic vector. This method firstly uses the Part-of-Speech (POS) dependency to calculate two sentences syntactic structure similarity, and then through the word vector to calculate two sentences semantic similarity. Finally, we combine the two methods to calculate two Thai language sentences similarity. The proposed method not only considers semantic, but also considers the sentence syntactic structure. The experiment result shows that this method in Thai language sentence similarity computation is feasible.

An optimal transportation approach for nuclear structure-based pathology.

PubMed

Wang, Wei; Ozolek, John A; Slepčev, Dejan; Lee, Ann B; Chen, Cheng; Rohde, Gustavo K

2011-03-01

Nuclear morphology and structure as visualized from histopathology microscopy images can yield important diagnostic clues in some benign and malignant tissue lesions. Precise quantitative information about nuclear structure and morphology, however, is currently not available for many diagnostic challenges. This is due, in part, to the lack of methods to quantify these differences from image data. We describe a method to characterize and contrast the distribution of nuclear structure in different tissue classes (normal, benign, cancer, etc.). The approach is based on quantifying chromatin morphology in different groups of cells using the optimal transportation (Kantorovich-Wasserstein) metric in combination with the Fisher discriminant analysis and multidimensional scaling techniques. We show that the optimal transportation metric is able to measure relevant biological information as it enables automatic determination of the class (e.g., normal versus cancer) of a set of nuclei. We show that the classification accuracies obtained using this metric are, on average, as good or better than those obtained utilizing a set of previously described numerical features. We apply our methods to two diagnostic challenges for surgical pathology: one in the liver and one in the thyroid. Results automatically computed using this technique show potentially biologically relevant differences in nuclear structure in liver and thyroid cancers.

An optimal transportation approach for nuclear structure-based pathology

PubMed Central

Wang, Wei; Ozolek, John A.; Slepčev, Dejan; Lee, Ann B.; Chen, Cheng; Rohde, Gustavo K.

2012-01-01

Nuclear morphology and structure as visualized from histopathology microscopy images can yield important diagnostic clues in some benign and malignant tissue lesions. Precise quantitative information about nuclear structure and morphology, however, is currently not available for many diagnostic challenges. This is due, in part, to the lack of methods to quantify these differences from image data. We describe a method to characterize and contrast the distribution of nuclear structure in different tissue classes (normal, benign, cancer, etc.). The approach is based on quantifying chromatin morphology in different groups of cells using the optimal transportation (Kantorovich-Wasserstein) metric in combination with the Fisher discriminant analysis and multidimensional scaling techniques. We show that the optimal transportation metric is able to measure relevant biological information as it enables automatic determination of the class (e.g. normal vs. cancer) of a set of nuclei. We show that the classification accuracies obtained using this metric are, on average, as good or better than those obtained utilizing a set of previously described numerical features. We apply our methods to two diagnostic challenges for surgical pathology: one in the liver and one in the thyroid. Results automatically computed using this technique show potentially biologically relevant differences in nuclear structure in liver and thyroid cancers. PMID:20977984

Large Eddy Simulation of "turbulent-like" flow in intracranial aneurysms

NASA Astrophysics Data System (ADS)

Khan, Muhammad Owais; Chnafa, Christophe; Steinman, David A.; Mendez, Simon; Nicoud, Franck

2016-11-01

Hemodynamic forces are thought to contribute to pathogenesis and rupture of intracranial aneurysms (IA). Recent high-resolution patient-specific computational fluid dynamics (CFD) simulations have highlighted the presence of "turbulent-like" flow features, characterized by transient high-frequency flow instabilities. In-vitro studies have shown that such "turbulent-like" flows can lead to lack of endothelial cell orientation and cell depletion, and thus, may also have relevance to IA rupture risk assessment. From a modelling perspective, previous studies have relied on DNS to resolve the small-scale structures in these flows. While accurate, DNS is clinically infeasible due to high computational cost and long simulation times. In this study, we present the applicability of LES for IAs using a LES/blood flow dedicated solver (YALES2BIO) and compare against respective DNS. As a qualitative analysis, we compute time-averaged WSS and OSI maps, as well as, novel frequency-based WSS indices. As a quantitative analysis, we show the differences in POD eigenspectra for LES vs. DNS and wavelet analysis of intra-saccular velocity traces. Differences in two SGS models (i.e. Dynamic Smagorinsky vs. Sigma) are also compared against DNS, and computational gains of LES are discussed.

Sortase Transpeptidases: Structural Biology and Catalytic Mechanism

PubMed Central

Jacobitz, Alex W.; Kattke, Michele D.; Wereszczynski, Jeff; Clubb, Robert T.

2017-01-01

Gram-positive bacteria use sortase cysteine transpeptidase enzymes to covalently attach proteins to their cell wall and to assemble pili. In pathogenic bacteria sortases are potential drug targets, as many of the proteins that they display on the microbial surface play key roles in the infection process. Moreover, the Staphylococcus aureus Sortase A (SaSrtA) enzyme has been developed into a valuable biochemical reagent because of its ability to ligate biomolecules together in vitro via a covalent peptide bond. Here we review what is known about the structures and catalytic mechanism of sortase enzymes. Based on their primary sequences, most sortase homologs can be classified into six distinct subfamilies, called class A–F enzymes. Atomic structures reveal unique, class-specific variations that support alternate substrate specificities, while structures of sortase enzymes bound to sorting signal mimics shed light onto the molecular basis of substrate recognition. The results of computational studies are reviewed that provide insight into how key reaction intermediates are stabilized during catalysis, as well as the mechanism and dynamics of substrate recognition. Lastly, the reported in vitro activities of sortases are compared, revealing that the transpeptidation activity of SaSrtA is at least 20-fold faster than other sortases that have thus far been characterized. Together, the results of the structural, computational, and biochemical studies discussed in this review begin to reveal how sortases decorate the microbial surface with proteins and pili, and may facilitate ongoing efforts to discover therapeutically useful small molecule inhibitors. PMID:28683919

Acid–base catalysis over perovskites: a review

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

Polo-Garzon, Felipe; Wu, Zili

We present that perovskite catalysts have been extensively studied for reduction–oxidation (redox) reactions; however, their acid–base catalytic properties are still under-explored. This review collects work aiming to study the acid–base catalytic properties of perovskites. Reports regarding combined acid–base/redox catalysis over perovskites lie beyond the scope of the present review. For the characterization of acid–base properties, researchers have studied the interaction of probe molecules with perovskite surfaces by means of multiple techniques that provide information about the density, strength and type of adsorption sites. The top-surface composition of perovskites, which relates to the abundance of the acid–base sites, has been studiedmore » by means of low energy ion scattering (LEIS), and, the less surface sensitive, conventional X-ray photoelectron spectroscopy (XPS). Probe reactions, with the conversion of 2-propanol as the common choice, have also been employed for characterizing the acid–base catalytic properties of perovskites. The complex nature of perovskite surfaces, which explains the still absent fundamental relations between the structure of the catalyst and reaction rates/selectivity, encounters a great challenge due to the surface reconstruction of these materials. In this review, we devote a special section to highlight recent publications that report the impact of surface reconstruction and particle shape on acid–base catalysis over perovskites. In addition, we review promising catalytic performances of perovskite catalysts for other reactions of interest. Challenges in acid–base catalysis over perovskites focus on the development of time-resolved monolayer-sensitive characterization of surfaces under operando conditions and the discernment of combined acid–base/redox reaction mechanisms. Finally, opportunities lay on tuning the acid–base characteristics of perovskites with computation-based catalytic descriptors to achieve desired selectivities and enhanced rates.« less

Acid–base catalysis over perovskites: a review

DOE PAGES

Polo-Garzon, Felipe; Wu, Zili

2018-01-15

We present that perovskite catalysts have been extensively studied for reduction–oxidation (redox) reactions; however, their acid–base catalytic properties are still under-explored. This review collects work aiming to study the acid–base catalytic properties of perovskites. Reports regarding combined acid–base/redox catalysis over perovskites lie beyond the scope of the present review. For the characterization of acid–base properties, researchers have studied the interaction of probe molecules with perovskite surfaces by means of multiple techniques that provide information about the density, strength and type of adsorption sites. The top-surface composition of perovskites, which relates to the abundance of the acid–base sites, has been studiedmore » by means of low energy ion scattering (LEIS), and, the less surface sensitive, conventional X-ray photoelectron spectroscopy (XPS). Probe reactions, with the conversion of 2-propanol as the common choice, have also been employed for characterizing the acid–base catalytic properties of perovskites. The complex nature of perovskite surfaces, which explains the still absent fundamental relations between the structure of the catalyst and reaction rates/selectivity, encounters a great challenge due to the surface reconstruction of these materials. In this review, we devote a special section to highlight recent publications that report the impact of surface reconstruction and particle shape on acid–base catalysis over perovskites. In addition, we review promising catalytic performances of perovskite catalysts for other reactions of interest. Challenges in acid–base catalysis over perovskites focus on the development of time-resolved monolayer-sensitive characterization of surfaces under operando conditions and the discernment of combined acid–base/redox reaction mechanisms. Finally, opportunities lay on tuning the acid–base characteristics of perovskites with computation-based catalytic descriptors to achieve desired selectivities and enhanced rates.« less

Damage mapping in structural health monitoring using a multi-grid architecture

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

Mathews, V. John

2015-03-31

This paper presents a multi-grid architecture for tomography-based damage mapping of composite aerospace structures. The system employs an array of piezo-electric transducers bonded on the structure. Each transducer may be used as an actuator as well as a sensor. The structure is excited sequentially using the actuators and the guided waves arriving at the sensors in response to the excitations are recorded for further analysis. The sensor signals are compared to their baseline counterparts and a damage index is computed for each actuator-sensor pair. These damage indices are then used as inputs to the tomographic reconstruction system. Preliminary damage mapsmore » are reconstructed on multiple coordinate grids defined on the structure. These grids are shifted versions of each other where the shift is a fraction of the spatial sampling interval associated with each grid. These preliminary damage maps are then combined to provide a reconstruction that is more robust to measurement noise in the sensor signals and the ill-conditioned problem formulation for single-grid algorithms. Experimental results on a composite structure with complexity that is representative of aerospace structures included in the paper demonstrate that for sufficiently high sensor densities, the algorithm of this paper is capable of providing damage detection and characterization with accuracy comparable to traditional C-scan and A-scan-based ultrasound non-destructive inspection systems quickly and without human supervision.« less

The unfolding effects on the protein hydration shell and partial molar volume: a computational study.

PubMed

Del Galdo, Sara; Amadei, Andrea

2016-10-12

In this paper we apply the computational analysis recently proposed by our group to characterize the solvation properties of a native protein in aqueous solution, and to four model aqueous solutions of globular proteins in their unfolded states thus characterizing the protein unfolded state hydration shell and quantitatively evaluating the protein unfolded state partial molar volumes. Moreover, by using both the native and unfolded protein partial molar volumes, we obtain the corresponding variations (unfolding partial molar volumes) to be compared with the available experimental estimates. We also reconstruct the temperature and pressure dependence of the unfolding partial molar volume of Myoglobin dissecting the structural and hydration effects involved in the process.

Computer Aided Drug Design: Success and Limitations.

PubMed

Baig, Mohammad Hassan; Ahmad, Khurshid; Roy, Sudeep; Ashraf, Jalaluddin Mohammad; Adil, Mohd; Siddiqui, Mohammad Haris; Khan, Saif; Kamal, Mohammad Amjad; Provazník, Ivo; Choi, Inho

2016-01-01

Over the last few decades, computer-aided drug design has emerged as a powerful technique playing a crucial role in the development of new drug molecules. Structure-based drug design and ligand-based drug design are two methods commonly used in computer-aided drug design. In this article, we discuss the theory behind both methods, as well as their successful applications and limitations. To accomplish this, we reviewed structure based and ligand based virtual screening processes. Molecular dynamics simulation, which has become one of the most influential tool for prediction of the conformation of small molecules and changes in their conformation within the biological target, has also been taken into account. Finally, we discuss the principles and concepts of molecular docking, pharmacophores and other methods used in computer-aided drug design.

Computational approaches for drug discovery.

PubMed

Hung, Che-Lun; Chen, Chi-Chun

2014-09-01

Cellular proteins are the mediators of multiple organism functions being involved in physiological mechanisms and disease. By discovering lead compounds that affect the function of target proteins, the target diseases or physiological mechanisms can be modulated. Based on knowledge of the ligand-receptor interaction, the chemical structures of leads can be modified to improve efficacy, selectivity and reduce side effects. One rational drug design technology, which enables drug discovery based on knowledge of target structures, functional properties and mechanisms, is computer-aided drug design (CADD). The application of CADD can be cost-effective using experiments to compare predicted and actual drug activity, the results from which can used iteratively to improve compound properties. The two major CADD-based approaches are structure-based drug design, where protein structures are required, and ligand-based drug design, where ligand and ligand activities can be used to design compounds interacting with the protein structure. Approaches in structure-based drug design include docking, de novo design, fragment-based drug discovery and structure-based pharmacophore modeling. Approaches in ligand-based drug design include quantitative structure-affinity relationship and pharmacophore modeling based on ligand properties. Based on whether the structure of the receptor and its interaction with the ligand are known, different design strategies can be seed. After lead compounds are generated, the rule of five can be used to assess whether these have drug-like properties. Several quality validation methods, such as cost function analysis, Fisher's cross-validation analysis and goodness of hit test, can be used to estimate the metrics of different drug design strategies. To further improve CADD performance, multi-computers and graphics processing units may be applied to reduce costs. © 2014 Wiley Periodicals, Inc.

Employing a Structured Interface to Advance Primary Students' Communicative Competence in a Text-Based Computer Mediated Environment

ERIC Educational Resources Information Center

Chiu, Chiung-Hui; Wu, Chiu-Yi; Hsieh, Sheng-Jieh; Cheng, Hsiao-Wei; Huang, Chung-Kai

2013-01-01

This study investigated whether a structured communication interface fosters primary students' communicative competence in a synchronous typewritten computer-mediated collaborative learning environment. The structured interface provided a set of predetermined utterance patterns for elementary students to use or imitate to develop communicative…

High performance transcription factor-DNA docking with GPU computing

PubMed Central

2012-01-01

Background Protein-DNA docking is a very challenging problem in structural bioinformatics and has important implications in a number of applications, such as structure-based prediction of transcription factor binding sites and rational drug design. Protein-DNA docking is very computational demanding due to the high cost of energy calculation and the statistical nature of conformational sampling algorithms. More importantly, experiments show that the docking quality depends on the coverage of the conformational sampling space. It is therefore desirable to accelerate the computation of the docking algorithm, not only to reduce computing time, but also to improve docking quality. Methods In an attempt to accelerate the sampling process and to improve the docking performance, we developed a graphics processing unit (GPU)-based protein-DNA docking algorithm. The algorithm employs a potential-based energy function to describe the binding affinity of a protein-DNA pair, and integrates Monte-Carlo simulation and a simulated annealing method to search through the conformational space. Algorithmic techniques were developed to improve the computation efficiency and scalability on GPU-based high performance computing systems. Results The effectiveness of our approach is tested on a non-redundant set of 75 TF-DNA complexes and a newly developed TF-DNA docking benchmark. We demonstrated that the GPU-based docking algorithm can significantly accelerate the simulation process and thereby improving the chance of finding near-native TF-DNA complex structures. This study also suggests that further improvement in protein-DNA docking research would require efforts from two integral aspects: improvement in computation efficiency and energy function design. Conclusions We present a high performance computing approach for improving the prediction accuracy of protein-DNA docking. The GPU-based docking algorithm accelerates the search of the conformational space and thus increases the chance of finding more near-native structures. To the best of our knowledge, this is the first ad hoc effort of applying GPU or GPU clusters to the protein-DNA docking problem. PMID:22759575

Characterization and Measurement of Passive and Active Metamaterial Devices

DTIC Science & Technology

2010-03-01

A periodic bound- ary mirrors the computational domain along an axis. Unit cell boundary conditions mirror the computational domain along two axes... mirrored a number of times in each direction to create a square matrix of ring resonators. Figure 33(b) shows a 4× 4 array. The frequency domain...created by mirroring the previous structure three times. Thus, the dimensions of the particles are identical. The same boundary conditions and spacing

Structural brain aberrations associated with the dissociative subtype of post-traumatic stress disorder.

PubMed

Daniels, J K; Frewen, P; Theberge, J; Lanius, R A

2016-03-01

One factor potentially contributing to the heterogeneity of previous results on structural grey matter alterations in adult participants suffering from post-traumatic stress disorder (PTSD) is the varying levels of dissociative symptomatology. The aim of this study was therefore to test whether the recently defined dissociative subtype of PTSD characterized by symptoms of depersonalization and derealization is characterized by specific differences in volumetric brain morphology. Whole-brain MRI data were acquired for 59 patients with PTSD. Voxel-based morphometry was carried out to test for group differences between patients classified as belonging (n = 15) vs. not belonging (n = 44) to the dissociative subtype of PTSD. The correlation between dissociation (depersonalization/derealization) severity and grey matter volume was computed. Patients with PTSD classified as belonging to the dissociative subtype exhibited greater grey matter volume in the right precentral and fusiform gyri as well as less volume in the right inferior temporal gyrus. Greater dissociation severity was associated with greater volume in the right middle frontal gyrus. The results of this first whole-brain investigation of specific grey matter volume in dissociative subtype PTSD indentified structural aberrations in regions subserving the processing and regulation of emotional arousal. These might constitute characteristic biomarkers for the dissociative subtype PTSD. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Local numerical modelling of ultrasonic guided waves in linear and nonlinear media

NASA Astrophysics Data System (ADS)

Packo, Pawel; Radecki, Rafal; Kijanka, Piotr; Staszewski, Wieslaw J.; Uhl, Tadeusz; Leamy, Michael J.

2017-04-01

Nonlinear ultrasonic techniques provide improved damage sensitivity compared to linear approaches. The combination of attractive properties of guided waves, such as Lamb waves, with unique features of higher harmonic generation provides great potential for characterization of incipient damage, particularly in plate-like structures. Nonlinear ultrasonic structural health monitoring techniques use interrogation signals at frequencies other than the excitation frequency to detect changes in structural integrity. Signal processing techniques used in non-destructive evaluation are frequently supported by modeling and numerical simulations in order to facilitate problem solution. This paper discusses known and newly-developed local computational strategies for simulating elastic waves, and attempts characterization of their numerical properties in the context of linear and nonlinear media. A hybrid numerical approach combining advantages of the Local Interaction Simulation Approach (LISA) and Cellular Automata for Elastodynamics (CAFE) is proposed for unique treatment of arbitrary strain-stress relations. The iteration equations of the method are derived directly from physical principles employing stress and displacement continuity, leading to an accurate description of the propagation in arbitrarily complex media. Numerical analysis of guided wave propagation, based on the newly developed hybrid approach, is presented and discussed in the paper for linear and nonlinear media. Comparisons to Finite Elements (FE) are also discussed.

Improving finite element results in modeling heart valve mechanics.

PubMed

Earl, Emily; Mohammadi, Hadi

2018-06-01

Finite element analysis is a well-established computational tool which can be used for the analysis of soft tissue mechanics. Due to the structural complexity of the leaflet tissue of the heart valve, the currently available finite element models do not adequately represent the leaflet tissue. A method of addressing this issue is to implement computationally expensive finite element models, characterized by precise constitutive models including high-order and high-density mesh techniques. In this study, we introduce a novel numerical technique that enhances the results obtained from coarse mesh finite element models to provide accuracy comparable to that of fine mesh finite element models while maintaining a relatively low computational cost. Introduced in this study is a method by which the computational expense required to solve linear and nonlinear constitutive models, commonly used in heart valve mechanics simulations, is reduced while continuing to account for large and infinitesimal deformations. This continuum model is developed based on the least square algorithm procedure coupled with the finite difference method adhering to the assumption that the components of the strain tensor are available at all nodes of the finite element mesh model. The suggested numerical technique is easy to implement, practically efficient, and requires less computational time compared to currently available commercial finite element packages such as ANSYS and/or ABAQUS.

An experimental-computational platform for investigating microbial interactions and dynamics in communities with two codependent species

NASA Astrophysics Data System (ADS)

Fuentes-Cabrera, Miguel; Anderson, John D.; Wilmoth, Jared; Ginovart, Marta; Prats, Clara; Portell-Canal, Xavier; Retterer, Scott

Microbial interactions are critical for governing community behavior and structure in natural environments. Examination of microbial interactions in the lab involves growth under ideal conditions in batch culture; conditions that occur in nature are, however, characterized by disequilibrium. Of particular interest is the role that system variables play in shaping cell-to-cell interactions and organization at ultrafine spatial scales. We seek to use experiments and agent-based modeling to help discover mechanisms relevant to microbial dynamics and interactions in the environment. Currently, we are using an agent-based model to simulate microbial growth, dynamics and interactions that occur on a microwell-array device developed in our lab. Bacterial cells growing in the microwells of this platform can be studied with high-throughput and high-content image analyses using brightfield and fluorescence microscopy. The agent-based model is written in the language Netlogo, which in turn is ''plugged into'' a computational framework that allows submitting many calculations in parallel for different initial parameters; visualizing the outcomes in an interactive phase-like diagram; and searching, with a genetic algorithm, for the parameters that lead to the most optimal simulation outcome.

Mass spectrometry for the biophysical characterization of therapeutic monoclonal antibodies.

PubMed

Zhang, Hao; Cui, Weidong; Gross, Michael L

2014-01-21

Monoclonal antibodies (mAbs) are powerful therapeutics, and their characterization has drawn considerable attention and urgency. Unlike small-molecule drugs (150-600 Da) that have rigid structures, mAbs (∼150 kDa) are engineered proteins that undergo complicated folding and can exist in a number of low-energy structures, posing a challenge for traditional methods in structural biology. Mass spectrometry (MS)-based biophysical characterization approaches can provide structural information, bringing high sensitivity, fast turnaround, and small sample consumption. This review outlines various MS-based strategies for protein biophysical characterization and then reviews how these strategies provide structural information of mAbs at the protein level (intact or top-down approaches), peptide, and residue level (bottom-up approaches), affording information on higher order structure, aggregation, and the nature of antibody complexes. Copyright © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

"Group IV Nanomembranes, Nanoribbons, and Quantum Dots: Processing, Characterization, and Novel Devices"

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

liu, feng

This theoretical project has been carried out in close interaction with the experimental project at UW-Madison under the same title led by PI Max Lagally and co-PI Mark Eriksson. Extensive computational studies have been performed to address a broad range of topics from atomic structure, stability, mechanical property, to electronic structure, optoelectronic and transport properties of various nanoarchitectures in the context of Si and other solid nanomembranes. These have been done by using combinations of different theoretical and computational approaches, ranging from first-principles calculations and molecular dynamics (MD) simulations to finite-element (FE) analyses and continuum modeling.

Well-characterized sequence features of eukaryote genomes and implications for ab initio gene prediction.

PubMed

Huang, Ying; Chen, Shi-Yi; Deng, Feilong

2016-01-01

In silico analysis of DNA sequences is an important area of computational biology in the post-genomic era. Over the past two decades, computational approaches for ab initio prediction of gene structure from genome sequence alone have largely facilitated our understanding on a variety of biological questions. Although the computational prediction of protein-coding genes has already been well-established, we are also facing challenges to robustly find the non-coding RNA genes, such as miRNA and lncRNA. Two main aspects of ab initio gene prediction include the computed values for describing sequence features and used algorithm for training the discriminant function, and by which different combinations are employed into various bioinformatic tools. Herein, we briefly review these well-characterized sequence features in eukaryote genomes and applications to ab initio gene prediction. The main purpose of this article is to provide an overview to beginners who aim to develop the related bioinformatic tools.

Image-based models of cardiac structure in health and disease

PubMed Central

Vadakkumpadan, Fijoy; Arevalo, Hermenegild; Prassl, Anton J.; Chen, Junjie; Kickinger, Ferdinand; Kohl, Peter; Plank, Gernot; Trayanova, Natalia

2010-01-01

Computational approaches to investigating the electromechanics of healthy and diseased hearts are becoming essential for the comprehensive understanding of cardiac function. In this article, we first present a brief review of existing image-based computational models of cardiac structure. We then provide a detailed explanation of a processing pipeline which we have recently developed for constructing realistic computational models of the heart from high resolution structural and diffusion tensor (DT) magnetic resonance (MR) images acquired ex vivo. The presentation of the pipeline incorporates a review of the methodologies that can be used to reconstruct models of cardiac structure. In this pipeline, the structural image is segmented to reconstruct the ventricles, normal myocardium, and infarct. A finite element mesh is generated from the segmented structural image, and fiber orientations are assigned to the elements based on DTMR data. The methods were applied to construct seven different models of healthy and diseased hearts. These models contain millions of elements, with spatial resolutions in the order of hundreds of microns, providing unprecedented detail in the representation of cardiac structure for simulation studies. PMID:20582162

Mapping the Conformation Space of Wildtype and Mutant H-Ras with a Memetic, Cellular, and Multiscale Evolutionary Algorithm

PubMed Central

Clausen, Rudy; Ma, Buyong; Nussinov, Ruth; Shehu, Amarda

2015-01-01

An important goal in molecular biology is to understand functional changes upon single-point mutations in proteins. Doing so through a detailed characterization of structure spaces and underlying energy landscapes is desirable but continues to challenge methods based on Molecular Dynamics. In this paper we propose a novel algorithm, SIfTER, which is based instead on stochastic optimization to circumvent the computational challenge of exploring the breadth of a protein’s structure space. SIfTER is a data-driven evolutionary algorithm, leveraging experimentally-available structures of wildtype and variant sequences of a protein to define a reduced search space from where to efficiently draw samples corresponding to novel structures not directly observed in the wet laboratory. The main advantage of SIfTER is its ability to rapidly generate conformational ensembles, thus allowing mapping and juxtaposing landscapes of variant sequences and relating observed differences to functional changes. We apply SIfTER to variant sequences of the H-Ras catalytic domain, due to the prominent role of the Ras protein in signaling pathways that control cell proliferation, its well-studied conformational switching, and abundance of documented mutations in several human tumors. Many Ras mutations are oncogenic, but detailed energy landscapes have not been reported until now. Analysis of SIfTER-computed energy landscapes for the wildtype and two oncogenic variants, G12V and Q61L, suggests that these mutations cause constitutive activation through two different mechanisms. G12V directly affects binding specificity while leaving the energy landscape largely unchanged, whereas Q61L has pronounced, starker effects on the landscape. An implementation of SIfTER is made available at http://www.cs.gmu.edu/~ashehu/?q=OurTools. We believe SIfTER is useful to the community to answer the question of how sequence mutations affect the function of a protein, when there is an abundance of experimental structures that can be exploited to reconstruct an energy landscape that would be computationally impractical to do via Molecular Dynamics. PMID:26325505

Computational approaches for de novo design and redesign of metal-binding sites on proteins.

PubMed

Akcapinar, Gunseli Bayram; Sezerman, Osman Ugur

2017-04-28

Metal ions play pivotal roles in protein structure, function and stability. The functional and structural diversity of proteins in nature expanded with the incorporation of metal ions or clusters in proteins. Approximately one-third of these proteins in the databases contain metal ions. Many biological and chemical processes in nature involve metal ion-binding proteins, aka metalloproteins. Many cellular reactions that underpin life require metalloproteins. Most of the remarkable, complex chemical transformations are catalysed by metalloenzymes. Realization of the importance of metal-binding sites in a variety of cellular events led to the advancement of various computational methods for their prediction and characterization. Furthermore, as structural and functional knowledgebase about metalloproteins is expanding with advances in computational and experimental fields, the focus of the research is now shifting towards de novo design and redesign of metalloproteins to extend nature's own diversity beyond its limits. In this review, we will focus on the computational toolbox for prediction of metal ion-binding sites, de novo metalloprotein design and redesign. We will also give examples of tailor-made artificial metalloproteins designed with the computational toolbox. © 2017 The Author(s).

Influence of sample preparation on the transformation of low-density to high-density amorphous ice: An explanation based on the potential energy landscape

NASA Astrophysics Data System (ADS)

Giovambattista, Nicolas; Starr, Francis W.; Poole, Peter H.

2017-07-01

Experiments and computer simulations of the transformations of amorphous ices display different behaviors depending on sample preparation methods and on the rates of change of temperature and pressure to which samples are subjected. In addition to these factors, simulation results also depend strongly on the chosen water model. Using computer simulations of the ST2 water model, we study how the sharpness of the compression-induced transition from low-density amorphous ice (LDA) to high-density amorphous ice (HDA) is influenced by the preparation of LDA. By studying LDA samples prepared using widely different procedures, we find that the sharpness of the LDA-to-HDA transformation is correlated with the depth of the initial LDA sample in the potential energy landscape (PEL), as characterized by the inherent structure energy. Our results show that the complex phenomenology of the amorphous ices reported in experiments and computer simulations can be understood and predicted in a unified way from knowledge of the PEL of the system.

SUPIN: A Computational Tool for Supersonic Inlet Design

NASA Technical Reports Server (NTRS)

Slater, John W.

2016-01-01

A computational tool named SUPIN is being developed to design and analyze the aerodynamic performance of supersonic inlets. The inlet types available include the axisymmetric pitot, three-dimensional pitot, axisymmetric outward-turning, two-dimensional single-duct, two-dimensional bifurcated-duct, and streamline-traced inlets. The aerodynamic performance is characterized by the flow rates, total pressure recovery, and drag. The inlet flow-field is divided into parts to provide a framework for the geometry and aerodynamic modeling. Each part of the inlet is defined in terms of geometric factors. The low-fidelity aerodynamic analysis and design methods are based on analytic, empirical, and numerical methods which provide for quick design and analysis. SUPIN provides inlet geometry in the form of coordinates, surface angles, and cross-sectional areas. SUPIN can generate inlet surface grids and three-dimensional, structured volume grids for use with higher-fidelity computational fluid dynamics (CFD) analysis. Capabilities highlighted in this paper include the design and analysis of streamline-traced external-compression inlets, modeling of porous bleed, and the design and analysis of mixed-compression inlets. CFD analyses are used to verify the SUPIN results.

Transcriptome profile of a bovine respiratory disease pathogen: Mannheimia haemolytica PHL213

PubMed Central

2012-01-01

Background Computational methods for structural gene annotation have propelled gene discovery but face certain drawbacks with regards to prokaryotic genome annotation. Identification of transcriptional start sites, demarcating overlapping gene boundaries, and identifying regulatory elements such as small RNA are not accurate using these approaches. In this study, we re-visit the structural annotation of Mannheimia haemolytica PHL213, a bovine respiratory disease pathogen. M. haemolytica is one of the causative agents of bovine respiratory disease that results in about $3 billion annual losses to the cattle industry. We used RNA-Seq and analyzed the data using freely-available computational methods and resources. The aim was to identify previously unannotated regions of the genome using RNA-Seq based expression profile to complement the existing annotation of this pathogen. Results Using the Illumina Genome Analyzer, we generated 9,055,826 reads (average length ~76 bp) and aligned them to the reference genome using Bowtie. The transcribed regions were analyzed using SAMTOOLS and custom Perl scripts in conjunction with BLAST searches and available gene annotation information. The single nucleotide resolution map enabled the identification of 14 novel protein coding regions as well as 44 potential novel sRNA. The basal transcription profile revealed that 2,506 of the 2,837 annotated regions were expressed in vitro, at 95.25% coverage, representing all broad functional gene categories in the genome. The expression profile also helped identify 518 potential operon structures involving 1,086 co-expressed pairs. We also identified 11 proteins with mutated/alternate start codons. Conclusions The application of RNA-Seq based transcriptome profiling to structural gene annotation helped correct existing annotation errors and identify potential novel protein coding regions and sRNA. We used computational tools to predict regulatory elements such as promoters and terminators associated with the novel expressed regions for further characterization of these novel functional elements. Our study complements the existing structural annotation of Mannheimia haemolytica PHL213 based on experimental evidence. Given the role of sRNA in virulence gene regulation and stress response, potential novel sRNA described in this study can form the framework for future studies to determine the role of sRNA, if any, in M. haemolytica pathogenesis. PMID:23046475

Computational Redesign of Thioredoxin Is Hypersensitive toward Minor Conformational Changes in the Backbone Template

PubMed Central

Christensen, Signe; Horowitz, Scott; Bardwell, James C.A.; Olsen, Johan G.; Willemoës, Martin; Lindorff-Larsen, Kresten; Ferkinghoff-Borg, Jesper; Hamelryck, Thomas; Winther, Jakob R.

2017-01-01

Despite the development of powerful computational tools, the full-sequence design of proteins still remains a challenging task. To investigate the limits and capabilities of computational tools, we conducted a study of the ability of the program Rosetta to predict sequences that recreate the authentic fold of thioredoxin. Focusing on the influence of conformational details in the template structures, we based our study on 8 experimentally determined template structures and generated 120 designs from each. For experimental evaluation, we chose six sequences from each of the eight templates by objective criteria. The 48 selected sequences were evaluated based on their progressive ability to (1) produce soluble protein in Escherichia coli and (2) yield stable monomeric protein, and (3) on the ability of the stable, soluble proteins to adopt the target fold. Of the 48 designs, we were able to synthesize 32, 20 of which resulted in soluble protein. Of these, only two were sufficiently stable to be purified. An X-ray crystal structure was solved for one of the designs, revealing a close resemblance to the target structure. We found a significant difference among the eight template structures to realize the above three criteria despite their high structural similarity. Thus, in order to improve the success rate of computational full-sequence design methods, we recommend that multiple template structures are used. Furthermore, this study shows that special care should be taken when optimizing the geometry of a structure prior to computational design when using a method that is based on rigid conformations. PMID:27659562

Computational Redesign of Thioredoxin Is Hypersensitive toward Minor Conformational Changes in the Backbone Template.

PubMed

Johansson, Kristoffer E; Tidemand Johansen, Nicolai; Christensen, Signe; Horowitz, Scott; Bardwell, James C A; Olsen, Johan G; Willemoës, Martin; Lindorff-Larsen, Kresten; Ferkinghoff-Borg, Jesper; Hamelryck, Thomas; Winther, Jakob R

2016-10-23

Despite the development of powerful computational tools, the full-sequence design of proteins still remains a challenging task. To investigate the limits and capabilities of computational tools, we conducted a study of the ability of the program Rosetta to predict sequences that recreate the authentic fold of thioredoxin. Focusing on the influence of conformational details in the template structures, we based our study on 8 experimentally determined template structures and generated 120 designs from each. For experimental evaluation, we chose six sequences from each of the eight templates by objective criteria. The 48 selected sequences were evaluated based on their progressive ability to (1) produce soluble protein in Escherichia coli and (2) yield stable monomeric protein, and (3) on the ability of the stable, soluble proteins to adopt the target fold. Of the 48 designs, we were able to synthesize 32, 20 of which resulted in soluble protein. Of these, only two were sufficiently stable to be purified. An X-ray crystal structure was solved for one of the designs, revealing a close resemblance to the target structure. We found a significant difference among the eight template structures to realize the above three criteria despite their high structural similarity. Thus, in order to improve the success rate of computational full-sequence design methods, we recommend that multiple template structures are used. Furthermore, this study shows that special care should be taken when optimizing the geometry of a structure prior to computational design when using a method that is based on rigid conformations. Copyright © 2016 Elsevier Ltd. All rights reserved.

A new taxonomy for distributed computer systems based upon operating system structure

NASA Technical Reports Server (NTRS)

Foudriat, E. C.

1985-01-01

Characteristics of the resource structure found in the operating system are considered as a mechanism for classifying distributed computer systems. Since the operating system resources, themselves, are too diversified to provide a consistent classification, the structure upon which resources are built and shared are examined. The location and control character of this indivisibility provides the taxonomy for separating uniprocessors, computer networks, network computers (fully distributed processing systems or decentralized computers) and algorithm and/or data control multiprocessors. The taxonomy is important because it divides machines into a classification that is relevant or important to the client and not the hardware architect. It also defines the character of the kernel O/S structure needed for future computer systems. What constitutes an operating system for a fully distributed processor is discussed in detail.

Theoretical modeling of multiprotein complexes by iSPOT: Integration of small-angle X-ray scattering, hydroxyl radical footprinting, and computational docking.

PubMed

Huang, Wei; Ravikumar, Krishnakumar M; Parisien, Marc; Yang, Sichun

2016-12-01

Structural determination of protein-protein complexes such as multidomain nuclear receptors has been challenging for high-resolution structural techniques. Here, we present a combined use of multiple biophysical methods, termed iSPOT, an integration of shape information from small-angle X-ray scattering (SAXS), protection factors probed by hydroxyl radical footprinting, and a large series of computationally docked conformations from rigid-body or molecular dynamics (MD) simulations. Specifically tested on two model systems, the power of iSPOT is demonstrated to accurately predict the structures of a large protein-protein complex (TGFβ-FKBP12) and a multidomain nuclear receptor homodimer (HNF-4α), based on the structures of individual components of the complexes. Although neither SAXS nor footprinting alone can yield an unambiguous picture for each complex, the combination of both, seamlessly integrated in iSPOT, narrows down the best-fit structures that are about 3.2Å and 4.2Å in RMSD from their corresponding crystal structures, respectively. Furthermore, this proof-of-principle study based on the data synthetically derived from available crystal structures shows that the iSPOT-using either rigid-body or MD-based flexible docking-is capable of overcoming the shortcomings of standalone computational methods, especially for HNF-4α. By taking advantage of the integration of SAXS-based shape information and footprinting-based protection/accessibility as well as computational docking, this iSPOT platform is set to be a powerful approach towards accurate integrated modeling of many challenging multiprotein complexes. Copyright © 2016 Elsevier Inc. All rights reserved.

Characterization of N-Glycan Structures on the Surface of Mature Dengue 2 Virus Derived from Insect Cells.

PubMed

Lei, Y; Yu, H; Dong, Y; Yang, J; Ye, W; Wang, Y; Chen, W; Jia, Z; Xu, Z; Li, Z; Zhang, F

2015-01-01

DENV envelope glycoprotein (E) is responsible for interacting with host cell receptors and is the main target for the development of a dengue vaccine based on an induction of neutralizing antibodies. It is well known that DENV E glycoprotein has two potential N-linked glycosylation sites at Asn67 and Asn153. The N-glycans of E glycoprotein have been shown to influence the proper folding of the protein, its cellular localization, its interactions with receptors and its immunogenicity. However, the precise structures of the N-glycans that are attached to E glycoprotein remain elusive, although the crystal structure of DENV E has been determined. This study characterized the structures of envelope protein N-linked glycans on mature DENV-2 particles derived from insect cells via an integrated method that used both lectin microarray and MALDI-TOF-MS. By combining these methods, a high heterogeneity of DENV N-glycans was found. Five types of N-glycan were identified on DENV-2, including mannose, GalNAc, GlcNAc, fucose and sialic acid; high mannose-type N-linked oligosaccharides and the galactosylation of N-glycans were the major structures that were found. Furthermore, a complex between a glycan on DENV and the carbohydrate recognition domain (CRD) of DC-SIGN was mimicked with computational docking experiments. For the first time, this study provides a comprehensive understanding of the N-linked glycan profile of whole DENV-2 particles derived from insect cells.

A Software Laboratory Environment for Computer-Based Problem Solving.

ERIC Educational Resources Information Center

Kurtz, Barry L.; O'Neal, Micheal B.

This paper describes a National Science Foundation-sponsored project at Louisiana Technological University to develop computer-based laboratories for "hands-on" introductions to major topics of computer science. The underlying strategy is to develop structured laboratory environments that present abstract concepts through the use of…

The Application of Web-based Computer-assisted Instruction Courseware within Health Assessment

NASA Astrophysics Data System (ADS)

Xiuyan, Guo

Health assessment is a clinical nursing course and places emphasis on clinical skills. The application of computer-assisted instruction in the field of nursing teaching solved the problems in the traditional lecture class. This article stated teaching experience of web-based computer-assisted instruction, based upon a two-year study of computer-assisted instruction courseware use within the course health assessment. The computer-assisted instruction courseware could develop teaching structure, simulate clinical situations, create teaching situations and facilitate students study.

A compositional approach to building applications in a computational environment

NASA Astrophysics Data System (ADS)

Roslovtsev, V. V.; Shumsky, L. D.; Wolfengagen, V. E.

2014-04-01

The paper presents an approach to creating an applicative computational environment to feature computational processes and data decomposition, and a compositional approach to application building. The approach in question is based on the notion of combinator - both in systems with variable binding (such as λ-calculi) and those allowing programming without variables (combinatory logic style). We present a computation decomposition technique based on objects' structural decomposition, with the focus on computation decomposition. The computational environment's architecture is based on a network with nodes playing several roles simultaneously.

ParallelStructure: A R Package to Distribute Parallel Runs of the Population Genetics Program STRUCTURE on Multi-Core Computers

PubMed Central

Besnier, Francois; Glover, Kevin A.

2013-01-01

This software package provides an R-based framework to make use of multi-core computers when running analyses in the population genetics program STRUCTURE. It is especially addressed to those users of STRUCTURE dealing with numerous and repeated data analyses, and who could take advantage of an efficient script to automatically distribute STRUCTURE jobs among multiple processors. It also consists of additional functions to divide analyses among combinations of populations within a single data set without the need to manually produce multiple projects, as it is currently the case in STRUCTURE. The package consists of two main functions: MPI_structure() and parallel_structure() as well as an example data file. We compared the performance in computing time for this example data on two computer architectures and showed that the use of the present functions can result in several-fold improvements in terms of computation time. ParallelStructure is freely available at https://r-forge.r-project.org/projects/parallstructure/. PMID:23923012

Inference and Analysis of Population Structure Using Genetic Data and Network Theory

PubMed Central

Greenbaum, Gili; Templeton, Alan R.; Bar-David, Shirli

2016-01-01

Clustering individuals to subpopulations based on genetic data has become commonplace in many genetic studies. Inference about population structure is most often done by applying model-based approaches, aided by visualization using distance-based approaches such as multidimensional scaling. While existing distance-based approaches suffer from a lack of statistical rigor, model-based approaches entail assumptions of prior conditions such as that the subpopulations are at Hardy-Weinberg equilibria. Here we present a distance-based approach for inference about population structure using genetic data by defining population structure using network theory terminology and methods. A network is constructed from a pairwise genetic-similarity matrix of all sampled individuals. The community partition, a partition of a network to dense subgraphs, is equated with population structure, a partition of the population to genetically related groups. Community-detection algorithms are used to partition the network into communities, interpreted as a partition of the population to subpopulations. The statistical significance of the structure can be estimated by using permutation tests to evaluate the significance of the partition’s modularity, a network theory measure indicating the quality of community partitions. To further characterize population structure, a new measure of the strength of association (SA) for an individual to its assigned community is presented. The strength of association distribution (SAD) of the communities is analyzed to provide additional population structure characteristics, such as the relative amount of gene flow experienced by the different subpopulations and identification of hybrid individuals. Human genetic data and simulations are used to demonstrate the applicability of the analyses. The approach presented here provides a novel, computationally efficient model-free method for inference about population structure that does not entail assumption of prior conditions. The method is implemented in the software NetStruct (available at https://giligreenbaum.wordpress.com/software/). PMID:26888080

Inference and Analysis of Population Structure Using Genetic Data and Network Theory.

PubMed

Greenbaum, Gili; Templeton, Alan R; Bar-David, Shirli

2016-04-01

Clustering individuals to subpopulations based on genetic data has become commonplace in many genetic studies. Inference about population structure is most often done by applying model-based approaches, aided by visualization using distance-based approaches such as multidimensional scaling. While existing distance-based approaches suffer from a lack of statistical rigor, model-based approaches entail assumptions of prior conditions such as that the subpopulations are at Hardy-Weinberg equilibria. Here we present a distance-based approach for inference about population structure using genetic data by defining population structure using network theory terminology and methods. A network is constructed from a pairwise genetic-similarity matrix of all sampled individuals. The community partition, a partition of a network to dense subgraphs, is equated with population structure, a partition of the population to genetically related groups. Community-detection algorithms are used to partition the network into communities, interpreted as a partition of the population to subpopulations. The statistical significance of the structure can be estimated by using permutation tests to evaluate the significance of the partition's modularity, a network theory measure indicating the quality of community partitions. To further characterize population structure, a new measure of the strength of association (SA) for an individual to its assigned community is presented. The strength of association distribution (SAD) of the communities is analyzed to provide additional population structure characteristics, such as the relative amount of gene flow experienced by the different subpopulations and identification of hybrid individuals. Human genetic data and simulations are used to demonstrate the applicability of the analyses. The approach presented here provides a novel, computationally efficient model-free method for inference about population structure that does not entail assumption of prior conditions. The method is implemented in the software NetStruct (available at https://giligreenbaum.wordpress.com/software/). Copyright © 2016 by the Genetics Society of America.

A web-based system for neural network based classification in temporomandibular joint osteoarthritis.

PubMed

de Dumast, Priscille; Mirabel, Clément; Cevidanes, Lucia; Ruellas, Antonio; Yatabe, Marilia; Ioshida, Marcos; Ribera, Nina Tubau; Michoud, Loic; Gomes, Liliane; Huang, Chao; Zhu, Hongtu; Muniz, Luciana; Shoukri, Brandon; Paniagua, Beatriz; Styner, Martin; Pieper, Steve; Budin, Francois; Vimort, Jean-Baptiste; Pascal, Laura; Prieto, Juan Carlos

2018-07-01

The purpose of this study is to describe the methodological innovations of a web-based system for storage, integration and computation of biomedical data, using a training imaging dataset to remotely compute a deep neural network classifier of temporomandibular joint osteoarthritis (TMJOA). This study imaging dataset consisted of three-dimensional (3D) surface meshes of mandibular condyles constructed from cone beam computed tomography (CBCT) scans. The training dataset consisted of 259 condyles, 105 from control subjects and 154 from patients with diagnosis of TMJ OA. For the image analysis classification, 34 right and left condyles from 17 patients (39.9 ± 11.7 years), who experienced signs and symptoms of the disease for less than 5 years, were included as the testing dataset. For the integrative statistical model of clinical, biological and imaging markers, the sample consisted of the same 17 test OA subjects and 17 age and sex matched control subjects (39.4 ± 15.4 years), who did not show any sign or symptom of OA. For these 34 subjects, a standardized clinical questionnaire, blood and saliva samples were also collected. The technological methodologies in this study include a deep neural network classifier of 3D condylar morphology (ShapeVariationAnalyzer, SVA), and a flexible web-based system for data storage, computation and integration (DSCI) of high dimensional imaging, clinical, and biological data. The DSCI system trained and tested the neural network, indicating 5 stages of structural degenerative changes in condylar morphology in the TMJ with 91% close agreement between the clinician consensus and the SVA classifier. The DSCI remotely ran with a novel application of a statistical analysis, the Multivariate Functional Shape Data Analysis, that computed high dimensional correlations between shape 3D coordinates, clinical pain levels and levels of biological markers, and then graphically displayed the computation results. The findings of this study demonstrate a comprehensive phenotypic characterization of TMJ health and disease at clinical, imaging and biological levels, using novel flexible and versatile open-source tools for a web-based system that provides advanced shape statistical analysis and a neural network based classification of temporomandibular joint osteoarthritis. Published by Elsevier Ltd.