Three-Dimensional Multiscale Modeling of Dendritic Spacing Selection During Al-Si Directional Solidification

NASA Astrophysics Data System (ADS)

Tourret, Damien; Clarke, Amy J.; Imhoff, Seth D.; Gibbs, Paul J.; Gibbs, John W.; Karma, Alain

2015-08-01

We present a three-dimensional extension of the multiscale dendritic needle network (DNN) model. This approach enables quantitative simulations of the unsteady dynamics of complex hierarchical networks in spatially extended dendritic arrays. We apply the model to directional solidification of Al-9.8 wt.%Si alloy and directly compare the model predictions with measurements from experiments with in situ x-ray imaging. We focus on the dynamical selection of primary spacings over a range of growth velocities, and the influence of sample geometry on the selection of spacings. Simulation results show good agreement with experiments. The computationally efficient DNN model opens new avenues for investigating the dynamics of large dendritic arrays at scales relevant to solidification experiments and processes.

Supramolecular architectures constructed by lanthanum, amino acids and 1,10-phenanthroline via non-covalent bond interactions

NASA Astrophysics Data System (ADS)

Zheng, Xiang-Jun; Jin, Lin-Pei

2003-07-01

Three supramolecular lanthanum coordination compounds of amino acids, with 1,10-phenanthroline (phen), [La 2(APA) 6(phen) 2(H 2O) 2](ClO 4) 6(phen) 4·2H 2O ( 1), [La 2(ABA) 6(phen) 2(H 2O) 2](ClO 4) 6 (phen) 6·4H 2O ( 2), and [La 2(AHA) 4(phen) 4](ClO 4) 6(phen) 4·2H 2O ( 3) (APA=3-aminopropionic acid; ABA=4-aminobutanoic acid; AHA=6-aminohexanoic acid) were synthesized and characterized by single crystal X-ray diffraction. The results show that the three coordination compounds are all composed of binuclear coordination cations built by metal-ligand coordination. Through hydrogen bonding and π-π stacking interactions, complex 1 forms a two-dimensional supramolecular sheet structure extending in the (001) plane, complex 2 forms a three-dimensional supramolecular network with many cavities occupied by ClO 4- and lattice H 2O molecules, and complex 3 forms a two-dimensional supramolecular lamellar structure in the (100) plane.

Complex network view of evolving manifolds

NASA Astrophysics Data System (ADS)

da Silva, Diamantino C.; Bianconi, Ginestra; da Costa, Rui A.; Dorogovtsev, Sergey N.; Mendes, José F. F.

2018-03-01

We study complex networks formed by triangulations and higher-dimensional simplicial complexes representing closed evolving manifolds. In particular, for triangulations, the set of possible transformations of these networks is restricted by the condition that at each step, all the faces must be triangles. Stochastic application of these operations leads to random networks with different architectures. We perform extensive numerical simulations and explore the geometries of growing and equilibrium complex networks generated by these transformations and their local structural properties. This characterization includes the Hausdorff and spectral dimensions of the resulting networks, their degree distributions, and various structural correlations. Our results reveal a rich zoo of architectures and geometries of these networks, some of which appear to be small worlds while others are finite dimensional with Hausdorff dimension equal or higher than the original dimensionality of their simplices. The range of spectral dimensions of the evolving triangulations turns out to be from about 1.4 to infinity. Our models include simplicial complexes representing manifolds with evolving topologies, for example, an h -holed torus with a progressively growing number of holes. This evolving graph demonstrates features of a small-world network and has a particularly heavy-tailed degree distribution.

Three-dimensional multiscale modeling of dendritic spacing selection during Al-Si directional solidification

DOE PAGES

Tourret, Damien; Clarke, Amy J.; Imhoff, Seth D.; ...

2015-05-27

We present a three-dimensional extension of the multiscale dendritic needle network (DNN) model. This approach enables quantitative simulations of the unsteady dynamics of complex hierarchical networks in spatially extended dendritic arrays. We apply the model to directional solidification of Al-9.8 wt.%Si alloy and directly compare the model predictions with measurements from experiments with in situ x-ray imaging. The focus is on the dynamical selection of primary spacings over a range of growth velocities, and the influence of sample geometry on the selection of spacings. Simulation results show good agreement with experiments. The computationally efficient DNN model opens new avenues formore » investigating the dynamics of large dendritic arrays at scales relevant to solidification experiments and processes.« less

Programmable disorder in random DNA tilings

NASA Astrophysics Data System (ADS)

Tikhomirov, Grigory; Petersen, Philip; Qian, Lulu

2017-03-01

Scaling up the complexity and diversity of synthetic molecular structures will require strategies that exploit the inherent stochasticity of molecular systems in a controlled fashion. Here we demonstrate a framework for programming random DNA tilings and show how to control the properties of global patterns through simple, local rules. We constructed three general forms of planar network—random loops, mazes and trees—on the surface of self-assembled DNA origami arrays on the micrometre scale with nanometre resolution. Using simple molecular building blocks and robust experimental conditions, we demonstrate control of a wide range of properties of the random networks, including the branching rules, the growth directions, the proximity between adjacent networks and the size distribution. Much as combinatorial approaches for generating random one-dimensional chains of polymers have been used to revolutionize chemical synthesis and the selection of functional nucleic acids, our strategy extends these principles to random two-dimensional networks of molecules and creates new opportunities for fabricating more complex molecular devices that are organized by DNA nanostructures.

TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions

PubMed Central

2017-01-01

Although deep learning approaches have had tremendous success in image, video and audio processing, computer vision, and speech recognition, their applications to three-dimensional (3D) biomolecular structural data sets have been hindered by the geometric and biological complexity. To address this problem we introduce the element-specific persistent homology (ESPH) method. ESPH represents 3D complex geometry by one-dimensional (1D) topological invariants and retains important biological information via a multichannel image-like representation. This representation reveals hidden structure-function relationships in biomolecules. We further integrate ESPH and deep convolutional neural networks to construct a multichannel topological neural network (TopologyNet) for the predictions of protein-ligand binding affinities and protein stability changes upon mutation. To overcome the deep learning limitations from small and noisy training sets, we propose a multi-task multichannel topological convolutional neural network (MM-TCNN). We demonstrate that TopologyNet outperforms the latest methods in the prediction of protein-ligand binding affinities, mutation induced globular protein folding free energy changes, and mutation induced membrane protein folding free energy changes. Availability: weilab.math.msu.edu/TDL/ PMID:28749969

The Virtual Pelvic Floor, a tele-immersive educational environment.

PubMed Central

Pearl, R. K.; Evenhouse, R.; Rasmussen, M.; Dech, F.; Silverstein, J. C.; Prokasy, S.; Panko, W. B.

1999-01-01

This paper describes the development of the Virtual Pelvic Floor, a new method of teaching the complex anatomy of the pelvic region utilizing virtual reality and advanced networking technology. Virtual reality technology allows improved visualization of three-dimensional structures over conventional media because it supports stereo vision, viewer-centered perspective, large angles of view, and interactivity. Two or more ImmersaDesk systems, drafting table format virtual reality displays, are networked together providing an environment where teacher and students share a high quality three-dimensional anatomical model, and are able to converse, see each other, and to point in three dimensions to indicate areas of interest. This project was realized by the teamwork of surgeons, medical artists and sculptors, computer scientists, and computer visualization experts. It demonstrates the future of virtual reality for surgical education and applications for the Next Generation Internet. Images Figure 1 Figure 2 Figure 3 PMID:10566378

What HR-CT imaging can teach us about xylem structure and function

USDA-ARS?s Scientific Manuscript database

It is well established that plant xylem is composed of a complex and interconnected system of vascular elements, but little is known about how the three-dimensional (3D) organization of this network influences properties such as plant hydraulics (Tyree & Zimmermann, 2002), and few studies have measu...

Starch-based aerogels: airy materials from amylose-sodium palmitate inclusion complexes

USDA-ARS?s Scientific Manuscript database

Aerogels are a class of interesting low density porous materials prepared by replacing the water phase contained within a hydrogel with a gas phase while maintaining the three dimensional network structure of the gel. The investigation of starch and hydrocolloid-based aerogels has received attentio...

Microfluidic neurite guidance to study structure-function relationships in topologically-complex population-based neural networks.

PubMed

Honegger, Thibault; Thielen, Moritz I; Feizi, Soheil; Sanjana, Neville E; Voldman, Joel

2016-06-22

The central nervous system is a dense, layered, 3D interconnected network of populations of neurons, and thus recapitulating that complexity for in vitro CNS models requires methods that can create defined topologically-complex neuronal networks. Several three-dimensional patterning approaches have been developed but none have demonstrated the ability to control the connections between populations of neurons. Here we report a method using AC electrokinetic forces that can guide, accelerate, slow down and push up neurites in un-modified collagen scaffolds. We present a means to create in vitro neural networks of arbitrary complexity by using such forces to create 3D intersections of primary neuronal populations that are plated in a 2D plane. We report for the first time in vitro basic brain motifs that have been previously observed in vivo and show that their functional network is highly decorrelated to their structure. This platform can provide building blocks to reproduce in vitro the complexity of neural circuits and provide a minimalistic environment to study the structure-function relationship of the brain circuitry.

Microfluidic neurite guidance to study structure-function relationships in topologically-complex population-based neural networks

NASA Astrophysics Data System (ADS)

Honegger, Thibault; Thielen, Moritz I.; Feizi, Soheil; Sanjana, Neville E.; Voldman, Joel

2016-06-01

The central nervous system is a dense, layered, 3D interconnected network of populations of neurons, and thus recapitulating that complexity for in vitro CNS models requires methods that can create defined topologically-complex neuronal networks. Several three-dimensional patterning approaches have been developed but none have demonstrated the ability to control the connections between populations of neurons. Here we report a method using AC electrokinetic forces that can guide, accelerate, slow down and push up neurites in un-modified collagen scaffolds. We present a means to create in vitro neural networks of arbitrary complexity by using such forces to create 3D intersections of primary neuronal populations that are plated in a 2D plane. We report for the first time in vitro basic brain motifs that have been previously observed in vivo and show that their functional network is highly decorrelated to their structure. This platform can provide building blocks to reproduce in vitro the complexity of neural circuits and provide a minimalistic environment to study the structure-function relationship of the brain circuitry.

Ensemble Sensitivity Analysis of a Severe Downslope Windstorm in Complex Terrain: Implications for Forecast Predictability Scales and Targeted Observing Networks

DTIC Science & Technology

2013-09-01

wave breaking (NWB) and eight wave breaking (WB) storms are shown...studies, and it follows that the wind storm characteristics are likely more three dimensional as well. For the purposes of this study, a severe DSWS is...regularly using the HWAS network at USAFA since its installation in 2004. A careful examination of these events reveals downslope storms that are

Two three-dimensional coordination polymers of lead(II) with iminodiacetate and naphthalene-dicarboxylate anions: Synthesis, characterization and luminescence behavior

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

Hazari, Debdoot; Jana, Swapan Kumar; Fleck, Michel

2014-11-15

Two lead(II) compounds [Pb{sub 3}(idiac){sub 3}(phen){sub 2}(H{sub 2}O)]·2(H{sub 2}O) (1) and [Pb(ndc)]{sub n} (2), where H{sub 2}idiac=iminodiacetic acid, phen=1,10-phenanthroline and H{sub 2}ndc=naphthalene-2,6-dicarboxylic acid, have been synthesized and structurally characterized. Single crystal X-ray diffraction analysis showed that compound 1 is a discrete trinuclear complex (of two-fold symmetry) which evolves to a supramolecular 3D network via π–π interactions, while in compound 2 the naphthalene dicarboxylate anion act as a linker to form a three dimensional architecture, where the anion adopts a bis-(bidentate bridging) coordination mode connecting four Pb(II) centers. The photoluminescence property of the two complexes has been studied. - graphical abstract:more » Two new topologically different 1D coordination polymers formed by Pb{sub 4} clusters have been synthesized and characterized by x-ray analysis. The luminescence and thermal properties have been studied. - Highlights: • 1 is a trinuclear complex of Pb(II) growing to 3D network via weak interactions. • In 1, layers of (4,4) rhomboidal topology are identified. • In 2, the ndc anion adopts interesting bis-(bidentate bridging) coordination. • In 2, network is reinforced by C–H…π-ring interactions between the ndc rings.« less

Self-assembled three dimensional network designs for soft electronics

PubMed Central

Jang, Kyung-In; Li, Kan; Chung, Ha Uk; Xu, Sheng; Jung, Han Na; Yang, Yiyuan; Kwak, Jean Won; Jung, Han Hee; Song, Juwon; Yang, Ce; Wang, Ao; Liu, Zhuangjian; Lee, Jong Yoon; Kim, Bong Hoon; Kim, Jae-Hwan; Lee, Jungyup; Yu, Yongjoon; Kim, Bum Jun; Jang, Hokyung; Yu, Ki Jun; Kim, Jeonghyun; Lee, Jung Woo; Jeong, Jae-Woong; Song, Young Min; Huang, Yonggang; Zhang, Yihui; Rogers, John A.

2017-01-01

Low modulus, compliant systems of sensors, circuits and radios designed to intimately interface with the soft tissues of the human body are of growing interest, due to their emerging applications in continuous, clinical-quality health monitors and advanced, bioelectronic therapeutics. Although recent research establishes various materials and mechanics concepts for such technologies, all existing approaches involve simple, two-dimensional (2D) layouts in the constituent micro-components and interconnects. Here we introduce concepts in three-dimensional (3D) architectures that bypass important engineering constraints and performance limitations set by traditional, 2D designs. Specifically, open-mesh, 3D interconnect networks of helical microcoils formed by deterministic compressive buckling establish the basis for systems that can offer exceptional low modulus, elastic mechanics, in compact geometries, with active components and sophisticated levels of functionality. Coupled mechanical and electrical design approaches enable layout optimization, assembly processes and encapsulation schemes to yield 3D configurations that satisfy requirements in demanding, complex systems, such as wireless, skin-compatible electronic sensors. PMID:28635956

Self-assembled three dimensional network designs for soft electronics

NASA Astrophysics Data System (ADS)

Jang, Kyung-In; Li, Kan; Chung, Ha Uk; Xu, Sheng; Jung, Han Na; Yang, Yiyuan; Kwak, Jean Won; Jung, Han Hee; Song, Juwon; Yang, Ce; Wang, Ao; Liu, Zhuangjian; Lee, Jong Yoon; Kim, Bong Hoon; Kim, Jae-Hwan; Lee, Jungyup; Yu, Yongjoon; Kim, Bum Jun; Jang, Hokyung; Yu, Ki Jun; Kim, Jeonghyun; Lee, Jung Woo; Jeong, Jae-Woong; Song, Young Min; Huang, Yonggang; Zhang, Yihui; Rogers, John A.

2017-06-01

Low modulus, compliant systems of sensors, circuits and radios designed to intimately interface with the soft tissues of the human body are of growing interest, due to their emerging applications in continuous, clinical-quality health monitors and advanced, bioelectronic therapeutics. Although recent research establishes various materials and mechanics concepts for such technologies, all existing approaches involve simple, two-dimensional (2D) layouts in the constituent micro-components and interconnects. Here we introduce concepts in three-dimensional (3D) architectures that bypass important engineering constraints and performance limitations set by traditional, 2D designs. Specifically, open-mesh, 3D interconnect networks of helical microcoils formed by deterministic compressive buckling establish the basis for systems that can offer exceptional low modulus, elastic mechanics, in compact geometries, with active components and sophisticated levels of functionality. Coupled mechanical and electrical design approaches enable layout optimization, assembly processes and encapsulation schemes to yield 3D configurations that satisfy requirements in demanding, complex systems, such as wireless, skin-compatible electronic sensors.

Developing a Magnetic Resonance Imaging measurement of the forces within 3D granular materials under external loads

NASA Astrophysics Data System (ADS)

Elrington, Stefan; Bertrand, Thibault; Frey, Merideth; Shattuck, Mark; O'Hern, Corey; Barrett, Sean

2014-03-01

Granular materials are comprised of an ensemble of discrete macroscopic grains that interact with each other via highly dissipative forces. These materials are ubiquitous in our everyday life ranging in scale from the granular media that forms the Earth's crust to that used in agricultural and pharmaceutical industries. Granular materials exhibit complex behaviors that are poorly understood and cannot be easily described by statistical mechanics. Under external loads individual grains are jammed into place by a network of force chains. These networks have been imaged in quasi two-dimensional and on the outer surface of three-dimensional granular materials. Our goal is to use magnetic resonance imaging (MRI) to detect contact forces deep within three-dimensional granular materials, using hydrogen-1 relaxation times as a reporter for changes in local stress and strain. To this end, we use a novel pulse sequence to narrow the line width of hydrogen-1 in rubber. Here we present our progress to date, and prospects for future improvements.

High Sensitivity Gas Detection Using a Macroscopic Three-Dimensional Graphene Foam Network

PubMed Central

Yavari, Fazel; Chen, Zongping; Thomas, Abhay V.; Ren, Wencai; Cheng, Hui-Ming; Koratkar, Nikhil

2011-01-01

Nanostructures are known to be exquisitely sensitive to the chemical environment and offer ultra-high sensitivity for gas-sensing. However, the fabrication and operation of devices that use individual nanostructures for sensing is complex, expensive and suffers from poor reliability due to contamination and large variability from sample-to-sample. By contrast, conventional solid-state and conducting-polymer sensors offer excellent reliability but suffer from reduced sensitivity at room-temperature. Here we report a macro graphene foam-like three-dimensional network which combines the best of both worlds. The walls of the foam are comprised of few-layer graphene sheets resulting in high sensitivity; we demonstrate parts-per-million level detection of NH3 and NO2 in air at room-temperature. Further, the foam is a mechanically robust and flexible macro-scale network that is easy to contact (without Lithography) and can rival the durability and affordability of traditional sensors. Moreover, Joule-heating expels chemisorbed molecules from the foam's surface leading to fully-reversible and low-power operation. PMID:22355681

Interface between path and orbital angular momentum entanglement for high-dimensional photonic quantum information.

PubMed

Fickler, Robert; Lapkiewicz, Radek; Huber, Marcus; Lavery, Martin P J; Padgett, Miles J; Zeilinger, Anton

2014-07-30

Photonics has become a mature field of quantum information science, where integrated optical circuits offer a way to scale the complexity of the set-up as well as the dimensionality of the quantum state. On photonic chips, paths are the natural way to encode information. To distribute those high-dimensional quantum states over large distances, transverse spatial modes, like orbital angular momentum possessing Laguerre Gauss modes, are favourable as flying information carriers. Here we demonstrate a quantum interface between these two vibrant photonic fields. We create three-dimensional path entanglement between two photons in a nonlinear crystal and use a mode sorter as the quantum interface to transfer the entanglement to the orbital angular momentum degree of freedom. Thus our results show a flexible way to create high-dimensional spatial mode entanglement. Moreover, they pave the way to implement broad complex quantum networks where high-dimensionally entangled states could be distributed over distant photonic chips.

Music Signal Processing Using Vector Product Neural Networks

NASA Astrophysics Data System (ADS)

Fan, Z. C.; Chan, T. S.; Yang, Y. H.; Jang, J. S. R.

2017-05-01

We propose a novel neural network model for music signal processing using vector product neurons and dimensionality transformations. Here, the inputs are first mapped from real values into three-dimensional vectors then fed into a three-dimensional vector product neural network where the inputs, outputs, and weights are all three-dimensional values. Next, the final outputs are mapped back to the reals. Two methods for dimensionality transformation are proposed, one via context windows and the other via spectral coloring. Experimental results on the iKala dataset for blind singing voice separation confirm the efficacy of our model.

2-(hydroxymethyl)-1H-benzo[d]imidazole-5-carboxylic acid as linker for Co(II)/Ni(II)/Cu(II) coordination polymers: Synthesis, structures and properties

NASA Astrophysics Data System (ADS)

Wang, Duo-Zhi; Wang, Xin-Fang; Du, Jia-Qiang; Dong, Jun-Liang; Xie, Fei

2018-02-01

We report the synthesis and characterization of five transition metal coordination polymers (CPs) based on M(II) (M: Co, Ni and Cu), 2-(hydroxymethyl)-1H-benzo[d]imidazole-5-carboxylic acid (H2L) ligand. They are formulated as {[Co2(HL)2(H2O)3(SO4)]·H2O}n (1), {[Co2(HL)2(H2O)2]·SiF6}n (2), {[Ni2(HL)2(H2O)3(SO4)]·2H2O}n (3), {[Ni2(HL)2(H2O)4]·H2O·SiF6}n (4), {[Cu2(HL)2(H2O)2]·SiF6}n (5). The complexes 1-5 structure were characterized by single-crystal X-ray diffraction, elemental analyses, infrared spectroscopy (IR), powder X-ray diffraction (PXRD), and thermogravimetric analyses (TGA). Complexes 1-5 are two-dimensional (2D) network type coordination polymers that 1-3, 5 crystallize in monoclinic system within the centrosymmetric space group P2(1)/c, and 4 in triclinic system P-1 space group, they show the same coordination modes (κ1-κ1)-(κ1)-(κ1)-μ3 in coordination polymers. Complexes 1 and 3 expand to three-dimensional framework by means of hydrogen bond interactions, and can be rationalized to be three-connected {63} topological network, while 2, 4, 5 exhibit the topological network with a four-connected {44·62} topological sql network. The luminescent properties (for complexes 1, 2) and UV diffuse reflectance (for complexes 1-5) in the solid state at room temperature were also investigated and discussed. Complexes 1-5 act as effective heterogeneous catalysts, under mild conditions, for the homocoupling reaction of 4-substituted aryl iodides bearing electron-donating groups (-CH3, -OCH3).

A universal indicator of critical state transitions in noisy complex networked systems

PubMed Central

Liang, Junhao; Hu, Yanqing; Chen, Guanrong; Zhou, Tianshou

2017-01-01

Critical transition, a phenomenon that a system shifts suddenly from one state to another, occurs in many real-world complex networks. We propose an analytical framework for exactly predicting the critical transition in a complex networked system subjected to noise effects. Our prediction is based on the characteristic return time of a simple one-dimensional system derived from the original higher-dimensional system. This characteristic time, which can be easily calculated using network data, allows us to systematically separate the respective roles of dynamics, noise and topology of the underlying networked system. We find that the noise can either prevent or enhance critical transitions, playing a key role in compensating the network structural defect which suffers from either internal failures or environmental changes, or both. Our analysis of realistic or artificial examples reveals that the characteristic return time is an effective indicator for forecasting the sudden deterioration of complex networks. PMID:28230166

Discovering hidden relationships between renal diseases and regulated genes through 3D network visualizations

PubMed Central

2010-01-01

Background In a recent study, two-dimensional (2D) network layouts were used to visualize and quantitatively analyze the relationship between chronic renal diseases and regulated genes. The results revealed complex relationships between disease type, gene specificity, and gene regulation type, which led to important insights about the underlying biological pathways. Here we describe an attempt to extend our understanding of these complex relationships by reanalyzing the data using three-dimensional (3D) network layouts, displayed through 2D and 3D viewing methods. Findings The 3D network layout (displayed through the 3D viewing method) revealed that genes implicated in many diseases (non-specific genes) tended to be predominantly down-regulated, whereas genes regulated in a few diseases (disease-specific genes) tended to be up-regulated. This new global relationship was quantitatively validated through comparison to 1000 random permutations of networks of the same size and distribution. Our new finding appeared to be the result of using specific features of the 3D viewing method to analyze the 3D renal network. Conclusions The global relationship between gene regulation and gene specificity is the first clue from human studies that there exist common mechanisms across several renal diseases, which suggest hypotheses for the underlying mechanisms. Furthermore, the study suggests hypotheses for why the 3D visualization helped to make salient a new regularity that was difficult to detect in 2D. Future research that tests these hypotheses should enable a more systematic understanding of when and how to use 3D network visualizations to reveal complex regularities in biological networks. PMID:21070623

Flight control with adaptive critic neural network

NASA Astrophysics Data System (ADS)

Han, Dongchen

2001-10-01

In this dissertation, the adaptive critic neural network technique is applied to solve complex nonlinear system control problems. Based on dynamic programming, the adaptive critic neural network can embed the optimal solution into a neural network. Though trained off-line, the neural network forms a real-time feedback controller. Because of its general interpolation properties, the neurocontroller has inherit robustness. The problems solved here are an agile missile control for U.S. Air Force and a midcourse guidance law for U.S. Navy. In the first three papers, the neural network was used to control an air-to-air agile missile to implement a minimum-time heading-reverse in a vertical plane corresponding to following conditions: a system without constraint, a system with control inequality constraint, and a system with state inequality constraint. While the agile missile is a one-dimensional problem, the midcourse guidance law is the first test-bed for multiple-dimensional problem. In the fourth paper, the neurocontroller is synthesized to guide a surface-to-air missile to a fixed final condition, and to a flexible final condition from a variable initial condition. In order to evaluate the adaptive critic neural network approach, the numerical solutions for these cases are also obtained by solving two-point boundary value problem with a shooting method. All of the results showed that the adaptive critic neural network could solve complex nonlinear system control problems.

Two sodium and lanthanide(III) MOFs based on oxalate and V-shaped 4,4‧-oxybis(benzoate) ligands: Hydrothermal synthesis, crystal structure, and luminescence properties

NASA Astrophysics Data System (ADS)

Wang, Chongchen; Guo, Guangliang; Wang, Peng

2013-01-01

Two lanthanide based metal-organic frameworks, [NaLn(oba)(ox)(H2O)] (Lndbnd6 Eu(1) and Sm(2)) were obtained from 4,4'-oxybisbenzoic acid, sodium oxalate and corresponding lanthanide salts by hydrothermal synthesis. They were characterized by single-crystal X-ray diffraction, IR spectra, and photoluminescent spectra. The crystallographic data reveals that complexes 1 and 2 are isomorphous and isostructural, composed of three-dimensional framework built up of distorted tricapped trigonal EuO9 units, distorted octahedron NaO6 units, 4,4'-oxybis(benzoate) and oxalate. The carboxylate oxygen atoms of the 4,4'-oxybis(benzoate) and oxalate ligand are coordinated to lanthanide ions and sodium ions, resulting into two-dimensional inorganic sheets, which are further linked into three-dimensional network by organic ligands. Thermogravimetric analyses of 1-2 display a considerable thermal stability. Photoluminescent measurements indicated that europium complex 1 displayed strong red emission.

Automatic delineation and 3D visualization of the human ventricular system using probabilistic neural networks

NASA Astrophysics Data System (ADS)

Hatfield, Fraser N.; Dehmeshki, Jamshid

1998-09-01

Neurosurgery is an extremely specialized area of medical practice, requiring many years of training. It has been suggested that virtual reality models of the complex structures within the brain may aid in the training of neurosurgeons as well as playing an important role in the preparation for surgery. This paper focuses on the application of a probabilistic neural network to the automatic segmentation of the ventricles from magnetic resonance images of the brain, and their three dimensional visualization.

Assembly of micro/nanomaterials into complex, three-dimensional architectures by compressive buckling

NASA Astrophysics Data System (ADS)

Xu, Sheng; Yan, Zheng; Jang, Kyung-In; Huang, Wen; Fu, Haoran; Kim, Jeonghyun; Wei, Zijun; Flavin, Matthew; McCracken, Joselle; Wang, Renhan; Badea, Adina; Liu, Yuhao; Xiao, Dongqing; Zhou, Guoyan; Lee, Jungwoo; Chung, Ha Uk; Cheng, Huanyu; Ren, Wen; Banks, Anthony; Li, Xiuling; Paik, Ungyu; Nuzzo, Ralph G.; Huang, Yonggang; Zhang, Yihui; Rogers, John A.

2015-01-01

Complex three-dimensional (3D) structures in biology (e.g., cytoskeletal webs, neural circuits, and vasculature networks) form naturally to provide essential functions in even the most basic forms of life. Compelling opportunities exist for analogous 3D architectures in human-made devices, but design options are constrained by existing capabilities in materials growth and assembly. We report routes to previously inaccessible classes of 3D constructs in advanced materials, including device-grade silicon. The schemes involve geometric transformation of 2D micro/nanostructures into extended 3D layouts by compressive buckling. Demonstrations include experimental and theoretical studies of more than 40 representative geometries, from single and multiple helices, toroids, and conical spirals to structures that resemble spherical baskets, cuboid cages, starbursts, flowers, scaffolds, fences, and frameworks, each with single- and/or multiple-level configurations.

Network geometry with flavor: From complexity to quantum geometry

NASA Astrophysics Data System (ADS)

Bianconi, Ginestra; Rahmede, Christoph

2016-03-01

Network geometry is attracting increasing attention because it has a wide range of applications, ranging from data mining to routing protocols in the Internet. At the same time advances in the understanding of the geometrical properties of networks are essential for further progress in quantum gravity. In network geometry, simplicial complexes describing the interaction between two or more nodes play a special role. In fact these structures can be used to discretize a geometrical d -dimensional space, and for this reason they have already been widely used in quantum gravity. Here we introduce the network geometry with flavor s =-1 ,0 ,1 (NGF) describing simplicial complexes defined in arbitrary dimension d and evolving by a nonequilibrium dynamics. The NGF can generate discrete geometries of different natures, ranging from chains and higher-dimensional manifolds to scale-free networks with small-world properties, scale-free degree distribution, and nontrivial community structure. The NGF admits as limiting cases both the Bianconi-Barabási models for complex networks, the stochastic Apollonian network, and the recently introduced model for complex quantum network manifolds. The thermodynamic properties of NGF reveal that NGF obeys a generalized area law opening a new scenario for formulating its coarse-grained limit. The structure of NGF is strongly dependent on the dimensionality d . In d =1 NGFs grow complex networks for which the preferential attachment mechanism is necessary in order to obtain a scale-free degree distribution. Instead, for NGF with dimension d >1 it is not necessary to have an explicit preferential attachment rule to generate scale-free topologies. We also show that NGF admits a quantum mechanical description in terms of associated quantum network states. Quantum network states evolve by a Markovian dynamics and a quantum network state at time t encodes all possible NGF evolutions up to time t . Interestingly the NGF remains fully classical but its statistical properties reveal the relation to its quantum mechanical description. In fact the δ -dimensional faces of the NGF have generalized degrees that follow either the Fermi-Dirac, Boltzmann, or Bose-Einstein statistics depending on the flavor s and the dimensions d and δ .

Network geometry with flavor: From complexity to quantum geometry.

PubMed

Bianconi, Ginestra; Rahmede, Christoph

2016-03-01

Network geometry is attracting increasing attention because it has a wide range of applications, ranging from data mining to routing protocols in the Internet. At the same time advances in the understanding of the geometrical properties of networks are essential for further progress in quantum gravity. In network geometry, simplicial complexes describing the interaction between two or more nodes play a special role. In fact these structures can be used to discretize a geometrical d-dimensional space, and for this reason they have already been widely used in quantum gravity. Here we introduce the network geometry with flavor s=-1,0,1 (NGF) describing simplicial complexes defined in arbitrary dimension d and evolving by a nonequilibrium dynamics. The NGF can generate discrete geometries of different natures, ranging from chains and higher-dimensional manifolds to scale-free networks with small-world properties, scale-free degree distribution, and nontrivial community structure. The NGF admits as limiting cases both the Bianconi-Barabási models for complex networks, the stochastic Apollonian network, and the recently introduced model for complex quantum network manifolds. The thermodynamic properties of NGF reveal that NGF obeys a generalized area law opening a new scenario for formulating its coarse-grained limit. The structure of NGF is strongly dependent on the dimensionality d. In d=1 NGFs grow complex networks for which the preferential attachment mechanism is necessary in order to obtain a scale-free degree distribution. Instead, for NGF with dimension d>1 it is not necessary to have an explicit preferential attachment rule to generate scale-free topologies. We also show that NGF admits a quantum mechanical description in terms of associated quantum network states. Quantum network states evolve by a Markovian dynamics and a quantum network state at time t encodes all possible NGF evolutions up to time t. Interestingly the NGF remains fully classical but its statistical properties reveal the relation to its quantum mechanical description. In fact the δ-dimensional faces of the NGF have generalized degrees that follow either the Fermi-Dirac, Boltzmann, or Bose-Einstein statistics depending on the flavor s and the dimensions d and δ.

Three-dimensional Dendritic Needle Network model with application to Al-Cu directional solidification experiments

NASA Astrophysics Data System (ADS)

Tourret, D.; Karma, A.; Clarke, A. J.; Gibbs, P. J.; Imhoff, S. D.

2015-06-01

We present a three-dimensional (3D) extension of a previously proposed multi-scale Dendritic Needle Network (DNN) approach for the growth of complex dendritic microstructures. Using a new formulation of the DNN dynamics equations for dendritic paraboloid-branches of a given thickness, one can directly extend the DNN approach to 3D modeling. We validate this new formulation against known scaling laws and analytical solutions that describe the early transient and steady-state growth regimes, respectively. Finally, we compare the predictions of the model to in situ X-ray imaging of Al-Cu alloy solidification experiments. The comparison shows a very good quantitative agreement between 3D simulations and thin sample experiments. It also highlights the importance of full 3D modeling to accurately predict the primary dendrite arm spacing that is significantly over-estimated by 2D simulations.

Three-dimensional Dendritic Needle Network model with application to Al-Cu directional solidification experiments

DOE PAGES

Tourret, D.; Karma, A.; Clarke, A. J.; ...

2015-06-11

We present a three-dimensional (3D) extension of a previously proposed multi-scale Dendritic Needle Network (DNN) approach for the growth of complex dendritic microstructures. Using a new formulation of the DNN dynamics equations for dendritic paraboloid-branches of a given thickness, one can directly extend the DNN approach to 3D modeling. We validate this new formulation against known scaling laws and analytical solutions that describe the early transient and steady-state growth regimes, respectively. Finally, we compare the predictions of the model to in situ X-ray imaging of Al-Cu alloy solidification experiments. The comparison shows a very good quantitative agreement between 3D simulationsmore » and thin sample experiments. It also highlights the importance of full 3D modeling to accurately predict the primary dendrite arm spacing that is significantly over-estimated by 2D simulations.« less

An exploration of alternative visualisations of the basic helix-loop-helix protein interaction network

PubMed Central

Holden, Brian J; Pinney, John W; Lovell, Simon C; Amoutzias, Grigoris D; Robertson, David L

2007-01-01

Background Alternative representations of biochemical networks emphasise different aspects of the data and contribute to the understanding of complex biological systems. In this study we present a variety of automated methods for visualisation of a protein-protein interaction network, using the basic helix-loop-helix (bHLH) family of transcription factors as an example. Results Network representations that arrange nodes (proteins) according to either continuous or discrete information are investigated, revealing the existence of protein sub-families and the retention of interactions following gene duplication events. Methods of network visualisation in conjunction with a phylogenetic tree are presented, highlighting the evolutionary relationships between proteins, and clarifying the context of network hubs and interaction clusters. Finally, an optimisation technique is used to create a three-dimensional layout of the phylogenetic tree upon which the protein-protein interactions may be projected. Conclusion We show that by incorporating secondary genomic, functional or phylogenetic information into network visualisation, it is possible to move beyond simple layout algorithms based on network topology towards more biologically meaningful representations. These new visualisations can give structure to complex networks and will greatly help in interpreting their evolutionary origins and functional implications. Three open source software packages (InterView, TVi and OptiMage) implementing our methods are available. PMID:17683601

Manufacturing of three-dimensionally microstructured nanocomposites through microfluidic infiltration.

PubMed

Dermanaki-Farahani, Rouhollah; Lebel, Louis Laberge; Therriault, Daniel

2014-03-12

Microstructured composite beams reinforced with complex three-dimensionally (3D) patterned nanocomposite microfilaments are fabricated via nanocomposite infiltration of 3D interconnected microfluidic networks. The manufacturing of the reinforced beams begins with the fabrication of microfluidic networks, which involves layer-by-layer deposition of fugitive ink filaments using a dispensing robot, filling the empty space between filaments using a low viscosity resin, curing the resin and finally removing the ink. Self-supported 3D structures with other geometries and many layers (e.g. a few hundreds layers) could be built using this method. The resulting tubular microfluidic networks are then infiltrated with thermosetting nanocomposite suspensions containing nanofillers (e.g. single-walled carbon nanotubes), and subsequently cured. The infiltration is done by applying a pressure gradient between two ends of the empty network (either by applying a vacuum or vacuum-assisted microinjection). Prior to the infiltration, the nanocomposite suspensions are prepared by dispersing nanofillers into polymer matrices using ultrasonication and three-roll mixing methods. The nanocomposites (i.e. materials infiltrated) are then solidified under UV exposure/heat cure, resulting in a 3D-reinforced composite structure. The technique presented here enables the design of functional nanocomposite macroscopic products for microengineering applications such as actuators and sensors.

Manufacturing of Three-dimensionally Microstructured Nanocomposites through Microfluidic Infiltration

PubMed Central

Dermanaki-Farahani, Rouhollah; Lebel, Louis Laberge; Therriault, Daniel

2014-01-01

Microstructured composite beams reinforced with complex three-dimensionally (3D) patterned nanocomposite microfilaments are fabricated via nanocomposite infiltration of 3D interconnected microfluidic networks. The manufacturing of the reinforced beams begins with the fabrication of microfluidic networks, which involves layer-by-layer deposition of fugitive ink filaments using a dispensing robot, filling the empty space between filaments using a low viscosity resin, curing the resin and finally removing the ink. Self-supported 3D structures with other geometries and many layers (e.g. a few hundreds layers) could be built using this method. The resulting tubular microfluidic networks are then infiltrated with thermosetting nanocomposite suspensions containing nanofillers (e.g. single-walled carbon nanotubes), and subsequently cured. The infiltration is done by applying a pressure gradient between two ends of the empty network (either by applying a vacuum or vacuum-assisted microinjection). Prior to the infiltration, the nanocomposite suspensions are prepared by dispersing nanofillers into polymer matrices using ultrasonication and three-roll mixing methods. The nanocomposites (i.e. materials infiltrated) are then solidified under UV exposure/heat cure, resulting in a 3D-reinforced composite structure. The technique presented here enables the design of functional nanocomposite macroscopic products for microengineering applications such as actuators and sensors. PMID:24686754

Silver(I) coordination polymers assembled from flexible cyclotriphosphazene ligand: structures, topologies and investigation of the counteranion effects.

PubMed

Davarcı, Derya; Gür, Rüştü; Beşli, Serap; Şenkuytu, Elif; Zorlu, Yunus

2016-06-01

The reactions of a flexible ligand hexakis(3-pyridyloxy)cyclotriphosphazene (HPCP) with a variety of silver(I) salts (AgX; X = NO3(-), PF6(-), ClO4(-), CH3PhSO3(-), BF4(-) and CF3SO3(-)) afforded six silver(I) coordination polymers, namely {[Ag2(HPCP)]·(NO3)2·H2O}n (1), {[Ag2(HPCP)(CH3CN)]·(PF6)2}n (2), {[Ag2(HPCP)(CH3CN)]·(ClO4)2}n (3), [Ag3(HPCP)(CH3PhSO3)3]n (4), [Ag2(HPCP)(CH3CN)(BF4)2]n (5) and {[Ag(HPCP)]·(CF3SO3)}n (6). All of the isolated crystalline compounds were structurally determined by X-ray crystallography. Changing the counteranions in the reactions, which were conducted under similar conditions of M/L ratio (1:1), temperature and solvent, resulted in structures with different types of topologies. In complexes (1)-(6), the ligand HPCP shows different coordination modes with Ag(I) ions giving two-dimensional layered structures and three-dimensional frameworks with different topologies. Complex (1) displays a new three-dimensional framework adopting a (3,3,6)-connected 3-nodal net with point symbol {4.6(2)}2{4(2).6(10).8(3)}. Complexes (2) and (3) are isomorphous and have a two-dimensional layered structure showing the same 3,6L60 topology with point symbol {4.2(6)}2{4(8).6(6).8}. Complex (4) is a two-dimensional structure incorporating short Ag...Ag argentophilic interactions and has a uninodal 4-connected sql/Shubnikov tetragonal plane net with {4(4).6(2)} topology. Complex (5) exhibits a novel three-dimensional framework and more suprisingly contains twofold interpenetrated honeycomb-like networks, in which the single net has a trinodal (2,3,5)-connected 3-nodal net with point symbol {6(3).8(6).12}{6(3)}{8}. Complex (6) crystallizes in a trigonal crystal system with the space group R\\bar 3 and possesses a three-dimensional polymeric structure showing a binodal (4,6)-connected fsh net with the point symbol (4(3).6(3))2.(4(6).6(6).8(3)). The effect of the counteranions on the formation of coordination polymers is discussed in this study.

A neural network approach for image reconstruction in electron magnetic resonance tomography.

PubMed

Durairaj, D Christopher; Krishna, Murali C; Murugesan, Ramachandran

2007-10-01

An object-oriented, artificial neural network (ANN) based, application system for reconstruction of two-dimensional spatial images in electron magnetic resonance (EMR) tomography is presented. The standard back propagation algorithm is utilized to train a three-layer sigmoidal feed-forward, supervised, ANN to perform the image reconstruction. The network learns the relationship between the 'ideal' images that are reconstructed using filtered back projection (FBP) technique and the corresponding projection data (sinograms). The input layer of the network is provided with a training set that contains projection data from various phantoms as well as in vivo objects, acquired from an EMR imager. Twenty five different network configurations are investigated to test the ability of the generalization of the network. The trained ANN then reconstructs two-dimensional temporal spatial images that present the distribution of free radicals in biological systems. Image reconstruction by the trained neural network shows better time complexity than the conventional iterative reconstruction algorithms such as multiplicative algebraic reconstruction technique (MART). The network is further explored for image reconstruction from 'noisy' EMR data and the results show better performance than the FBP method. The network is also tested for its ability to reconstruct from limited-angle EMR data set.

Three-dimensional neural cultures produce networks that mimic native brain activity.

PubMed

Bourke, Justin L; Quigley, Anita F; Duchi, Serena; O'Connell, Cathal D; Crook, Jeremy M; Wallace, Gordon G; Cook, Mark J; Kapsa, Robert M I

2018-02-01

Development of brain function is critically dependent on neuronal networks organized through three dimensions. Culture of central nervous system neurons has traditionally been limited to two dimensions, restricting growth patterns and network formation to a single plane. Here, with the use of multichannel extracellular microelectrode arrays, we demonstrate that neurons cultured in a true three-dimensional environment recapitulate native neuronal network formation and produce functional outcomes more akin to in vivo neuronal network activity. Copyright © 2017 John Wiley & Sons, Ltd.

Materials science. Assembly of micro/nanomaterials into complex, three-dimensional architectures by compressive buckling.

PubMed

Xu, Sheng; Yan, Zheng; Jang, Kyung-In; Huang, Wen; Fu, Haoran; Kim, Jeonghyun; Wei, Zijun; Flavin, Matthew; McCracken, Joselle; Wang, Renhan; Badea, Adina; Liu, Yuhao; Xiao, Dongqing; Zhou, Guoyan; Lee, Jungwoo; Chung, Ha Uk; Cheng, Huanyu; Ren, Wen; Banks, Anthony; Li, Xiuling; Paik, Ungyu; Nuzzo, Ralph G; Huang, Yonggang; Zhang, Yihui; Rogers, John A

2015-01-09

Complex three-dimensional (3D) structures in biology (e.g., cytoskeletal webs, neural circuits, and vasculature networks) form naturally to provide essential functions in even the most basic forms of life. Compelling opportunities exist for analogous 3D architectures in human-made devices, but design options are constrained by existing capabilities in materials growth and assembly. We report routes to previously inaccessible classes of 3D constructs in advanced materials, including device-grade silicon. The schemes involve geometric transformation of 2D micro/nanostructures into extended 3D layouts by compressive buckling. Demonstrations include experimental and theoretical studies of more than 40 representative geometries, from single and multiple helices, toroids, and conical spirals to structures that resemble spherical baskets, cuboid cages, starbursts, flowers, scaffolds, fences, and frameworks, each with single- and/or multiple-level configurations. Copyright © 2015, American Association for the Advancement of Science.

Cell-ECM Interactions During Cancer Invasion

NASA Astrophysics Data System (ADS)

Jiang, Yi

The extracellular matrix (ECM), a fibrous material that forms a network in a tissue, significantly affects many aspects of cellular behavior, including cell movement and proliferation. Transgenic mouse tumor studies indicate that excess collagen, a major component of ECM, enhances tumor formation and invasiveness. Clinically, tumor associated collagen signatures are strong markers for breast cancer survival. However, the underlying mechanisms are unclear since the properties of ECM are complex, with diverse structural and mechanical properties depending on various biophysical parameters. We have developed a three-dimensional elastic fiber network model, and parameterized it with in vitro collagen mechanics. Using this model, we study ECM remodeling as a result of local deformation and cell migration through the ECM as a network percolation problem. We have also developed a three-dimensional, multiscale model of cell migration and interaction with ECM. Our model reproduces quantitative single cell migration experiments. This model is a first step toward a fully biomechanical cell-matrix interaction model and may shed light on tumor associated collagen signatures in breast cancer. This work was partially supported by NIH-U01CA143069.

Complex Environmental Data Modelling Using Adaptive General Regression Neural Networks

NASA Astrophysics Data System (ADS)

Kanevski, Mikhail

2015-04-01

The research deals with an adaptation and application of Adaptive General Regression Neural Networks (GRNN) to high dimensional environmental data. GRNN [1,2,3] are efficient modelling tools both for spatial and temporal data and are based on nonparametric kernel methods closely related to classical Nadaraya-Watson estimator. Adaptive GRNN, using anisotropic kernels, can be also applied for features selection tasks when working with high dimensional data [1,3]. In the present research Adaptive GRNN are used to study geospatial data predictability and relevant feature selection using both simulated and real data case studies. The original raw data were either three dimensional monthly precipitation data or monthly wind speeds embedded into 13 dimensional space constructed by geographical coordinates and geo-features calculated from digital elevation model. GRNN were applied in two different ways: 1) adaptive GRNN with the resulting list of features ordered according to their relevancy; and 2) adaptive GRNN applied to evaluate all possible models N [in case of wind fields N=(2^13 -1)=8191] and rank them according to the cross-validation error. In both cases training were carried out applying leave-one-out procedure. An important result of the study is that the set of the most relevant features depends on the month (strong seasonal effect) and year. The predictabilities of precipitation and wind field patterns, estimated using the cross-validation and testing errors of raw and shuffled data, were studied in detail. The results of both approaches were qualitatively and quantitatively compared. In conclusion, Adaptive GRNN with their ability to select features and efficient modelling of complex high dimensional data can be widely used in automatic/on-line mapping and as an integrated part of environmental decision support systems. 1. Kanevski M., Pozdnoukhov A., Timonin V. Machine Learning for Spatial Environmental Data. Theory, applications and software. EPFL Press. With a CD: data, software, guides. (2009). 2. Kanevski M. Spatial Predictions of Soil Contamination Using General Regression Neural Networks. Systems Research and Information Systems, Volume 8, number 4, 1999. 3. Robert S., Foresti L., Kanevski M. Spatial prediction of monthly wind speeds in complex terrain with adaptive general regression neural networks. International Journal of Climatology, 33 pp. 1793-1804, 2013.

A two-dimensional hydrogen-bonded water layer in the structure of a cobalt(III) cubane complex.

PubMed

Qi, Ji; Zhai, Xiang-Sheng; Zhu, Hong-Lin; Lin, Jian-Li

2014-02-01

A tetranuclear Co(III) oxide complex with cubane topology, tetrakis(2,2'-bipyridine-κ(2)N,N')di-μ2-carbonato-κ(4)O:O'-tetra-μ3-oxido-tetracobalt(III) pentadecahydrate, [Co4(CO3)2O4(C10H8N2)4]·15H2O, with an unbounded hydrogen-bonded water layer, has been synthesized by reaction of CoCO3 and 2,2'-bipyridine. The solvent water molecules form a hydrogen-bonded net with tetrameric and pentameric water clusters as subunits. The Co4O4 cubane-like cores are sandwiched between the water layers, which are further stacked into a three-dimensional metallo-supramolecular network.

Ordered three-dimensional interconnected nanoarchitectures in anodic porous alumina

PubMed Central

Martín, Jaime; Martín-González, Marisol; Fernández, Jose Francisco; Caballero-Calero, Olga

2014-01-01

Three-dimensional nanostructures combine properties of nanoscale materials with the advantages of being macro-sized pieces when the time comes to manipulate, measure their properties, or make a device. However, the amount of compounds with the ability to self-organize in ordered three-dimensional nanostructures is limited. Therefore, template-based fabrication strategies become the key approach towards three-dimensional nanostructures. Here we report the simple fabrication of a template based on anodic aluminum oxide, having a well-defined, ordered, tunable, homogeneous 3D nanotubular network in the sub 100 nm range. The three-dimensional templates are then employed to achieve three-dimensional, ordered nanowire-networks in Bi2Te3 and polystyrene. Lastly, we demonstrate the photonic crystal behavior of both the template and the polystyrene three-dimensional nanostructure. Our approach may establish the foundations for future high-throughput, cheap, photonic materials and devices made of simple commodity plastics, metals, and semiconductors. PMID:25342247

Interfacing 3D Engineered Neuronal Cultures to Micro-Electrode Arrays: An Innovative In Vitro Experimental Model.

PubMed

Tedesco, Mariateresa; Frega, Monica; Martinoia, Sergio; Pesce, Mattia; Massobrio, Paolo

2015-10-18

Currently, large-scale networks derived from dissociated neurons growing and developing in vitro on extracellular micro-transducer devices are the gold-standard experimental model to study basic neurophysiological mechanisms involved in the formation and maintenance of neuronal cell assemblies. However, in vitro studies have been limited to the recording of the electrophysiological activity generated by bi-dimensional (2D) neural networks. Nonetheless, given the intricate relationship between structure and dynamics, a significant improvement is necessary to investigate the formation and the developing dynamics of three-dimensional (3D) networks. In this work, a novel experimental platform in which 3D hippocampal or cortical networks are coupled to planar Micro-Electrode Arrays (MEAs) is presented. 3D networks are realized by seeding neurons in a scaffold constituted of glass microbeads (30-40 µm in diameter) on which neurons are able to grow and form complex interconnected 3D assemblies. In this way, it is possible to design engineered 3D networks made up of 5-8 layers with an expected final cell density. The increasing complexity in the morphological organization of the 3D assembly induces an enhancement of the electrophysiological patterns displayed by this type of networks. Compared with the standard 2D networks, where highly stereotyped bursting activity emerges, the 3D structure alters the bursting activity in terms of duration and frequency, as well as it allows observation of more random spiking activity. In this sense, the developed 3D model more closely resembles in vivo neural networks.

Interfacing 3D Engineered Neuronal Cultures to Micro-Electrode Arrays: An Innovative In Vitro Experimental Model

PubMed Central

Tedesco, Mariateresa; Frega, Monica; Martinoia, Sergio; Pesce, Mattia; Massobrio, Paolo

2015-01-01

Currently, large-scale networks derived from dissociated neurons growing and developing in vitro on extracellular micro-transducer devices are the gold-standard experimental model to study basic neurophysiological mechanisms involved in the formation and maintenance of neuronal cell assemblies. However, in vitro studies have been limited to the recording of the electrophysiological activity generated by bi-dimensional (2D) neural networks. Nonetheless, given the intricate relationship between structure and dynamics, a significant improvement is necessary to investigate the formation and the developing dynamics of three-dimensional (3D) networks. In this work, a novel experimental platform in which 3D hippocampal or cortical networks are coupled to planar Micro-Electrode Arrays (MEAs) is presented. 3D networks are realized by seeding neurons in a scaffold constituted of glass microbeads (30-40 µm in diameter) on which neurons are able to grow and form complex interconnected 3D assemblies. In this way, it is possible to design engineered 3D networks made up of 5-8 layers with an expected final cell density. The increasing complexity in the morphological organization of the 3D assembly induces an enhancement of the electrophysiological patterns displayed by this type of networks. Compared with the standard 2D networks, where highly stereotyped bursting activity emerges, the 3D structure alters the bursting activity in terms of duration and frequency, as well as it allows observation of more random spiking activity. In this sense, the developed 3D model more closely resembles in vivo neural networks. PMID:26554533

Generation of Complex Karstic Conduit Networks with a Hydro-chemical Model

NASA Astrophysics Data System (ADS)

De Rooij, R.; Graham, W. D.

2016-12-01

The discrete-continuum approach is very well suited to simulate flow and solute transport within karst aquifers. Using this approach, discrete one-dimensional conduits are embedded within a three-dimensional continuum representative of the porous limestone matrix. Typically, however, little is known about the geometry of the karstic conduit network. As such the discrete-continuum approach is rarely used for practical applications. It may be argued, however, that the uncertainty associated with the geometry of the network could be handled by modeling an ensemble of possible karst conduit networks within a stochastic framework. We propose to generate stochastically realistic karst conduit networks by simulating the widening of conduits as caused by the dissolution of limestone over geological relevant timescales. We illustrate that advanced numerical techniques permit to solve the non-linear and coupled hydro-chemical processes efficiently, such that relatively large and complex networks can be generated in acceptable time frames. Instead of specifying flow boundary conditions on conduit cells to recharge the network as is typically done in classical speleogenesis models, we specify an effective rainfall rate over the land surface and let model physics determine the amount of water entering the network. This is advantageous since the amount of water entering the network is extremely difficult to reconstruct, whereas the effective rainfall rate may be quantified using paleoclimatic data. Furthermore, we show that poorly known flow conditions may be constrained by requiring a realistic flow field. Using our speleogenesis model we have investigated factors that influence the geometry of simulated conduit networks. We illustrate that our model generates typical branchwork, network and anastomotic conduit systems. Flow, solute transport and water ages in karst aquifers are simulated using a few illustrative networks.

Online signature recognition using principal component analysis and artificial neural network

NASA Astrophysics Data System (ADS)

Hwang, Seung-Jun; Park, Seung-Je; Baek, Joong-Hwan

2016-12-01

In this paper, we propose an algorithm for on-line signature recognition using fingertip point in the air from the depth image acquired by Kinect. We extract 10 statistical features from X, Y, Z axis, which are invariant to changes in shifting and scaling of the signature trajectories in three-dimensional space. Artificial neural network is adopted to solve the complex signature classification problem. 30 dimensional features are converted into 10 principal components using principal component analysis, which is 99.02% of total variances. We implement the proposed algorithm and test to actual on-line signatures. In experiment, we verify the proposed method is successful to classify 15 different on-line signatures. Experimental result shows 98.47% of recognition rate when using only 10 feature vectors.

Spectral-spatial classification of hyperspectral image using three-dimensional convolution network

NASA Astrophysics Data System (ADS)

Liu, Bing; Yu, Xuchu; Zhang, Pengqiang; Tan, Xiong; Wang, Ruirui; Zhi, Lu

2018-01-01

Recently, hyperspectral image (HSI) classification has become a focus of research. However, the complex structure of an HSI makes feature extraction difficult to achieve. Most current methods build classifiers based on complex handcrafted features computed from the raw inputs. The design of an improved 3-D convolutional neural network (3D-CNN) model for HSI classification is described. This model extracts features from both the spectral and spatial dimensions through the application of 3-D convolutions, thereby capturing the important discrimination information encoded in multiple adjacent bands. The designed model views the HSI cube data altogether without relying on any pre- or postprocessing. In addition, the model is trained in an end-to-end fashion without any handcrafted features. The designed model was applied to three widely used HSI datasets. The experimental results demonstrate that the 3D-CNN-based method outperforms conventional methods even with limited labeled training samples.

Dimensionality and entropy of spontaneous and evoked rate activity

NASA Astrophysics Data System (ADS)

Engelken, Rainer; Wolf, Fred

Cortical circuits exhibit complex activity patterns both spontaneously and evoked by external stimuli. Finding low-dimensional structure in population activity is a challenge. What is the diversity of the collective neural activity and how is it affected by an external stimulus? Using concepts from ergodic theory, we calculate the attractor dimensionality and dynamical entropy production of these networks. We obtain these two canonical measures of the collective network dynamics from the full set of Lyapunov exponents. We consider a randomly-wired firing-rate network that exhibits chaotic rate fluctuations for sufficiently strong synaptic weights. We show that dynamical entropy scales logarithmically with synaptic coupling strength, while the attractor dimensionality saturates. Thus, despite the increasing uncertainty, the diversity of collective activity saturates for strong coupling. We find that a time-varying external stimulus drastically reduces both entropy and dimensionality. Finally, we analytically approximate the full Lyapunov spectrum in several limiting cases by random matrix theory. Our study opens a novel avenue to characterize the complex dynamics of rate networks and the geometric structure of the corresponding high-dimensional chaotic attractor. received funding from Evangelisches Studienwerk Villigst, DFG through CRC 889 and Volkswagen Foundation.

Three-dimensional image signals: processing methods

NASA Astrophysics Data System (ADS)

Schiopu, Paul; Manea, Adrian; Craciun, Anca-Ileana; Craciun, Alexandru

2010-11-01

Over the years extensive studies have been carried out to apply coherent optics methods in real-time processing, communications and transmission image. This is especially true when a large amount of information needs to be processed, e.g., in high-resolution imaging. The recent progress in data-processing networks and communication systems has considerably increased the capacity of information exchange. We describe the results of literature investigation research of processing methods for the signals of the three-dimensional images. All commercially available 3D technologies today are based on stereoscopic viewing. 3D technology was once the exclusive domain of skilled computer-graphics developers with high-end machines and software. The images capture from the advanced 3D digital camera can be displayed onto screen of the 3D digital viewer with/ without special glasses. For this is needed considerable processing power and memory to create and render the complex mix of colors, textures, and virtual lighting and perspective necessary to make figures appear three-dimensional. Also, using a standard digital camera and a technique called phase-shift interferometry we can capture "digital holograms." These are holograms that can be stored on computer and transmitted over conventional networks. We present some research methods to process "digital holograms" for the Internet transmission and results.

Rapidly prototyped three-dimensional nanofluidic channel networks in glass substrates.

PubMed

Ke, Kevin; Hasselbrink, Ernest F; Hunt, Alan J

2005-08-15

Microfluidic and nanofluidic technologies have long sought a fast, reliable method to overcome the creative limitations of planar fabrication methods, the resolution limits of lithography, and the materials limitations for fast prototyping. In the present work, we demonstrate direct 3D machining of submicrometer diameter, subsurface fluidic channels in glass, via optical breakdown near critical intensity, using a femtosecond pulsed laser. No postexposure etching or bonding is required; the channel network (or almost any arbitrary-shaped cavity below the surface) is produced directly from "art-to-part". The key to this approach is to use very low energy, highly focused, pulses in the presence of liquid. Microbubbles that result from laser energy deposition gently expand and extrude machining debris from the channels. These bubbles are in a highly damped, low Reynolds number regime, implying that surface spalling due to bubble collapse is unimportant. We demonstrate rapid prototyping of three-dimensional "jumpers", mixers, and other key components of complex 3D microscale analysis systems in glass substrates.

A series of Cadmium(II) complexes with 2-substituted terephthalate building block and N-Donor co-ligands: Structural diversity and fluorescence properties

NASA Astrophysics Data System (ADS)

Ren, Yixia; Zhou, Shanhong; Wang, Zhixiang; Zhang, Meili; Wang, Jijiang; Cao, Jia

2017-11-01

Four new Cd(II) complexes have been prepared based on 1,2,4-trimellitic acid (H3tma) and monosodium 2-sulfoterephthalate (2-NaH2stp), formulated as [Cd2(Htma)2 (dpp)2(H2O)] (1), [Cd3 (tma)2 (2,4-bipy)4(H2O)2] (2), [Cd (2-Hstp) (2,2'-bipy)2]·2H2O (3) and [Cd (2-Hstp) (2,4-bipy) (H2O)2] (4) (dpp = dipyrido [3,2-a:2‧,3'-c] phenazine, 2,4-bipy = 2,4-bipyridine, 2,2'-bipy = 2,2'- bipyridine) by hydrothermal method. X-ray diffraction structural analyses show all these complexes crystallized in triclinic crystal system of Pī space group, but their structures are diverse. Complex 1 exhibits an infinite one-dimensional chain featuring the left- and right-handed stranded chains interweaved each other. For 2, the two-dimensional network is constructed by one-dimensional ladder-like chain linked by Cd2 ions. In complex 3, the cadmium ion is surrounded with one 2-Hstp2- anion and two 2,2'-bipy molecules. Complex 4 is also a discrete structure based on a metallic dimer unit. In all these complexes, the N-donor co-ligands take the important roles in the assembly of three-dimensional supramolecular structures. The fluorescence properties of complexes 1-4 could be assigned to the π - π* transition of organic ligands.

Extreme fluctuations in stochastic network coordination with time delays

NASA Astrophysics Data System (ADS)

Hunt, D.; Molnár, F.; Szymanski, B. K.; Korniss, G.

2015-12-01

We study the effects of uniform time delays on the extreme fluctuations in stochastic synchronization and coordination problems with linear couplings in complex networks. We obtain the average size of the fluctuations at the nodes from the behavior of the underlying modes of the network. We then obtain the scaling behavior of the extreme fluctuations with system size, as well as the distribution of the extremes on complex networks, and compare them to those on regular one-dimensional lattices. For large complex networks, when the delay is not too close to the critical one, fluctuations at the nodes effectively decouple, and the limit distributions converge to the Fisher-Tippett-Gumbel density. In contrast, fluctuations in low-dimensional spatial graphs are strongly correlated, and the limit distribution of the extremes is the Airy density. Finally, we also explore the effects of nonlinear couplings on the stability and on the extremes of the synchronization landscapes.

Crystal structure of fac-tri-chlorido-[tris-(pyridin-2-yl-N)amine]-chromium(III).

PubMed

Yamaguchi-Terasaki, Yukiko; Fujihara, Takashi; Nagasawa, Akira; Kaizaki, Sumio

2015-01-01

In the neutral complex mol-ecule of the title compound, fac-[CrCl3(tpa)] [tpa is tris-(pyridin-2-yl)amine; C15H12N4], the Cr(III) ion is bonded to three N atoms that are constrained to a facial arrangement by the tpa ligand and by three chloride ligands, leading to a distorted octa-hedral coordination sphere. The average Cr-N and Cr-Cl bond lengths are 2.086 (5) and 2.296 (4) Å, respectively. The complex mol-ecule is located on a mirror plane. In the crystal, a combination of C-H⋯N and C-H⋯Cl hydrogen-bonding inter-actions connect the mol-ecules into a three-dimensional network.

Transient PVT measurements and model predictions for vessel heat transfer. Part II.

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

Felver, Todd G.; Paradiso, Nicholas Joseph; Winters, William S., Jr.

2010-07-01

Part I of this report focused on the acquisition and presentation of transient PVT data sets that can be used to validate gas transfer models. Here in Part II we focus primarily on describing models and validating these models using the data sets. Our models are intended to describe the high speed transport of compressible gases in arbitrary arrangements of vessels, tubing, valving and flow branches. Our models fall into three categories: (1) network flow models in which flow paths are modeled as one-dimensional flow and vessels are modeled as single control volumes, (2) CFD (Computational Fluid Dynamics) models inmore » which flow in and between vessels is modeled in three dimensions and (3) coupled network/CFD models in which vessels are modeled using CFD and flows between vessels are modeled using a network flow code. In our work we utilized NETFLOW as our network flow code and FUEGO for our CFD code. Since network flow models lack three-dimensional resolution, correlations for heat transfer and tube frictional pressure drop are required to resolve important physics not being captured by the model. Here we describe how vessel heat transfer correlations were improved using the data and present direct model-data comparisons for all tests documented in Part I. Our results show that our network flow models have been substantially improved. The CFD modeling presented here describes the complex nature of vessel heat transfer and for the first time demonstrates that flow and heat transfer in vessels can be modeled directly without the need for correlations.« less

A system of three-dimensional complex variables

NASA Technical Reports Server (NTRS)

Martin, E. Dale

1986-01-01

Some results of a new theory of multidimensional complex variables are reported, including analytic functions of a three-dimensional (3-D) complex variable. Three-dimensional complex numbers are defined, including vector properties and rules of multiplication. The necessary conditions for a function of a 3-D variable to be analytic are given and shown to be analogous to the 2-D Cauchy-Riemann equations. A simple example also demonstrates the analogy between the newly defined 3-D complex velocity and 3-D complex potential and the corresponding ordinary complex velocity and complex potential in two dimensions.

Three-dimensional periodic supramolecular organic framework ion sponge in water and microcrystals

DOE PAGES

Tian, Jia; Zhou, Tian-You; Zhang, Shao-Chen; ...

2014-12-02

Self-assembly has emerged as a powerful approach to generating complex supramolecular architectures. Despite there being many crystalline frameworks reported in the solid state, the construction of highly soluble periodic supramolecular networks in a three-dimensional space is still a challenge. In this paper we demonstrate that the encapsulation motif, which involves the dimerization of two aromatic units within cucurbit[8]uril, can be used to direct the co-assembly of a tetratopic molecular block and cucurbit[8]uril into a periodic three-dimensional supramolecular organic framework in water. The periodicity of the supramolecular organic framework is supported by solution-phase small-angle X-ray-scattering and diffraction experiments. Upon evaporating themore » solvent, the periodicity of the framework is maintained in porous microcrystals. Lastly, as a supramolecular 'ion sponge', the framework can absorb different kinds of anionic guests, including drugs, in both water and microcrystals, and drugs absorbed in microcrystals can be released to water with selectivity.« less

Extracellular matrix structure.

PubMed

Theocharis, Achilleas D; Skandalis, Spyros S; Gialeli, Chrysostomi; Karamanos, Nikos K

2016-02-01

Extracellular matrix (ECM) is a non-cellular three-dimensional macromolecular network composed of collagens, proteoglycans/glycosaminoglycans, elastin, fibronectin, laminins, and several other glycoproteins. Matrix components bind each other as well as cell adhesion receptors forming a complex network into which cells reside in all tissues and organs. Cell surface receptors transduce signals into cells from ECM, which regulate diverse cellular functions, such as survival, growth, migration, and differentiation, and are vital for maintaining normal homeostasis. ECM is a highly dynamic structural network that continuously undergoes remodeling mediated by several matrix-degrading enzymes during normal and pathological conditions. Deregulation of ECM composition and structure is associated with the development and progression of several pathologic conditions. This article emphasizes in the complex ECM structure as to provide a better understanding of its dynamic structural and functional multipotency. Where relevant, the implication of the various families of ECM macromolecules in health and disease is also presented. Copyright © 2015 Elsevier B.V. All rights reserved.

Three-dimensional structure of thymidine phosphorylase from E. coli in complex with 3'-azido-2'-fluoro-2',3'-dideoxyuridine

NASA Astrophysics Data System (ADS)

Timofeev, V. I.; Abramchik, Yu. A.; Fateev, I. V.; Zhukhlistova, N. E.; Murav'eva, T. I.; Kuranova, I. P.; Esipov, R. S.

2013-11-01

The three-dimensional structures of thymidine phosphorylase from E. coli containing the bound sulfate ion in the phosphate-binding site and of the complex of thymidine phosphorylase with sulfate in the phosphate-binding site and the inhibitor 3'-azido-2'-fluoro-2',3'-dideoxyuridine (N3F-ddU) in the nucleoside-binding site were determined at 1.55 and 1.50 Å resolution, respectively. The amino-acid residues involved in the ligand binding and the hydrogen-bond network in the active site occupied by a large number of bound water molecules are described. A comparison of the structure of thymidine phosphorylase in complex with N3F-ddU with the structure of pyrimidine nucleoside phosphorylase from St. Aureus in complex with the natural substrate thymidine (PDB_ID: 3H5Q) shows that the substrate and the inhibitor in the nucleoside-binding pocket have different orientations. It is suggested that the position of N3F-ddU can be influenced by the presence of the azido group, which prefers a hydrophobic environment. In both structures, the active sites of the subunits are in the open conformation.

Guiding of Plasmons and Phonons in Complex Three Dimensional Structures

DTIC Science & Technology

2013-01-01

typical sample. We employed X - ray diffraction (XRD) to measure the average grain size across the entire depth of the sample over spot sizes Figure...propagation distance L as the 1/e decay length of the field intensity along x ...as well as the network layout with subwavelegth gap size and internode distance on the order of the effective wavelength, a small 2 x 2 resonant

Two-Dimensional Wetting of a Stepped Copper Surface

NASA Astrophysics Data System (ADS)

Lin, C.; Avidor, N.; Corem, G.; Godsi, O.; Alexandrowicz, G.; Darling, G. R.; Hodgson, A.

2018-02-01

Highly corrugated, stepped surfaces present regular 1D arrays of binding sites, creating a complex, heterogeneous environment to water. Rather than decorating the hydrophilic step sites to form 1D chains, water on stepped Cu(511) forms an extended 2D network that binds strongly to the steps but bridges across the intervening hydrophobic Cu(100) terraces. The hydrogen-bonded network contains pentamer, hexamer, and octomer water rings that leave a third of the stable Cu step sites unoccupied in order to bind water H down close to the step dipole and complete three hydrogen bonds per molecule.

Reconfigurable microfluidic hanging drop network for multi-tissue interaction and analysis.

PubMed

Frey, Olivier; Misun, Patrick M; Fluri, David A; Hengstler, Jan G; Hierlemann, Andreas

2014-06-30

Integration of multiple three-dimensional microtissues into microfluidic networks enables new insights in how different organs or tissues of an organism interact. Here, we present a platform that extends the hanging-drop technology, used for multi-cellular spheroid formation, to multifunctional complex microfluidic networks. Engineered as completely open, 'hanging' microfluidic system at the bottom of a substrate, the platform features high flexibility in microtissue arrangements and interconnections, while fabrication is simple and operation robust. Multiple spheroids of different cell types are formed in parallel on the same platform; the different tissues are then connected in physiological order for multi-tissue experiments through reconfiguration of the fluidic network. Liquid flow is precisely controlled through the hanging drops, which enable nutrient supply, substance dosage and inter-organ metabolic communication. The possibility to perform parallelized microtissue formation on the same chip that is subsequently used for complex multi-tissue experiments renders the developed platform a promising technology for 'body-on-a-chip'-related research.

Thermoreversible Folding as a Route to the Unique Shape-Memory Character in Ductile Polymer Networks.

PubMed

McBride, Matthew K; Podgorski, Maciej; Chatani, Shunsuke; Worrell, Brady T; Bowman, Christopher N

2018-06-21

Ductile, cross-linked films were folded as a means to program temporary shapes without the need for complex heating cycles or specialized equipment. Certain cross-linked polymer networks, formed here with the thiol-isocyanate reaction, possessed the ability to be pseudoplastically deformed below the glass transition, and the original shape was recovered during heating through the glass transition. To circumvent the large forces required to plastically deform a glassy polymer network, we have utilized folding, which localizes the deformation in small creases, and achieved large dimensional changes with simple programming procedures. In addition to dimension changes, three-dimensional objects such as swans and airplanes were developed to demonstrate applying origami principles to shape memory. We explored the fundamental mechanical properties that are required to fold polymer sheets and observed that a yield point that does not correspond to catastrophic failure is required. Unfolding occurred during heating through the glass transition, indicating the vitrification of the network that maintained the temporary, folded shape. Folding was demonstrated as a powerful tool to simply and effectively program ductile shape-memory polymers without the need for thermal cycling.

Probing hydrogen bond networks in half-sandwich Ru(II) building blocks by a combined 1H DQ CRAMPS solid-state NMR, XRPD, and DFT approach.

PubMed

Chierotti, Michele R; Gobetto, Roberto; Nervi, Carlo; Bacchi, Alessia; Pelagatti, Paolo; Colombo, Valentina; Sironi, Angelo

2014-01-06

The hydrogen bond network of three polymorphs (1α, 1β, and 1γ) and one solvate form (1·H2O) arising from the hydration-dehydration process of the Ru(II) complex [(p-cymene)Ru(κN-INA)Cl2] (where INA is isonicotinic acid), has been ascertained by means of one-dimensional (1D) and two-dimensional (2D) double quantum (1)H CRAMPS (Combined Rotation and Multiple Pulses Sequences) and (13)C CPMAS solid-state NMR experiments. The resolution improvement provided by homonuclear decoupling pulse sequences, with respect to fast MAS experiments, has been highlighted. The solid-state structure of 1γ has been fully characterized by combining X-ray powder diffraction (XRPD), solid-state NMR, and periodic plane-wave first-principles calculations. None of the forms show the expected supramolecular cyclic dimerization of the carboxylic functions of INA, because of the presence of Cl atoms as strong hydrogen bond (HB) acceptors. The hydration-dehydration process of the complex has been discussed in terms of structure and HB rearrangements.

Hierarchical and Multifunctional Three-dimensional Network of Carbon Nanotubes for Supercapacitor and Strain Sensor Applications

DTIC Science & Technology

2016-05-19

cycles at 100 mV/s scan rate. 15. SUBJECT TERMS Carbon nano tubes, Nanotechnology , supercapacitor 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...5. Lee, H., Hierarchical and Multifunctional Three-dimensional Network of Carbon Nanotubes of Sensor Applications, College of Engineering Forum on

Capacity of Heterogeneous Mobile Wireless Networks with D-Delay Transmission Strategy.

PubMed

Wu, Feng; Zhu, Jiang; Xi, Zhipeng; Gao, Kai

2016-03-25

This paper investigates the capacity problem of heterogeneous wireless networks in mobility scenarios. A heterogeneous network model which consists of n normal nodes and m helping nodes is proposed. Moreover, we propose a D-delay transmission strategy to ensure that every packet can be delivered to its destination nodes with limited delay. Different from most existing network schemes, our network model has a novel two-tier architecture. The existence of helping nodes greatly improves the network capacity. Four types of mobile networks are studied in this paper: i.i.d. fast mobility model and slow mobility model in two-dimensional space, i.i.d. fast mobility model and slow mobility model in three-dimensional space. Using the virtual channel model, we present an intuitive analysis of the capacity of two-dimensional mobile networks and three-dimensional mobile networks, respectively. Given a delay constraint D, we derive the asymptotic expressions for the capacity of the four types of mobile networks. Furthermore, the impact of D and m to the capacity of the whole network is analyzed. Our findings provide great guidance for the future design of the next generation of networks.

Complex behavior in chains of nonlinear oscillators.

PubMed

Alonso, Leandro M

2017-06-01

This article outlines sufficient conditions under which a one-dimensional chain of identical nonlinear oscillators can display complex spatio-temporal behavior. The units are described by phase equations and consist of excitable oscillators. The interactions are local and the network is poised to a critical state by balancing excitation and inhibition locally. The results presented here suggest that in networks composed of many oscillatory units with local interactions, excitability together with balanced interactions is sufficient to give rise to complex emergent features. For values of the parameters where complex behavior occurs, the system also displays a high-dimensional bifurcation where an exponentially large number of equilibria are borne in pairs out of multiple saddle-node bifurcations.

Contribution of human skin topography to the characterization of dynamic skin tension during senescence: morpho-mechanical approach

NASA Astrophysics Data System (ADS)

Zahouani, H.; Djaghloul, M.; Vargiolu, R.; Mezghani, S.; Mansori, M. E. L.

2014-03-01

The structuring of the dermis with a network of collagen and elastic fibres gives a three-dimensional structure to the skin network with directions perpendicular and parallel to the skin surface. This three-dimensional morphology prints on the surface of the stratum corneum a three dimensional network of lines which express the mechanical tension of the skin at rest. To evaluate the changes of skin morphology, we used a three-dimensional confocal microscopy and characterization of skin imaging of volar forearm microrelief. We have accurately characterize the role of skin line network during chronological aging with the identification of depth scales on the network of lines (z <= 60μm) and the network of lines covering Langer's lines (z > 60 microns). During aging has been highlighted lower rows for elastic fibres, the decrease weakened the tension and results in enlargement of the plates of the microrelief, which gives us a geometric pertinent indicator to quantify the loss of skin tension and assess the stage of aging. The study of 120 Caucasian women shows that ageing in the volar forearm zone results in changes in the morphology of the line network organisation. The decrease in secondary lines (z <= 60 μm) is counterbalanced by an increase in the depth of the primary lines (z > 60 μm) and an accentuation of the anisotropy index.

Reconfigurable origami-inspired acoustic waveguides

PubMed Central

Babaee, Sahab; Overvelde, Johannes T. B.; Chen, Elizabeth R.; Tournat, Vincent; Bertoldi, Katia

2016-01-01

We combine numerical simulations and experiments to design a new class of reconfigurable waveguides based on three-dimensional origami-inspired metamaterials. Our strategy builds on the fact that the rigid plates and hinges forming these structures define networks of tubes that can be easily reconfigured. As such, they provide an ideal platform to actively control and redirect the propagation of sound. We design reconfigurable systems that, depending on the externally applied deformation, can act as networks of waveguides oriented along one, two, or three preferential directions. Moreover, we demonstrate that the capability of the structure to guide and radiate acoustic energy along predefined directions can be easily switched on and off, as the networks of tubes are reversibly formed and disrupted. The proposed designs expand the ability of existing acoustic metamaterials and exploit complex waveguiding to enhance control over propagation and radiation of acoustic energy, opening avenues for the design of a new class of tunable acoustic functional systems. PMID:28138527

Earthquake Complex Network applied along the Chilean Subduction Zone.

NASA Astrophysics Data System (ADS)

Martin, F.; Pasten, D.; Comte, D.

2017-12-01

In recent years the earthquake complex networks have been used as a useful tool to describe and characterize the behavior of seismicity. The earthquake complex network is built in space, dividing the three dimensional space in cubic cells. If the cubic cell contains a hypocenter, we call this cell like a node. The connections between nodes follows the time sequence of the occurrence of the seismic events. In this sense, we have a spatio-temporal configuration of a specific region using the seismicity in that zone. In this work, we are applying complex networks to characterize the subduction zone along the coast of Chile using two networks: a directed and an undirected network. The directed network takes in consideration the time-direction of the connections, that is very important for the connectivity of the network: we are considering the connectivity, ki of the i-th node, like the number of connections going out from the node i and we add the self-connections (if two seismic events occurred successive in time in the same cubic cell, we have a self-connection). The undirected network is the result of remove the direction of the connections and the self-connections from the directed network. These two networks were building using seismic data events recorded by CSN (Chilean Seismological Center) in Chile. This analysis includes the last largest earthquakes occurred in Iquique (April 2014) and in Illapel (September 2015). The result for the directed network shows a change in the value of the critical exponent along the Chilean coast. The result for the undirected network shows a small-world behavior without important changes in the topology of the network. Therefore, the complex network analysis shows a new form to characterize the Chilean subduction zone with a simple method that could be compared with another methods to obtain more details about the behavior of the seismicity in this region.

Mesoscale assembly of chemically modified graphene into complex cellular networks

PubMed Central

Barg, Suelen; Perez, Felipe Macul; Ni, Na; do Vale Pereira, Paula; Maher, Robert C.; Garcia-Tuñon, Esther; Eslava, Salvador; Agnoli, Stefano; Mattevi, Cecilia; Saiz, Eduardo

2014-01-01

The widespread technological introduction of graphene beyond electronics rests on our ability to assemble this two-dimensional building block into three-dimensional structures for practical devices. To achieve this goal we need fabrication approaches that are able to provide an accurate control of chemistry and architecture from nano to macroscopic levels. Here, we describe a versatile technique to build ultralight (density ≥1 mg cm−3) cellular networks based on the use of soft templates and the controlled segregation of chemically modified graphene to liquid interfaces. These novel structures can be tuned for excellent conductivity; versatile mechanical response (elastic-brittle to elastomeric, reversible deformation, high energy absorption) and organic absorption capabilities (above 600 g per gram of material). The approach can be used to uncover the basic principles that will guide the design of practical devices that by combining unique mechanical and functional performance will generate new technological opportunities. PMID:24999766

Learning Analytics for Networked Learning Models

ERIC Educational Resources Information Center

Joksimovic, Srecko; Hatala, Marek; Gaševic, Dragan

2014-01-01

Teaching and learning in networked settings has attracted significant attention recently. The central topic of networked learning research is human-human and human-information interactions occurring within a networked learning environment. The nature of these interactions is highly complex and usually requires a multi-dimensional approach to…

Monodisperse alginate microgel formation in a three-dimensional microfluidic droplet generator.

PubMed

Lian, Meng; Collier, C Patrick; Doktycz, Mitchel J; Retterer, Scott T

2012-01-01

Droplet based microfluidic systems provide an ideal platform for partitioning and manipulating aqueous samples for analysis. Identifying stable operating conditions under which droplets are generated is challenging yet crucial for real-world applications. A novel three-dimensional microfluidic platform that facilitates the consistent generation and gelation of alginate-calcium hydrogel microbeads for microbial encapsulation, over a broad range of input pressures, in the absence of surfactants is described. The unique three-dimensional design of the fluidic network utilizes a height difference at the junction between the aqueous sample injection and organic carrier channels to induce droplet formation via a surface tension enhanced self-shearing mechanism. Combined within a flow-focusing geometry, under constant pressure control, this arrangement facilitates predictable generation of droplets over a much broader range of operating conditions than that of conventional two-dimensional systems. The impact of operating pressures and geometry on droplet gelation, aqueous and organic material flow rates, microbead size, and bead generation frequency are described. The system presented provides a robust platform for encapsulating single microbes in complex mixtures into individual hydrogel beads, and provides the foundation for the development of a complete system for sorting and analyzing microbes at the single cell level.

Monodisperse alginate microgel formation in a three-dimensional microfluidic droplet generator

PubMed Central

Lian, Meng; Collier, C. Patrick; Doktycz, Mitchel J.; Retterer, Scott T.

2012-01-01

Droplet based microfluidic systems provide an ideal platform for partitioning and manipulating aqueous samples for analysis. Identifying stable operating conditions under which droplets are generated is challenging yet crucial for real-world applications. A novel three-dimensional microfluidic platform that facilitates the consistent generation and gelation of alginate-calcium hydrogel microbeads for microbial encapsulation, over a broad range of input pressures, in the absence of surfactants is described. The unique three-dimensional design of the fluidic network utilizes a height difference at the junction between the aqueous sample injection and organic carrier channels to induce droplet formation via a surface tension enhanced self-shearing mechanism. Combined within a flow-focusing geometry, under constant pressure control, this arrangement facilitates predictable generation of droplets over a much broader range of operating conditions than that of conventional two-dimensional systems. The impact of operating pressures and geometry on droplet gelation, aqueous and organic material flow rates, microbead size, and bead generation frequency are described. The system presented provides a robust platform for encapsulating single microbes in complex mixtures into individual hydrogel beads, and provides the foundation for the development of a complete system for sorting and analyzing microbes at the single cell level. PMID:24198865

Neural-Network Object-Recognition Program

NASA Technical Reports Server (NTRS)

Spirkovska, L.; Reid, M. B.

1993-01-01

HONTIOR computer program implements third-order neural network exhibiting invariance under translation, change of scale, and in-plane rotation. Invariance incorporated directly into architecture of network. Only one view of each object needed to train network for two-dimensional-translation-invariant recognition of object. Also used for three-dimensional-transformation-invariant recognition by training network on only set of out-of-plane rotated views. Written in C language.

Classification of brain MRI with big data and deep 3D convolutional neural networks

NASA Astrophysics Data System (ADS)

Wegmayr, Viktor; Aitharaju, Sai; Buhmann, Joachim

2018-02-01

Our ever-aging society faces the growing problem of neurodegenerative diseases, in particular dementia. Magnetic Resonance Imaging provides a unique tool for non-invasive investigation of these brain diseases. However, it is extremely difficult for neurologists to identify complex disease patterns from large amounts of three-dimensional images. In contrast, machine learning excels at automatic pattern recognition from large amounts of data. In particular, deep learning has achieved impressive results in image classification. Unfortunately, its application to medical image classification remains difficult. We consider two reasons for this difficulty: First, volumetric medical image data is considerably scarcer than natural images. Second, the complexity of 3D medical images is much higher compared to common 2D images. To address the problem of small data set size, we assemble the largest dataset ever used for training a deep 3D convolutional neural network to classify brain images as healthy (HC), mild cognitive impairment (MCI) or Alzheimers disease (AD). We use more than 20.000 images from subjects of these three classes, which is almost 9x the size of the previously largest data set. The problem of high dimensionality is addressed by using a deep 3D convolutional neural network, which is state-of-the-art in large-scale image classification. We exploit its ability to process the images directly, only with standard preprocessing, but without the need for elaborate feature engineering. Compared to other work, our workflow is considerably simpler, which increases clinical applicability. Accuracy is measured on the ADNI+AIBL data sets, and the independent CADDementia benchmark.

Small Artery Elastin Distribution and Architecture-Focus on Three Dimensional Organization.

PubMed

Hill, Michael A; Nourian, Zahra; Ho, I-Lin; Clifford, Philip S; Martinez-Lemus, Luis; Meininger, Gerald A

2016-11-01

The distribution of ECM proteins within the walls of resistance vessels is complex both in variety of proteins and structural arrangement. In particular, elastin exists as discrete fibers varying in orientation across the adventitia and media as well as often resembling a sheet-like structure in the case of the IEL. Adding to the complexity is the tissue heterogeneity that exists in these structural arrangements. For example, small intracranial cerebral arteries lack adventitial elastin while similar sized arteries from skeletal muscle and intestinal mesentery exhibit a complex adventitial network of elastin fibers. With regard to the IEL, several vascular beds exhibit an elastin sheet with punctate holes/fenestrae while in others the IEL is discontinuous and fibrous in appearance. Importantly, these structural patterns likely sub-serve specific functional properties, including mechanosensing, control of external forces, mechanical properties of the vascular wall, cellular positioning, and communication between cells. Of further significance, these processes are altered in vascular disorders such as hypertension and diabetes mellitus where there is modification of ECM. This brief report focuses on the three-dimensional wall structure of small arteries and considers possible implications with regard to mechanosensing under physiological and pathophysiological conditions. © 2016 John Wiley & Sons Ltd.

From globally coupled maps to complex-systems biology

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

Kaneko, Kunihiko, E-mail: kaneko@complex.c.u-tokyo.ac.jp

Studies of globally coupled maps, introduced as a network of chaotic dynamics, are briefly reviewed with an emphasis on novel concepts therein, which are universal in high-dimensional dynamical systems. They include clustering of synchronized oscillations, hierarchical clustering, chimera of synchronization and desynchronization, partition complexity, prevalence of Milnor attractors, chaotic itinerancy, and collective chaos. The degrees of freedom necessary for high dimensionality are proposed to equal the number in which the combinatorial exceeds the exponential. Future analysis of high-dimensional dynamical systems with regard to complex-systems biology is briefly discussed.

Single- and two-phase flow in microfluidic porous media analogs based on Voronoi tessellation

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

Wu, Mengjie; Xiao, Feng; Johnson-Paben, Rebecca

2012-01-01

The objective of this study was to create a microfluidic model of complex porous media for studying single and multiphase flows. Most experimental porous media models consist of periodic geometries that lend themselves to comparison with well-developed theoretical predictions. However, most real porous media such as geological formations and biological tissues contain a degree of randomness and complexity that is not adequately represented in periodic geometries. To design an experimental tool to study these complex geometries, we created microfluidic models of random homogeneous and heterogeneous networks based on Voronoi tessellations. These networks consisted of approximately 600 grains separated by amore » highly connected network of channels with an overall porosity of 0.11 0.20. We found that introducing heterogeneities in the form of large cavities within the network changed the permeability in a way that cannot be predicted by the classical porosity-permeability relationship known as the Kozeny equation. The values of permeability found in experiments were in excellent agreement with those calculated from three-dimensional lattice Boltzmann simulations. In two-phase flow experiments of oil displacement with water we found that the surface energy of channel walls determined the pattern of water invasion, while the network topology determined the residual oil saturation. These results suggest that complex network topologies lead to fluid flow behavior that is difficult to predict based solely on porosity. The microfluidic models developed in this study using a novel geometry generation algorithm based on Voronoi tessellation are a new experimental tool for studying fluid and solute transport problems within complex porous media.« less

Tetraammine(carbonato-κ(2) O,O')cobalt(III) perchlorate.

PubMed

Mohan, Singaravelu Chandra; Jenniefer, Samson Jegan; Muthiah, Packianathan Thomas; Jothivenkatachalam, Kandasamy

2013-01-01

In the title complex, [Co(CO3)(NH3)4]ClO4, both the cation and anion lie on a mirror plane. The Co(III) ion is coordinated by two NH3 ligands and a chelating carbonato ligand in the equatorial sites and by two NH3 groups in the axial sites, forming a distorted octa-hedral geometry. In the crystal, N-H⋯O hydrogen bonds connect the anions and cations, forming a three-dimensional network.

An Energy Model of Place Cell Network in Three Dimensional Space.

PubMed

Wang, Yihong; Xu, Xuying; Wang, Rubin

2018-01-01

Place cells are important elements in the spatial representation system of the brain. A considerable amount of experimental data and classical models are achieved in this area. However, an important question has not been addressed, which is how the three dimensional space is represented by the place cells. This question is preliminarily surveyed by energy coding method in this research. Energy coding method argues that neural information can be expressed by neural energy and it is convenient to model and compute for neural systems due to the global and linearly addable properties of neural energy. Nevertheless, the models of functional neural networks based on energy coding method have not been established. In this work, we construct a place cell network model to represent three dimensional space on an energy level. Then we define the place field and place field center and test the locating performance in three dimensional space. The results imply that the model successfully simulates the basic properties of place cells. The individual place cell obtains unique spatial selectivity. The place fields in three dimensional space vary in size and energy consumption. Furthermore, the locating error is limited to a certain level and the simulated place field agrees to the experimental results. In conclusion, this is an effective model to represent three dimensional space by energy method. The research verifies the energy efficiency principle of the brain during the neural coding for three dimensional spatial information. It is the first step to complete the three dimensional spatial representing system of the brain, and helps us further understand how the energy efficiency principle directs the locating, navigating, and path planning function of the brain.

Crystal structure of fac-tri­chlorido­[tris­(pyridin-2-yl-N)amine]­chromium(III)

PubMed Central

Yamaguchi-Terasaki, Yukiko; Fujihara, Takashi; Nagasawa, Akira; Kaizaki, Sumio

2015-01-01

In the neutral complex mol­ecule of the title compound, fac-[CrCl3(tpa)] [tpa is tris­(pyridin-2-yl)amine; C15H12N4], the CrIII ion is bonded to three N atoms that are constrained to a facial arrangement by the tpa ligand and by three chloride ligands, leading to a distorted octa­hedral coordination sphere. The average Cr—N and Cr—Cl bond lengths are 2.086 (5) and 2.296 (4) Å, respectively. The complex mol­ecule is located on a mirror plane. In the crystal, a combination of C—H⋯N and C—H⋯Cl hydrogen-bonding inter­actions connect the mol­ecules into a three-dimensional network. PMID:25705455

Multispectral embedding-based deep neural network for three-dimensional human pose recovery

NASA Astrophysics Data System (ADS)

Yu, Jialin; Sun, Jifeng

2018-01-01

Monocular image-based three-dimensional (3-D) human pose recovery aims to retrieve 3-D poses using the corresponding two-dimensional image features. Therefore, the pose recovery performance highly depends on the image representations. We propose a multispectral embedding-based deep neural network (MSEDNN) to automatically obtain the most discriminative features from multiple deep convolutional neural networks and then embed their penultimate fully connected layers into a low-dimensional manifold. This compact manifold can explore not only the optimum output from multiple deep networks but also the complementary properties of them. Furthermore, the distribution of each hierarchy discriminative manifold is sufficiently smooth so that the training process of our MSEDNN can be effectively implemented only using few labeled data. Our proposed network contains a body joint detector and a human pose regressor that are jointly trained. Extensive experiments conducted on four databases show that our proposed MSEDNN can achieve the best recovery performance compared with the state-of-the-art methods.

Characterizing the correlations between local phase fractions of gas-liquid two-phase flow with wire-mesh sensor.

PubMed

Tan, C; Liu, W L; Dong, F

2016-06-28

Understanding of flow patterns and their transitions is significant to uncover the flow mechanics of two-phase flow. The local phase distribution and its fluctuations contain rich information regarding the flow structures. A wire-mesh sensor (WMS) was used to study the local phase fluctuations of horizontal gas-liquid two-phase flow, which was verified through comparing the reconstructed three-dimensional flow structure with photographs taken during the experiments. Each crossing point of the WMS is treated as a node, so the measurement on each node is the phase fraction in this local area. An undirected and unweighted flow pattern network was established based on connections that are formed by cross-correlating the time series of each node under different flow patterns. The structure of the flow pattern network reveals the relationship of the phase fluctuations at each node during flow pattern transition, which is then quantified by introducing the topological index of the complex network. The proposed analysis method using the WMS not only provides three-dimensional visualizations of the gas-liquid two-phase flow, but is also a thorough analysis for the structure of flow patterns and the characteristics of flow pattern transition. This article is part of the themed issue 'Supersensing through industrial process tomography'. © 2016 The Author(s).

Characterizing the correlations between local phase fractions of gas–liquid two-phase flow with wire-mesh sensor

PubMed Central

Liu, W. L.; Dong, F.

2016-01-01

Understanding of flow patterns and their transitions is significant to uncover the flow mechanics of two-phase flow. The local phase distribution and its fluctuations contain rich information regarding the flow structures. A wire-mesh sensor (WMS) was used to study the local phase fluctuations of horizontal gas–liquid two-phase flow, which was verified through comparing the reconstructed three-dimensional flow structure with photographs taken during the experiments. Each crossing point of the WMS is treated as a node, so the measurement on each node is the phase fraction in this local area. An undirected and unweighted flow pattern network was established based on connections that are formed by cross-correlating the time series of each node under different flow patterns. The structure of the flow pattern network reveals the relationship of the phase fluctuations at each node during flow pattern transition, which is then quantified by introducing the topological index of the complex network. The proposed analysis method using the WMS not only provides three-dimensional visualizations of the gas–liquid two-phase flow, but is also a thorough analysis for the structure of flow patterns and the characteristics of flow pattern transition. This article is part of the themed issue ‘Supersensing through industrial process tomography’. PMID:27185959

Liouville action as path-integral complexity: from continuous tensor networks to AdS/CFT

NASA Astrophysics Data System (ADS)

Caputa, Pawel; Kundu, Nilay; Miyaji, Masamichi; Takayanagi, Tadashi; Watanabe, Kento

2017-11-01

We propose an optimization procedure for Euclidean path-integrals that evaluate CFT wave functionals in arbitrary dimensions. The optimization is performed by minimizing certain functional, which can be interpreted as a measure of computational complexity, with respect to background metrics for the path-integrals. In two dimensional CFTs, this functional is given by the Liouville action. We also formulate the optimization for higher dimensional CFTs and, in various examples, find that the optimized hyperbolic metrics coincide with the time slices of expected gravity duals. Moreover, if we optimize a reduced density matrix, the geometry becomes two copies of the entanglement wedge and reproduces the holographic entanglement entropy. Our approach resembles a continuous tensor network renormalization and provides a concrete realization of the proposed interpretation of AdS/CFT as tensor networks. The present paper is an extended version of our earlier report arXiv:1703.00456 and includes many new results such as evaluations of complexity functionals, energy stress tensor, higher dimensional extensions and time evolutions of thermofield double states.

Direct 3D bioprinting of prevascularized tissue constructs with complex microarchitecture

PubMed Central

Zhu, Wei; Qu, Xin; Zhu, Jie; Ma, Xuanyi; Patel, Sherrina; Liu, Justin; Wang, Pengrui; Lai, Cheuk Sun Edwin; Gou, Maling; Xu, Yang; Zhang, Kang; Chen, Shaochen

2017-01-01

Living tissues rely heavily on vascular networks to transport nutrients, oxygen and metabolic waste. However, there still remains a need for a simple and efficient approach to engineer vascularized tissues. Here, we created prevascularized tissues with complex three-dimensional (3D) microarchitectures using a rapid bioprinting method – microscale continuous optical bioprinting (μCOB). Multiple cell types mimicking the native vascular cell composition were encapsulated directly into hydrogels with precisely controlled distribution without the need of sacrificial materials or perfusion. With regionally controlled biomaterial properties the endothelial cells formed lumen-like structures spontaneously in vitro. In vivo implantation demonstrated the survival and progressive formation of the endothelial network in the prevascularized tissue. Anastomosis between the bioprinted endothelial network and host circulation was observed with functional blood vessels featuring red blood cells. With the superior bioprinting speed, flexibility and scalability, this new prevascularization approach can be broadly applicable to the engineering and translation of various functional tissues. PMID:28192772

Direct 3D bioprinting of prevascularized tissue constructs with complex microarchitecture.

PubMed

Zhu, Wei; Qu, Xin; Zhu, Jie; Ma, Xuanyi; Patel, Sherrina; Liu, Justin; Wang, Pengrui; Lai, Cheuk Sun Edwin; Gou, Maling; Xu, Yang; Zhang, Kang; Chen, Shaochen

2017-04-01

Living tissues rely heavily on vascular networks to transport nutrients, oxygen and metabolic waste. However, there still remains a need for a simple and efficient approach to engineer vascularized tissues. Here, we created prevascularized tissues with complex three-dimensional (3D) microarchitectures using a rapid bioprinting method - microscale continuous optical bioprinting (μCOB). Multiple cell types mimicking the native vascular cell composition were encapsulated directly into hydrogels with precisely controlled distribution without the need of sacrificial materials or perfusion. With regionally controlled biomaterial properties the endothelial cells formed lumen-like structures spontaneously in vitro. In vivo implantation demonstrated the survival and progressive formation of the endothelial network in the prevascularized tissue. Anastomosis between the bioprinted endothelial network and host circulation was observed with functional blood vessels featuring red blood cells. With the superior bioprinting speed, flexibility and scalability, this new prevascularization approach can be broadly applicable to the engineering and translation of various functional tissues. Copyright © 2017 Elsevier Ltd. All rights reserved.

Earthquake Complex Network Analysis Before and After the Mw 8.2 Earthquake in Iquique, Chile

NASA Astrophysics Data System (ADS)

Pasten, D.

2017-12-01

The earthquake complex networks have shown that they are abble to find specific features in seismic data set. In space, this networkshave shown a scale-free behavior for the probability distribution of connectivity, in directed networks and theyhave shown a small-world behavior, for the undirected networks.In this work, we present an earthquake complex network analysis for the large earthquake Mw 8.2 in the north ofChile (near to Iquique) in April, 2014. An earthquake complex network is made dividing the three dimensional space intocubic cells, if one of this cells contain an hypocenter, we name this cell like a node. The connections between nodes aregenerated in time. We follow the time sequence of seismic events and we are making the connections betweennodes. Now, we have two different networks: a directed and an undirected network. Thedirected network takes in consideration the time-direction of the connections, that is very important for the connectivityof the network: we are considering the connectivity, ki of the i-th node, like the number of connections going out ofthe node i plus the self-connections (if two seismic events occurred successive in time in the same cubic cell, we havea self-connection). The undirected network is made removing the direction of the connections and the self-connectionsfrom the directed network. For undirected networks, we are considering only if two nodes are or not connected.We have built a directed complex network and an undirected complex network, before and after the large earthquake in Iquique. We have used magnitudes greater than Mw = 1.0 and Mw = 3.0. We found that this method can recognize the influence of thissmall seismic events in the behavior of the network and we found that the size of the cell used to build the network isanother important factor to recognize the influence of the large earthquake in this complex system. This method alsoshows a difference in the values of the critical exponent γ (for the probability distribution of connectivity in the directednetwork) before and after the large earthquake, but this method does not show a change in the clustering behavior ofthe undirected network, before and after the large earthquake, showing a small-world behavior for the network beforeand after of this large seismic event.

Spatial Light Modulators as Optical Crossbar Switches

NASA Technical Reports Server (NTRS)

Juday, Richard

2003-01-01

A proposed method of implementing cross connections in an optical communication network is based on the use of a spatial light modulator (SLM) to form controlled diffraction patterns that connect inputs (light sources) and outputs (light sinks). Sources would typically include optical fibers and/or light-emitting diodes; sinks would typically include optical fibers and/or photodetectors. The sources and/or sinks could be distributed in two dimensions; that is, on planes. Alternatively or in addition, sources and/or sinks could be distributed in three dimensions -- for example, on curved surfaces or in more complex (including random) three-dimensional patterns.

Tris[(6S)-6-hy-droxy-4-epi-shikimic acid] monohydrate: an enanti-omerically pure hy-droxy-lated shikimic acid derived from methyl shikimate.

PubMed

Griesbeck, Axel G; Miara, Claus; Neudörfl, Jörg-M

2012-11-01

The title compound, 3C(7)H(10)O(6)·H(2)O, is the enanti-omerically pure product of a multi-step synthesis from the enanti-omerically pure natural shikimic acid. The asymmetric unit contains three mol-ecules of the acid and one mol-ecule of water. The cyclo-hexene rings of the acids have half-chair conformations. The carboxyl-ate, the four hydroxide groups and the additional water mol-ecule form a complex three-dimensional hydrogen-bonding network.

A full-dimensional ab initio potential energy surface and rovibrational energies of the Ar–HF complex

NASA Astrophysics Data System (ADS)

Huang, Jing; Zhou, Yanzi; Xie, Daiqian

2018-04-01

We report a new full-dimensional ab initio potential energy surface for the Ar-HF van der Waals complex at the level of coupled-cluster singles and doubles with noniterative inclusion of connected triples levels [CCSD(T)] using augmented correlation-consistent quintuple-zeta basis set (aV5Z) plus bond functions. Full counterpoise correction was employed to correct the basis-set superposition error. The hypersurface was fitted using artificial neural network method with a root mean square error of 0.1085 cm-1 for more than 8000 ab initio points. The complex was found to prefer a linear Ar-H-F equilibrium structure. The three-dimensional discrete variable representation method and the Lanczos propagation algorithm were then employed to calculate the rovibrational states without separating inter- and intra- molecular nuclear motions. The calculated vibrational energies of Ar-HF differ from the experiment values within about 1 cm-1 on the first four HF vibrational states, and the predicted pure rotational energies on (0000) and (1000) vibrational states are deviated from the observed value by about 1%, which shows the accuracy of our new PES.

One-step synthesis of three-dimensional Pd polyhedron networks with enhanced electrocatalytic performance.

PubMed

Xu, You; Xu, Rui; Cui, Jianhua; Liu, Yang; Zhang, Bin

2012-04-21

Three-dimensional Pd polyhedron networks (Pd PNs) have been fabricated for the first time through a one-step, Cu(2+)-assisted, solution-chemical approach. These as-prepared 3D Pd PNs exhibit high stability and remarkably improved electrocatalytic activity toward formic acid oxidation over commercially available Pd black. This journal is © The Royal Society of Chemistry 2012

Chemical processing of three-dimensional graphene networks on transparent conducting electrodes for depleted-heterojunction quantum dot solar cells.

PubMed

Tavakoli, Mohammad Mahdi; Simchi, Abdolreza; Fan, Zhiyong; Aashuri, Hossein

2016-01-07

We present a novel chemical procedure to prepare three-dimensional graphene networks (3DGNs) as a transparent conductive film to enhance the photovoltaic performance of PbS quantum-dot (QD) solar cells. It is shown that 3DGN electrodes enhance electron extraction, yielding a 30% improvement in performance compared with the conventional device.

Water-network percolation transitions in hydrated yeast

NASA Astrophysics Data System (ADS)

Sokołowska, Dagmara; Król-Otwinowska, Agnieszka; Mościcki, Józef K.

2004-11-01

We discovered two percolation processes in succession in dc conductivity of bulk baker’s yeast in the course of dehydration. Critical exponents characteristic for the three-dimensional network for heavily hydrated system, and two dimensions in the light hydration limit, evidenced a dramatic change of the water network dimensionality in the dehydration process.

Clinical application of three-dimensional printing to the management of complex univentricular hearts with abnormal systemic or pulmonary venous drainage.

PubMed

McGovern, Eimear; Kelleher, Eoin; Snow, Aisling; Walsh, Kevin; Gadallah, Bassem; Kutty, Shelby; Redmond, John M; McMahon, Colin J

2017-09-01

In recent years, three-dimensional printing has demonstrated reliable reproducibility of several organs including hearts with complex congenital cardiac anomalies. This represents the next step in advanced image processing and can be used to plan surgical repair. In this study, we describe three children with complex univentricular hearts and abnormal systemic or pulmonary venous drainage, in whom three-dimensional printed models based on CT data assisted with preoperative planning. For two children, after group discussion and examination of the models, a decision was made not to proceed with surgery. We extend the current clinical experience with three-dimensional printed modelling and discuss the benefits of such models in the setting of managing complex surgical problems in children with univentricular circulation and abnormal systemic or pulmonary venous drainage.

Secondary motion in three-dimensional branching networks

NASA Astrophysics Data System (ADS)

Guha, Abhijit; Pradhan, Kaustav

2017-06-01

A major aim of the present work is to understand and thoroughly document the generation, the three-dimensional distribution, and the evolution of the secondary motion as the fluid progresses downstream through a branched network. Six generations (G0-G5) of branches (involving 63 straight portions and 31 bifurcation modules) are computed in one go; such computational challenges are rarely taken in the literature. More than 30 × 106 computational elements are employed for high precision of computed results and fine quality of the flow visualization diagrams. The study of co-planar vis-à-vis non-planar space-filling configurations establishes a quantitative evaluation of the dependence of the fluid dynamics on the three-dimensional arrangement of the same individual branches. As compared to the secondary motion in a simple curved pipe, three distinctive features, viz., the change of shape and size of the flow-cross-section, the division of non-uniform primary flow in a bifurcation module, and repeated switchover from clockwise to anticlockwise curvature and vice versa in the flow path, make the present situation more complex. It is shown that the straight portions in the network, in general, attenuate the secondary motion, while the three-dimensionally complex bifurcation modules generate secondary motion and may alter the number, arrangement, and structure of vortices. A comprehensive picture of the evolution of quantitative flow visualizations of the secondary motion is achieved by constructing contours of secondary velocity | v → S | , streamwise vorticity ω S , and λ 2 iso-surfaces. It is demonstrated, for example, that for in-plane configuration, the vortices on any plane appear in pair (i.e., for each clockwise rotating vortex, there is an otherwise identical anticlockwise vortex), whereas the vortices on a plane for the out-of-plane configuration may be dissimilar, and there may even be an odd number of vortices. We have formulated three new parameters (ES/P, δ S F , and δ G n ) for a quantitative description of the overall features of the secondary flow field. δ S F represents a non-uniformity index of the secondary flow in an individual branch, ES/P represents the mass-flow-averaged relative kinetic energy of the secondary motion in an individual branch, and δ G n provides a measure of the non-uniformity of the secondary flow between various branches of the same generation Gn. The repeated enhancement of the secondary kinetic energy in the bifurcation modules is responsible for the occurrence of significant values of ES/P even in generation G5. For both configurations, it is found that for any bifurcation module, the value of ES/P is greater in that daughter branch in which the mass-flow rate is greater. Even though the various contour plots of the complex secondary flow structure appear visually very different from one another, the values of δ S F are found to lie within a small range ( 0.37 ≤ δ S F ≤ 0.66 ) for the six-generation networks studied. It is shown that δ G n grows as the generation number Gn increases. It is established that the out-of-plane configuration, in general, creates more secondary kinetic energy (higher ES/P), a similar level of non-uniformity in the secondary flow in an individual branch (similar δ S F ), and a significantly lower level of non-uniformity in the distribution of secondary motion among various branches of the same generation (much lower δ G n ), as compared to the in-plane arrangement of the same branches.

Secondary motion in three-dimensional branching networks

PubMed Central

Guha, Abhijit; Pradhan, Kaustav

2017-01-01

A major aim of the present work is to understand and thoroughly document the generation, the three-dimensional distribution, and the evolution of the secondary motion as the fluid progresses downstream through a branched network. Six generations (G0-G5) of branches (involving 63 straight portions and 31 bifurcation modules) are computed in one go; such computational challenges are rarely taken in the literature. More than 30 × 106 computational elements are employed for high precision of computed results and fine quality of the flow visualization diagrams. The study of co-planar vis-à-vis non-planar space-filling configurations establishes a quantitative evaluation of the dependence of the fluid dynamics on the three-dimensional arrangement of the same individual branches. As compared to the secondary motion in a simple curved pipe, three distinctive features, viz., the change of shape and size of the flow-cross-section, the division of non-uniform primary flow in a bifurcation module, and repeated switchover from clockwise to anticlockwise curvature and vice versa in the flow path, make the present situation more complex. It is shown that the straight portions in the network, in general, attenuate the secondary motion, while the three-dimensionally complex bifurcation modules generate secondary motion and may alter the number, arrangement, and structure of vortices. A comprehensive picture of the evolution of quantitative flow visualizations of the secondary motion is achieved by constructing contours of secondary velocity v→S, streamwise vorticity ωS, and λ2 iso-surfaces. It is demonstrated, for example, that for in-plane configuration, the vortices on any plane appear in pair (i.e., for each clockwise rotating vortex, there is an otherwise identical anticlockwise vortex), whereas the vortices on a plane for the out-of-plane configuration may be dissimilar, and there may even be an odd number of vortices. We have formulated three new parameters (ES/P, δSF, and δGn) for a quantitative description of the overall features of the secondary flow field. δSF represents a non-uniformity index of the secondary flow in an individual branch, ES/P represents the mass-flow-averaged relative kinetic energy of the secondary motion in an individual branch, and δGn provides a measure of the non-uniformity of the secondary flow between various branches of the same generation Gn. The repeated enhancement of the secondary kinetic energy in the bifurcation modules is responsible for the occurrence of significant values of ES/P even in generation G5. For both configurations, it is found that for any bifurcation module, the value of ES/P is greater in that daughter branch in which the mass-flow rate is greater. Even though the various contour plots of the complex secondary flow structure appear visually very different from one another, the values of δSF are found to lie within a small range (0.37≤δSF≤0.66) for the six-generation networks studied. It is shown that δGn grows as the generation number Gn increases. It is established that the out-of-plane configuration, in general, creates more secondary kinetic energy (higher ES/P), a similar level of non-uniformity in the secondary flow in an individual branch (similar δSF), and a significantly lower level of non-uniformity in the distribution of secondary motion among various branches of the same generation (much lower δGn), as compared to the in-plane arrangement of the same branches. PMID:28713213

Platonic Relationships among Resistors

ERIC Educational Resources Information Center

Allen, Bradley; Liu, Tongtian

2015-01-01

Calculating the effective resistance of an electrical network is a common problem in introductory physics courses. Such calculations are typically restricted to two-dimensional networks, though even such networks can become increasingly complex, leading to several studies on their properties. Furthermore, several authors have used advanced…

Decaaquabis(μ3-4-hydroxypyridine-2,6-dicarboxylato)bis(4-hydroxypyridine-2,6-dicarboxylato)tetramanganese(II) 3.34-hydrate: a new three-dimensional open metal-organic framework based on a tetranuclear Mn(II) complex of chelidamic acid and undecameric stitching water clusters.

PubMed

Mirzaei, M; Lippolis, V; Eshtiagh-Hosseini, H; Mahjoobizadeh, M

2012-01-01

4-Hydroxypyridine-2,6-dicarboxylic acid (chelidamic acid, cdaH(3)) reacts with MnCl(2)·2H(2)O in the presence of 2-amino-4-methylpyrimidine in water to afford the tetranuclear title complex, [Mn(4)(C(8)H(3)NO(5))(4)(H(2)O)(10)]·3.34H(2)O, built through carboxylate bridging. The tetranuclear complex sits on a centre of inversion at (½, ½, ½). In the crystal, discrete undecameric (H(2)O)(10.34) water clusters (involving both coordinated and uncoordinated water molecules, with one site of an uncoordinated water molecule not fully occupied) assemble these tetranuclear Mn(II) complex units via an intricate array of hydrogen bonding into an overall three-dimensional network. The degree of structuring of the (H(2)O)(10.34) supramolecular association of water molecules observed in the present compound, imposed by its environment and vice versa, will be discussed in comparison to that observed for the (H(2)O)(14) supramolecular clusters in the case of the dinuclear complex [Mn(2)(cdaH)(2)(H(2)O)(4)]·4H(2)O [Ghosh et al. (2005). Inorg. Chem. 44, 3856-3862]. © 2012 International Union of Crystallography

On learning navigation behaviors for small mobile robots with reservoir computing architectures.

PubMed

Antonelo, Eric Aislan; Schrauwen, Benjamin

2015-04-01

This paper proposes a general reservoir computing (RC) learning framework that can be used to learn navigation behaviors for mobile robots in simple and complex unknown partially observable environments. RC provides an efficient way to train recurrent neural networks by letting the recurrent part of the network (called reservoir) be fixed while only a linear readout output layer is trained. The proposed RC framework builds upon the notion of navigation attractor or behavior that can be embedded in the high-dimensional space of the reservoir after learning. The learning of multiple behaviors is possible because the dynamic robot behavior, consisting of a sensory-motor sequence, can be linearly discriminated in the high-dimensional nonlinear space of the dynamic reservoir. Three learning approaches for navigation behaviors are shown in this paper. The first approach learns multiple behaviors based on the examples of navigation behaviors generated by a supervisor, while the second approach learns goal-directed navigation behaviors based only on rewards. The third approach learns complex goal-directed behaviors, in a supervised way, using a hierarchical architecture whose internal predictions of contextual switches guide the sequence of basic navigation behaviors toward the goal.

SERS investigations and electrical recording of neuronal networks with three-dimensional plasmonic nanoantennas (Conference Presentation)

NASA Astrophysics Data System (ADS)

De Angelis, Francesco

2017-06-01

SERS investigations and electrical recording of neuronal networks with three-dimensional plasmonic nanoantennas Michele Dipalo, Valeria Caprettini, Anbrea Barbaglia, Laura Lovato, Francesco De Angelis e-mail: francesco.deangelis@iit.it Istituto Italiano di Tecnologia, Via Morego 30, 16163, Genova Biological systems are analysed mainly by optical, chemical or electrical methods. Normally each of these techniques provides only partial information about the environment, while combined investigations could reveal new phenomena occurring in complex systems such as in-vitro neuronal networks. Aiming at the merging of optical and electrical investigations of biological samples, we introduced three-dimensional plasmonic nanoantennas on CMOS-based electrical sensors [1]. The overall device is then capable of enhanced Raman Analysis of cultured cells combined with electrical recording of neuronal activity. The Raman measurements show a much higher sensitivity when performed on the tip of the nanoantenna in respect to the flat substrate [2]; this effect is a combination of the high plasmonic field enhancement and of the tight adhesion of cells on the nanoantenna tip. Furthermore, when plasmonic opto-poration is exploited [3] the 3D nanoelectrodes are able to penetrate through the cell membrane thus accessing the intracellular environment. Our latest results (unpublished) show that the technique is completely non-invasive and solves many problems related to state-of-the-art intracellular recording approaches on large neuronal networks. This research received funding from ERC-IDEAS Program: "Neuro-Plasmonics" [Grant n. 616213]. References: [1] M. Dipalo, G. C. Messina, H. Amin, R. La Rocca, V. Shalabaeva, A. Simi, A. Maccione, P. Zilio, L. Berdondini, F. De Angelis, Nanoscale 2015, 7, 3703. [2] R. La Rocca, G. C. Messina, M. Dipalo, V. Shalabaeva, F. De Angelis, Small 2015, 11, 4632. [3] G. C. Messina et al., Spatially, Temporally, and Quantitatively Controlled Delivery of Broad Range of Molecules into Selected Cells through Plasmonic Nanotubes. Advanced Materials 2015.

Two- and three-dimensional networks of gadolinium(III) with dicarboxylate ligands: synthesis, crystal structure, and magnetic properties.

PubMed

Cañadillas-Delgado, Laura; Pasan, Jorge; Fabelo, Oscar; Hernandez-Molina, María; Lloret, Francesc; Julve, Miguel; Ruiz-Pérez, Catalina

2006-12-25

Four gadolinium(III) complexes with dicarboxylate ligands of formulas [Gd2(mal)3(H2O)5]n.2nH2O (1), [Gd2(mal)3(H2O)6]n (2), [NaGd(mal)(ox)(H2O)3]n (3), and [Gd2(ox)3(H2O)6]n.2.5nH2O (4) (mal = malonate; ox = oxalate) have been prepared, and their magnetic properties have been investigated as a function of the temperature. The structures of 1-3 have been determined by X-ray diffraction methods. The crystal structure of 4 was already known, and it is made of hexagonal layers of Gd atoms that are bridged by bis-bidentate oxalate. Compound 1 is isostructural with the europium(III) malonate complex [Eu2(mal)3(H2O)5]n.2nH2O,1 whose structure was reported elsewhere. The Gd atoms in 1 define a two-dimensional network where a terminal bidentate and bridging bidentate/bis-monodentate and tris-bidentate coordination modes of malonate occur. Compound 2 has a three-dimensional structure with a structural phase transition at 226 K, which involves a change of the space group from I2/a to Ia. Although its structure at room temperature was already known, that below 226 K was not. Pairs of Gd atoms with a double oxo-carboxylate bridge occur in both phases, and the main differences between both structures deal with the Gd environment and the H-bond pattern. 3 is also a three-dimensional compound, and it was obtained by reacting Gd(III) ions with malonic acid in a silica gel medium. Oxalic acid results as an oxidized product of the malonic acid, and single crystals of the heteroleptic complex were produced. The Gd atoms in 3 are connected through bis-bidentate oxalate and carboxylate-malonate bridges in the anti-anti and anti-syn coordination modes. Compounds 1 and 2 exhibit weak but significant ferromagnetic couplings between the Gd(III) ions through the single (1) and double (2) oxo-carboxylate bridges, whereas antiferromagnetic interactions across the bis-bidentate oxalate account for the overall antiferromagnetic behavior observed in 3 and 4.

Power-scaling performance of a three-dimensional tritium betavoltaic diode

NASA Astrophysics Data System (ADS)

Liu, Baojun; Chen, Kevin P.; Kherani, Nazir P.; Zukotynski, Stefan

2009-12-01

Three-dimensional diodes fabricated by electrochemical etching are exposed to tritium gas at pressures from 0.05 to 33 atm at room temperature to examine its power scaling performance. It is shown that the three-dimensional microporous structure overcomes the self-absorption limited saturation of beta flux at high tritium pressures. These results are contrasted against the three-dimensional device powered in one instance by tritium absorbed in the near surface region of the three-dimensional microporous network, and in another by a planar scandium tritide foil. These findings suggest that direct tritium occlusion in the near surface of three-dimensional diode can improve the specific power production.

Three-dimensional WS2 nanosheet networks for H2O2 produced for cell signaling

NASA Astrophysics Data System (ADS)

Tang, Jing; Quan, Yingzhou; Zhang, Yueyu; Jiang, Min; Al-Enizi, Abdullah M.; Kong, Biao; An, Tiance; Wang, Wenshuo; Xia, Limin; Gong, Xingao; Zheng, Gengfeng

2016-03-01

Hydrogen peroxide (H2O2) is an important molecular messenger for cellular signal transduction. The capability of direct probing of H2O2 in complex biological systems can offer potential for elucidating its manifold roles in living systems. Here we report the fabrication of three-dimensional (3D) WS2 nanosheet networks with flower-like morphologies on a variety of conducting substrates. The semiconducting WS2 nanosheets with largely exposed edge sites on flexible carbon fibers enable abundant catalytically active sites, excellent charge transfer, and high permeability to chemicals and biomaterials. Thus, the 3D WS2-based nano-bio-interface exhibits a wide detection range, high sensitivity and rapid response time for H2O2, and is capable of visualizing endogenous H2O2 produced in living RAW 264.7 macrophage cells and neurons. First-principles calculations further demonstrate that the enhanced sensitivity of probing H2O2 is attributed to the efficient and spontaneous H2O2 adsorption on WS2 nanosheet edge sites. The combined features of 3D WS2 nanosheet networks suggest attractive new opportunities for exploring the physiological roles of reactive oxygen species like H2O2 in living systems.Hydrogen peroxide (H2O2) is an important molecular messenger for cellular signal transduction. The capability of direct probing of H2O2 in complex biological systems can offer potential for elucidating its manifold roles in living systems. Here we report the fabrication of three-dimensional (3D) WS2 nanosheet networks with flower-like morphologies on a variety of conducting substrates. The semiconducting WS2 nanosheets with largely exposed edge sites on flexible carbon fibers enable abundant catalytically active sites, excellent charge transfer, and high permeability to chemicals and biomaterials. Thus, the 3D WS2-based nano-bio-interface exhibits a wide detection range, high sensitivity and rapid response time for H2O2, and is capable of visualizing endogenous H2O2 produced in living RAW 264.7 macrophage cells and neurons. First-principles calculations further demonstrate that the enhanced sensitivity of probing H2O2 is attributed to the efficient and spontaneous H2O2 adsorption on WS2 nanosheet edge sites. The combined features of 3D WS2 nanosheet networks suggest attractive new opportunities for exploring the physiological roles of reactive oxygen species like H2O2 in living systems. Electronic supplementary information (ESI) available: Additional figures. See DOI: 10.1039/c5nr09236a

A hybrid intelligent method for three-dimensional short-term prediction of dissolved oxygen content in aquaculture.

PubMed

Chen, Yingyi; Yu, Huihui; Cheng, Yanjun; Cheng, Qianqian; Li, Daoliang

2018-01-01

A precise predictive model is important for obtaining a clear understanding of the changes in dissolved oxygen content in crab ponds. Highly accurate interval forecasting of dissolved oxygen content is fundamental to reduce risk, and three-dimensional prediction can provide more accurate results and overall guidance. In this study, a hybrid three-dimensional (3D) dissolved oxygen content prediction model based on a radial basis function (RBF) neural network, K-means and subtractive clustering was developed and named the subtractive clustering (SC)-K-means-RBF model. In this modeling process, K-means and subtractive clustering methods were employed to enhance the hyperparameters required in the RBF neural network model. The comparison of the predicted results of different traditional models validated the effectiveness and accuracy of the proposed hybrid SC-K-means-RBF model for three-dimensional prediction of dissolved oxygen content. Consequently, the proposed model can effectively display the three-dimensional distribution of dissolved oxygen content and serve as a guide for feeding and future studies.

Cocrystals of Kemp’s triacid. Part III: Structure of hydrogen-bonded complex of Kemp’s triacid with 1,1,3,3-tetramethylguanidine studied by X-ray and FT-IR methods

NASA Astrophysics Data System (ADS)

Huczyński, Adam; Ratajczak-Sitarz, Małgorzata; Katrusiak, Andrzej; Brzezinski, Bogumil

2008-12-01

The 2:2 hydrogen-bonded complex between Kemp's triacid (KTA) and 1,1,3,3-tetramethylguanidine (TMG) has been synthesised and studied by X-ray diffraction and by FT-IR spectroscopy. Cocrystals of KTA-TMG belong to the monoclinic system and crystallize in the space group is P21 with a = 10.5017(3) Å, b = 7.9504(3) Å, c = 11.8910(4) Å, β = 104.004(4)° and Z = 2. The ring of the KTA monoanion molecule exhibits a chair conformation with all three carboxylic groups in the axial positions and all three methyl groups in the equatorial positions. In the crystal of the complex, cooperative systems involving inter- and intra-molecular hydrogen bonds are formed. In the solid state two protonated TMG molecules and two deprotonated KTA molecules form a dimer in which three-dimensional hydrogen-bonded networks are found.

Computer-aided mechanogenesis of skeletal muscle organs from single cells in vitro

NASA Technical Reports Server (NTRS)

Vanderburgh, Herman H.; Swasdison, Somporn; Karlisch, Patricia

1991-01-01

Complex mechanical forces generated in the growing embryo play an important role in organogenesis. Computerized application of similar forces to differentiating skeletal muscle myoblasts in vitro generate three dimensional artificial muscle organs. These organs contain parallel networks of long unbranched myofibers organized into fascicle-like structures. Tendon development is initiated and the muscles are capable of performing directed, functional work. Kinetically engineered organs provide a new method for studying the growth and development of normal and diseased skeletal muscle.

Computer aided mechanogenesis of skeletal muscle organs from single cells in vitro

NASA Technical Reports Server (NTRS)

Vandenburgh, Herman H.; Swasdison, Somporn; Karlisch, Patricia

1990-01-01

Complex mechanical forces generated in the growing embryo play an important role in organogenesis. Computerized application of similar forces to differentiating skeletal muscle myoblasts in vitro generate three dimensional artificial muscle organs. These organs contain parallel networks of long unbranched myofibers organized into fascicle-like structures. Tendon development is initiated and the muscles are capable of performing directed, functional work. Kinetically engineered organs provide a new method for studying the growth and development of normal and diseased skeletal muscle.

IMPETUS - Interactive MultiPhysics Environment for Unified Simulations.

PubMed

Ha, Vi Q; Lykotrafitis, George

2016-12-08

We introduce IMPETUS - Interactive MultiPhysics Environment for Unified Simulations, an object oriented, easy-to-use, high performance, C++ program for three-dimensional simulations of complex physical systems that can benefit a large variety of research areas, especially in cell mechanics. The program implements cross-communication between locally interacting particles and continuum models residing in the same physical space while a network facilitates long-range particle interactions. Message Passing Interface is used for inter-processor communication for all simulations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Crystal structure of tin(IV) chloride octa­hydrate

PubMed Central

Hennings, Erik; Schmidt, Horst; Voigt, Wolfgang

2014-01-01

The title compound, [SnCl4(H2O)2]·6H2O, was crystallized according to the solid–liquid phase diagram at lower temperatures. It is built-up of SnCl4(H2O)2 octa­hedral units (point group symmetry 2) and lattice water mol­ecules. An intricate three-dimensional network of O—H⋯O and O—H⋯Cl hydrogen bonds between the complex molecules and the lattice water molecules is formed in the crystal structure. PMID:25552971

Tetraammine(carbonato-κ2 O,O′)cobalt(III) perchlorate

PubMed Central

Mohan, Singaravelu Chandra; Jenniefer, Samson Jegan; Muthiah, Packianathan Thomas; Jothivenkatachalam, Kandasamy

2013-01-01

In the title complex, [Co(CO3)(NH3)4]ClO4, both the cation and anion lie on a mirror plane. The CoIII ion is coordinated by two NH3 ligands and a chelating carbonato ligand in the equatorial sites and by two NH3 groups in the axial sites, forming a distorted octa­hedral geometry. In the crystal, N—H⋯O hydrogen bonds connect the anions and cations, forming a three-dimensional network. PMID:24109252

Ferromagnetic coupling in the three-dimensional malonato-bridged gadoliniumIII complex [Gd2(mal)3(H2O)6] (H2mal = malonic acid).

PubMed

Hernández-Molina, María; Ruiz-Pérez, Catalina; López, Trinidad; Lloret, Francesc; Julve, Miguel

2003-09-08

The novel gadolinium(III) complex of formula [Gd(2)(mal)(3)(H(2)O)(6)] (1) (H(2)mal = 1,3-propanedioic acid) has been prepared and characterized by X-ray diffraction analysis. Crystal data for 1: monoclinic, space group I2/a, a = 11.1064(10) A, b = 12.2524(10) A, c =13.6098(2) A, beta = 92.925(10) degrees, U = 1849.5(3) A(3), Z = 4. Compound 1 is a three-dimensional network made up of malonate-bridged gadolinium(III) ions where the malonate exhibits two bridging modes, eta(5)-bidentate + unidentate and eta(3):eta(3) + bis(unidentate). The gadolinium atom is nine-coordinate with three water molecules and six malonate oxygen atoms from three malonate ligands forming a distorted monocapped square antiprism. The shortest metal-metal separations are 4.2763(3) A [through the oxo-carboxylate bridge] and 6.541(3) A [through the carboxylate in the anti-syn coordination mode]. The value of the angle at the oxo-carboxylate atom is 116.8(2) degrees. Variable-temperature magnetic susceptibility measurements reveal the occurrence of a significant ferromagnetic interaction through the oxo-carboxylate pathway (J = +0.048(1) cm(-1), H = -JS(Gd(1)) x S(Gd(1a))).

Reconstruction of three-dimensional porous media using generative adversarial neural networks

NASA Astrophysics Data System (ADS)

Mosser, Lukas; Dubrule, Olivier; Blunt, Martin J.

2017-10-01

To evaluate the variability of multiphase flow properties of porous media at the pore scale, it is necessary to acquire a number of representative samples of the void-solid structure. While modern x-ray computer tomography has made it possible to extract three-dimensional images of the pore space, assessment of the variability in the inherent material properties is often experimentally not feasible. We present a method to reconstruct the solid-void structure of porous media by applying a generative neural network that allows an implicit description of the probability distribution represented by three-dimensional image data sets. We show, by using an adversarial learning approach for neural networks, that this method of unsupervised learning is able to generate representative samples of porous media that honor their statistics. We successfully compare measures of pore morphology, such as the Euler characteristic, two-point statistics, and directional single-phase permeability of synthetic realizations with the calculated properties of a bead pack, Berea sandstone, and Ketton limestone. Results show that generative adversarial networks can be used to reconstruct high-resolution three-dimensional images of porous media at different scales that are representative of the morphology of the images used to train the neural network. The fully convolutional nature of the trained neural network allows the generation of large samples while maintaining computational efficiency. Compared to classical stochastic methods of image reconstruction, the implicit representation of the learned data distribution can be stored and reused to generate multiple realizations of the pore structure very rapidly.

Catalytic Subunit 1 of Protein Phosphatase 2A Is a Subunit of the STRIPAK Complex and Governs Fungal Sexual Development.

PubMed

Beier, Anna; Teichert, Ines; Krisp, Christoph; Wolters, Dirk A; Kück, Ulrich

2016-06-21

The generation of complex three-dimensional structures is a key developmental step for most eukaryotic organisms. The details of the molecular machinery controlling this step remain to be determined. An excellent model system to study this general process is the generation of three-dimensional fruiting bodies in filamentous fungi like Sordaria macrospora Fruiting body development is controlled by subunits of the highly conserved striatin-interacting phosphatase and kinase (STRIPAK) complex, which has been described in organisms ranging from yeasts to humans. The highly conserved heterotrimeric protein phosphatase PP2A is a subunit of STRIPAK. Here, catalytic subunit 1 of PP2A was functionally characterized. The Δpp2Ac1 strain is sterile, unable to undergo hyphal fusion, and devoid of ascogonial septation. Further, PP2Ac1, together with STRIPAK subunit PRO22, governs vegetative and stress-related growth. We revealed in vitro catalytic activity of wild-type PP2Ac1, and our in vivo analysis showed that inactive PP2Ac1 blocks the complementation of the sterile deletion strain. Tandem affinity purification, followed by mass spectrometry and yeast two-hybrid analysis, verified that PP2Ac1 is a subunit of STRIPAK. Further, these data indicate links between the STRIPAK complex and other developmental signaling pathways, implying the presence of a large interconnected signaling network that controls eukaryotic developmental processes. The insights gained in our study can be transferred to higher eukaryotes and will be important for understanding eukaryotic cellular development in general. The striatin-interacting phosphatase and kinase (STRIPAK) complex is highly conserved from yeasts to humans and is an important regulator of numerous eukaryotic developmental processes, such as cellular signaling and cell development. Although functional insights into the STRIPAK complex are accumulating, the detailed molecular mechanisms of single subunits are only partially understood. The first fungal STRIPAK was described in Sordaria macrospora, which is a well-established model organism used to study the formation of fungal fruiting bodies, three-dimensional organ-like structures. We analyzed STRIPAK subunit PP2Ac1, catalytic subunit 1 of protein phosphatase PP2A, to study the importance of the catalytic activity of this protein during sexual development. The results of our yeast two-hybrid analysis and tandem affinity purification, followed by mass spectrometry, indicate that PP2Ac1 activity connects STRIPAK with other signaling pathways and thus forms a large interconnected signaling network. Copyright © 2016 Beier et al.

Transport and percolation in complex networks

NASA Astrophysics Data System (ADS)

Li, Guanliang

To design complex networks with optimal transport properties such as flow efficiency, we consider three approaches to understanding transport and percolation in complex networks. We analyze the effects of randomizing the strengths of connections, randomly adding long-range connections to regular lattices, and percolation of spatially constrained networks. Various real-world networks often have links that are differentiated in terms of their strength, intensity, or capacity. We study the distribution P(σ) of the equivalent conductance for Erdoḧs-Rényi (ER) and scale-free (SF) weighted resistor networks with N nodes, for which links are assigned with conductance σ i ≡ e-axi, where xi is a random variable with 0 < xi < 1. We find, both analytically and numerically, that P(σ) for ER networks exhibits two regimes: (i) For σ < e-apc, P(σ) is independent of N and scales as a power law P(σ) ˜ sk/a-1 . Here pc = 1/ is the critical percolation threshold of the network and is the average degree of the network. (ii) For σ > e -apc, P(σ) has strong N dependence and scales as P(σ) ˜ f(σ, apc/N1/3). Transport properties are greatly affected by the topology of networks. We investigate the transport problem in lattices with long-range connections and subject to a cost constraint, seeking design principles for optimal transport networks. Our network is built from a regular d-dimensional lattice to be improved by adding long-range connections with probability Pij ˜ r-aij , where rij is the lattice distance between site i and j. We introduce a cost constraint on the total length of the additional links and find optimal transport in the system for α = d + 1, established here for d = 1, 2 and 3 for regular lattices and df for fractals. Remarkably, this cost constraint approach remains optimal, regardless of the strategy used for transport, whether based on local or global knowledge of the network structure. To further understand the role that long-range connections play in optimizing the transport of complex systems, we study the percolation of spatially constrained networks. We now consider originally empty lattices embedded in d dimensions by adding long-range connections with the same power law probability p(r) ˜ r -α. We find that, for α ≤ d, the percolation transition belongs to the universality class of percolation in ER networks, while for α > 2d it belongs to the universality class of percolation in regular lattices (for one-dimensional linear chain, there is no percolation transition). However for d < α < 2d, the percolation properties show new intermediate behavior different from ER networks, with critical exponents that depend on α.

A novel method to acquire 3D data from serial 2D images of a dental cast

NASA Astrophysics Data System (ADS)

Yi, Yaxing; Li, Zhongke; Chen, Qi; Shao, Jun; Li, Xinshe; Liu, Zhiqin

2007-05-01

This paper introduced a newly developed method to acquire three-dimensional data from serial two-dimensional images of a dental cast. The system consists of a computer and a set of data acquiring device. The data acquiring device is used to take serial pictures of the a dental cast; an artificial neural network works to translate two-dimensional pictures to three-dimensional data; then three-dimensional image can reconstruct by the computer. The three-dimensional data acquiring of dental casts is the foundation of computer-aided diagnosis and treatment planning in orthodontics.

ADFNE: Open source software for discrete fracture network engineering, two and three dimensional applications

NASA Astrophysics Data System (ADS)

Fadakar Alghalandis, Younes

2017-05-01

Rapidly growing topic, the discrete fracture network engineering (DFNE), has already attracted many talents from diverse disciplines in academia and industry around the world to challenge difficult problems related to mining, geothermal, civil, oil and gas, water and many other projects. Although, there are few commercial software capable of providing some useful functionalities fundamental for DFNE, their costs, closed code (black box) distributions and hence limited programmability and tractability encouraged us to respond to this rising demand with a new solution. This paper introduces an open source comprehensive software package for stochastic modeling of fracture networks in two- and three-dimension in discrete formulation. Functionalities included are geometric modeling (e.g., complex polygonal fracture faces, and utilizing directional statistics), simulations, characterizations (e.g., intersection, clustering and connectivity analyses) and applications (e.g., fluid flow). The package is completely written in Matlab scripting language. Significant efforts have been made to bring maximum flexibility to the functions in order to solve problems in both two- and three-dimensions in an easy and united way that is suitable for beginners, advanced and experienced users.

Neural network computer simulation of medical aerosols.

PubMed

Richardson, C J; Barlow, D J

1996-06-01

Preliminary investigations have been conducted to assess the potential for using artificial neural networks to simulate aerosol behaviour, with a view to employing this type of methodology in the evaluation and design of pulmonary drug-delivery systems. Details are presented of the general purpose software developed for these tasks; it implements a feed-forward back-propagation algorithm with weight decay and connection pruning, the user having complete run-time control of the network architecture and mode of training. A series of exploratory investigations is then reported in which different network structures and training strategies are assessed in terms of their ability to simulate known patterns of fluid flow in simple model systems. The first of these involves simulations of cellular automata-generated data for fluid flow through a partially obstructed two-dimensional pipe. The artificial neural networks are shown to be highly successful in simulating the behaviour of this simple linear system, but with important provisos relating to the information content of the training data and the criteria used to judge when the network is properly trained. A second set of investigations is then reported in which similar networks are used to simulate patterns of fluid flow through aerosol generation devices, using training data furnished through rigorous computational fluid dynamics modelling. These more complex three-dimensional systems are modelled with equal success. It is concluded that carefully tailored, well trained networks could provide valuable tools not just for predicting but also for analysing the spatial dynamics of pharmaceutical aerosols.

Pruning artificial neural networks using neural complexity measures.

PubMed

Jorgensen, Thomas D; Haynes, Barry P; Norlund, Charlotte C F

2008-10-01

This paper describes a new method for pruning artificial neural networks, using a measure of the neural complexity of the neural network. This measure is used to determine the connections that should be pruned. The measure computes the information-theoretic complexity of a neural network, which is similar to, yet different from previous research on pruning. The method proposed here shows how overly large and complex networks can be reduced in size, whilst retaining learnt behaviour and fitness. The technique proposed here helps to discover a network topology that matches the complexity of the problem it is meant to solve. This novel pruning technique is tested in a robot control domain, simulating a racecar. It is shown, that the proposed pruning method is a significant improvement over the most commonly used pruning method Magnitude Based Pruning. Furthermore, some of the pruned networks prove to be faster learners than the benchmark network that they originate from. This means that this pruning method can also help to unleash hidden potential in a network, because the learning time decreases substantially for a pruned a network, due to the reduction of dimensionality of the network.

Supramolecular complexes of Co(II), Ni(II) and Zn(II) p-hydroxybenzoates with caffeine: Synthesis, spectral characterization and crystal structure

NASA Astrophysics Data System (ADS)

Taşdemir, Erdal; Özbek, Füreya Elif; Sertçelik, Mustafa; Hökelek, Tuncer; Çelik, Raziye Çatak; Necefoğlu, Hacali

2016-09-01

Three novel complexes Co(II), Ni(II) and Zn(II) containing p-hydroxybenzoates and caffeine ligands were synthesized and characterized by elemental analysis, FT-IR and UV-vis Spectroscopy, molar conductivity and single crystal X-ray diffraction methods. The thermal properties of the synthesized complexes were investigated by TGA/DTA. The general formula of the complexes is [M(HOC6H4COO)2(H2O)4]·2(C8H10N4O2)·8H2O (where: M: Co, Ni and Zn). The IR studies showed that carboxylate groups of p-hydroxybenzoate ligands have monodentate coordination mode. The M2+ ions are octahedrally coordinated by two p-hydroxybenzoate ligands, four water molecules leading to an overall MO6 coordination environment. The medium-strength hydrogen bondings involving the uncoordinated caffeine ligands and water molecules, coordinated and uncoordinated water molecules and p-hydroxybenzoate ligands lead to three-dimensional supramolecular networks in the crystal structures.

Fracture network created by 3D printer and its validation using CT images

NASA Astrophysics Data System (ADS)

Suzuki, A.; Watanabe, N.; Li, K.; Horne, R. N.

2017-12-01

Understanding flow mechanisms in fractured media is essential for geoscientific research and geological development industries. This study used 3D printed fracture networks in order to control the properties of fracture distributions inside the sample. The accuracy and appropriateness of creating samples by the 3D printer was investigated by using a X-ray CT scanner. The CT scan images suggest that the 3D printer is able to reproduce complex three-dimensional spatial distributions of fracture networks. Use of hexane after printing was found to be an effective way to remove wax for the post-treatment. Local permeability was obtained by the cubic law and used to calculate the global mean. The experimental value of the permeability was between the arithmetic and geometric means of the numerical results, which is consistent with conventional studies. This methodology based on 3D printed fracture networks can help validate existing flow modeling and numerical methods.

A network model for characterizing brine channels in sea ice

NASA Astrophysics Data System (ADS)

Lieblappen, Ross M.; Kumar, Deip D.; Pauls, Scott D.; Obbard, Rachel W.

2018-03-01

The brine pore space in sea ice can form complex connected structures whose geometry is critical in the governance of important physical transport processes between the ocean, sea ice, and surface. Recent advances in three-dimensional imaging using X-ray micro-computed tomography have enabled the visualization and quantification of the brine network morphology and variability. Using imaging of first-year sea ice samples at in situ temperatures, we create a new mathematical network model to characterize the topology and connectivity of the brine channels. This model provides a statistical framework where we can characterize the pore networks via two parameters, depth and temperature, for use in dynamical sea ice models. Our approach advances the quantification of brine connectivity in sea ice, which can help investigations of bulk physical properties, such as fluid permeability, that are key in both global and regional sea ice models.

Ultraviolet and Visible Photochemistry of Methanol at 3D Mesoporous Networks: TiO2 and Au-TiO2

DTIC Science & Technology

2013-05-23

methanol photochemistry at three-dimensionally (3D) networked aerogels of TiO2 or Au–TiO2 reveals that incorporated Au nanoparticles strongly sensitize...the oxide nanoarchitecture to visible light. Methanol dissociatively adsorbs at the surfaces of TiO2 and Au–TiO2 aerogels under dark, high-vacuum...photochemistry at three-dimensionally (3D) networked aerogels of TiO2 or Au–TiO2 reveals that incorporated Au nanoparticles strongly sensitize the oxide

Carbon nanotube dispersed conductive network for microbial fuel cells

NASA Astrophysics Data System (ADS)

Matsumoto, S.; Yamanaka, K.; Ogikubo, H.; Akasaka, H.; Ohtake, N.

2014-08-01

Microbial fuel cells (MFCs) are promising devices for capturing biomass energy. Although they have recently attracted considerable attention, their power densities are too low for practical use. Increasing their electrode surface area is a key factor for improving the performance of MFC. Carbon nanotubes (CNTs), which have excellent electrical conductivity and extremely high specific surface area, are promising materials for electrodes. However, CNTs are insoluble in aqueous solution because of their strong intertube van der Waals interactions, which make practical use of CNTs difficult. In this study, we revealed that CNTs have a strong interaction with Saccharomyces cerevisiae cells. CNTs attach to the cells and are dispersed in a mixture of water and S. cerevisiae, forming a three-dimensional CNT conductive network. Compared with a conventional two-dimensional electrode, such as carbon paper, the three-dimensional conductive network has a much larger surface area. By applying this conductive network to MFCs as an anode electrode, power density is increased to 176 μW/cm2, which is approximately 25-fold higher than that in the case without CNTs addition. Maximum current density is also increased to approximately 8-fold higher. These results suggest that three-dimensional CNT conductive network contributes to improve the performance of MFC by increasing surface area.

A VERSATILE SHARP INTERFACE IMMERSED BOUNDARY METHOD FOR INCOMPRESSIBLE FLOWS WITH COMPLEX BOUNDARIES

PubMed Central

Mittal, R.; Dong, H.; Bozkurttas, M.; Najjar, F.M.; Vargas, A.; von Loebbecke, A.

2010-01-01

A sharp interface immersed boundary method for simulating incompressible viscous flow past three-dimensional immersed bodies is described. The method employs a multi-dimensional ghost-cell methodology to satisfy the boundary conditions on the immersed boundary and the method is designed to handle highly complex three-dimensional, stationary, moving and/or deforming bodies. The complex immersed surfaces are represented by grids consisting of unstructured triangular elements; while the flow is computed on non-uniform Cartesian grids. The paper describes the salient features of the methodology with special emphasis on the immersed boundary treatment for stationary and moving boundaries. Simulations of a number of canonical two- and three-dimensional flows are used to verify the accuracy and fidelity of the solver over a range of Reynolds numbers. Flow past suddenly accelerated bodies are used to validate the solver for moving boundary problems. Finally two cases inspired from biology with highly complex three-dimensional bodies are simulated in order to demonstrate the versatility of the method. PMID:20216919

Complex Quantum Network Manifolds in Dimension d > 2 are Scale-Free

NASA Astrophysics Data System (ADS)

Bianconi, Ginestra; Rahmede, Christoph

2015-09-01

In quantum gravity, several approaches have been proposed until now for the quantum description of discrete geometries. These theoretical frameworks include loop quantum gravity, causal dynamical triangulations, causal sets, quantum graphity, and energetic spin networks. Most of these approaches describe discrete spaces as homogeneous network manifolds. Here we define Complex Quantum Network Manifolds (CQNM) describing the evolution of quantum network states, and constructed from growing simplicial complexes of dimension . We show that in d = 2 CQNM are homogeneous networks while for d > 2 they are scale-free i.e. they are characterized by large inhomogeneities of degrees like most complex networks. From the self-organized evolution of CQNM quantum statistics emerge spontaneously. Here we define the generalized degrees associated with the -faces of the -dimensional CQNMs, and we show that the statistics of these generalized degrees can either follow Fermi-Dirac, Boltzmann or Bose-Einstein distributions depending on the dimension of the -faces.

A Novel Deployment Scheme Based on Three-Dimensional Coverage Model for Wireless Sensor Networks

PubMed Central

Xiao, Fu; Yang, Yang; Wang, Ruchuan; Sun, Lijuan

2014-01-01

Coverage pattern and deployment strategy are directly related to the optimum allocation of limited resources for wireless sensor networks, such as energy of nodes, communication bandwidth, and computing power, and quality improvement is largely determined by these for wireless sensor networks. A three-dimensional coverage pattern and deployment scheme are proposed in this paper. Firstly, by analyzing the regular polyhedron models in three-dimensional scene, a coverage pattern based on cuboids is proposed, and then relationship between coverage and sensor nodes' radius is deduced; also the minimum number of sensor nodes to maintain network area's full coverage is calculated. At last, sensor nodes are deployed according to the coverage pattern after the monitor area is subdivided into finite 3D grid. Experimental results show that, compared with traditional random method, sensor nodes number is reduced effectively while coverage rate of monitor area is ensured using our coverage pattern and deterministic deployment scheme. PMID:25045747

Fast Two-Dimensional Bubble Analysis of Biopolymer Filamentous Networks Pore Size from Confocal Microscopy Thin Data Stacks

PubMed Central

Molteni, Matteo; Magatti, Davide; Cardinali, Barbara; Rocco, Mattia; Ferri, Fabio

2013-01-01

The average pore size ξ0 of filamentous networks assembled from biological macromolecules is one of the most important physical parameters affecting their biological functions. Modern optical methods, such as confocal microscopy, can noninvasively image such networks, but extracting a quantitative estimate of ξ0 is a nontrivial task. We present here a fast and simple method based on a two-dimensional bubble approach, which works by analyzing one by one the (thresholded) images of a series of three-dimensional thin data stacks. No skeletonization or reconstruction of the full geometry of the entire network is required. The method was validated by using many isotropic in silico generated networks of different structures, morphologies, and concentrations. For each type of network, the method provides accurate estimates (a few percent) of the average and the standard deviation of the three-dimensional distribution of the pore sizes, defined as the diameters of the largest spheres that can be fit into the pore zones of the entire gel volume. When applied to the analysis of real confocal microscopy images taken on fibrin gels, the method provides an estimate of ξ0 consistent with results from elastic light scattering data. PMID:23473499

Assessment of geometry in 2D immune systems using high accuracy laser-based bioprinting techniques (Conference Presentation)

NASA Astrophysics Data System (ADS)

Lauzurica, Sara; Márquez, Andrés.; Molpeceres, Carlos; Notario, Laura; Gómez-Fontela, Miguel; Lauzurica, Pilar

2017-02-01

The immune system is a very complex system that comprises a network of genetic and signaling pathways subtending a network of interacting cells. The location of the cells in a network, along with the gene products they interact with, rules the behavior of the immune system. Therefore, there is a great interest in understanding properly the role of a cell in such networks to increase our knowledge of the immune system response. In order to acquire a better understanding of these processes, cell printing with high spatial resolution emerges as one of the promising approaches to organize cells in two and three-dimensional patterns to enable the study the geometry influence in these interactions. In particular, laser assisted bio-printing techniques using sub-nanosecond laser sources have better characteristics for application in this field, mainly due to its higher spatial resolution, cell viability percentage and process automation. This work presents laser assisted bio-printing of antigen-presenting cells (APCs) in two-dimensional geometries, placing cellular components on a matrix previously generated on demand, permitting to test the molecular interactions between APCs and lymphocytes; as well as the generation of two-dimensional structures designed ad hoc in order to study the mechanisms of mobilization of immune system cells. The use of laser assisted bio-printing, along with APCs and lymphocytes emulate the structure of different niches of the immune system so that we can analyse functional requirement of these interaction.

Molecule-based magnets formed by bimetallic three-dimensional oxalate networks and chiral tris(bipyridyl) complex cations. The series [ZII(bpy)3][ClO4][MIICrIII(ox)3] (ZII = Ru, Fe, Co, and Ni; MII = Mn, Fe, Co, Ni, Cu, and Zn; ox = oxalate dianion).

PubMed

Coronado, E; Galán-Mascarós, J R; Gómez-García, C J; Martínez-Agudo, J M

2001-01-01

The synthesis, structure, and physical properties of the series of molecular magnets formulated as [ZII(bpy)3][ClO4][MIICrIII(ox)3] (ZII = Ru, Fe, Co, and Ni; MII = Mn, Fe, Co, Ni, Cu, and Zn; ox = oxalate dianion) are presented. All the compounds are isostructural to the [Ru(bpy)3][ClO4][MnCr(ox)3] member whose structure (cubic space group P4(1)32 with a = 15.506(2) A, Z = 4) consists of a three-dimensional bimetallic network formed by alternating MII and CrIII ions connected by oxalate anions. The identical chirality (lambda in the solved crystal) of all the metallic centers determines the 3D chiral structure adopted by these compounds. The anionic 3D sublattice leaves some holes where the chiral [Z(bpy)3]2+ and ClO4- counterions are located. These compounds behave as soft ferromagnets with ordering temperatures up to 6.6 K and coercive fields up to 8 mT.

From Networks to Time Series

NASA Astrophysics Data System (ADS)

Shimada, Yutaka; Ikeguchi, Tohru; Shigehara, Takaomi

2012-10-01

In this Letter, we propose a framework to transform a complex network to a time series. The transformation from complex networks to time series is realized by the classical multidimensional scaling. Applying the transformation method to a model proposed by Watts and Strogatz [Nature (London) 393, 440 (1998)], we show that ring lattices are transformed to periodic time series, small-world networks to noisy periodic time series, and random networks to random time series. We also show that these relationships are analytically held by using the circulant-matrix theory and the perturbation theory of linear operators. The results are generalized to several high-dimensional lattices.

Linear topology in amorphous metal oxide electrochromic networks obtained via low-temperature solution processing

NASA Astrophysics Data System (ADS)

Llordés, Anna; Wang, Yang; Fernandez-Martinez, Alejandro; Xiao, Penghao; Lee, Tom; Poulain, Agnieszka; Zandi, Omid; Saez Cabezas, Camila A.; Henkelman, Graeme; Milliron, Delia J.

2016-12-01

Amorphous transition metal oxides are recognized as leading candidates for electrochromic window coatings that can dynamically modulate solar irradiation and improve building energy efficiency. However, their thin films are normally prepared by energy-intensive sputtering techniques or high-temperature solution methods, which increase manufacturing cost and complexity. Here, we report on a room-temperature solution process to fabricate electrochromic films of niobium oxide glass (NbOx) and `nanocrystal-in-glass’ composites (that is, tin-doped indium oxide (ITO) nanocrystals embedded in NbOx glass) via acid-catalysed condensation of polyniobate clusters. A combination of X-ray scattering and spectroscopic characterization with complementary simulations reveals that this strategy leads to a unique one-dimensional chain-like NbOx structure, which significantly enhances the electrochromic performance, compared to a typical three-dimensional NbOx network obtained from conventional high-temperature thermal processing. In addition, we show how self-assembled ITO-in-NbOx composite films can be successfully integrated into high-performance flexible electrochromic devices.

Deformable image registration using convolutional neural networks

NASA Astrophysics Data System (ADS)

Eppenhof, Koen A. J.; Lafarge, Maxime W.; Moeskops, Pim; Veta, Mitko; Pluim, Josien P. W.

2018-03-01

Deformable image registration can be time-consuming and often needs extensive parameterization to perform well on a specific application. We present a step towards a registration framework based on a three-dimensional convolutional neural network. The network directly learns transformations between pairs of three-dimensional images. The outputs of the network are three maps for the x, y, and z components of a thin plate spline transformation grid. The network is trained on synthetic random transformations, which are applied to a small set of representative images for the desired application. Training therefore does not require manually annotated ground truth deformation information. The methodology is demonstrated on public data sets of inspiration-expiration lung CT image pairs, which come with annotated corresponding landmarks for evaluation of the registration accuracy. Advantages of this methodology are its fast registration times and its minimal parameterization.

X-ray diffraction study of Penicillium Vitale catalase in the complex with aminotriazole

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

Borovik, A. A.; Grebenko, A. I.; Melik-Adamyan, V. R., E-mail: mawr@ns.crys.ras.ru

2011-07-15

The three-dimensional structure of the enzyme catalase from Penicillium vitale in a complex with the inhibitor aminotriazole was solved and refined by protein X-ray crystallography methods. An analysis of the three-dimensional structure of the complex showed that the inhibition of the enzyme occurs as a result of the covalent binding of aminotriazole to the amino-acid residue His64 in the active site of the enzyme. An investigation of the three-dimensional structure of the complex resulted in the amino-acid residues being more precisely identified. The binding sites of saccharide residues and calcium ions in the protein molecule were found.

Convolutional neural network based side attack explosive hazard detection in three dimensional voxel radar

NASA Astrophysics Data System (ADS)

Brockner, Blake; Veal, Charlie; Dowdy, Joshua; Anderson, Derek T.; Williams, Kathryn; Luke, Robert; Sheen, David

2018-04-01

The identification followed by avoidance or removal of explosive hazards in past and/or present conflict zones is a serious threat for both civilian and military personnel. This is a challenging task as variability exists with respect to the objects, their environment and emplacement context, to name a few factors. A goal is the development of automatic or human-in-the-loop sensor technologies that leverage signal processing, data fusion and machine learning. Herein, we explore the detection of side attack explosive hazards (SAEHs) in three dimensional voxel space radar via different shallow and deep convolutional neural network (CNN) architectures. Dimensionality reduction is performed by using multiple projected images versus the raw three dimensional voxel data, which leads to noteworthy savings in input size and associated network hyperparameters. Last, we explore the accuracy and interpretation of solutions learned via random versus intelligent network weight initialization. Experiments are provided on a U.S. Army data set collected over different times, weather conditions, target types and concealments. Preliminary results indicate that deep learning can perform as good as, if not better, than a skilled domain expert, even in light of limited training data with a class imbalance.

Wet Chemistry Synthesis of Multidimensional Nanocarbon-Sulfur Hybrid Materials with Ultrahigh Sulfur Loading for Lithium-Sulfur Batteries.

PubMed

Du, Wen-Cheng; Yin, Ya-Xia; Zeng, Xian-Xiang; Shi, Ji-Lei; Zhang, Shuai-Feng; Wan, Li-Jun; Guo, Yu-Guo

2016-02-17

An optimized nanocarbon-sulfur cathode material with ultrahigh sulfur loading of up to 90 wt % is realized in the form of sulfur nanolayer-coated three-dimensional (3D) conducting network. This 3D nanocarbon-sulfur network combines three different nanocarbons, as follows: zero-dimensional carbon nanoparticle, one-dimensional carbon nanotube, and two-dimensional graphene. This 3D nanocarbon-sulfur network is synthesized by using a method based on soluble chemistry of elemental sulfur and three types of nanocarbons in well-chosen solvents. The resultant sulfur-carbon material shows a high specific capacity of 1115 mA h g(-1) at 0.02C and good rate performance of 551 mA h g(-1) at 1C based on the mass of sulfur-carbon composite. Good battery performance can be attributed to the homogeneous compositing of sulfur with the 3D hierarchical hybrid nanocarbon networks at nanometer scale, which provides efficient multidimensional transport pathways for electrons and ions. Wet chemical method developed here provides an easy and cost-effective way to prepare sulfur-carbon cathode materials with high sulfur loading for application in high-energy Li-S batteries.

A conceptual model of the copper-porphyry ore formation based on joint analysis of deep 3D geophysical models: Sorskoe complex (Russia) case study

NASA Astrophysics Data System (ADS)

Spichak, Viacheslav V.; Goidina, Alexandra G.

2017-12-01

Joint analysis of deep three-dimensional models of the electrical resistivity, seismic velocity, and density of the complex hosting the Sorskoe Cu-Mo deposit (Russia) is carried out aimed at finding geophysical markers characterizing the areas of ore generation, transportation and deposition. The three-dimensional lithology model of the study area is built based on the empirical relationship between the silica content of the rocks and seismic velocities. It is in agreement with geological and geochemical studies provided in this area earlier and could be used as a basis for forecasting locations of the copper-molybdenum ore deposits at depth. A conceptual model of the copper-porphyry complex explaining the mechanisms of ore generation, transportation from the lower to the upper crust and deposition in the upper crust is suggested. In particular, it is supposed that post-magmatic supercritical gas-water ore-bearing fluids are upwelling through the plastic crust due to the sliding of the fluid films along the cleavage planes of the foliated rocks while at the depths of the brittle upper crust this mechanism could be changed by volumetric fluid transportation along the network of large pores and cracks.

Tris[(6S)-6-hy­droxy-4-epi-shikimic acid] monohydrate: an enanti­omerically pure hy­droxy­lated shikimic acid derived from methyl shikimate

PubMed Central

Griesbeck, Axel G.; Miara, Claus; Neudörfl, Jörg-M.

2012-01-01

The title compound, 3C7H10O6·H2O, is the enanti­omerically pure product of a multi-step synthesis from the enanti­omerically pure natural shikimic acid. The asymmetric unit contains three mol­ecules of the acid and one mol­ecule of water. The cyclo­hexene rings of the acids have half-chair conformations. The carboxyl­ate, the four hydroxide groups and the additional water mol­ecule form a complex three-dimensional hydrogen-bonding network. PMID:23284468

Geostatistical three-dimensional modeling of oolite shoals, St. Louis Limestone, southwest Kansas

USGS Publications Warehouse

Qi, L.; Carr, T.R.; Goldstein, R.H.

2007-01-01

In the Hugoton embayment of southwestern Kansas, reservoirs composed of relatively thin (<4 m; <13.1 ft) oolitic deposits within the St. Louis Limestone have produced more than 300 million bbl of oil. The geometry and distribution of oolitic deposits control the heterogeneity of the reservoirs, resulting in exploration challenges and relatively low recovery. Geostatistical three-dimensional (3-D) models were constructed to quantify the geometry and spatial distribution of oolitic reservoirs, and the continuity of flow units within Big Bow and Sand Arroyo Creek fields. Lithofacies in uncored wells were predicted from digital logs using a neural network. The tilting effect from the Laramide orogeny was removed to construct restored structural surfaces at the time of deposition. Well data and structural maps were integrated to build 3-D models of oolitic reservoirs using stochastic simulations with geometry data. Three-dimensional models provide insights into the distribution, the external and internal geometry of oolitic deposits, and the sedimentologic processes that generated reservoir intervals. The structural highs and general structural trend had a significant impact on the distribution and orientation of the oolitic complexes. The depositional pattern and connectivity analysis suggest an overall aggradation of shallow-marine deposits during pulses of relative sea level rise followed by deepening near the top of the St. Louis Limestone. Cemented oolitic deposits were modeled as barriers and baffles and tend to concentrate at the edge of oolitic complexes. Spatial distribution of porous oolitic deposits controls the internal geometry of rock properties. Integrated geostatistical modeling methods can be applicable to other complex carbonate or siliciclastic reservoirs in shallow-marine settings. Copyright ?? 2007. The American Association of Petroleum Geologists. All rights reserved.

Synthesis, structure, and characterization of two Zn(II) complex containing two-dimensional bilayer structure

NASA Astrophysics Data System (ADS)

Zhang, Meili; Ren, Yixia; Chen, Xiaoli

2014-10-01

Two new Zn(II) complexes, [Zn2(L)(H2O)3]ṡH2O (1) and [Zn3(HL)2(bpp)2(Hbpp)2]ṡ10H2Oṡ2ClO4 (2) (H4L = cis,cis,cis,cis-1,2,3,4-cyclopentanetracarboxylic acid, bpp = 1,3-bis(4-pyridyl)propane), have been synthesized and characterized by elemental analysis, IR spectroscopy and single-crystal X-ray diffraction techniques. The structure indicates that the complex 1 crystallizes in triclinic, space group Pī, in which, the four carboxylate groups of L ligand adopt μ2-η1:η0, μ2-η1:η1, μ1-η1:η1 coordination modes, respectively, bridging Zn(II) atoms to generate a (4,6)-connected 2D bilayer network. The structure indicates that the complex 2 crystallizes in monoclinic, space group C2/c, in which, three deprotonated carboxylate groups of L ligand adopt uniform μ1-η1:η0 coordination mode linking Zn(II) atoms to form a 1D polymeric ribbon, the bpp ligands further extend such ribbon giving rised to a (3,4)-connected 2D bilayer network. The most striking feature of 1 and 2 is that both of bilayer networks contain 1D solvent channel, where water molecules are located. In additional, luminescent properties of two complexes have also been studied.

Two-dimensional plasmons in the random impedance network model of disordered thin film nanocomposites

NASA Astrophysics Data System (ADS)

Olekhno, N. A.; Beltukov, Y. M.

2018-05-01

Random impedance networks are widely used as a model to describe plasmon resonances in disordered metal-dielectric nanocomposites. Two-dimensional networks are applied when considering thin films despite the fact that such networks correspond to the two-dimensional electrodynamics [Clerc et al., J. Phys. A 29, 4781 (1996), 10.1088/0305-4470/29/16/006]. In the present work, we propose a model of two-dimensional systems with the three-dimensional Coulomb interaction and show that this model is equivalent to the planar network with long-range capacitive links between distant sites. In the case of a metallic film, we obtain the well-known dispersion of two-dimensional plasmons ω ∝√{k } . We study the evolution of resonances with a decrease in the metal filling factor within the framework of the proposed model. In the subcritical region with the metal filling p lower than the percolation threshold pc, we observe a gap with Lifshitz tails in the spectral density of states (DOS). In the supercritical region p >pc , the DOS demonstrates a crossover between plane-wave two-dimensional plasmons and resonances of finite clusters.

A hybrid intelligent method for three-dimensional short-term prediction of dissolved oxygen content in aquaculture

PubMed Central

Yu, Huihui; Cheng, Yanjun; Cheng, Qianqian; Li, Daoliang

2018-01-01

A precise predictive model is important for obtaining a clear understanding of the changes in dissolved oxygen content in crab ponds. Highly accurate interval forecasting of dissolved oxygen content is fundamental to reduce risk, and three-dimensional prediction can provide more accurate results and overall guidance. In this study, a hybrid three-dimensional (3D) dissolved oxygen content prediction model based on a radial basis function (RBF) neural network, K-means and subtractive clustering was developed and named the subtractive clustering (SC)-K-means-RBF model. In this modeling process, K-means and subtractive clustering methods were employed to enhance the hyperparameters required in the RBF neural network model. The comparison of the predicted results of different traditional models validated the effectiveness and accuracy of the proposed hybrid SC-K-means-RBF model for three-dimensional prediction of dissolved oxygen content. Consequently, the proposed model can effectively display the three-dimensional distribution of dissolved oxygen content and serve as a guide for feeding and future studies. PMID:29466394

Local self-uniformity in photonic networks.

PubMed

Sellers, Steven R; Man, Weining; Sahba, Shervin; Florescu, Marian

2017-02-17

The interaction of a material with light is intimately related to its wavelength-scale structure. Simple connections between structure and optical response empower us with essential intuition to engineer complex optical functionalities. Here we develop local self-uniformity (LSU) as a measure of a random network's internal structural similarity, ranking networks on a continuous scale from crystalline, through glassy intermediate states, to chaotic configurations. We demonstrate that complete photonic bandgap structures possess substantial LSU and validate LSU's importance in gap formation through design of amorphous gyroid structures. Amorphous gyroid samples are fabricated via three-dimensional ceramic printing and the bandgaps experimentally verified. We explore also the wing-scale structuring in the butterfly Pseudolycaena marsyas and show that it possesses substantial amorphous gyroid character, demonstrating the subtle order achieved by evolutionary optimization and the possibility of an amorphous gyroid's self-assembly.

Local self-uniformity in photonic networks

NASA Astrophysics Data System (ADS)

Sellers, Steven R.; Man, Weining; Sahba, Shervin; Florescu, Marian

2017-02-01

The interaction of a material with light is intimately related to its wavelength-scale structure. Simple connections between structure and optical response empower us with essential intuition to engineer complex optical functionalities. Here we develop local self-uniformity (LSU) as a measure of a random network's internal structural similarity, ranking networks on a continuous scale from crystalline, through glassy intermediate states, to chaotic configurations. We demonstrate that complete photonic bandgap structures possess substantial LSU and validate LSU's importance in gap formation through design of amorphous gyroid structures. Amorphous gyroid samples are fabricated via three-dimensional ceramic printing and the bandgaps experimentally verified. We explore also the wing-scale structuring in the butterfly Pseudolycaena marsyas and show that it possesses substantial amorphous gyroid character, demonstrating the subtle order achieved by evolutionary optimization and the possibility of an amorphous gyroid's self-assembly.

75 FR 77885 - Government-Owned Inventions; Availability for Licensing

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-14

... of federally-funded research and development. Foreign patent applications are filed on selected... applications. Software System for Quantitative Assessment of Vasculature in Three Dimensional Images... three dimensional vascular networks from medical and basic research images. Deregulation of angiogenesis...

Spreading of infection in a two species reaction-diffusion process in networks

NASA Astrophysics Data System (ADS)

Korosoglou, Paschalis; Kittas, Aristotelis; Argyrakis, Panos

2010-12-01

We study the dynamics of the infection of a two mobile species reaction from a single infected agent in a population of healthy agents. Historically, the main focus for infection propagation has been through spreading phenomena, where a random location of the system is initially infected and then propagates by successfully infecting its neighbor sites. Here both the infected and healthy agents are mobile, performing classical random walks. This may be a more realistic picture to such epidemiological models, such as the spread of a virus in communication networks of routers, where data travel in packets, the communication time of stations in ad hoc mobile networks, information spreading (such as rumor spreading) in social networks, etc. We monitor the density of healthy particles ρ(t) , which we find in all cases to be an exponential function in the long-time limit in two-dimensional and three-dimensional lattices and Erdős-Rényi (ER) and scale-free (SF) networks. We also investigate the scaling of the crossover time tc from short- to long-time exponential behavior, which we find to be a power law in lattices and ER networks. This crossover is shown to be absent in SF networks, where we reveal the role of the connectivity of the network in the infection process. We compare this behavior to ER networks and lattices and highlight the significance of various connectivity patterns, as well as the important differences of this process in the various underlying geometries, revealing a more complex behavior of ρ(t) .

Gestational Age is Dimensionally Associated with Structural Brain Network Abnormalities Across Development.

PubMed

Nassar, Rula; Kaczkurkin, Antonia N; Xia, Cedric Huchuan; Sotiras, Aristeidis; Pehlivanova, Marieta; Moore, Tyler M; Garcia de La Garza, Angel; Roalf, David R; Rosen, Adon F G; Lorch, Scott A; Ruparel, Kosha; Shinohara, Russell T; Davatzikos, Christos; Gur, Ruben C; Gur, Raquel E; Satterthwaite, Theodore D

2018-04-21

Prematurity is associated with diverse developmental abnormalities, yet few studies relate cognitive and neurostructural deficits to a dimensional measure of prematurity. Leveraging a large sample of children, adolescents, and young adults (age 8-22 years) studied as part of the Philadelphia Neurodevelopmental Cohort, we examined how variation in gestational age impacted cognition and brain structure later in development. Participants included 72 preterm youth born before 37 weeks' gestation and 206 youth who were born at term (37 weeks or later). Using a previously-validated factor analysis, cognitive performance was assessed in three domains: (1) executive function and complex reasoning, (2) social cognition, and (3) episodic memory. All participants completed T1-weighted neuroimaging at 3 T to measure brain volume. Structural covariance networks were delineated using non-negative matrix factorization, an advanced multivariate analysis technique. Lower gestational age was associated with both deficits in executive function and reduced volume within 11 of 26 structural covariance networks, which included orbitofrontal, temporal, and parietal cortices as well as subcortical regions including the hippocampus. Notably, the relationship between lower gestational age and executive dysfunction was accounted for in part by structural network deficits. Together, these findings emphasize the durable impact of prematurity on cognition and brain structure, which persists across development.

Investigations of photosynthetic light harvesting by two-dimensional electronic spectroscopy

NASA Astrophysics Data System (ADS)

Read, Elizabeth Louise

Photosynthesis begins with the harvesting of sunlight by antenna pigments, organized in a network of pigment-protein complexes that rapidly funnel energy to photochemical reaction centers. The intricate design of these systems---the widely varying structural motifs of pigment organization within proteins and protein organization within a larger, cooperative network---underlies the remarkable speed and efficiency of light harvesting. Advances in femtosecond laser spectroscopy have enabled researchers to follow light energy on its course through the energetic levels of photosynthetic systems. Now, newly-developed femtosecond two-dimensional electronic spectroscopy reveals deeper insight into the fundamental molecular interactions and dynamics that emerge in these structures. The following chapters present investigations of a number of natural light-harvesting complexes using two-dimensional electronic spectroscopy. These studies demonstrate the various types of information contained in experimental two-dimensional spectra, and they show that the technique makes it possible to probe pigment-protein complexes on the length- and time-scales relevant to their functioning. New methods are described that further extend the capabilities of two-dimensional electronic spectroscopy, for example, by independently controlling the excitation laser pulse polarizations. The experiments, coupled with theoretical simulation, elucidate spatial pathways of energy flow, unravel molecular and electronic structures, and point to potential new quantum mechanical mechanisms of light harvesting.

Interdisciplinary Matchmaking: Choosing Collaborators by Skill, Acquaintance and Trust

NASA Astrophysics Data System (ADS)

Hupa, Albert; Rzadca, Krzysztof; Wierzbicki, Adam; Datta, Anwitaman

Social networks are commonly used to enhance recommender systems. Most of such systems recommend a single resource or a person. However, complex problems or projects usually require a team of experts that must work together on a solution. Team recommendation is much more challenging, mostly because of the complex interpersonal relations between members. This chapter presents fundamental concepts on how to score a team based on members' social context and their suitability for a particular project. We represent the social context of an individual as a three-dimensional social network (3DSN) composed of a knowledge dimension expressing skills, a trust dimension and an acquaintance dimension. Dimensions of a 3DSN are used to mathematically formalize the criteria for prediction of the team's performance. We use these criteria to formulate the team recommendation problem as a multi-criteria optimization problem. We demonstrate our approach on empirical data crawled from two web2.0 sites: onephoto.net and a social networking site. We construct 3DSNs and analyze properties of team's performance criteria.

Solid-state acid-base interactions in complexes of heterocyclic bases with dicarboxylic acids: crystallography, hydrogen bond analysis, and 15N NMR spectroscopy.

PubMed

Li, Z Jane; Abramov, Yuriy; Bordner, Jon; Leonard, Jason; Medek, Ales; Trask, Andrew V

2006-06-28

A cancer candidate, compound 1, is a weak base with two heterocyclic basic nitrogens and five hydrogen-bonding functional groups, and is sparingly soluble in water rendering it unsuitable for pharmaceutical development. The crystalline acid-base pairs of 1, collectively termed solid acid-base complexes, provide significant increases in the solubility and bioavailability compared to the free base, 1. Three dicarboxylic acid-base complexes, sesquisuccinate 2, dimalonate 3, and dimaleate 4, show the most favorable physicochemical profiles and are studied in greater detail. The structural analyses of the three complexes using crystal structure and solid-state NMR reveal that the proton-transfer behavior in these organic acid-base complexes vary successively correlating with Delta pKa. As a result, 2 is a neutral complex, 3 is a mixed ionic and zwitterionic complex and 4 is an ionic salt. The addition of the acidic components leads to maximized hydrogen bond interactions forming extended three-dimensional networks. Although structurally similar, the packing arrangements of the three complexes are considerably different due to the presence of multiple functional groups and the flexible backbone of 1. The findings in this study provide insight into the structural characteristics of complexes involving heterocyclic bases and carboxylic acids, and demonstrate that X-ray crystallography and 15N solid-state NMR are truly complementary in elucidating hydrogen bonding interactions and the degree of proton transfer of these complexes.

Phase Diagrams of Three-Dimensional Anderson and Quantum Percolation Models Using Deep Three-Dimensional Convolutional Neural Network

NASA Astrophysics Data System (ADS)

Mano, Tomohiro; Ohtsuki, Tomi

2017-11-01

The three-dimensional Anderson model is a well-studied model of disordered electron systems that shows the delocalization-localization transition. As in our previous papers on two- and three-dimensional (2D, 3D) quantum phase transitions [J. Phys. Soc. Jpn. 85, 123706 (2016), 86, 044708 (2017)], we used an image recognition algorithm based on a multilayered convolutional neural network. However, in contrast to previous papers in which 2D image recognition was used, we applied 3D image recognition to analyze entire 3D wave functions. We show that a full phase diagram of the disorder-energy plane is obtained once the 3D convolutional neural network has been trained at the band center. We further demonstrate that the full phase diagram for 3D quantum bond and site percolations can be drawn by training the 3D Anderson model at the band center.

Comparisons Of Two- And Three-Dimensional Convection In Type I X-Ray Bursts

DOE PAGES

Zingale, M.; Malone, C. M.; Nonaka, A.; ...

2015-07-01

We perform the first detailed three-dimensional simulation of low Mach number convection preceding runaway thermonuclear ignition in a mixed H/He X-ray burst. Our simulations include a moderate-sized, approximate network that captures hydrogen and helium burning up through rp-process breakout. We look at the difference between two- and three-dimensional convective fields, including the details of the turbulent convection.

Complexity and dynamics of topological and community structure in complex networks

NASA Astrophysics Data System (ADS)

Berec, Vesna

2017-07-01

Complexity is highly susceptible to variations in the network dynamics, reflected on its underlying architecture where topological organization of cohesive subsets into clusters, system's modular structure and resulting hierarchical patterns, are cross-linked with functional dynamics of the system. Here we study connection between hierarchical topological scales of the simplicial complexes and the organization of functional clusters - communities in complex networks. The analysis reveals the full dynamics of different combinatorial structures of q-th-dimensional simplicial complexes and their Laplacian spectra, presenting spectral properties of resulting symmetric and positive semidefinite matrices. The emergence of system's collective behavior from inhomogeneous statistical distribution is induced by hierarchically ordered topological structure, which is mapped to simplicial complex where local interactions between the nodes clustered into subcomplexes generate flow of information that characterizes complexity and dynamics of the full system.

High resolution structural characterisation of laser-induced defect clusters inside diamond

NASA Astrophysics Data System (ADS)

Salter, Patrick S.; Booth, Martin J.; Courvoisier, Arnaud; Moran, David A. J.; MacLaren, Donald A.

2017-08-01

Laser writing with ultrashort pulses provides a potential route for the manufacture of three-dimensional wires, waveguides, and defects within diamond. We present a transmission electron microscopy study of the intrinsic structure of the laser modifications and reveal a complex distribution of defects. Electron energy loss spectroscopy indicates that the majority of the irradiated region remains as sp3 bonded diamond. Electrically conductive paths are attributed to the formation of multiple nano-scale, sp2-bonded graphitic wires and a network of strain-relieving micro-cracks.

Optimization of Turbine Blade Design for Reusable Launch Vehicles

NASA Technical Reports Server (NTRS)

Shyy, Wei

1998-01-01

To facilitate design optimization of turbine blade shape for reusable launching vehicles, appropriate techniques need to be developed to process and estimate the characteristics of the design variables and the response of the output with respect to the variations of the design variables. The purpose of this report is to offer insight into developing appropriate techniques for supporting such design and optimization needs. Neural network and polynomial-based techniques are applied to process aerodynamic data obtained from computational simulations for flows around a two-dimensional airfoil and a generic three- dimensional wing/blade. For the two-dimensional airfoil, a two-layered radial-basis network is designed and trained. The performances of two different design functions for radial-basis networks, one based on the accuracy requirement, whereas the other one based on the limit on the network size. While the number of neurons needed to satisfactorily reproduce the information depends on the size of the data, the neural network technique is shown to be more accurate for large data set (up to 765 simulations have been used) than the polynomial-based response surface method. For the three-dimensional wing/blade case, smaller aerodynamic data sets (between 9 to 25 simulations) are considered, and both the neural network and the polynomial-based response surface techniques improve their performance as the data size increases. It is found while the relative performance of two different network types, a radial-basis network and a back-propagation network, depends on the number of input data, the number of iterations required for radial-basis network is less than that for the back-propagation network.

Characterizing complex networks through statistics of Möbius transformations

NASA Astrophysics Data System (ADS)

Jaćimović, Vladimir; Crnkić, Aladin

2017-04-01

It is well-known now that dynamics of large populations of globally (all-to-all) coupled oscillators can be reduced to low-dimensional submanifolds (WS transformation and OA ansatz). Marvel et al. (2009) described an intriguing algebraic structure standing behind this reduction: oscillators evolve by the action of the group of Möbius transformations. Of course, dynamics in complex networks of coupled oscillators is highly complex and not reducible. Still, closer look unveils that even in complex networks some (possibly overlapping) groups of oscillators evolve by Möbius transformations. In this paper, we study properties of the network by identifying Möbius transformations in the dynamics of oscillators. This enables us to introduce some new (statistical) concepts that characterize the network. In particular, the notion of coherence of the network (or subnetwork) is proposed. This conceptual approach is meaningful for the broad class of networks, including those with time-delayed, noisy or mixed interactions. In this paper, several simple (random) graphs are studied illustrating the meaning of the concepts introduced in the paper.

Complex Quantum Network Manifolds in Dimension d > 2 are Scale-Free

PubMed Central

Bianconi, Ginestra; Rahmede, Christoph

2015-01-01

In quantum gravity, several approaches have been proposed until now for the quantum description of discrete geometries. These theoretical frameworks include loop quantum gravity, causal dynamical triangulations, causal sets, quantum graphity, and energetic spin networks. Most of these approaches describe discrete spaces as homogeneous network manifolds. Here we define Complex Quantum Network Manifolds (CQNM) describing the evolution of quantum network states, and constructed from growing simplicial complexes of dimension . We show that in d = 2 CQNM are homogeneous networks while for d > 2 they are scale-free i.e. they are characterized by large inhomogeneities of degrees like most complex networks. From the self-organized evolution of CQNM quantum statistics emerge spontaneously. Here we define the generalized degrees associated with the -faces of the -dimensional CQNMs, and we show that the statistics of these generalized degrees can either follow Fermi-Dirac, Boltzmann or Bose-Einstein distributions depending on the dimension of the -faces. PMID:26356079

Complex Quantum Network Manifolds in Dimension d > 2 are Scale-Free.

PubMed

Bianconi, Ginestra; Rahmede, Christoph

2015-09-10

In quantum gravity, several approaches have been proposed until now for the quantum description of discrete geometries. These theoretical frameworks include loop quantum gravity, causal dynamical triangulations, causal sets, quantum graphity, and energetic spin networks. Most of these approaches describe discrete spaces as homogeneous network manifolds. Here we define Complex Quantum Network Manifolds (CQNM) describing the evolution of quantum network states, and constructed from growing simplicial complexes of dimension d. We show that in d = 2 CQNM are homogeneous networks while for d > 2 they are scale-free i.e. they are characterized by large inhomogeneities of degrees like most complex networks. From the self-organized evolution of CQNM quantum statistics emerge spontaneously. Here we define the generalized degrees associated with the δ-faces of the d-dimensional CQNMs, and we show that the statistics of these generalized degrees can either follow Fermi-Dirac, Boltzmann or Bose-Einstein distributions depending on the dimension of the δ-faces.

A clustering algorithm for determining community structure in complex networks

NASA Astrophysics Data System (ADS)

Jin, Hong; Yu, Wei; Li, ShiJun

2018-02-01

Clustering algorithms are attractive for the task of community detection in complex networks. DENCLUE is a representative density based clustering algorithm which has a firm mathematical basis and good clustering properties allowing for arbitrarily shaped clusters in high dimensional datasets. However, this method cannot be directly applied to community discovering due to its inability to deal with network data. Moreover, it requires a careful selection of the density parameter and the noise threshold. To solve these issues, a new community detection method is proposed in this paper. First, we use a spectral analysis technique to map the network data into a low dimensional Euclidean Space which can preserve node structural characteristics. Then, DENCLUE is applied to detect the communities in the network. A mathematical method named Sheather-Jones plug-in is chosen to select the density parameter which can describe the intrinsic clustering structure accurately. Moreover, every node on the network is meaningful so there were no noise nodes as a result the noise threshold can be ignored. We test our algorithm on both benchmark and real-life networks, and the results demonstrate the effectiveness of our algorithm over other popularity density based clustering algorithms adopted to community detection.

Generalized three-dimensional lattice Boltzmann color-gradient method for immiscible two-phase pore-scale imbibition and drainage in porous media

NASA Astrophysics Data System (ADS)

Leclaire, Sébastien; Parmigiani, Andrea; Malaspinas, Orestis; Chopard, Bastien; Latt, Jonas

2017-03-01

This article presents a three-dimensional numerical framework for the simulation of fluid-fluid immiscible compounds in complex geometries, based on the multiple-relaxation-time lattice Boltzmann method to model the fluid dynamics and the color-gradient approach to model multicomponent flow interaction. New lattice weights for the lattices D3Q15, D3Q19, and D3Q27 that improve the Galilean invariance of the color-gradient model as well as for modeling the interfacial tension are derived and provided in the Appendix. The presented method proposes in particular an approach to model the interaction between the fluid compound and the solid, and to maintain a precise contact angle between the two-component interface and the wall. Contrarily to previous approaches proposed in the literature, this method yields accurate solutions even in complex geometries and does not suffer from numerical artifacts like nonphysical mass transfer along the solid wall, which is crucial for modeling imbibition-type problems. The article also proposes an approach to model inflow and outflow boundaries with the color-gradient method by generalizing the regularized boundary conditions. The numerical framework is first validated for three-dimensional (3D) stationary state (Jurin's law) and time-dependent (Washburn's law and capillary waves) problems. Then, the usefulness of the method for practical problems of pore-scale flow imbibition and drainage in porous media is demonstrated. Through the simulation of nonwetting displacement in two-dimensional random porous media networks, we show that the model properly reproduces three main invasion regimes (stable displacement, capillary fingering, and viscous fingering) as well as the saturating zone transition between these regimes. Finally, the ability to simulate immiscible two-component flow imbibition and drainage is validated, with excellent results, by numerical simulations in a Berea sandstone, a frequently used benchmark case used in this field, using a complex geometry that originates from a 3D scan of a porous sandstone. The methods presented in this article were implemented in the open-source PALABOS library, a general C++ matrix-based library well adapted for massive fluid flow parallel computation.

Three-dimensional aromatic networks.

PubMed

Toyota, Shinji; Iwanaga, Tetsuo

2014-01-01

Three-dimensional (3D) networks consisting of aromatic units and linkers are reviewed from various aspects. To understand principles for the construction of such compounds, we generalize the roles of building units, the synthetic approaches, and the classification of networks. As fundamental compounds, cyclophanes with large aromatic units and aromatic macrocycles with linear acetylene linkers are highlighted in terms of transannular interactions between aromatic units, conformational preference, and resolution of chiral derivatives. Polycyclic cage compounds are constructed from building units by linkages via covalent bonds, metal-coordination bonds, or hydrogen bonds. Large cage networks often include a wide range of guest species in their cavity to afford novel inclusion compounds. Topological isomers consisting of two or more macrocycles are formed by cyclization of preorganized species. Some complicated topological networks are constructed by self-assembly of simple building units.

Three-dimensional imaging of the craniofacial complex.

PubMed

Nguyen, Can X.; Nissanov, Jonathan; Öztürk, Cengizhan; Nuveen, Michiel J.; Tuncay, Orhan C.

2000-02-01

Orthodontic treatment requires the rearrangement of craniofacial complex elements in three planes of space, but oddly the diagnosis is done with two-dimensional images. Here we report on a three-dimensional (3D) imaging system that employs the stereoimaging method of structured light to capture the facial image. The images can be subsequently integrated with 3D cephalometric tracings derived from lateral and PA films (www.clinorthodres.com/cor-c-070). The accuracy of the reconstruction obtained with this inexpensive system is about 400 µ.

Dense power-law networks and simplicial complexes

NASA Astrophysics Data System (ADS)

Courtney, Owen T.; Bianconi, Ginestra

2018-05-01

There is increasing evidence that dense networks occur in on-line social networks, recommendation networks and in the brain. In addition to being dense, these networks are often also scale-free, i.e., their degree distributions follow P (k ) ∝k-γ with γ ∈(1 ,2 ] . Models of growing networks have been successfully employed to produce scale-free networks using preferential attachment, however these models can only produce sparse networks as the numbers of links and nodes being added at each time step is constant. Here we present a modeling framework which produces networks that are both dense and scale-free. The mechanism by which the networks grow in this model is based on the Pitman-Yor process. Variations on the model are able to produce undirected scale-free networks with exponent γ =2 or directed networks with power-law out-degree distribution with tunable exponent γ ∈(1 ,2 ) . We also extend the model to that of directed two-dimensional simplicial complexes. Simplicial complexes are generalization of networks that can encode the many body interactions between the parts of a complex system and as such are becoming increasingly popular to characterize different data sets ranging from social interacting systems to the brain. Our model produces dense directed simplicial complexes with power-law distribution of the generalized out-degrees of the nodes.

Hydrothermal synthesis and structural characterization of a novel three-dimensional supramolecular framework constructed by zinc salt and pyridine-2,5-dicarboxylate

NASA Astrophysics Data System (ADS)

Wang, Xinlong; Qin, Chao; Wang, Enbo; Hu, Changwen; Xu, Lin

2004-07-01

A novel metal-organic coordination polymer, [Zn(PDB)(H 2O) 2] 4 n (H 2PDB=pyridine-2,5-dicarboxylic acid), has been hydrothermally synthesized and characterized by elemental analysis, IR, TG and single crystal X-ray diffraction. Colorless crystals crystallized in the triclinic system, space group P-1, a=7.0562(14) Å, b=7.38526(15) Å, c=18.4611(4) Å, α=90.01(3)°, β=96.98(3)°, γ=115.67(3)°, V=859.1(3) Å 3, Z=1 and R=0.0334. The structure of the compound exhibits a novel three-dimensional supramolecular network, mainly based on multipoint hydrogen bonds originated from within and outside of a large 24-membered ring. Interestingly, the three-dimensional network consists of one-dimensional parallelogrammic channels in which coordinated water molecules point into the channel wall.

A three-dimensional neural spheroid model for capillary-like network formation.

PubMed

Boutin, Molly E; Kramer, Liana L; Livi, Liane L; Brown, Tyler; Moore, Christopher; Hoffman-Kim, Diane

2018-04-01

In vitro three-dimensional neural spheroid models have an in vivo-like cell density, and have the potential to reduce animal usage and increase experimental throughput. The aim of this study was to establish a spheroid model to study the formation of capillary-like networks in a three-dimensional environment that incorporates both neuronal and glial cell types, and does not require exogenous vasculogenic growth factors. We created self-assembled, scaffold-free cellular spheroids using primary-derived postnatal rodent cortex as a cell source. The interactions between relevant neural cell types, basement membrane proteins, and endothelial cells were characterized by immunohistochemistry. Transmission electron microscopy was used to determine if endothelial network structures had lumens. Endothelial cells within cortical spheroids assembled into capillary-like networks with lumens. Networks were surrounded by basement membrane proteins, including laminin, fibronectin and collagen IV, as well as key neurovascular cell types. Existing in vitro models of the cortical neurovascular environment study monolayers of endothelial cells, either on transwell inserts or coating cellular spheroids. These models are not well suited to study vasculogenesis, a process hallmarked by endothelial cell cord formation and subsequent lumenization. The neural spheroid is a new model to study the formation of endothelial cell capillary-like structures in vitro within a high cell density three-dimensional environment that contains both neuronal and glial populations. This model can be applied to investigate vascular assembly in healthy or disease states, such as stroke, traumatic brain injury, or neurodegenerative disorders. Copyright © 2017 Elsevier B.V. All rights reserved.

Data based identification and prediction of nonlinear and complex dynamical systems

NASA Astrophysics Data System (ADS)

Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

2016-07-01

The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The "inverse" problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear dynamical systems theories with tools from statistical physics, optimization, engineering control, applied mathematics, and scientific computing enables the development of a number of paradigms to address the problem of nonlinear and complex systems reconstruction. In this Review, we describe the recent advances in this forefront and rapidly evolving field, with a focus on compressive sensing based methods. In particular, compressive sensing is a paradigm developed in recent years in applied mathematics, electrical engineering, and nonlinear physics to reconstruct sparse signals using only limited data. It has broad applications ranging from image compression/reconstruction to the analysis of large-scale sensor networks, and it has become a powerful technique to obtain high-fidelity signals for applications where sufficient observations are not available. We will describe in detail how compressive sensing can be exploited to address a diverse array of problems in data based reconstruction of nonlinear and complex networked systems. The problems include identification of chaotic systems and prediction of catastrophic bifurcations, forecasting future attractors of time-varying nonlinear systems, reconstruction of complex networks with oscillatory and evolutionary game dynamics, detection of hidden nodes, identification of chaotic elements in neuronal networks, reconstruction of complex geospatial networks and nodal positioning, and reconstruction of complex spreading networks with binary data.. A number of alternative methods, such as those based on system response to external driving, synchronization, and noise-induced dynamical correlation, will also be discussed. Due to the high relevance of network reconstruction to biological sciences, a special section is devoted to a brief survey of the current methods to infer biological networks. Finally, a number of open problems including control and controllability of complex nonlinear dynamical networks are discussed. The methods outlined in this Review are principled on various concepts in complexity science and engineering such as phase transitions, bifurcations, stabilities, and robustness. The methodologies have the potential to significantly improve our ability to understand a variety of complex dynamical systems ranging from gene regulatory systems to social networks toward the ultimate goal of controlling such systems.

1D-3D hybrid modeling-from multi-compartment models to full resolution models in space and time.

PubMed

Grein, Stephan; Stepniewski, Martin; Reiter, Sebastian; Knodel, Markus M; Queisser, Gillian

2014-01-01

Investigation of cellular and network dynamics in the brain by means of modeling and simulation has evolved into a highly interdisciplinary field, that uses sophisticated modeling and simulation approaches to understand distinct areas of brain function. Depending on the underlying complexity, these models vary in their level of detail, in order to cope with the attached computational cost. Hence for large network simulations, single neurons are typically reduced to time-dependent signal processors, dismissing the spatial aspect of each cell. For single cell or networks with relatively small numbers of neurons, general purpose simulators allow for space and time-dependent simulations of electrical signal processing, based on the cable equation theory. An emerging field in Computational Neuroscience encompasses a new level of detail by incorporating the full three-dimensional morphology of cells and organelles into three-dimensional, space and time-dependent, simulations. While every approach has its advantages and limitations, such as computational cost, integrated and methods-spanning simulation approaches, depending on the network size could establish new ways to investigate the brain. In this paper we present a hybrid simulation approach, that makes use of reduced 1D-models using e.g., the NEURON simulator-which couples to fully resolved models for simulating cellular and sub-cellular dynamics, including the detailed three-dimensional morphology of neurons and organelles. In order to couple 1D- and 3D-simulations, we present a geometry-, membrane potential- and intracellular concentration mapping framework, with which graph- based morphologies, e.g., in the swc- or hoc-format, are mapped to full surface and volume representations of the neuron and computational data from 1D-simulations can be used as boundary conditions for full 3D simulations and vice versa. Thus, established models and data, based on general purpose 1D-simulators, can be directly coupled to the emerging field of fully resolved, highly detailed 3D-modeling approaches. We present the developed general framework for 1D/3D hybrid modeling and apply it to investigate electrically active neurons and their intracellular spatio-temporal calcium dynamics.

1D-3D hybrid modeling—from multi-compartment models to full resolution models in space and time

PubMed Central

Grein, Stephan; Stepniewski, Martin; Reiter, Sebastian; Knodel, Markus M.; Queisser, Gillian

2014-01-01

Investigation of cellular and network dynamics in the brain by means of modeling and simulation has evolved into a highly interdisciplinary field, that uses sophisticated modeling and simulation approaches to understand distinct areas of brain function. Depending on the underlying complexity, these models vary in their level of detail, in order to cope with the attached computational cost. Hence for large network simulations, single neurons are typically reduced to time-dependent signal processors, dismissing the spatial aspect of each cell. For single cell or networks with relatively small numbers of neurons, general purpose simulators allow for space and time-dependent simulations of electrical signal processing, based on the cable equation theory. An emerging field in Computational Neuroscience encompasses a new level of detail by incorporating the full three-dimensional morphology of cells and organelles into three-dimensional, space and time-dependent, simulations. While every approach has its advantages and limitations, such as computational cost, integrated and methods-spanning simulation approaches, depending on the network size could establish new ways to investigate the brain. In this paper we present a hybrid simulation approach, that makes use of reduced 1D-models using e.g., the NEURON simulator—which couples to fully resolved models for simulating cellular and sub-cellular dynamics, including the detailed three-dimensional morphology of neurons and organelles. In order to couple 1D- and 3D-simulations, we present a geometry-, membrane potential- and intracellular concentration mapping framework, with which graph- based morphologies, e.g., in the swc- or hoc-format, are mapped to full surface and volume representations of the neuron and computational data from 1D-simulations can be used as boundary conditions for full 3D simulations and vice versa. Thus, established models and data, based on general purpose 1D-simulators, can be directly coupled to the emerging field of fully resolved, highly detailed 3D-modeling approaches. We present the developed general framework for 1D/3D hybrid modeling and apply it to investigate electrically active neurons and their intracellular spatio-temporal calcium dynamics. PMID:25120463

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

Shen, Lei; Bai, Yu; Min, Yu-Ting

Three different tetrazole-carboxylate ligands, monotetrazole-carboxylate H{sub 2}tza (H{sub 2}tza=1,5-tetrazole-diacetic acid), Hpztza (Hpztza=5-(2-pyrazinyl)tetrazole-2(1-methyl)acetic acid), ditetrazole-carboxylate H{sub 2}tzpha (H{sub 2}tzpha=1,3-di(tetrazole-5-yl)benzene-N2,N2′-diacetic acid) have been chosen to react with CdCl{sub 2}·6H{sub 2}O, resulting in the formation of three new compounds [Cd{sub 2}(tza){sub 2}] (1), [Cd(pztza){sub 2}] (2) and [Cd(tzpha)(CH{sub 3}OH){sub 2}] (3). The coordinate sites of the three ligands are major influenced by the different substituted group of tetrazole ring. These compounds have been characterized by elemental analysis, IR and single crystal X-ray diffraction. Compound 1 displays a complex 3D structure; compound 2 shows a 3D network and compound 3 features a 2D layermore » network. Furthermore, the luminescence properties investigated at room temperature in the solid state showed excellent ligand-centered luminescence. The obvious enhancement in luminescence makes these compounds potential materials for optical use. The differential scanning calorimetry (DSC) and thermogravimetric-differential thermogravimetric (TG-DTG) analyses were applied to evaluate the thermal decomposition behavior of such compounds, showing that compounds 2 and 3 can be used as potential energetic materials. The relevant thermodynamic parameters ΔH, ΔS and ΔG were calculated as well. - Graphical abstract: H{sub 2}tza, Hpztza and H{sub 2}tzpha have been prepared. Three novel Cd (II)compounds were synthesized by reactions of CdCl{sub 2}·6H{sub 2}O, namely three dimensional [Cd{sub 2}(tza){sub 2}] (1), three dimensional [Cd(pztza){sub 2}] (2), and two dimensional [Cd(tzpha)(CH{sub 3}O){sub 2}] (3). The luminescences were investigated. Furthermore, the DSC show compounds 1 and 3 can be used as potential explosive materials.« less

[Advances in the research of application of hydrogels in three-dimensional bioprinting].

PubMed

Yang, J; Zhao, Y; Li, H H; Zhu, S H

2016-08-20

Hydrogels are three-dimensional networks made of hydrophilic polymer crosslinked through covalent bonds or physical intermolecular attractions, which can contain growth media and growth factors to support cell growth. In bioprinting, hydrogels are used to provide accurate control over cellular microenvironment and to dramatically reduce experimental repetition times, meanwhile we can obtain three-dimensional cell images of high quality. Hydrogels in three-dimensional bioprinting have received a considerable interest due to their structural similarities to the natural extracellular matrix and polyporous frameworks which can support the cellular proliferation and survival. Meanwhile, they are accompanied by many challenges.

Three-dimensional Bragg coherent diffraction imaging of an extended ZnO crystal.

PubMed

Huang, Xiaojing; Harder, Ross; Leake, Steven; Clark, Jesse; Robinson, Ian

2012-08-01

A complex three-dimensional quantitative image of an extended zinc oxide (ZnO) crystal has been obtained using Bragg coherent diffraction imaging integrated with ptychography. By scanning a 2.5 µm-long arm of a ZnO tetrapod across a 1.3 µm X-ray beam with fine step sizes while measuring a three-dimensional diffraction pattern at each scan spot, the three-dimensional electron density and projected displacement field of the entire crystal were recovered. The simultaneously reconstructed complex wavefront of the illumination combined with its coherence properties determined by a partial coherence analysis implemented in the reconstruction process provide a comprehensive characterization of the incident X-ray beam.

Three-Dimensional Gene Map of Cancer Cell Types: Structural Entropy Minimisation Principle for Defining Tumour Subtypes

PubMed Central

Li, Angsheng; Yin, Xianchen; Pan, Yicheng

2016-01-01

In this study, we propose a method for constructing cell sample networks from gene expression profiles, and a structural entropy minimisation principle for detecting natural structure of networks and for identifying cancer cell subtypes. Our method establishes a three-dimensional gene map of cancer cell types and subtypes. The identified subtypes are defined by a unique gene expression pattern, and a three-dimensional gene map is established by defining the unique gene expression pattern for each identified subtype for cancers, including acute leukaemia, lymphoma, multi-tissue, lung cancer and healthy tissue. Our three-dimensional gene map demonstrates that a true tumour type may be divided into subtypes, each defined by a unique gene expression pattern. Clinical data analyses demonstrate that most cell samples of an identified subtype share similar survival times, survival indicators and International Prognostic Index (IPI) scores and indicate that distinct subtypes identified by our algorithms exhibit different overall survival times, survival ratios and IPI scores. Our three-dimensional gene map establishes a high-definition, one-to-one map between the biologically and medically meaningful tumour subtypes and the gene expression patterns, and identifies remarkable cells that form singleton submodules. PMID:26842724

Microvascular Guidance: A Challenge to Support the Development of Vascularised Tissue Engineering Construct

PubMed Central

Sukmana, Irza

2012-01-01

The guidance of endothelial cell organization into a capillary network has been a long-standing challenge in tissue engineering. Some research efforts have been made to develop methods to promote capillary networks inside engineered tissue constructs. Capillary and vascular networks that would mimic blood microvessel function can be used to subsequently facilitate oxygen and nutrient transfer as well as waste removal. Vascularization of engineering tissue construct is one of the most favorable strategies to overpass nutrient and oxygen supply limitation, which is often the major hurdle in developing thick and complex tissue and artificial organ. This paper addresses recent advances and future challenges in developing three-dimensional culture systems to promote tissue construct vascularization allowing mimicking blood microvessel development and function encountered in vivo. Bioreactors systems that have been used to create fully vascularized functional tissue constructs will also be outlined. PMID:22623881

Stereoscopic depth increases intersubject correlations of brain networks.

PubMed

Gaebler, Michael; Biessmann, Felix; Lamke, Jan-Peter; Müller, Klaus-Robert; Walter, Henrik; Hetzer, Stefan

2014-10-15

Three-dimensional movies presented via stereoscopic displays have become more popular in recent years aiming at a more engaging viewing experience. However, neurocognitive processes associated with the perception of stereoscopic depth in complex and dynamic visual stimuli remain understudied. Here, we investigate the influence of stereoscopic depth on both neurophysiology and subjective experience. Using multivariate statistical learning methods, we compare the brain activity of subjects when freely watching the same movies in 2D and in 3D. Subjective reports indicate that 3D movies are more strongly experienced than 2D movies. On the neural level, we observe significantly higher intersubject correlations of cortical networks when subjects are watching 3D movies relative to the same movies in 2D. We demonstrate that increases in intersubject correlations of brain networks can serve as neurophysiological marker for stereoscopic depth and for the strength of the viewing experience. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Topological dynamics of vortex-line networks in hexagonal manganites

NASA Astrophysics Data System (ADS)

Xue, Fei; Wang, Nan; Wang, Xueyun; Ji, Yanzhou; Cheong, Sang-Wook; Chen, Long-Qing

2018-01-01

The two-dimensional X Y model is the first well-studied system with topological point defects. On the other hand, although topological line defects are common in three-dimensional systems, the evolution mechanism of line defects is not fully understood. The six domains in hexagonal manganites converge to vortex lines in three dimensions. Using phase-field simulations, we predicted that during the domain coarsening process, the vortex-line network undergoes three types of basic topological changes, i.e., vortex-line loop shrinking, coalescence, and splitting. It is shown that the vortex-antivortex annihilation controls the scaling dynamics.

Three dimensional microstructural network of elastin, collagen, and cells in Achilles tendons.

PubMed

Pang, Xin; Wu, Jian-Ping; Allison, Garry T; Xu, Jiake; Rubenson, Jonas; Zheng, Ming-Hao; Lloyd, David G; Gardiner, Bruce; Wang, Allan; Kirk, Thomas Brett

2017-06-01

Similar to most biological tissues, the biomechanical, and functional characteristics of the Achilles tendon are closely related to its composition and microstructure. It is commonly reported that type I collagen is the predominant component of tendons and is mainly responsible for the tissue's function. Although elastin has been found in varying proportions in other connective tissues, previous studies report that tendons contain very small quantities of elastin. However, the morphology and the microstructural relationship among the elastic fibres, collagen, and cells in tendon tissue have not been well examined. We hypothesize the elastic fibres, as another fibrillar component in the extracellular matrix, have a unique role in mechanical function and microstructural arrangement in Achilles tendons. It has been shown that elastic fibres present a close connection with the tenocytes. The close relationship of the three components has been revealed as a distinct, integrated and complex microstructural network. Notably, a "spiral" structure within fibril bundles in Achilles tendons was observed in some samples in specialized regions. This study substantiates the hierarchical system of the spatial microstructure of tendon, including the mapping of collagen, elastin and tenocytes, with 3-dimensional confocal images. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:1203-1214, 2017. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Exploitation of knowledge databases in the synthesis of zinc(II) malonates with photo-sensitive and photo-insensitive N,N'-containing linkers.

PubMed

Zorina-Tikhonova, Ekaterina N; Chistyakov, Aleksandr S; Kiskin, Mikhail A; Sidorov, Aleksei A; Dorovatovskii, Pavel V; Zubavichus, Yan V; Voronova, Eugenia D; Godovikov, Ivan A; Korlyukov, Alexander A; Eremenko, Igor L; Vologzhanina, Anna V

2018-05-01

Photoinitiated solid-state reactions are known to affect the physical properties of coordination polymers, such as fluorescence and sorption behaviour, and also afford extraordinary architectures ( e.g. three-periodic structures with polyorganic ligands). However, the construction of novel photo-sensitive coordination polymers requires an understanding of the factors which govern the mutual disposition of reactive fragments. A series of zinc(II) malonate complexes with 1,2-bis(pyridin-4-yl)ethylene and its photo-insensitive analogues has been synthesized for the purpose of systematic analysis of their underlying nets and mutual disposition of N -donor ligands. The application of a big data-set analysis for the prediction of a variety of possible complex compositions, coordination environments and networks for a four-component system has been demonstrated for the first time. Seven of the nine compounds possess one of the highly probable topologies for their underlying nets; in addition, two novel closely related four-coordinated networks were obtained. Complexes containing 1,2-bis(pyridin-4-yl)ethylene and 1,2-bis(pyridin-4-yl)ethane form isoreticular compounds more readily than those with 4,4'-bipyridine and 1,2-bis(pyridin-4-yl)ethylene. The effects of the precursor, either zinc(II) nitrate or zinc(II) acetate, on the composition and dimensionality of the resulting architecture are discussed. For three of the four novel complexes containing 1,2-bis(pyridin-4-yl)ethylene, the single-crystal-to-single-crystal [2 + 2] cycloaddition reactions were carried out. UV irradiation of these crystals afforded either the 0D→1D or the 3D→3D transformations, with and without network changes. One of the two 3D→3D transformations was accompanied by solvent (H 2 O) cleavage.

Sequence co-evolution gives 3D contacts and structures of protein complexes

PubMed Central

Hopf, Thomas A; Schärfe, Charlotta P I; Rodrigues, João P G L M; Green, Anna G; Kohlbacher, Oliver; Sander, Chris; Bonvin, Alexandre M J J; Marks, Debora S

2014-01-01

Protein–protein interactions are fundamental to many biological processes. Experimental screens have identified tens of thousands of interactions, and structural biology has provided detailed functional insight for select 3D protein complexes. An alternative rich source of information about protein interactions is the evolutionary sequence record. Building on earlier work, we show that analysis of correlated evolutionary sequence changes across proteins identifies residues that are close in space with sufficient accuracy to determine the three-dimensional structure of the protein complexes. We evaluate prediction performance in blinded tests on 76 complexes of known 3D structure, predict protein–protein contacts in 32 complexes of unknown structure, and demonstrate how evolutionary couplings can be used to distinguish between interacting and non-interacting protein pairs in a large complex. With the current growth of sequences, we expect that the method can be generalized to genome-wide elucidation of protein–protein interaction networks and used for interaction predictions at residue resolution. DOI: http://dx.doi.org/10.7554/eLife.03430.001 PMID:25255213

Unusual (mu-aqua)bis(mu-carboxylate) bridge in homometallic M(II) (M=Mn, Co and Ni) two-dimensional compounds based on the 1,2,3,4-butanetetracarboxylic acid: synthesis, structure, and magnetic properties.

PubMed

Cañadillas-Delgado, Laura; Fabelo, Oscar; Pásan, Jorge; Delgado, Fernando S; Lloret, Francesc; Julve, Miguel; Ruiz-Pérez, Catalina

2007-09-03

The first coordination compounds of 1,2,3,4-butanetetracarboxylate anion (butca4-) of the formula [M2(butca)(H2O)5]n.2nH2O [M=Mn(II) (1), Co(II) (2), and Ni(II) (3)] were prepared and their X-ray crystal structures and magnetic properties investigated. The three complexes have a very similar two-dimensional structure which consists of (4,4) networks, 1 and 2 being isostructural. The tetracarboxylate ligand acts as a 4-fold connector leading to two-dimensional (4,4) networks of metal atoms, this topology being possible because of its planar conformation. The nodes of these networks are formed by dinuclear motifs which exhibit the unusual (mu-aqua)bis(mu-carboxylate) bridging unit which is analogous to that observed in some molecules of biological interest. The variable-temperature magnetic susceptibility measurements of 1-3 show that 1 and 2 are antiferromagnetically coupled systems whereas 3 exhibits a ferromagnetic behavior. The analysis of the magnetic data of 1-3 through a simple dinuclear model allowed the determination of the values of the magnetic coupling (J) -3.6 (1), -1.2 (2), and +1.47 cm(-1) (3) with the Hamiltonian being defined as H=-JSA.SB. The countercomplementarity between the two bridges (aqua and syn-syn carboxylate) accounts for the trend exhibited by the values of the magnetic coupling in this family.

Chaotic interactions of self-replicating RNA.

PubMed

Forst, C V

1996-03-01

A general system of high-order differential equations describing complex dynamics of replicating biomolecules is given. Symmetry relations and coordinate transformations of general replication systems leading to topologically equivalent systems are derived. Three chaotic attractors observed in Lotka-Volterra equations of dimension n = 3 are shown to represent three cross-sections of one and the same chaotic regime. Also a fractal torus in a generalized three-dimensional Lotka-Volterra Model has been linked to one of the chaotic attractors. The strange attractors are studied in the equivalent four-dimensional catalytic replicator network. The fractal torus has been examined in adapted Lotka-Volterra equations. Analytic expressions are derived for the Lyapunov exponents of the flow in the replicator system. Lyapunov spectra for different pathways into chaos has been calculated. In the generalized Lotka-Volterra system a second inner rest point--coexisting with (quasi)-periodic orbits--can be observed; with an abundance of different bifurcations. Pathways from chaotic tori, via quasi-periodic tori, via limit cycles, via multi-periodic orbits--emerging out of periodic doubling bifurcations--to "simple" chaotic attractors can be found.

Three-dimensional mapping in the electrophysiological laboratory.

PubMed

Maury, Philippe; Monteil, Benjamin; Marty, Lilian; Duparc, Alexandre; Mondoly, Pierre; Rollin, Anne

2018-06-07

Investigation and catheter ablation of cardiac arrhythmias are currently still based on optimal knowledge of arrhythmia mechanisms in relation to the cardiac anatomy involved, in order to target their crucial components. Currently, most complex arrhythmias are investigated using three-dimensional electroanatomical navigation systems, because these are felt to optimally integrate both the anatomical and electrophysiological features of a given arrhythmia in a given patient. In this article, we review the technical background of available three-dimensional electroanatomical navigation systems, and their potential use in complex ablations. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

A Three-Dimensional Variational Data Assimilation Scheme for the Regional Ocean Modeling System: Implementation and Basic Experiments

NASA Technical Reports Server (NTRS)

Li, Zhijin; Chao, Yi; McWilliams, James C.; Ide, Kayo

2008-01-01

A three-dimensional variational data assimilation scheme for the Regional Ocean Modeling System (ROMS), named ROMS3DVAR, has been described in the work of Li et al. (2008). In this paper, ROMS3DVAR is applied to the central California coastal region, an area characterized by inhomogeneity and anisotropy, as well as by dynamically unbalanced flows. A method for estimating the model error variances from limited observations is presented, and the construction of the inhomogeneous and anisotropic error correlations based on the Kronecker product is demonstrated. A set of single observation experiments illustrates the inhomogeneous and anisotropic error correlations and weak dynamic constraints used. Results are presented from the assimilation of data gathered during the Autonomous Ocean Sampling Network (AOSN) experiment during August 2003. The results show that ROMS3DVAR is capable of reproducing complex flows associated with upwelling and relaxation, as well as the rapid transitions between them. Some difficulties encountered during the experiment are also discussed.

Collaborative activity between parietal and dorso-lateral prefrontal cortex in dynamic spatial working memory revealed by fMRI.

PubMed

Diwadkar, V A; Carpenter, P A; Just, M A

2000-07-01

Functional MRI was used to determine how the constituents of the cortical network subserving dynamic spatial working memory respond to two types of increases in task complexity. Participants mentally maintained the most recent location of either one or three objects as the three objects moved discretely in either a two- or three-dimensional array. Cortical activation in the dorsolateral prefrontal (DLPFC) and the parietal cortex increased as a function of the number of object locations to be maintained and the dimensionality of the display. An analysis of the response characteristics of the individual voxels showed that a large proportion were activated only when both the variables imposed the higher level of demand. A smaller proportion were activated specifically in response to increases in task demand associated with each of the independent variables. A second experiment revealed the same effect of dimensionality in the parietal cortex when the movement of objects was signaled auditorily rather than visually, indicating that the additional representational demands induced by 3-D space are independent of input modality. The comodulation of activation in the prefrontal and parietal areas by the amount of computational demand suggests that the collaboration between areas is a basic feature underlying much of the functionality of spatial working memory. Copyright 2000 Academic Press.

Two-dimensional 3d-4f heterometallic coordination polymers: syntheses, crystal structures, and magnetic properties of six new Co(II)-Ln(III) compounds.

PubMed

Díaz-Gallifa, Pau; Fabelo, Oscar; Pasán, Jorge; Cañadillas-Delgado, Laura; Lloret, Francesc; Julve, Miguel; Ruiz-Pérez, Catalina

2014-06-16

Six new heterometallic cobalt(II)-lanthanide(III) complexes of formulas [Ln(bta)(H2O)2]2[Co(H2O)6]·10H2O [Ln = Nd(III) (1) and Eu(III) (2)] and [Ln2Co(bta)2(H2O)8]n·6nH2O [Ln = Eu(III) (3), Sm(III) (4), Gd(III) (5), and Tb(III) (6)] (H4bta = 1,2,4,5-benzenetretracaboxylic acid) have been synthesized and characterized via single-crystal X-ray diffraction. 1 and 2 are isostructural compounds with a structure composed of anionic layers of [Ln(bta)(H2O)2]n(n-) sandwiching mononuclear [Co(H2O)6](2+) cations plus crystallization water molecules, which are interlinked by electrostatic forces and hydrogen bonds, leading to a supramolecular three-dimensional network. 3-6 are also isostructural compounds, and their structure consists of neutral layers of formula [Ln2Co(bta)2(H2O)8]n and crystallization water molecules, which are connected through hydrogen bonds to afford a supramolecular three-dimensional network. Heterometallic chains formed by the regular alternation of two nine-coordinate lanthanide(III) polyhedra [Ln(III)O9] and one compressed cobalt(II) octahedron [Co(II)O6] along the crystallographic c-axis are cross-linked by bta ligands within each layer of 3-6. Magnetic susceptibility measurements on polycrystalline samples for 3-6 have been carried out in the temperature range of 2.0-300 K. The magnetic behavior of these types of Ln(III)-Co(II) complexes, which have been modeled by using matrix dagonalization techniques, reveals the lack of magnetic coupling for 3 and 4, and the occurrence of weak antiferromagnetic interactions within the Gd(III)-Gd(III) (5) and Tb(III)-Tb(III) (6) dinuclear units through the exchange pathway provided by the double oxo(carboxylate) and double syn-syn carboxylate bridges.

Dissecting the Calcium-Induced Differentiation of Human Primary Keratinocytes Stem Cells by Integrative and Structural Network Analyses

PubMed Central

Toufighi, Kiana; Yang, Jae-Seong; Luis, Nuno Miguel; Aznar Benitah, Salvador; Lehner, Ben; Serrano, Luis; Kiel, Christina

2015-01-01

The molecular details underlying the time-dependent assembly of protein complexes in cellular networks, such as those that occur during differentiation, are largely unexplored. Focusing on the calcium-induced differentiation of primary human keratinocytes as a model system for a major cellular reorganization process, we look at the expression of genes whose products are involved in manually-annotated protein complexes. Clustering analyses revealed only moderate co-expression of functionally related proteins during differentiation. However, when we looked at protein complexes, we found that the majority (55%) are composed of non-dynamic and dynamic gene products (‘di-chromatic’), 19% are non-dynamic, and 26% only dynamic. Considering three-dimensional protein structures to predict steric interactions, we found that proteins encoded by dynamic genes frequently interact with a common non-dynamic protein in a mutually exclusive fashion. This suggests that during differentiation, complex assemblies may also change through variation in the abundance of proteins that compete for binding to common proteins as found in some cases for paralogous proteins. Considering the example of the TNF-α/NFκB signaling complex, we suggest that the same core complex can guide signals into diverse context-specific outputs by addition of time specific expressed subunits, while keeping other cellular functions constant. Thus, our analysis provides evidence that complex assembly with stable core components and competition could contribute to cell differentiation. PMID:25946651

Particle tracking approach for transport in three-dimensional discrete fracture networks: Particle tracking in 3-D DFNs

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

Makedonska, Nataliia; Painter, Scott L.; Bui, Quan M.

The discrete fracture network (DFN) model is a method to mimic discrete pathways for fluid flow through a fractured low-permeable rock mass, and may be combined with particle tracking simulations to address solute transport. However, experience has shown that it is challenging to obtain accurate transport results in three-dimensional DFNs because of the high computational burden and difficulty in constructing a high-quality unstructured computational mesh on simulated fractures. We present a new particle tracking capability, which is adapted to control volume (Voronoi polygons) flow solutions on unstructured grids (Delaunay triangulations) on three-dimensional DFNs. The locally mass-conserving finite-volume approach eliminates massmore » balance-related problems during particle tracking. The scalar fluxes calculated for each control volume face by the flow solver are used to reconstruct a Darcy velocity at each control volume centroid. The groundwater velocities can then be continuously interpolated to any point in the domain of interest. The control volumes at fracture intersections are split into four pieces, and the velocity is reconstructed independently on each piece, which results in multiple groundwater velocities at the intersection, one for each fracture on each side of the intersection line. This technique enables detailed particle transport representation through a complex DFN structure. Verified for small DFNs, the new simulation capability enables numerical experiments on advective transport in large DFNs to be performed. As a result, we demonstrate this particle transport approach on a DFN model using parameters similar to those of crystalline rock at a proposed geologic repository for spent nuclear fuel in Forsmark, Sweden.« less

Particle tracking approach for transport in three-dimensional discrete fracture networks: Particle tracking in 3-D DFNs

DOE PAGES

Makedonska, Nataliia; Painter, Scott L.; Bui, Quan M.; ...

2015-09-16

The discrete fracture network (DFN) model is a method to mimic discrete pathways for fluid flow through a fractured low-permeable rock mass, and may be combined with particle tracking simulations to address solute transport. However, experience has shown that it is challenging to obtain accurate transport results in three-dimensional DFNs because of the high computational burden and difficulty in constructing a high-quality unstructured computational mesh on simulated fractures. We present a new particle tracking capability, which is adapted to control volume (Voronoi polygons) flow solutions on unstructured grids (Delaunay triangulations) on three-dimensional DFNs. The locally mass-conserving finite-volume approach eliminates massmore » balance-related problems during particle tracking. The scalar fluxes calculated for each control volume face by the flow solver are used to reconstruct a Darcy velocity at each control volume centroid. The groundwater velocities can then be continuously interpolated to any point in the domain of interest. The control volumes at fracture intersections are split into four pieces, and the velocity is reconstructed independently on each piece, which results in multiple groundwater velocities at the intersection, one for each fracture on each side of the intersection line. This technique enables detailed particle transport representation through a complex DFN structure. Verified for small DFNs, the new simulation capability enables numerical experiments on advective transport in large DFNs to be performed. As a result, we demonstrate this particle transport approach on a DFN model using parameters similar to those of crystalline rock at a proposed geologic repository for spent nuclear fuel in Forsmark, Sweden.« less

Synthesis, growth, structural and optical studies of a new organic three dimensional framework: 4-(aminocarbonyl)pyridine 4-(aminocarbonyl)pyridinium hydrogen L-malate

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

Vijayalakshmi, A.; Vidyavathy, B., E-mail: vidyavathybalraj@gmail.com; Peramaiyan, G.

2017-02-15

4-(aminocarbonyl)pyridine 4-(aminocarbonyl)pyridinium hydrogen L-malate [(4ACP)(4ACP).(LM)] a new organic nonlinear optical (NLO) crystal was grown by the slow evaporation method. Single crystal X-ray diffraction analysis revealed that the [(4ACP)(4ACP).(LM)] crystal belongs to monoclinic crystal system, space group P2{sub 1}/n, with a three dimensional network. Thermogravimetry (TG) and differential thermal (DT) analyses showed that [(4ACP)(4ACP).(LM)] is thermally stable up to 165 °C. The optical transmittance window and the lower cut-off wavelength of [(4ACP)(4ACP).(LM)] were found out by UV–vis–NIR spectral study. The molecular structure of [(4ACP)(4ACP).(LM)] was further confirmed by FTIR spectral studies. The relative dielectric permittivity and dielectric loss were determined asmore » function of frequency and temperature. The third order nonlinear optical property of [(4ACP)(4ACP).(LM)] was studied by the Z-scan technique using a 532 nm diode pumped CW Nd:YAG laser. Nonlinear refractive index, nonlinear absorption coefficient and third order nonlinear susceptibility of the grown crystal were found to be 7.38×10{sup −8} cm{sup 2}/W, 0.08×10{sup −4} cm/W and 5.36×10{sup −6} esu, respectively. The laser damage threshold value is found to be 1.75 GW/cm{sup 2} - Graphical abstract: In the crystal structure of the title complex, the asymmetric unit contains one hydrogen L-malate anion, 4-(aminocarbonyl)pyridinium cation and a neutral isonicotinamide molecule. It is stabilized by intermolecular N-H…O, C-H…O and O-H…O hydrogen bonds which generate a three dimensional network.« less

The sea urchin egg jelly coat is a three-dimensional fibrous network as seen by intermediate voltage electron microscopy and deep etching analysis.

PubMed

Bonnell, B S; Larabell, C; Chandler, D E

1993-06-01

The egg jelly (EJ) coat which surrounds the unfertilized sea urchin egg undergoes extensive swelling upon contact with sea water, forming a three-dimensional network of interconnected fibers extending nearly 50 microns from the egg surface. Owing to its solubility, this coat has been difficult to visualize by light and electron microscopy. However, Lytechinus pictus EJ coats remain intact, if the fixation medium is maintained at pH 9. The addition of alcian blue during the final dehydration step of sample preparation stains the EJ for visualization of resin embedded eggs by both light and electron microscopy. Stereo pairs taken of thick sections prepared for intermediate voltage electron microscopy (IVEM) produce a three-dimensional image of the EJ network, consisting of interconnected fibers decorated along their length by globular jelly components. Using scanning electron microscopy (SEM), we have shown that before swelling, EJ exists in a tightly bound network of jelly fibers, 50-60 nm in diameter. In contrast, swollen EJ consists of a greatly extended network whose fibrous components measure 10 to 30 nm in diameter. High resolution stereo images of hydrated jelly produced by the quick-freeze/deep-etch/rotary-shadowing technique (QF/DE/RS) show nearly identical EJ networks, suggesting that dehydration does not markedly alter the structure of this extracellular matrix.

Melanoma Spheroid Formation Involves Laminin-Associated Vasculogenic Mimicry

PubMed Central

Larson, Allison R.; Lee, Chung-Wei; Lezcano, Cecilia; Zhan, Qian; Huang, John; Fischer, Andrew H.; Murphy, George F.

2015-01-01

Melanoma is a tumor where virulence is conferred on transition from flat (radial) to three-dimensional (tumorigenic) growth. Virulence of tumorigenic growth is governed by numerous attributes, including presence of self-renewing stem-like cells and related formation of patterned networks associated with the melanoma mitogen, laminin, a phenomenon known as vasculogenic mimicry. Vasculogenic mimicry is posited to contribute to melanoma perfusion and nutrition in vivo; we hypothesized that it may also play a role in stem cell–driven spheroid formation in vitro. Using a model of melanoma in vitro tumorigenesis, laminin-associated networks developed in association with three-dimensional melanoma spheroids. Real-time PCR analysis of laminin subunits showed that spheroids formed from anchorage-independent melanoma cells expressed increased α4 and β1 laminin chains and α4 laminin expression was confirmed by in situ hybridization. Association of laminin networks with melanoma stem cell–associated nestin and vascular endothelial growth factor receptor-1 also was documented. Moreover, knockdown of nestin gene expression impaired laminin expression and network formation within spheroids. Laminin networks were remarkably similar to those observed in melanoma xenografts in mice and to those seen in patient melanomas. These data indicate that vasculogenic mimicry–like laminin networks, in addition to their genesis in vivo, are integral to the extracellular architecture of melanoma spheroids in vitro, where they may serve as stimulatory scaffolds to support three-dimensional growth. PMID:24332013

Development of Three-Dimensional Completion of Complex Objects

ERIC Educational Resources Information Center

Soska, Kasey C.; Johnson, Scott P.

2013-01-01

Three-dimensional (3D) object completion, the ability to perceive the backs of objects seen from a single viewpoint, emerges at around 6 months of age. Yet, only relatively simple 3D objects have been used in assessing its development. This study examined infants' 3D object completion when presented with more complex stimuli. Infants…

Syntheses, crystal structures, and properties of four coordination polymers based on mixed multi-N donor and polycarboxylate ligands

NASA Astrophysics Data System (ADS)

Chen, Shui-Sheng; Guo, Xing-Zhe; Zhao, Yue; Li, Wei-Dong

2018-02-01

Four new coordination polymers [Ni2(HL1)2(L1)3(BTC)2]·6H2O (1), [Ni2(L1)3(HBTC)2]·4H2O (2), [Cd2(L2)(BTC)(H2O)3]·2H2O (3) and [Cd2(HL2)(BTCA)] (4) were synthesized by reactions of nickel(II)/ cadmium(II) salts with rigid ligands of 1,4-di(1H-imidazol-4-yl)benzene (L1), 1,3-di(1-imidazolyl)-5-(4H-tetrazol-5-yl)benzene (HL2) and polycarboxylic acids of 1,3,5-benzenetricarboxylic acid (H3BTC), 1,2,4,5-benzenetetracarboxylic acid (H4BTCA), respectively. The structures of the complexes were determined by single crystal X-ray diffraction analysis. The complex 1 is one-dimensional (1D) chain while 2 is a (4, 4)-connected two-dimensional (2D) layered structure with 2D → 2D parallel interpenetration. Complex 3 is a rare tetranodal (3,4)-connected three-dimensional (3D) CrVTiSc architecture with Point (Schläfli) symbol of (4·82)(4·84·10)(42·82·102)(83), and compound 4 has the 2D network with (4,4) topology based on the [Cd2(COO)4] SBUs. The weak interactions such as hydrogen bonds and π···π stacking contribute to stabilize crystal structure and extend the low-dimensional entities into high-dimensional frameworks. The UV-vis absorption spectra of 1 - 4 are discussed. Moreover, the photo luminescent properties of 3 and 4 and gas sorption property of 2 have been investigated.

Multi-Dimensional Prioritization of Dental Caries Candidate Genes and Its Enriched Dense Network Modules

PubMed Central

Wang, Quan; Jia, Peilin; Cuenco, Karen T.; Feingold, Eleanor; Marazita, Mary L.; Wang, Lily; Zhao, Zhongming

2013-01-01

A number of genetic studies have suggested numerous susceptibility genes for dental caries over the past decade with few definite conclusions. The rapid accumulation of relevant information, along with the complex architecture of the disease, provides a challenging but also unique opportunity to review and integrate the heterogeneous data for follow-up validation and exploration. In this study, we collected and curated candidate genes from four major categories: association studies, linkage scans, gene expression analyses, and literature mining. Candidate genes were prioritized according to the magnitude of evidence related to dental caries. We then searched for dense modules enriched with the prioritized candidate genes through their protein-protein interactions (PPIs). We identified 23 modules comprising of 53 genes. Functional analyses of these 53 genes revealed three major clusters: cytokine network relevant genes, matrix metalloproteinases (MMPs) family, and transforming growth factor-beta (TGF-β) family, all of which have been previously implicated to play important roles in tooth development and carious lesions. Through our extensive data collection and an integrative application of gene prioritization and PPI network analyses, we built a dental caries-specific sub-network for the first time. Our study provided insights into the molecular mechanisms underlying dental caries. The framework we proposed in this work can be applied to other complex diseases. PMID:24146904

Imaging and three-dimensional reconstruction of chemical groups inside a protein complex using atomic force microscopy

NASA Astrophysics Data System (ADS)

Kim, Duckhoe; Sahin, Ozgur

2015-03-01

Scanning probe microscopes can be used to image and chemically characterize surfaces down to the atomic scale. However, the localized tip-sample interactions in scanning probe microscopes limit high-resolution images to the topmost atomic layer of surfaces, and characterizing the inner structures of materials and biomolecules is a challenge for such instruments. Here, we show that an atomic force microscope can be used to image and three-dimensionally reconstruct chemical groups inside a protein complex. We use short single-stranded DNAs as imaging labels that are linked to target regions inside a protein complex, and T-shaped atomic force microscope cantilevers functionalized with complementary probe DNAs allow the labels to be located with sequence specificity and subnanometre resolution. After measuring pairwise distances between labels, we reconstruct the three-dimensional structure formed by the target chemical groups within the protein complex using simple geometric calculations. Experiments with the biotin-streptavidin complex show that the predicted three-dimensional loci of the carboxylic acid groups of biotins are within 2 Å of their respective loci in the corresponding crystal structure, suggesting that scanning probe microscopes could complement existing structural biological techniques in solving structures that are difficult to study due to their size and complexity.

Recognition Of Complex Three Dimensional Objects Using Three Dimensional Moment Invariants

NASA Astrophysics Data System (ADS)

Sadjadi, Firooz A.

1985-01-01

A technique for the recognition of complex three dimensional objects is presented. The complex 3-D objects are represented in terms of their 3-D moment invariants, algebraic expressions that remain invariant independent of the 3-D objects' orientations and locations in the field of view. The technique of 3-D moment invariants has been used successfully for simple 3-D object recognition in the past. In this work we have extended this method for the representation of more complex objects. Two complex objects are represented digitally; their 3-D moment invariants have been calculated, and then the invariancy of these 3-D invariant moment expressions is verified by changing the orientation and the location of the objects in the field of view. The results of this study have significant impact on 3-D robotic vision, 3-D target recognition, scene analysis and artificial intelligence.

Tuning zinc coordination architectures by benzenedicarboxylate position isomers and bis(triazole)

NASA Astrophysics Data System (ADS)

Peng, Yan-fen; Li, Ke; Zhao, Shan; Han, Shan-shan; Li, Bao-long; Li, Hai-Yan

2015-08-01

Three position isomers 1,2-, 1,3-, 1,4-benzenedicarboxylate and 1,4-bis(1,2,4-triazol-4-yl)benzene were used to assembly zinc(II) coordination polymers {[Zn2(btx)0.5(1,2-bdc)2(H2O)]·H2O}n (1), {[Zn(btx)(1,3-bdc)]·2H2O·(DMF)}n (2) and {[Zn(btx)(1,4-bdc)]·3H2O}n (3). 1 is a (3,4,4,4)-connected two-dimensional network with point symbol (42·6)(44·62)(43·62·8)(42·6·103). 2 shows a two-dimensional (4,4) network. 3 exhibits a 5-fold interpenetrated three-dimensional diamondoid network. The structural versatility shows that the structures of coordination polymers can be tuned by the position isomers ligands. The luminescence and thermal stability were investigated.

Rational Organization of Lanthanide-Based SMM Dimers into Three-Dimensional Networks.

PubMed

Yi, Xiaohui; Calvez, Guillaume; Daiguebonne, Carole; Guillou, Olivier; Bernot, Kevin

2015-06-01

Optimization of the reaction of [Ln(hfac)3]·2H2O and pyridine-N-oxide (PyNO), which is known to afford double-bridged dimers, leads to triple-bridged dimers of formula [(Ln(hfac)3)2(PyNO)3] (Ln = Gd (1), Dy (2)) from which the Dy derivative (2) behaves as a single-molecule magnet (SMM). The pseudo threefold axis symmetry of this zero-dimensional building block makes possible its extension into a tridimensional network. By changing PyNO for 4,4'-bipyridine N,N'-dioxide (4,4'BipyNO) a tridimensional compound of formula {[Ln(hfac)3]2(4,4'BipyNO)2]} (Ln = Eu (3), Gd (4), and Dy (5)) is then rationally obtained. This covalent three-dimensional (3D) network has a remarkably high cell volume (V = 24 419 A(3)) and is an arrangement of interpenetrated 3D subnetworks whose triple-bridged dimers still behave as SMMs.

Nonlinear dimensionality reduction of electroencephalogram (EEG) for Brain Computer interfaces.

PubMed

Teli, Mohammad Nayeem; Anderson, Charles

2009-01-01

Patterns in electroencephalogram (EEG) signals are analyzed for a Brain Computer Interface (BCI). An important aspect of this analysis is the work on transformations of high dimensional EEG data to low dimensional spaces in which we can classify the data according to mental tasks being performed. In this research we investigate how a Neural Network (NN) in an auto-encoder with bottleneck configuration can find such a transformation. We implemented two approximate second-order methods to optimize the weights of these networks, because the more common first-order methods are very slow to converge for networks like these with more than three layers of computational units. The resulting non-linear projections of time embedded EEG signals show interesting separations that are related to tasks. The bottleneck networks do indeed discover nonlinear transformations to low-dimensional spaces that capture much of the information present in EEG signals. However, the resulting low-dimensional representations do not improve classification rates beyond what is possible using Quadratic Discriminant Analysis (QDA) on the original time-lagged EEG.

Architectural design, interior decoration, and three-dimensional plumbing en route to multifunctional nanoarchitectures.

PubMed

Long, Jeffrey W

2007-09-01

Ultraporous aperiodic solids, such as aerogels and ambigels, are sol-gel-derived equivalents of architectures. The walls are defined by the nanoscopic, covalently bonded solid network of the gel. The vast open, interconnected space characteristic of a building is represented by the three-dimensionally continuous nanoscopic pore network. We discuss how an architectural construct serves as a powerful metaphor that guides the chemist in the design of aerogel-like nanoarchitectures and in their physical and chemical transformation into multifunctional objects that yield high performance for rate-critical applications.

Percolation in three-dimensional fracture networks for arbitrary size and shape distributions

NASA Astrophysics Data System (ADS)

Thovert, J.-F.; Mourzenko, V. V.; Adler, P. M.

2017-04-01

The percolation threshold of fracture networks is investigated by extensive direct numerical simulations. The fractures are randomly located and oriented in three-dimensional space. A very wide range of regular, irregular, and random fracture shapes is considered, in monodisperse or polydisperse networks containing fractures with different shapes and/or sizes. The results are rationalized in terms of a dimensionless density. A simple model involving a new shape factor is proposed, which accounts very efficiently for the influence of the fracture shape. It applies with very good accuracy in monodisperse or moderately polydisperse networks, and provides a good first estimation in other situations. A polydispersity index is shown to control the need for a correction, and the corrective term is modelled for the investigated size distributions.

Poly-dimensional network comparative analysis reveals the pure pharmacological mechanism of baicalin in the targeted network of mouse cerebral ischemia.

PubMed

Liu, Qiong; Liu, Jun; Wang, Pengqian; Zhang, Yingying; Li, Bing; Yu, Yanan; Dang, Haixia; Li, Haixia; Zhang, Xiaoxu; Wang, Zhong

2017-07-01

This study aimed to investigate the pure pharmacological mechanisms of baicalin/baicalein (BA) in the targeted network of mouse cerebral ischemia using a poly-dimensional network comparative analysis. Eighty mice with induced focal cerebral ischemia were randomly divided into four groups: BA, Concha Margaritifera (CM), vehicle and sham group. A poly-dimensional comparative analysis of the expression levels of 374 stroke-related genes in each of the four groups was performed using MetaCore. BA significantly reduced the ischemic infarct volume (P<0.05), whereas CM was ineffective. Two processes and 10 network nodes were shared between "BA vs CM" and vehicle, but there were no overlapping pathways. Two pathways, three processes and 12 network nodes overlapped in "BA vs CM" and BA. The pure pharmacological mechanism of BA resulted in targeting of pathways related to development, G-protein signaling, apoptosis, signal transduction and immunity. The biological processes affected by BA were primarily found to correlate with apoptotic, anti-apoptotic and neurophysiological processes. Three network nodes changed from up-regulation to down-regulation, while mitogen-activated protein kinase kinase 6 (MAP2K6, also known as MEK6) changed from down-regulation to up-regulation in "BA vs CM" and vehicle. The changed nodes were all related to cell death and development. The pure pharmacological mechanism of BA is related to immunity, apoptosis, development, cytoskeletal remodeling, transduction and neurophysiology, as ascertained using a poly-dimensional network comparative analysis. Copyright © 2017. Published by Elsevier B.V.

Structure of the nocturnal boundary layer over a complex terrain

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

Parker, M.J.; Raman, S.

The complex nature of the nocturnal boundary layer (NBL) has been shown extensively in the literature Project STABLE was conducted in 1988 to study NBL turbulence and diffusion over the complex terrain of the Savannah River Site (SRS) near Augusta, Georgia. The third night of the study was particularly interesting because of the unusual phenomena observed in the structure of the NBL. Further analyses of microscale and mesoscale data from this night are presented using data from SRS network of eight 61 m towers over 900 km{sup 2}, from six launches of an instrumented tethersonde, from permanent SRL meteorological instrumentationmore » at seven levels of the 304 m (1,000 ft) WJBF-TV tower near SRS, and additional data collected at 36 m (CC) by North Carolina State University (NCSU) including a one dimensional sonic anemometer, fine wire thermocouple, and a three dimensional propeller anemometer. Also, data from the nearby Plant Vogtle nuclear power plant observation tower and the National Weather Service at Augusta`s Bush Field (AGS) are presented. The passage of a mesoscale phenomenon, defined as a microfront (with an explanation of the nomenclature used), and a vertical composite schematic of the NBL which shows dual low level wind maxima, dual inversions, and a persistent, elevated turbulent layer over a complex terrain are described.« less

Structure of the nocturnal boundary layer over a complex terrain

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

Parker, M.J.; Raman, S.

The complex nature of the nocturnal boundary layer (NBL) has been shown extensively in the literature Project STABLE was conducted in 1988 to study NBL turbulence and diffusion over the complex terrain of the Savannah River Site (SRS) near Augusta, Georgia. The third night of the study was particularly interesting because of the unusual phenomena observed in the structure of the NBL. Further analyses of microscale and mesoscale data from this night are presented using data from SRS network of eight 61 m towers over 900 km{sup 2}, from six launches of an instrumented tethersonde, from permanent SRL meteorological instrumentationmore » at seven levels of the 304 m (1,000 ft) WJBF-TV tower near SRS, and additional data collected at 36 m (CC) by North Carolina State University (NCSU) including a one dimensional sonic anemometer, fine wire thermocouple, and a three dimensional propeller anemometer. Also, data from the nearby Plant Vogtle nuclear power plant observation tower and the National Weather Service at Augusta's Bush Field (AGS) are presented. The passage of a mesoscale phenomenon, defined as a microfront (with an explanation of the nomenclature used), and a vertical composite schematic of the NBL which shows dual low level wind maxima, dual inversions, and a persistent, elevated turbulent layer over a complex terrain are described.« less

Structure of the nocturnal boundary layer over a complex terrain

NASA Astrophysics Data System (ADS)

Parker, M. J.; Raman, S.

The complex nature of the nocturnal boundary layer (NBL) has been shown extensively in the literature Project STABLE was conducted in 1988 to study NBL turbulence and diffusion over the complex terrain of the Savannah River Site (SRS) near Augusta, Georgia. The third night of the study was particularly interesting because of the unusual phenomena observed in the structure of the NBL. Further analyses of microscale and mesoscale data from this night are presented using data from SRS network of eight 61 m towers over 900 sq km, from six launches of an instrumented tethersonde, from permanent SRL meteorological instrumentation at seven levels of the 304 m (1,000 ft) WJBF-TV tower near SRS, and additional data collected at 36 m (CC) by North Carolina State University (NCSU) including a one dimensional sonic anemometer, fine wire thermocouple, and a three dimensional propeller anemometer. Also, data from the nearby Plant Vogtle nuclear power plant observation tower and the National Weather Service at Augusta's Bush Field (AGS) are presented. The passage of a mesoscale phenomenon, defined as a microfront (with an explanation of the nomenclature used), and a vertical composite schematic of the NBL which shows dual low level wind maxima, dual inversions, and a persistent, elevated turbulent layer over a complex terrain are described.

Three-dimensional study of grain boundary engineering effects on intergranular stress corrosion cracking of 316 stainless steel in high temperature water

NASA Astrophysics Data System (ADS)

Liu, Tingguang; Xia, Shuang; Bai, Qin; Zhou, Bangxin; Zhang, Lefu; Lu, Yonghao; Shoji, Tetsuo

2018-01-01

The intergranular cracks and grain boundary (GB) network of a GB-engineered 316 stainless steel after stress corrosion cracking (SCC) test in high temperature high pressure water of reactor environment were investigated by two-dimensional and three-dimensional (3D) characterization in order to expose the mechanism that GB-engineering mitigates intergranular SCC. The 3D microstructure shown that the essential characteristic of the GB-engineered microstructure is formation of many large twin-boundaries as a result of multiple-twinning, which results in the formation of large grain-clusters. The large grain-clusters played a key role to the improvement of intergranular SCC resistance by GB-engineering. The main intergranular cracks propagated in a zigzag along the outer boundaries of these large grain-clusters because all inner boundaries of the grain-clusters were twin-boundaries (∑3) or twin-related boundaries (∑3n) which had much lower susceptibility to SCC than random boundaries. These large grain-clusters had tree-ring-shaped topology structure and very complex morphology. They got tangled so that difficult to be separated during SCC, resulting in some large crack-bridges retained in the crack surface.

A complex systems analysis of stick-slip dynamics of a laboratory fault

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

Walker, David M.; Tordesillas, Antoinette, E-mail: atordesi@unimelb.edu.au; Small, Michael

2014-03-15

We study the stick-slip behavior of a granular bed of photoelastic disks sheared by a rough slider pulled along the surface. Time series of a proxy for granular friction are examined using complex systems methods to characterize the observed stick-slip dynamics of this laboratory fault. Nonlinear surrogate time series methods show that the stick-slip behavior appears more complex than a periodic dynamics description. Phase space embedding methods show that the dynamics can be locally captured within a four to six dimensional subspace. These slider time series also provide an experimental test for recent complex network methods. Phase space networks, constructedmore » by connecting nearby phase space points, proved useful in capturing the key features of the dynamics. In particular, network communities could be associated to slip events and the ranking of small network subgraphs exhibited a heretofore unreported ordering.« less

Network representation of protein interactions: Theory of graph description and analysis.

PubMed

Kurzbach, Dennis

2016-09-01

A methodological framework is presented for the graph theoretical interpretation of NMR data of protein interactions. The proposed analysis generalizes the idea of network representations of protein structures by expanding it to protein interactions. This approach is based on regularization of residue-resolved NMR relaxation times and chemical shift data and subsequent construction of an adjacency matrix that represents the underlying protein interaction as a graph or network. The network nodes represent protein residues. Two nodes are connected if two residues are functionally correlated during the protein interaction event. The analysis of the resulting network enables the quantification of the importance of each amino acid of a protein for its interactions. Furthermore, the determination of the pattern of correlations between residues yields insights into the functional architecture of an interaction. This is of special interest for intrinsically disordered proteins, since the structural (three-dimensional) architecture of these proteins and their complexes is difficult to determine. The power of the proposed methodology is demonstrated at the example of the interaction between the intrinsically disordered protein osteopontin and its natural ligand heparin. © 2016 The Protein Society.

Weak signal transmission in complex networks and its application in detecting connectivity.

PubMed

Liang, Xiaoming; Liu, Zonghua; Li, Baowen

2009-10-01

We present a network model of coupled oscillators to study how a weak signal is transmitted in complex networks. Through both theoretical analysis and numerical simulations, we find that the response of other nodes to the weak signal decays exponentially with their topological distance to the signal source and the coupling strength between two neighboring nodes can be figured out by the responses. This finding can be conveniently used to detect the topology of unknown network, such as the degree distribution, clustering coefficient and community structure, etc., by repeatedly choosing different nodes as the signal source. Through four typical networks, i.e., the regular one dimensional, small world, random, and scale-free networks, we show that the features of network can be approximately given by investigating many fewer nodes than the network size, thus our approach to detect the topology of unknown network may be efficient in practical situations with large network size.

Poly[mu2-(N-hydroxypyridine-2-carboxamidine)-mu2-nitrato-silver(I)].

PubMed

Cui, Ai-Li; Han, Peng; Yang, Hui-Juan; Wang, Ru-Ji; Kou, Hui-Zhong

2007-12-01

In the title complex, [Ag(NO3)(C6H7N3O)]n or [Ag(NO3)(pyaoxH2)] (pyaoxH2 is N-hydroxypyridine-2-carboxamidine), the Ag+ ion is bridged by the pyaoxH2 ligands and nitrate anions, giving rise to a two-dimensional molecular structure. Each pyaoxH2 ligand coordinates to two Ag+ ions using its pyridyl and carboxamidine N atoms, and the OH and the NH2 groups are uncoordinated. Each nitrate anion uses two O atoms to coordinate to two Ag+ ions. The Ag...Ag separation via the pyaoxH2 bridge is 2.869 (1) A, markedly shorter than that of 6.452 (1) A via the nitrate bridge. The two-dimensional structure is fishscale-like, and can be described as pyaoxH2-bridged Ag2 nodes that are further linked by nitrate anions. Hydrogen bonding between the amidine groups and the nitrate O atoms connects adjacent layers into a three-dimensional network.

Neural Network Machine Learning and Dimension Reduction for Data Visualization

NASA Technical Reports Server (NTRS)

Liles, Charles A.

2014-01-01

Neural network machine learning in computer science is a continuously developing field of study. Although neural network models have been developed which can accurately predict a numeric value or nominal classification, a general purpose method for constructing neural network architecture has yet to be developed. Computer scientists are often forced to rely on a trial-and-error process of developing and improving accurate neural network models. In many cases, models are constructed from a large number of input parameters. Understanding which input parameters have the greatest impact on the prediction of the model is often difficult to surmise, especially when the number of input variables is very high. This challenge is often labeled the "curse of dimensionality" in scientific fields. However, techniques exist for reducing the dimensionality of problems to just two dimensions. Once a problem's dimensions have been mapped to two dimensions, it can be easily plotted and understood by humans. The ability to visualize a multi-dimensional dataset can provide a means of identifying which input variables have the highest effect on determining a nominal or numeric output. Identifying these variables can provide a better means of training neural network models; models can be more easily and quickly trained using only input variables which appear to affect the outcome variable. The purpose of this project is to explore varying means of training neural networks and to utilize dimensional reduction for visualizing and understanding complex datasets.

Neural Connectivity Evidence for a Categorical-Dimensional Hybrid Model of Autism Spectrum Disorder.

PubMed

Elton, Amanda; Di Martino, Adriana; Hazlett, Heather Cody; Gao, Wei

2016-07-15

Autism spectrum disorder (ASD) encompasses a complex manifestation of symptoms that include deficits in social interaction and repetitive or stereotyped interests and behaviors. In keeping with the increasing recognition of the dimensional characteristics of ASD symptoms and the categorical nature of a diagnosis, we sought to delineate the neural mechanisms of ASD symptoms based on the functional connectivity of four known neural networks (i.e., default mode network, dorsal attention network, salience network, and executive control network). We leveraged an open data resource (Autism Brain Imaging Data Exchange) providing resting-state functional magnetic resonance imaging data sets from 90 boys with ASD and 95 typically developing boys. This data set also included the Social Responsiveness Scale as a dimensional measure of ASD traits. Seed-based functional connectivity was paired with linear regression to identify functional connectivity abnormalities associated with categorical effects of ASD diagnosis, dimensional effects of ASD-like behaviors, and their interaction. Our results revealed the existence of dimensional mechanisms of ASD uniquely affecting each network based on the presence of connectivity-behavioral relationships; these were independent of diagnostic category. However, we also found evidence of categorical differences (i.e., diagnostic group differences) in connectivity strength for each network as well as categorical differences in connectivity-behavioral relationships (i.e., diagnosis-by-behavior interactions), supporting the coexistence of categorical mechanisms of ASD. Our findings support a hybrid model for ASD characterization that includes a combination of categorical and dimensional brain mechanisms and provide a novel understanding of the neural underpinnings of ASD. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Preparation of organogel with tea polyphenols complex for enhancing the antioxidation properties of edible oil.

PubMed

Shi, Rong; Zhang, Qiuyue; Vriesekoop, Frank; Yuan, Qipeng; Liang, Hao

2014-08-20

Food-grade organogels are semisolid systems with immobilized liquid edible oil in a three-dimensional network of self-assembled gelators, and they are supposed to have a broad range of potential applications in food industries. In this work, an edible organogel with tea polyphenols was developed, which possesses a highly effective antioxidative function. To enhance the dispersibility of the tea polyphenols in the oil phase, a solid lipid-surfactant-tea polyphenols complex (organogel complex) was first prepared according to a novel method. Then, a food-grade organogel was prepared by mixing this organogel complex with fresh peanut oil. Compared with adding free tea polyphenols, the organogel complex could be more homogeneously distributed in the prepared organogel system, especially under heating condition. Furthermore, the organogel loading of tea polyphenols performed a 2.5-fold higher antioxidation compared with other chemically synthesized antioxidants (butylated hydroxytoluene and propyl gallate) by evaluating the peroxide value of the fresh peanut oil based organogel in accelerated oxidation conditions.

Beyond the known functions of the CCR4-NOT complex in gene expression regulatory mechanisms: New structural insights to unravel CCR4-NOT mRNA processing machinery.

PubMed

Ukleja, Marta; Valpuesta, José María; Dziembowski, Andrzej; Cuellar, Jorge

2016-10-01

Large protein assemblies are usually the effectors of major cellular processes. The intricate cell homeostasis network is divided into numerous interconnected pathways, each controlled by a set of protein machines. One of these master regulators is the CCR4-NOT complex, which ultimately controls protein expression levels. This multisubunit complex assembles around a scaffold platform, which enables a wide variety of well-studied functions from mRNA synthesis to transcript decay, as well as other tasks still being identified. Solving the structure of the entire CCR4-NOT complex will help to define the distribution of its functions. The recently published three-dimensional reconstruction of the complex, in combination with the known crystal structures of some of the components, has begun to address this. Methodological improvements in structural biology, especially in cryoelectron microscopy, encourage further structural and protein-protein interaction studies, which will advance our comprehension of the gene expression machinery. © 2016 WILEY Periodicals, Inc.

Assortativity Patterns in Multi-dimensional Inter-organizational Networks: A Case Study of the Humanitarian Relief Sector

NASA Astrophysics Data System (ADS)

Zhao, Kang; Ngamassi, Louis-Marie; Yen, John; Maitland, Carleen; Tapia, Andrea

We use computational tools to study assortativity patterns in multi-dimensional inter-organizational networks on the basis of different node attributes. In the case study of an inter-organizational network in the humanitarian relief sector, we consider not only macro-level topological patterns, but also assortativity on the basis of micro-level organizational attributes. Unlike assortative social networks, this inter-organizational network exhibits disassortative or random patterns on three node attributes. We believe organizations' seek of complementarity is one of the main reasons for the special patterns. Our analysis also provides insights on how to promote collaborations among the humanitarian relief organizations.

Three-dimensional object recognitions from two-dimensional images using wavelet transforms and neural networks

NASA Astrophysics Data System (ADS)

Deschenes, Sylvain; Sheng, Yunlong; Chevrette, Paul C.

1998-03-01

3D object classification from 2D IR images is shown. The wavelet transform is used for edge detection. Edge tracking is used for removing noise effectively int he wavelet transform. The invariant Fourier descriptor is used to describe the contour curves. Invariance under out-of-plane rotation is achieved by the feature space trajectory neural network working as a classifier.

Artificial neural network methods in quantum mechanics

NASA Astrophysics Data System (ADS)

Lagaris, I. E.; Likas, A.; Fotiadis, D. I.

1997-08-01

In a previous article we have shown how one can employ Artificial Neural Networks (ANNs) in order to solve non-homogeneous ordinary and partial differential equations. In the present work we consider the solution of eigenvalue problems for differential and integrodifferential operators, using ANNs. We start by considering the Schrödinger equation for the Morse potential that has an analytically known solution, to test the accuracy of the method. We then proceed with the Schrödinger and the Dirac equations for a muonic atom, as well as with a nonlocal Schrödinger integrodifferential equation that models the n + α system in the framework of the resonating group method. In two dimensions we consider the well-studied Henon-Heiles Hamiltonian and in three dimensions the model problem of three coupled anharmonic oscillators. The method in all of the treated cases proved to be highly accurate, robust and efficient. Hence it is a promising tool for tackling problems of higher complexity and dimensionality.

Three-dimensional matrix fiber alignment modulates cell migration and MT1-MMP utility by spatially and temporally directing protrusions

NASA Astrophysics Data System (ADS)

Fraley, Stephanie I.; Wu, Pei-Hsun; He, Lijuan; Feng, Yunfeng; Krisnamurthy, Ranjini; Longmore, Gregory D.; Wirtz, Denis

2015-10-01

Multiple attributes of the three-dimensional (3D) extracellular matrix (ECM) have been independently implicated as regulators of cell motility, including pore size, crosslink density, structural organization, and stiffness. However, these parameters cannot be independently varied within a complex 3D ECM protein network. We present an integrated, quantitative study of these parameters across a broad range of complex matrix configurations using self-assembling 3D collagen and show how each parameter relates to the others and to cell motility. Increasing collagen density resulted in a decrease and then an increase in both pore size and fiber alignment, which both correlated significantly with cell motility but not bulk matrix stiffness within the range tested. However, using the crosslinking enzyme Transglutaminase II to alter microstructure independently of density revealed that motility is most significantly predicted by fiber alignment. Cellular protrusion rate, protrusion orientation, speed of migration, and invasion distance showed coupled biphasic responses to increasing collagen density not predicted by 2D models or by stiffness, but instead by fiber alignment. The requirement of matrix metalloproteinase (MMP) activity was also observed to depend on microstructure, and a threshold of MMP utility was identified. Our results suggest that fiber topography guides protrusions and thereby MMP activity and motility.

Robustness and percolation of holes in complex networks

NASA Astrophysics Data System (ADS)

Zhou, Andu; Maletić, Slobodan; Zhao, Yi

2018-07-01

Efficient robustness and fault tolerance of complex network is significantly influenced by its connectivity, commonly modeled by the structure of pairwise relations between network elements, i.e., nodes. Nevertheless, aggregations of nodes build higher-order structures embedded in complex network, which may be more vulnerable when the fraction of nodes is removed. The structure of higher-order aggregations of nodes can be naturally modeled by simplicial complexes, whereas the removal of nodes affects the values of topological invariants, like the number of higher-dimensional holes quantified with Betti numbers. Following the methodology of percolation theory, as the fraction of nodes is removed, new holes appear, which have the role of merger between already present holes. In the present article, relationship between the robustness and homological properties of complex network is studied, through relating the graph-theoretical signatures of robustness and the quantities derived from topological invariants. The simulation results of random failures and intentional attacks on networks suggest that the changes of graph-theoretical signatures of robustness are followed by differences in the distribution of number of holes per cluster under different attack strategies. In the broader sense, the results indicate the importance of topological invariants research for obtaining further insights in understanding dynamics taking place over complex networks.

LANDMON a new integrated system for the management of landslide monitoring networks

NASA Astrophysics Data System (ADS)

Wrzesniak, Aleksandra; Giordan, Daniele; Allasia, Paolo

2017-04-01

Over the last decades, technological development has strongly increased the number of instruments that can be used to monitor landslide phenomena. Robotized Total Stations, GB-InSAR and GPS are only few examples of the devices that can be adapted to monitor the topographic changes due to mass movements. They are often organized in a complex network, aimed at controlling physical parameters related to the evolution of landslide activity. The level of complexity of these monitoring networks increases with the number of new available monitoring devices and this could generate a paradox: the source of data is so numerous and difficult to interpret that a full understanding of the phenomenon could be hampered. The Geohazard Monitoring Group (GMG) of Italian National Research Council (CNR) has a long experience in landslide monitoring. Over the years, GMG has developed a multidisciplinary approach for landslide management strategy called LANDMON (LANDslide MOnitoring Network). It is an automatic hybrid system focused not only on capturing and elaborating data from monitored site but also on web applications and on publishing bulletins aimed to disseminate monitoring results and to support decision makers. LANDMON is currently active in many landslide sites distributed in several areas in Italy and in Europe. LANDMON is derived from the previously developed systems like ADVICE (ADVanced dIsplaCement monitoring system for Early warning) and 3DA (three-dimensional Displacement Analysis). These systems are aimed to collect and to process monitoring dataset, to manage early warning application based on pre-defined thresholds, and to publish three-dimensional displacement maps in near real time. In addition, LANDMON integrates several new features, such as WebGIS application, modelling using inverse velocity method, and management of webcam monitoring system, meteorological parameters and borehole inclinometric data. Moreover, LANDMON is a communication strategy that focuses on dissemination of the landslide monitoring results in order to obtain a user-friendly system. In fact, this kind of results are usually very complex and they are dedicated exclusively to professionals with a proper background. This approach may be inefficient during the management of emergencies, especially when groups of non-expert people (decision and policy makers, population) are involved. For this purpose, an automatic procedure to produce a single page bulletin has been developed. The algorithm performs the analysis of complex data regarding the activity of the monitored landslide, but the results shared with end-users of LANDMON are summarized in a clear, illustrative and quickly interpretable manner. Therefore, LANDMON is a complex, complete and self-contained system, designed for efficient acquisition, analysis, representation and appropriate dissemination of the monitoring data.

Effect of hydrogen peroxide on the three-dimensional polymer network in composites.

PubMed

Durner, Jürgen; Stojanovic, Marija; Urcan, Ebru; Spahl, Werner; Haertel, Ursula; Hickel, Reinhard; Reichl, Franx-Xaver

2011-06-01

Less data are available about the effects of hydrogen peroxide on the three-dimensional polymer network of polymerized composites. Therefore the study was performed to test the effects of hydrogen peroxide on the three-dimensional polymer network in composites. Polymerized specimens from Tetric Flow®, Tetric Ceram® and Filtek™ Supreme XT were bleached with Opalescence® PF 15% for 5h or PF 35% for 0.5h, respectively, and then stored in methanol for 1d and 7d. Controls were unbleached specimens. The eluates were analyzed by gas chromatography/mass spectrometry. More methacrylic acid (MAA), bisphenol-A (BPA), ethoxylated bisphenol-A-dimethacrylate (BisEMA), hydroquinone monomethyl ether (HQME), 1,10-decanediol dimethacrylate (DDDMA) and/or triethylene glycol dimethacrylate (TEGDMA) were eluted from bleached specimens compared with non bleached controls (1d). The highest DDDMA amount of 419.8 μmol/l was found in the eluates after 7d in Tetric Flow® specimens treated with PF 15. The highest HQME amount of 159.6 μmol/l was found in eluates from Tetric Ceram® specimens treated with PF after 7d. The highest TEGDMA amount of 178.7 μmol/l was found in eluates from Filtek™ Supreme XT specimens treated with PF 35 after 7d. Bleaching with hydrogen peroxide has an effect on the three-dimensional polymer network in polymerized composites leading to an increase in the release of unpolymerized monomers, additives and unspecific oxidative products. Copyright © 2011 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Experiments on an unsteady, three-dimensional separation

NASA Technical Reports Server (NTRS)

Henk, R. W.; Reynolds, W. C.; Reed, H. L.

1992-01-01

Unsteady, three-dimensional flow separation occurs in a variety of technical situations including turbomachinery and low-speed aircraft. An experimental program at Stanford in unsteady, three-dimensional, pressure-driven laminar separation has investigated the structure and time-scaling of these flows; of particular interest is the development, washout, and control of flow separation. Results reveal that a two-dimensional, laminar boundary layer passes through several stages on its way to a quasi-steady three-dimensional separation. The quasi-steady state of the separation embodies a complex, unsteady, vortical structure.

Trading spaces: building three-dimensional nets from two-dimensional tilings

PubMed Central

Castle, Toen; Evans, Myfanwy E.; Hyde, Stephen T.; Ramsden, Stuart; Robins, Vanessa

2012-01-01

We construct some examples of finite and infinite crystalline three-dimensional nets derived from symmetric reticulations of homogeneous two-dimensional spaces: elliptic (S2), Euclidean (E2) and hyperbolic (H2) space. Those reticulations are edges and vertices of simple spherical, planar and hyperbolic tilings. We show that various projections of the simplest symmetric tilings of those spaces into three-dimensional Euclidean space lead to topologically and geometrically complex patterns, including multiple interwoven nets and tangled nets that are otherwise difficult to generate ab initio in three dimensions. PMID:24098839

Geometry of complex networks and topological centrality

NASA Astrophysics Data System (ADS)

Ranjan, Gyan; Zhang, Zhi-Li

2013-09-01

We explore the geometry of complex networks in terms of an n-dimensional Euclidean embedding represented by the Moore-Penrose pseudo-inverse of the graph Laplacian (L). The squared distance of a node i to the origin in this n-dimensional space (lii+), yields a topological centrality index, defined as C∗(i)=1/lii+. In turn, the sum of reciprocals of individual node centralities, ∑i1/C∗(i)=∑ilii+, or the trace of L, yields the well-known Kirchhoff index (K), an overall structural descriptor for the network. To put into context this geometric definition of centrality, we provide alternative interpretations of the proposed indices that connect them to meaningful topological characteristics - first, as forced detour overheads and frequency of recurrences in random walks that has an interesting analogy to voltage distributions in the equivalent electrical network; and then as the average connectedness of i in all the bi-partitions of the graph. These interpretations respectively help establish the topological centrality (C∗(i)) of node i as a measure of its overall position as well as its overall connectedness in the network; thus reflecting the robustness of i to random multiple edge failures. Through empirical evaluations using synthetic and real world networks, we demonstrate how the topological centrality is better able to distinguish nodes in terms of their structural roles in the network and, along with Kirchhoff index, is appropriately sensitive to perturbations/re-wirings in the network.

The three-dimensional Event-Driven Graphics Environment (3D-EDGE)

NASA Technical Reports Server (NTRS)

Freedman, Jeffrey; Hahn, Roger; Schwartz, David M.

1993-01-01

Stanford Telecom developed the Three-Dimensional Event-Driven Graphics Environment (3D-EDGE) for NASA GSFC's (GSFC) Communications Link Analysis and Simulation System (CLASS). 3D-EDGE consists of a library of object-oriented subroutines which allow engineers with little or no computer graphics experience to programmatically manipulate, render, animate, and access complex three-dimensional objects.

Density-based clustering: A 'landscape view' of multi-channel neural data for inference and dynamic complexity analysis.

PubMed

Baglietto, Gabriel; Gigante, Guido; Del Giudice, Paolo

2017-01-01

Two, partially interwoven, hot topics in the analysis and statistical modeling of neural data, are the development of efficient and informative representations of the time series derived from multiple neural recordings, and the extraction of information about the connectivity structure of the underlying neural network from the recorded neural activities. In the present paper we show that state-space clustering can provide an easy and effective option for reducing the dimensionality of multiple neural time series, that it can improve inference of synaptic couplings from neural activities, and that it can also allow the construction of a compact representation of the multi-dimensional dynamics, that easily lends itself to complexity measures. We apply a variant of the 'mean-shift' algorithm to perform state-space clustering, and validate it on an Hopfield network in the glassy phase, in which metastable states are largely uncorrelated from memories embedded in the synaptic matrix. In this context, we show that the neural states identified as clusters' centroids offer a parsimonious parametrization of the synaptic matrix, which allows a significant improvement in inferring the synaptic couplings from the neural activities. Moving to the more realistic case of a multi-modular spiking network, with spike-frequency adaptation inducing history-dependent effects, we propose a procedure inspired by Boltzmann learning, but extending its domain of application, to learn inter-module synaptic couplings so that the spiking network reproduces a prescribed pattern of spatial correlations; we then illustrate, in the spiking network, how clustering is effective in extracting relevant features of the network's state-space landscape. Finally, we show that the knowledge of the cluster structure allows casting the multi-dimensional neural dynamics in the form of a symbolic dynamics of transitions between clusters; as an illustration of the potential of such reduction, we define and analyze a measure of complexity of the neural time series.

Three-Dimensional Computer Simulation as an Important Competence Based Aspect of a Modern Mining Professional

NASA Astrophysics Data System (ADS)

Aksenova, Olesya; Pachkina, Anna

2017-11-01

The article deals with the problem of necessity of educational process transformation to meet the requirements of modern miming industry; cooperative developing of new educational programs and implementation of educational process taking into account modern manufacturability. The paper proves the idea of introduction into mining professionals learning process studying of three-dimensional models of surface technological complex, ore reserves and underground digging complex as well as creating these models in different graphic editors and working with the information analysis model obtained on the basis of these three-dimensional models. The technological process of manless coal mining at the premises of the mine Polysaevskaya controlled by the information analysis models built on the basis of three-dimensional models of individual objects and technological process as a whole, and at the same time requiring the staff able to use the programs of three-dimensional positioning in the miners and equipment global frame of reference is covered.

A constrained Delaunay discretization method for adaptively meshing highly discontinuous geological media

NASA Astrophysics Data System (ADS)

Wang, Yang; Ma, Guowei; Ren, Feng; Li, Tuo

2017-12-01

A constrained Delaunay discretization method is developed to generate high-quality doubly adaptive meshes of highly discontinuous geological media. Complex features such as three-dimensional discrete fracture networks (DFNs), tunnels, shafts, slopes, boreholes, water curtains, and drainage systems are taken into account in the mesh generation. The constrained Delaunay triangulation method is used to create adaptive triangular elements on planar fractures. Persson's algorithm (Persson, 2005), based on an analogy between triangular elements and spring networks, is enriched to automatically discretize a planar fracture into mesh points with varying density and smooth-quality gradient. The triangulated planar fractures are treated as planar straight-line graphs (PSLGs) to construct piecewise-linear complex (PLC) for constrained Delaunay tetrahedralization. This guarantees the doubly adaptive characteristic of the resulted mesh: the mesh is adaptive not only along fractures but also in space. The quality of elements is compared with the results from an existing method. It is verified that the present method can generate smoother elements and a better distribution of element aspect ratios. Two numerical simulations are implemented to demonstrate that the present method can be applied to various simulations of complex geological media that contain a large number of discontinuities.

OmicsNet: a web-based tool for creation and visual analysis of biological networks in 3D space.

PubMed

Zhou, Guangyan; Xia, Jianguo

2018-06-07

Biological networks play increasingly important roles in omics data integration and systems biology. Over the past decade, many excellent tools have been developed to support creation, analysis and visualization of biological networks. However, important limitations remain: most tools are standalone programs, the majority of them focus on protein-protein interaction (PPI) or metabolic networks, and visualizations often suffer from 'hairball' effects when networks become large. To help address these limitations, we developed OmicsNet - a novel web-based tool that allows users to easily create different types of molecular interaction networks and visually explore them in a three-dimensional (3D) space. Users can upload one or multiple lists of molecules of interest (genes/proteins, microRNAs, transcription factors or metabolites) to create and merge different types of biological networks. The 3D network visualization system was implemented using the powerful Web Graphics Library (WebGL) technology that works natively in most major browsers. OmicsNet supports force-directed layout, multi-layered perspective layout, as well as spherical layout to help visualize and navigate complex networks. A rich set of functions have been implemented to allow users to perform coloring, shading, topology analysis, and enrichment analysis. OmicsNet is freely available at http://www.omicsnet.ca.

Three-dimensional printed ultrasound and photoacoustic training phantoms for vasculature access (Conference Presentation)

NASA Astrophysics Data System (ADS)

Nikitichev, Daniil I.; Xia, Wenfeng; West, Simeon J.; Desjardins, Adrien E.; Ourselin, Sebastien; Vercauteren, Tom

2017-03-01

Ultrasound (US) imaging is widely used to guide vascular access procedures such as arterial and venous cannulation. As needle visualisation with US imaging can be very challenging, it is easy to misplace the needle in the patient and it can be life threating. Photoacoustic (PA) imaging is well suited to image medical needles and catheters that are commonly used for vascular access. To improve the success rate, a certain level of proficiency is required that can be gained through extensive practice on phantoms. Unfortunately, commercial training phantoms are expensive and custom-made phantoms usually do not replicate the anatomy very well. Thus, there is a great demand for more realistic and affordable ultrasound and photoacoustic imaging phantoms for vasculature access procedures training. Three-dimensional (3D) printing can help create models that replicate complex anatomical geometries. However, the available 3D printed materials do not possess realistic tissue properties. Alternatively, tissue-mimicking materials can be employed using casting and 3D printed moulds but this approach is limited to the creation of realistic outer shapes with no replication of complex internal structures. In this study, we developed a realistic vasculature access phantom using a combination of mineral oil based materials as background tissue and a non-toxic, water dissolvable filament material to create complex vascular structure using 3D printing. US and PA images of the phantoms comprising the complex vasculature network were acquired. The results show that 3D printing can facilitate the fabrication of anatomically realistic training phantoms, with designs that can be customized and shared electronically.

Adaptable Hydrogel Networks with Reversible Linkages for Tissue Engineering

PubMed Central

Wang, Huiyuan

2015-01-01

Adaptable hydrogels have recently emerged as a promising platform for three-dimensional (3D) cell encapsulation and culture. In conventional, covalently crosslinked hydrogels, degradation is typically required to allow complex cellular functions to occur, leading to bulk material degradation. In contrast, adaptable hydrogels are formed by reversible crosslinks. Through breaking and re-forming of the reversible linkages, adaptable hydrogels can be locally modified to permit complex cellular functions while maintaining their long-term integrity. In addition, these adaptable materials can have biomimetic viscoelastic properties that make them well suited for several biotechnology and medical applications. In this review, adaptable hydrogel design considerations and linkage selections are overviewed, with a focus on various cell compatible crosslinking mechanisms that can be exploited to form adaptable hydrogels for tissue engineering. PMID:25989348

Modeling extracellular fields for a three-dimensional network of cells using NEURON.

PubMed

Appukuttan, Shailesh; Brain, Keith L; Manchanda, Rohit

2017-10-01

Computational modeling of biological cells usually ignores their extracellular fields, assuming them to be inconsequential. Though such an assumption might be justified in certain cases, it is debatable for networks of tightly packed cells, such as in the central nervous system and the syncytial tissues of cardiac and smooth muscle. In the present work, we demonstrate a technique to couple the extracellular fields of individual cells within the NEURON simulation environment. The existing features of the simulator are extended by explicitly defining current balance equations, resulting in the coupling of the extracellular fields of adjacent cells. With this technique, we achieved continuity of extracellular space for a network model, thereby allowing the exploration of extracellular interactions computationally. Using a three-dimensional network model, passive and active electrical properties were evaluated under varying levels of extracellular volumes. Simultaneous intracellular and extracellular recordings for synaptic and action potentials were analyzed, and the potential of ephaptic transmission towards functional coupling of cells was explored. We have implemented a true bi-domain representation of a network of cells, with the extracellular domain being continuous throughout the entire model. This has hitherto not been achieved using NEURON, or other compartmental modeling platforms. We have demonstrated the coupling of the extracellular field of every cell in a three-dimensional model to obtain a continuous uniform extracellular space. This technique provides a framework for the investigation of interactions in tightly packed networks of cells via their extracellular fields. Copyright © 2017 Elsevier B.V. All rights reserved.

Upscaling permeability for three-dimensional fractured porous rocks with the multiple boundary method

NASA Astrophysics Data System (ADS)

Chen, Tao; Clauser, Christoph; Marquart, Gabriele; Willbrand, Karen; Hiller, Thomas

2018-02-01

Upscaling permeability of grid blocks is crucial for groundwater models. A novel upscaling method for three-dimensional fractured porous rocks is presented. The objective of the study was to compare this method with the commonly used Oda upscaling method and the volume averaging method. First, the multiple boundary method and its computational framework were defined for three-dimensional stochastic fracture networks. Then, the different upscaling methods were compared for a set of rotated fractures, for tortuous fractures, and for two discrete fracture networks. The results computed by the multiple boundary method are comparable with those of the other two methods and fit best the analytical solution for a set of rotated fractures. The errors in flow rate of the equivalent fracture model decrease when using the multiple boundary method. Furthermore, the errors of the equivalent fracture models increase from well-connected fracture networks to poorly connected ones. Finally, the diagonal components of the equivalent permeability tensors tend to follow a normal or log-normal distribution for the well-connected fracture network model with infinite fracture size. By contrast, they exhibit a power-law distribution for the poorly connected fracture network with multiple scale fractures. The study demonstrates the accuracy and the flexibility of the multiple boundary upscaling concept. This makes it attractive for being incorporated into any existing flow-based upscaling procedures, which helps in reducing the uncertainty of groundwater models.

Spin wave steering in three-dimensional magnonic networks

NASA Astrophysics Data System (ADS)

Beginin, E. N.; Sadovnikov, A. V.; Sharaevskaya, A. Yu.; Stognij, A. I.; Nikitov, S. A.

2018-03-01

We report the concept of three-dimensional (3D) magnonic structures which are especially promising for controlling and manipulating magnon currents. The approach for fabrication of 3D magnonic crystals (MCs) and 3D magnonic networks is presented. A meander type ferromagnetic film grown at the top of the initially structured substrate can be a candidate for such 3D crystals. Using the finite element method, transfer matrix method, and micromagnetic simulations, we study spin-wave propagation in both isolated and coupled 3D MCs and reconstruct spin-wave dispersion and transmission response to elucidate the mechanism of magnonic bandgap formation. Our results show the possibility of the utilization of proposed structures for fabrication of a 3D magnonic network.

High-speed all-optical DNA local sequence alignment based on a three-dimensional artificial neural network.

PubMed

Maleki, Ehsan; Babashah, Hossein; Koohi, Somayyeh; Kavehvash, Zahra

2017-07-01

This paper presents an optical processing approach for exploring a large number of genome sequences. Specifically, we propose an optical correlator for global alignment and an extended moiré matching technique for local analysis of spatially coded DNA, whose output is fed to a novel three-dimensional artificial neural network for local DNA alignment. All-optical implementation of the proposed 3D artificial neural network is developed and its accuracy is verified in Zemax. Thanks to its parallel processing capability, the proposed structure performs local alignment of 4 million sequences of 150 base pairs in a few seconds, which is much faster than its electrical counterparts, such as the basic local alignment search tool.

Multi-physics optimization of three-dimensional microvascular polymeric components

NASA Astrophysics Data System (ADS)

Aragón, Alejandro M.; Saksena, Rajat; Kozola, Brian D.; Geubelle, Philippe H.; Christensen, Kenneth T.; White, Scott R.

2013-01-01

This work discusses the computational design of microvascular polymeric materials, which aim at mimicking the behavior found in some living organisms that contain a vascular system. The optimization of the topology of the embedded three-dimensional microvascular network is carried out by coupling a multi-objective constrained genetic algorithm with a finite-element based physics solver, the latter validated through experiments. The optimization is carried out on multiple conflicting objective functions, namely the void volume fraction left by the network, the energy required to drive the fluid through the network and the maximum temperature when the material is subjected to thermal loads. The methodology presented in this work results in a viable alternative for the multi-physics optimization of these materials for active-cooling applications.

KRISSY: user's guide to modeling three-dimensional wind flow in complex terrain

Treesearch

Michael A. Fosberg; Michael L. Sestak

1986-01-01

KRISSY is a computer model for generating three-dimensional wind flows in complex terrain from data that were not or perhaps cannot be collected. The model is written in FORTRAN IV This guide describes data requirements, modeling, and output from an applications viewpoint rather than that of programming or theoretical modeling. KRISSY is designed to minimize...

Three dimensional display of underground water-supplying network by combining VTK with SiCAD/open GIS system

NASA Astrophysics Data System (ADS)

Chen, Shaobin; Zhang, Xubo; Wang, Wenyuan; Zhou, Chengping; Ding, Mingyue

2007-11-01

Nowadays many Geographic Information System (GIS) have been widely used in many municipal corporations. Water-supplying corporations in many cities developed GIS application system based on SiCAD/Open GIS platform several years ago for their daily management and engineering construction. With the increasing of commercial business, many corporations now need to add the functionality of three dimensional to display to their GIS System without too much financial cost. Because of the expensiveness of updating SiCAD/Open GIS system to the up-to-date version, the introduction of a third-part 3D display technology is considered. In our solution, Visualization Toolkit (VTK) is used to achieve three dimensional display of underground water-supplying network on the basis of an existing SiCAD/Open GIS system. This paper addresses on the system architecture and key implementation technologies of this solution.

Automated detection of Schlemm's canal in spectral-domain optical coherence tomography

NASA Astrophysics Data System (ADS)

Tom, Manu; Ramakrishnan, Vignesh; van Oterendorp, Christian; Deserno, Thomas M.

2015-03-01

Recent advances in optical coherence tomography (OCT) technology allow in vivo imaging of the complex network of intra-scleral aqueous veins in the anterior segment of the eye. Pathological changes in this network, draining the aqueous humor from the eye, are considered to play a role in intraocular pressure elevation, which can lead to glaucoma, one of the major causes of blindness in the world. Through acquisition of OCT volume scans of the anterior eye segment, we aim at reconstructing the three dimensional network of aqueous veins in healthy and glaucomatous subjects. A novel algorithm for segmentation of the three-dimensional (3D) vessel system in human Schlemms canal is presented analyzing frames of spectral domain OCT (SD-OCT) of the eyes surface in either horizontal or vertical orientation. Distortions such as vertical stripes are caused by the superficial blood vessels in the conjunctiva and the episclera. They are removed in the discrete Fourier domain (DFT) masking particular frequencies. Feature-based rigid registration of these noise-filtered images is then performed using the scale invariant feature transform (SIFT). Segmentation of the vessels deep in the sclera originating at or in the vicinity of or having indirect connection to the Schlemm's canal is then performed with 3D region growing technique. The segmented vessels are visualized in 3D providing diagnostically relevant information to the physicians. A proof-of-concept study was performed on a healthy volunteer before and after a pharmaceutical narrowing of Schlemm's canal. A relative decreases 17% was measured based on manual ground truth and the image processing method.

Classification of 2-dimensional array patterns: assembling many small neural networks is better than using a large one.

PubMed

Chen, Liang; Xue, Wei; Tokuda, Naoyuki

2010-08-01

In many pattern classification/recognition applications of artificial neural networks, an object to be classified is represented by a fixed sized 2-dimensional array of uniform type, which corresponds to the cells of a 2-dimensional grid of the same size. A general neural network structure, called an undistricted neural network, which takes all the elements in the array as inputs could be used for problems such as these. However, a districted neural network can be used to reduce the training complexity. A districted neural network usually consists of two levels of sub-neural networks. Each of the lower level neural networks, called a regional sub-neural network, takes the elements in a region of the array as its inputs and is expected to output a temporary class label, called an individual opinion, based on the partial information of the entire array. The higher level neural network, called an assembling sub-neural network, uses the outputs (opinions) of regional sub-neural networks as inputs, and by consensus derives the label decision for the object. Each of the sub-neural networks can be trained separately and thus the training is less expensive. The regional sub-neural networks can be trained and performed in parallel and independently, therefore a high speed can be achieved. We prove theoretically in this paper, using a simple model, that a districted neural network is actually more stable than an undistricted neural network in noisy environments. We conjecture that the result is valid for all neural networks. This theory is verified by experiments involving gender classification and human face recognition. We conclude that a districted neural network is highly recommended for neural network applications in recognition or classification of 2-dimensional array patterns in highly noisy environments. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Synthesis and characterization of a cadmium(II)-organic supramolecular coordination compound based on the multifunctional 2-amino-5-sulfobenzoic acid ligand.

PubMed

Yuan, Gan Yin; Zhang, Lei; Wang, Meng Jie; Zhang, Kou Lin

2016-12-01

Much attention has been paid by chemists to the construction of supramolecular coordination compounds based on the multifunctional ligand 5-sulfosalicylic acid (H 3 SSA) due to the structural and biological interest of these compounds. However, no coordination compounds have been reported for the multifunctional amino-substituted sulfobenzoate ligand 2-amino-5-sulfobenzoic acid (H 2 asba). We expected that H 2 asba could be a suitable building block for the assembly of supramolecular networks due to its interesting structural characteristics. The reaction of cadmium(II) nitrate with H 2 asba in the presence of the auxiliary flexible dipyridylamide ligand N,N'-bis[(pyridin-4-yl)methyl]oxamide (4bpme) under ambient conditions formed a new mixed-ligand coordination compound, namely bis(3-amino-4-carboxybenzenesulfonato-κO 1 )diaquabis{N,N'-bis[(pyridin-4-yl)methyl]oxamide-κN}cadmium(II)-N,N'-bis[(pyridin-4-yl)methyl]oxamide-water (1/1/4), [Cd(C 7 H 6 NO 5 S) 2 (C 14 H 14 N 4 O 2 ) 2 (H 2 O) 2 ]·C 14 H 14 N 4 O 2 ·4H 2 O, (1), which was characterized by single-crystal and powder X-ray diffraction analysis (PXRD), FT-IR spectroscopy, thermogravimetric analysis (TG), and UV-Vis and photoluminescence spectroscopic analyses in the solid state. The central Cd II atom in (1) occupies a special position on a centre of inversion and exhibits a slightly distorted octahedral geometry, being coordinated by two N atoms from two monodentate 4bpme ligands, four O atoms from two monodentate 4-amino-3-carboxybenzenesulfonate (Hasba - ) ligands and two coordinated water molecules. Interestingly, complex (1) further extends into a threefold polycatenated 0D→2D (0D is zero-dimensional and 2D is two-dimensional) interpenetrated supramolecular two-dimensional (4,4) layer through intermolecular hydrogen bonding. The interlayer hydrogen bonding further links adjacent threefold polycatenated two-dimensional layers into a three-dimensional network. The optical properties of complex (1) indicate that it may be used as a potential indirect band gap semiconductor material. Complex (1) exhibits an irreversible dehydration-rehydration behaviour. The fluorescence properties have also been investigated in the solid state at room temperature.

Exploring the effects of dimensionality reduction in deep networks for force estimation in robotic-assisted surgery

NASA Astrophysics Data System (ADS)

Aviles, Angelica I.; Alsaleh, Samar; Sobrevilla, Pilar; Casals, Alicia

2016-03-01

Robotic-Assisted Surgery approach overcomes the limitations of the traditional laparoscopic and open surgeries. However, one of its major limitations is the lack of force feedback. Since there is no direct interaction between the surgeon and the tissue, there is no way of knowing how much force the surgeon is applying which can result in irreversible injuries. The use of force sensors is not practical since they impose different constraints. Thus, we make use of a neuro-visual approach to estimate the applied forces, in which the 3D shape recovery together with the geometry of motion are used as input to a deep network based on LSTM-RNN architecture. When deep networks are used in real time, pre-processing of data is a key factor to reduce complexity and improve the network performance. A common pre-processing step is dimensionality reduction which attempts to eliminate redundant and insignificant information by selecting a subset of relevant features to use in model construction. In this work, we show the effects of dimensionality reduction in a real-time application: estimating the applied force in Robotic-Assisted Surgeries. According to the results, we demonstrated positive effects of doing dimensionality reduction on deep networks including: faster training, improved network performance, and overfitting prevention. We also show a significant accuracy improvement, ranging from about 33% to 86%, over existing approaches related to force estimation.

Use of a three-layer distributed RC network to produce two pairs of complex conjugate zeros

NASA Technical Reports Server (NTRS)

Huelsman, L. P.

1972-01-01

The properties of a three layer distributed RC network consisting of two layers of resistive material separated by a dielectric are described. When the three layer network is used as a three terminal element by connecting conducting terminal strips across the ends of one of the resistive layers and the center of the other resistive layer, the network may be used to produce pairs of complex conjugate transmission zeros. The location of these zeros are determined by the parameters of the network. Design charts for determining the zero positions are included as part of the report.

[Construction and validation of a three-dimensional finite element model of cranio-maxillary complex with sutures in unilateral cleft lip and palate patient].

PubMed

Wu, Zhi-fang; Lei, Yong-hua; Li, Wen-jie; Liao, Sheng-hui; Zhao, Zi-jin

2013-02-01

To explore an effective method to construct and validate a finite element model of the unilateral cleft lip and palate(UCLP) craniomaxillary complex with sutures, which could be applied in further three-dimensional finite element analysis (FEA). One male patient aged 9 with left complete lip and palate cleft was selected and CT scan was taken at 0.75mm intervals on the skull. The CT data was saved in Dicom format, which was, afterwards, imported into Software Mimics 10.0 to generate a three-dimensional anatomic model. Then Software Geomagic Studio 12.0 was used to match, smoothen and transfer the anatomic model into a CAD model with NURBS patches. Then, 12 circum-maxillary sutures were integrated into the CAD model by Solidworks (2011 version). Finally meshing by E-feature Biomedical Modeler was done and a three-dimensional finite element model with sutures was obtained. A maxillary protraction force (500 g per side, 20° downward and forward from the occlusal plane) was applied. Displacement and stress distribution of some important craniofacial structures were measured and compared with the results of related researches in the literature. A three-dimensional finite element model of UCLP craniomaxillary complex with 12 sutures was established from the CT scan data. This simulation model consisted of 206 753 individual elements with 260 662 nodes, which was a more precise simulation and a better representation of human craniomaxillary complex than the formerly available FEA models. By comparison, this model was proved to be valid. It is an effective way to establish the three-dimensional finite element model of UCLP cranio-maxillary complex with sutures from CT images with the help of the following softwares: Mimics 10.0, Geomagic Studio 12.0, Solidworks and E-feature Biomedical Modeler.

Order parameter for bursting polyrhythms in multifunctional central pattern generators

NASA Astrophysics Data System (ADS)

Wojcik, Jeremy; Clewley, Robert; Shilnikov, Andrey

2011-05-01

We examine multistability of several coexisting bursting patterns in a central pattern generator network composed of three Hodgkin-Huxley type cells coupled reciprocally by inhibitory synapses. We establish that the control of switching between bursting polyrhythms and their bifurcations are determined by the temporal characteristics, such as the duty cycle, of networked interneurons and the coupling strength asymmetry. A computationally effective approach to the reduction of dynamics of the nine-dimensional network to two-dimensional Poincaré return mappings for phase lags between the interneurons is presented.

Stability analysis of an autocatalytic protein model

NASA Astrophysics Data System (ADS)

Lee, Julian

2016-05-01

A self-regulatory genetic circuit, where a protein acts as a positive regulator of its own production, is known to be the simplest biological network with a positive feedback loop. Although at least three components—DNA, RNA, and the protein—are required to form such a circuit, stability analysis of the fixed points of this self-regulatory circuit has been performed only after reducing the system to a two-component system, either by assuming a fast equilibration of the DNA component or by removing the RNA component. Here, stability of the fixed points of the three-component positive feedback loop is analyzed by obtaining eigenvalues of the full three-dimensional Hessian matrix. In addition to rigorously identifying the stable fixed points and saddle points, detailed information about the system can be obtained, such as the existence of complex eigenvalues near a fixed point.

Explorable Three-Dimensional Digital Model of the Female Pelvis, Pelvic Contents, and Perineum for Anatomical Education

ERIC Educational Resources Information Center

Sergovich, Aimee; Johnson, Marjorie; Wilson, Timothy D.

2010-01-01

The anatomy of the pelvis is complex, multilayered, and its three-dimensional organization is conceptually difficult for students to grasp. The aim of this project was to create an explorable and projectable stereoscopic, three-dimensional (3D) model of the female pelvis and pelvic contents for anatomical education. The model was created using…

Three Dimensional Mesoscale Analysis of Translamellar Cross-Bridge Morphologies in the Annulus Fibrosus using Optical Coherence Tomography

PubMed Central

Han, Sang Kuy; Chen, Chao-Wei; Wierwille, Jerry; Chen, Yu; Hsieh, Adam H.

2014-01-01

The defining characteristic of the annulus fibrosus (AF) of the intervertebral disc (IVD) has long been the lamellar structures that consist of highly ordered collagen fibers arranged in alternating oblique angles from one layer to the next. However, a series of recent histologic studies have demonstrated that AF lamellae contain elastin- and type VI collagen-rich secondary “cross-bridge” structures across lamellae. In this study, we use optical coherence tomography (OCT) to elucidate the three-dimensional (3D) morphologies of these translamellar cross-bridge in AF tissues. Mesoscale volumetric images by OCT reveal a highly heterogeneous spatial network and distribution of 3-D translamellar cross-bridges. The results of this study confirm the translamellar cross-bridge is identified as a distinguishable structure, which is laid in the interbundle space of adjacent lamellae and crisscrosses multiple lamellae in the radial direction. In contrast to previously proposed models extrapolated from 2-D sections, results from this current study show that translamellar cross-bridges exist as a complex, interconnected network. We also found much greater variation in lengths of cross-bridges within the interbundle space of lamellae (0.8-1.4 mm from the current study versus 0.3-0.6 mm from 2-D sections). OCT-based 3-D morphology of translamellar cross-bridge provides novel insight into the AF structure. PMID:25564974

Statistical investigation of avalanches of three-dimensional small-world networks and their boundary and bulk cross-sections

NASA Astrophysics Data System (ADS)

Najafi, M. N.; Dashti-Naserabadi, H.

2018-03-01

In many situations we are interested in the propagation of energy in some portions of a three-dimensional system with dilute long-range links. In this paper, a sandpile model is defined on the three-dimensional small-world network with real dissipative boundaries and the energy propagation is studied in three dimensions as well as the two-dimensional cross-sections. Two types of cross-sections are defined in the system, one in the bulk and another in the system boundary. The motivation of this is to make clear how the statistics of the avalanches in the bulk cross-section tend to the statistics of the dissipative avalanches, defined in the boundaries as the concentration of long-range links (α ) increases. This trend is numerically shown to be a power law in a manner described in the paper. Two regimes of α are considered in this work. For sufficiently small α s the dominant behavior of the system is just like that of the regular BTW, whereas for the intermediate values the behavior is nontrivial with some exponents that are reported in the paper. It is shown that the spatial extent up to which the statistics is similar to the regular BTW model scales with α just like the dissipative BTW model with the dissipation factor (mass in the corresponding ghost model) m2˜α for the three-dimensional system as well as its two-dimensional cross-sections.

Copper(II) ion catalytic oxidation of o-phenylenediamine and characterization, X-ray crystal structure and solution studies of the final product [DAPH][H3O][Cu(dipic)2]·3H2O

NASA Astrophysics Data System (ADS)

Ghasemi, Khaled; Rezvani, Ali Reza; Shokrollahi, Ardeshir; Abdul Razak, Ibrahim; Refahi, Masoud; Moghimi, Abolghasem; Rosli, Mohd Mustaqim

2015-09-01

The complex [DAPH][H3O][Cu(dipic)2]·3H2O, (1) (dipicH2 = 2,6-pyridinedicarboxylic acid and DAP = 2,3-diaminophenazine) was prepared from the reaction of Cu(NO3)2·2H2O with mixture of o-phenylenediamine (OPD) and 2,6-pyridinedicarboxylic acid in water. The complex was characterized by FTIR, elemental analysis, UV-Vis and the single-crystal X-ray diffraction. The crystal system is monoclinic with the space group P21/c. This complex is stabilized in the solid state by an extensive network of hydrogen bonds between crystallized water, anionic and cationic fragments, which form a three-dimensional network. Furthermore, hydrogen bonds, π⋯π and Csbnd O⋯π stacking interactions seem to be effective in stabilizing the crystal structures. The protonation constants of dipic (L) and DAP (Q), the equilibrium constants for the dipic-DAP proton transfer system and the stoichiometry and stability constants of binary complexes including each of ligands (dipic, DAP) in presence Cu2+ ion, ternary complexes including, both of ligands (dipic-DAP) in presence of metal ion were calculated in aqueous solutions by potentiometric pH titration method using the Hyperquad2008 program. The stoichiometry of the most complexes species in solution was found to be very similar to the solid-state of cited metal ion complex.

Three-Dimensional Bi₂Te₃ Networks of Interconnected Nanowires: Synthesis and Optimization.

PubMed

Ruiz-Clavijo, Alejandra; Caballero-Calero, Olga; Martín-González, Marisol

2018-05-18

Self-standing Bi₂Te₃ networks of interconnected nanowires were fabricated in three-dimensional porous anodic alumina templates (3D⁻AAO) with a porous structure spreading in all three spatial dimensions. Pulsed electrodeposition parameters were optimized to grow highly oriented Bi₂Te₃ interconnected nanowires with stoichiometric composition inside those 3D⁻AAO templates. The nanowire networks were analyzed by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray analysis (EDX), and Raman spectroscopy. The results are compared to those obtained in films and 1D nanowires grown under similar conditions. The crystalline structure and composition of the 3D Bi⁻Te nanowire network are finely tuned by controlling the applied voltage and the relaxation time off at zero current density during the deposition. With this fabrication method, and controlling the electrodeposition parameters, stoichiometric Bi₂Te₃ networks of interconnected nanowires have been obtained, with a preferential orientation along [1 1 0], which makes them optimal candidates for out-of-plane thermoelectric applications. Moreover, the templates in which they are grown can be dissolved and the network of interconnected nanowires is self-standing without affecting its composition and orientation properties.

Three-Particle Complexes in Two-Dimensional Semiconductors

NASA Astrophysics Data System (ADS)

Ganchev, Bogdan; Drummond, Neil; Aleiner, Igor; Fal'ko, Vladimir

2015-03-01

We evaluate binding energies of trions X±, excitons bound by a donor or acceptor charge XD (A ) , and overcharged acceptors or donors in two-dimensional atomic crystals by mapping the three-body problem in two dimensions onto one particle in a three-dimensional potential treatable by a purposely developed boundary-matching-matrix method. We find that in monolayers of transition metal dichalcogenides the dissociation energy of X± is typically much larger than that of localized exciton complexes, so that trions are more resilient to heating, despite the fact that their recombination line in optics is less redshifted from the exciton line than the line of XD (A ) .

Calibration of a Hall effect displacement measurement system for complex motion analysis using a neural network.

PubMed

Northey, G W; Oliver, M L; Rittenhouse, D M

2006-01-01

Biomechanics studies often require the analysis of position and orientation. Although a variety of transducer and camera systems can be utilized, a common inexpensive alternative is the Hall effect sensor. Hall effect sensors have been used extensively for one-dimensional position analysis but their non-linear behavior and cross-talk effects make them difficult to calibrate for effective and accurate two- and three-dimensional position and orientation analysis. The aim of this study was to develop and calibrate a displacement measurement system for a hydraulic-actuation joystick used for repetitive motion analysis of heavy equipment operators. The system utilizes an array of four Hall effect sensors that are all active during any joystick movement. This built-in redundancy allows the calibration to utilize fully connected feed forward neural networks in conjunction with a Microscribe 3D digitizer. A fully connected feed forward neural network with one hidden layer containing five neurons was developed. Results indicate that the ability of the neural network to accurately predict the x, y and z coordinates of the joystick handle was good with r(2) values of 0.98 and higher. The calibration technique was found to be equally as accurate when used on data collected 5 days after the initial calibration, indicating the system is robust and stable enough to not require calibration every time the joystick is used. This calibration system allowed an infinite number of joystick orientations and positions to be found within the range of joystick motion.

Steerable sound transport in a 3D acoustic network

NASA Astrophysics Data System (ADS)

Xia, Bai-Zhan; Jiao, Jun-Rui; Dai, Hong-Qing; Yin, Sheng-Wen; Zheng, Sheng-Jie; Liu, Ting-Ting; Chen, Ning; Yu, De-Jie

2017-10-01

Quasi-lossless and asymmetric sound transports, which are exceedingly desirable in various modern physical systems, are almost always based on nonlinear or angular momentum biasing effects with extremely high power levels and complex modulation schemes. A practical route for the steerable sound transport along any arbitrary acoustic pathway, especially in a three-dimensional (3D) acoustic network, can revolutionize the sound power propagation and the sound communication. Here, we design an acoustic device containing a regular-tetrahedral cavity with four cylindrical waveguides. A smaller regular-tetrahedral solid in this cavity is eccentrically emplaced to break spatial symmetry of the acoustic device. The numerical and experimental results show that the sound power flow can unimpededly transport between two waveguides away from the eccentric solid within a wide frequency range. Based on the quasi-lossless and asymmetric transport characteristic of the single acoustic device, we construct a 3D acoustic network, in which the sound power flow can flexibly propagate along arbitrary sound pathways defined by our acoustic devices with eccentrically emplaced regular-tetrahedral solids.

Nanocelluloses from jute fibers and their nanocomposites with natural rubber: Preparation and characterization.

PubMed

Thomas, Martin George; Abraham, Eldho; Jyotishkumar, P; Maria, Hanna J; Pothen, Laly A; Thomas, Sabu

2015-11-01

Nanocellulose fibers having an average diameter of 50nm were isolated from raw jute fibers by steam explosion process. The isolation of nanocellulose from jute fibers by this extraction process is proved by SEM, XRD, FTIR, birefringence and TEM characterizations. This nanocellulose was used as the reinforcing agent in natural rubber (NR) latex along with crosslinking agents to prepare crosslinked nanocomposite films. The effects of nanocellulose loading on the morphology and mechanics of the nanocomposites have been carefully analyzed. Significant improvements in the Young's modulus and tensile strength of the nanocomposite were observed because of the reinforcing ability of the nanocellulose in the rubber matrix. A mechanism is suggested for the formation of the Zn-cellulose complex. The three-dimensional network of cellulose nanofibers (cellulose/cellulose network and Zn/cellulose network) in the NR matrix plays a major role in improving the properties of the crosslinked nanocomposites. Copyright © 2015 Elsevier B.V. All rights reserved.

Microfilament distribution in protonemata of the moss Ceratodon

NASA Technical Reports Server (NTRS)

Walker, L. M.; Sack, F. D.

1995-01-01

Microfilaments were visualized in dark-grown protonemata of the moss Ceratodon to assess their possible role in tip growth and gravitropism. The relative effectiveness of rhodamine phalloidin (with or without m-maleimidobenzoyl-N-hydroxysuccinimide ester (MBS)) and of immunofluorescence (using the C4 antibody) was evaluated for actin localization in the same cell type. Using immunofluorescence, microfilaments were primarily in an axial orientation within the apical cell. However, a more complex network of microfilaments was observed using rhodamine phalloidin after MBS pretreatment, especially when viewed by confocal laser scanning microscopy. This method revealed a rich three dimensional network of fine microfilaments throughout the apical cell, including the extreme apex. Although there were numerous internal microfilaments, peripheral microfilaments were more abundant. No major redistribution of microfilaments was detected after gravistimulation. The combination of MBS, rhodamine phalloidin, and confocal laser scanning microscopy preserves and reveals microfilaments remarkably well and documents perhaps the most extensive F-actin network visualized to date in any tip-growing cell.

Chaos and Robustness in a Single Family of Genetic Oscillatory Networks

PubMed Central

Fu, Daniel; Tan, Patrick; Kuznetsov, Alexey; Molkov, Yaroslav I.

2014-01-01

Genetic oscillatory networks can be mathematically modeled with delay differential equations (DDEs). Interpreting genetic networks with DDEs gives a more intuitive understanding from a biological standpoint. However, it presents a problem mathematically, for DDEs are by construction infinitely-dimensional and thus cannot be analyzed using methods common for systems of ordinary differential equations (ODEs). In our study, we address this problem by developing a method for reducing infinitely-dimensional DDEs to two- and three-dimensional systems of ODEs. We find that the three-dimensional reductions provide qualitative improvements over the two-dimensional reductions. We find that the reducibility of a DDE corresponds to its robustness. For non-robust DDEs that exhibit high-dimensional dynamics, we calculate analytic dimension lines to predict the dependence of the DDEs’ correlation dimension on parameters. From these lines, we deduce that the correlation dimension of non-robust DDEs grows linearly with the delay. On the other hand, for robust DDEs, we find that the period of oscillation grows linearly with delay. We find that DDEs with exclusively negative feedback are robust, whereas DDEs with feedback that changes its sign are not robust. We find that non-saturable degradation damps oscillations and narrows the range of parameter values for which oscillations exist. Finally, we deduce that natural genetic oscillators with highly-regular periods likely have solely negative feedback. PMID:24667178

System Error Compensation Methodology Based on a Neural Network for a Micromachined Inertial Measurement Unit

PubMed Central

Liu, Shi Qiang; Zhu, Rong

2016-01-01

Errors compensation of micromachined-inertial-measurement-units (MIMU) is essential in practical applications. This paper presents a new compensation method using a neural-network-based identification for MIMU, which capably solves the universal problems of cross-coupling, misalignment, eccentricity, and other deterministic errors existing in a three-dimensional integrated system. Using a neural network to model a complex multivariate and nonlinear coupling system, the errors could be readily compensated through a comprehensive calibration. In this paper, we also present a thermal-gas MIMU based on thermal expansion, which measures three-axis angular rates and three-axis accelerations using only three thermal-gas inertial sensors, each of which capably measures one-axis angular rate and one-axis acceleration simultaneously in one chip. The developed MIMU (100 × 100 × 100 mm3) possesses the advantages of simple structure, high shock resistance, and large measuring ranges (three-axes angular rates of ±4000°/s and three-axes accelerations of ±10 g) compared with conventional MIMU, due to using gas medium instead of mechanical proof mass as the key moving and sensing elements. However, the gas MIMU suffers from cross-coupling effects, which corrupt the system accuracy. The proposed compensation method is, therefore, applied to compensate the system errors of the MIMU. Experiments validate the effectiveness of the compensation, and the measurement errors of three-axis angular rates and three-axis accelerations are reduced to less than 1% and 3% of uncompensated errors in the rotation range of ±600°/s and the acceleration range of ±1 g, respectively. PMID:26840314

In situ Gelable Interpenetrating Double Network Hydrogel Formulated from Binary Components: Thiolated Chitosan and Oxidized Dextran

PubMed Central

Zhang, Hanwei; Qadeer, Aisha; Chen, Weiliam

2011-01-01

In situ gelable interpenetrating double network hydrogels composed of thiolated chitosan (Chitosan-NAC) and oxidized dextran (Odex), completely devoid of potentially cytotoxic small molecule crosslinkers and do not require complex maneuvers or catalysis, have been formulated. The interpenetrating network structure is created by Schiff base formations and disulfide bond inter-crosslinkings through exploiting the disparity of their reaction times. Compare to the auto-gelable thiolated chitosan hydrogels that typically require a relatively long time span for gelation to occur, the Odex/Chitosan-NAC composition solidifies rapidly and forms a well-developed three-dimensional network in a short time span. Compare to typical hydrogels derived from natural materials, the Odex/Chitosan-NAC hydrogels are mechanically strong and resist degradation. The cytotoxicity potential of the hydrogels was determined by an in vitro viability assay using fibroblast as a model cell and the results reveal that the hydrogels are non-cytotoxic. In parallel, in vivo results from subdermal implantation in mice models demonstrate that this hydrogel is not only highly resistant to degradation but also induces very mild tissue response. PMID:21410248

[Analysis of a three-dimensional finite element model of atlas and axis complex fracture].

PubMed

Tang, X M; Liu, C; Huang, K; Zhu, G T; Sun, H L; Dai, J; Tian, J W

2018-05-22

Objective: To explored the clinical application of the three-dimensional finite element model of atlantoaxial complex fracture. Methods: A three-dimensional finite element model of cervical spine (FEM/intact) was established by software of Abaqus6.12.On the basis of this model, a three-dimensional finite element model of four types of atlantoaxial complex fracture was established: C(1) fracture (Jefferson)+ C(2) fracture (type Ⅱfracture), Jefferson+ C(2) fracture(type Ⅲfracture), Jefferson+ C(2) fracture(Hangman), Jefferson+ stable C(2) fracture (FEM/fracture). The range of motion under flexion, extension, lateral bending and axial rotation were measured and compared with the model of cervical spine. Results: The three-dimensional finite element model of four types of atlantoaxial complex fracture had the same similarity and profile.The range of motion (ROM) of different segments had different changes.Compared with those in the normal model, the ROM of C(0/1) and C(1/2) in C(1) combined Ⅱ odontoid fracture model in flexion/extension, lateral bending and rotation increased by 57.45%, 29.34%, 48.09% and 95.49%, 88.52%, 36.71%, respectively.The ROM of C(0/1) and C(1/2) in C(1) combined Ⅲodontoid fracture model in flexion/extension, lateral bending and rotation increased by 47.01%, 27.30%, 45.31% and 90.38%, 27.30%, 30.0%.The ROM of C(0/1) and C(1/2) in C(1) combined Hangman fracture model in flexion/extension, lateral bending and rotation increased by 32.68%, 79.34%, 77.62% and 60.53%, 81.20%, 21.48%, respectively.The ROM of C(0/1) and C(1/2) in C(1) combined axis fracture model in flexion/extension, lateral bending and rotation increased by 15.00%, 29.30%, 8.47% and 37.87%, 75.57%, 8.30%, respectively. Conclusions: The three-dimensional finite element model can be used to simulate the biomechanics of atlantoaxial complex fracture.The ROM of atlantoaxial complex fracture is larger than nomal model, which indicates that surgical treatment should be performed.

Crystal structures of the three closely related compounds: bis-[(1H-tetra-zol-5-yl)meth-yl]nitramide, tri-amino-guanidinium 5-({[(1H-tetra-zol-5-yl)meth-yl](nitro)-amino}-meth-yl)tetra-zol-1-ide, and di-ammonium bis-[(tetra-zol-1-id-5-yl)meth-yl]nitramide monohydrate.

PubMed

Mitchell, Lauren A; Imler, Gregory H; Parrish, Damon A; Deschamps, Jeffrey R; Leonard, Philip W; Chavez, David E

2017-07-01

In the mol-ecule of neutral bis-[(1 H -tetra-zol-5-yl)meth-yl]nitramide, (I), C 4 H 6 N 10 O 2 , there are two intra-molecular N-H⋯O hydrogen bonds. In the crystal, N-H⋯N hydrogen bonds link mol-ecules, forming a two-dimensional network parallel to (-201) and weak C-H⋯O, C-H⋯N hydrogen bonds, and inter-molecular π-π stacking completes the three-dimensional network. The anion in the molecular salt, tri-amino-guanidinium 5-({[(1 H -tetra-zol-5-yl)meth-yl](nitro)-amino}-meth-yl)tetra-zol-1-ide, (II), CH 9 N 6 + ·C 4 H 5 N 10 O 2 - , displays intra-molecular π-π stacking and in the crystal, N-H⋯N and N-H⋯O hydrogen bonds link the components of the structure, forming a three-dimensional network. In the crystal of di-ammonium bis-[(tetra-zol-1-id-5-yl)meth-yl]nitramide monohydrate, (III), 2NH 4 + ·C 4 H 4 N 10 O 2 2- ·H 2 O, O-H⋯N, N-H⋯N, and N-H⋯O hydrogen bonds link the components of the structure into a three-dimensional network. In addition, there is inter-molecular π-π stacking. In all three structures, the central N atom of the nitramide is mainly sp 2 -hybridized. Bond lengths indicate delocalization of charges on the tetra-zole rings for all three compounds. Compound (II) was found to be a non-merohedral twin and was solved and refined in the major component.

A Coordination Network with Ligand-Centered Redox Activity Based on facial-[CrIII (2-mercaptophenolato)3 ]3- Metalloligands.

PubMed

Wakizaka, Masanori; Matsumoto, Takeshi; Kobayashi, Atsushi; Kato, Masako; Chang, Ho-Chol

2017-07-21

The design of redox-active metal-organic frameworks and coordination networks (CNs), which exhibit metal- and/or ligand-centered redox activity, has recently received increased attention. In this study, the redox-active metalloligand (RML) [Me 4 N] 3 fac-[Cr III (mp) 3 ] (1) (mp=2-mercaptophenolato) was synthesized and characterized by single-crystal X-ray diffraction analysis, and its reversible ligand-centered one-electron oxidation was examined by cyclic voltammetry and spectroelectrochemical measurements. Since complex 1 contains O/S coordination sites in three directions, complexation with K + ions led to the formation of the two-dimensional honeycomb sheet-structured [K 3 fac-{Cr III (mp) 3 }(H 2 O) 6 ] n (2⋅6 H 2 O), which is the first example of a redox-active CN constructed from a RML with o-disubstituted benzene ligands. Herein, we unambiguously demonstrate the ligand-centered redox activity of the RML within the CN 2⋅6 H 2 O in the solid state. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Three-dimensional Organization of Layered Apical Cytoskeletal Networks Associated with Mouse Airway Tissue Development

NASA Astrophysics Data System (ADS)

Tateishi, Kazuhiro; Nishida, Tomoki; Inoue, Kanako; Tsukita, Sachiko

2017-03-01

The cytoskeleton is an essential cellular component that enables various sophisticated functions of epithelial cells by forming specialized subcellular compartments. However, the functional and structural roles of cytoskeletons in subcellular compartmentalization are still not fully understood. Here we identified a novel network structure consisting of actin filaments, intermediate filaments, and microtubules directly beneath the apical membrane in mouse airway multiciliated cells and in cultured epithelial cells. Three-dimensional imaging by ultra-high voltage electron microscopy and immunofluorescence revealed that the morphological features of each network depended on the cell type and were spatiotemporally integrated in association with tissue development. Detailed analyses using Odf2 mutant mice, which lack ciliary basal feet and apical microtubules, suggested a novel contribution of the intermediate filaments to coordinated ciliary beating. These findings provide a new perspective for viewing epithelial cell differentiation and tissue morphogenesis through the structure and function of apical cytoskeletal networks.

Software Defined Networking (SDN) controlled all optical switching networks with multi-dimensional switching architecture

NASA Astrophysics Data System (ADS)

Zhao, Yongli; Ji, Yuefeng; Zhang, Jie; Li, Hui; Xiong, Qianjin; Qiu, Shaofeng

2014-08-01

Ultrahigh throughout capacity requirement is challenging the current optical switching nodes with the fast development of data center networks. Pbit/s level all optical switching networks need to be deployed soon, which will cause the high complexity of node architecture. How to control the future network and node equipment together will become a new problem. An enhanced Software Defined Networking (eSDN) control architecture is proposed in the paper, which consists of Provider NOX (P-NOX) and Node NOX (N-NOX). With the cooperation of P-NOX and N-NOX, the flexible control of the entire network can be achieved. All optical switching network testbed has been experimentally demonstrated with efficient control of enhanced Software Defined Networking (eSDN). Pbit/s level all optical switching nodes in the testbed are implemented based on multi-dimensional switching architecture, i.e. multi-level and multi-planar. Due to the space and cost limitation, each optical switching node is only equipped with four input line boxes and four output line boxes respectively. Experimental results are given to verify the performance of our proposed control and switching architecture.

Stromagenesis: the changing face of fibroblastic microenvironments during tumor progression.

PubMed

Beacham, Dorothy A; Cukierman, Edna

2005-10-01

During tumorigenesis, reciprocal changes in stromal fibroblasts and tumor cells induce changes to the neoplastic microenvironmental landscape. In stromagenesis, both the complex network of bi-directional stromal fibroblastic signaling pathways and the stromal extracellular matrix are modified. The presence of a 'primed' stroma during the early, reversible stage of tumorigenesis is optimal for stromal-directed therapeutic intervention. Three-dimensional (3D) cell culture systems have been developed that mimic the in vivo microenvironment. These systems provide unique experimental tools to identify early alterations in stromagenesis that are supportive of tumor progression with the ultimate goal of blocking neoplastic permissiveness and restoring normal phenotypes.

Microfluidic vascular channels in gels using commercial 3D printers

NASA Astrophysics Data System (ADS)

Selvaganapathy, P. Ravi; Attalla, Rana

2016-03-01

This paper details the development of a three dimensional (3D) printing system with a modified microfluidic printhead used for the generation of complex vascular tissue scaffolds. The print-head features an integrated coaxial nozzle that allows the fabrication of hollow, calcium-polymerized alginate tubes that can easily be patterned using 3Dbioprinting techniques. This microfluidic design allows the incorporation of a wide range of scaffold materials as well as biological constituents such as cells, growth factors, and ECM material. With this setup, gel constructs with embedded arrays of hollow channels can be created and used as a potential substitute for blood vessel networks.

Extraction of three-dimensional silver nanostructures with supercritical fluid

NASA Astrophysics Data System (ADS)

Taguchi, Natsuo; Takeyasu, Nobuyuki; Kawata, Satoshi

2018-02-01

In a previous report, a self-growing approach was proposed for fabricating complex silver nanostructures, where silver dendrites were grown at silver nanoseeds in silver ion solution owing to plasmonic heating with ultraviolet light. Structures were deformed or destroyed when they were extracted with acetone and dried in air. In this Letter, we discuss the use of supercritical carbon dioxide fluid for the nondestructive extraction of nanostructures. We show the experimental results and discuss the laser power dependence of resultant structures. Another experiment was performed for nanostructure growth inside an agarose gel as a matrix. Silver nanostructures were immobilized without damage in an agarose skeleton network.

Asp-Gly based peptides confined at the surface of cationic gemini surfactant aggregates.

PubMed

Brizard, Aurélie; Dolain, Christel; Huc, Ivan; Oda, Reiko

2006-04-11

Cationic gemini surfactants complexed with anionic oligoglycine-aspartate (called gemini peptides hereafter) were synthesized, and their aggregation behaviors were studied. The effects of the hydrophobic chain length (C10-C22) and the length of the oligoglycine (0-4) were investigated, and it was clearly shown by critical micellar concentration, Krafft temperature, and isothermal surface pressure measurements that the hydrophobic effect and interpeptidic interaction influence the aggregation behavior in a cooperative manner. Below their Krafft temperatures, some of them formed both hydro- and organogels with three-dimensional networks and the Fourier transform infrared measurements show the presence of interpeptidic hydrogen bonds.

Numerical simulations of a reduced model for blood coagulation

NASA Astrophysics Data System (ADS)

Pavlova, Jevgenija; Fasano, Antonio; Sequeira, Adélia

2016-04-01

In this work, the three-dimensional numerical resolution of a complex mathematical model for the blood coagulation process is presented. The model was illustrated in Fasano et al. (Clin Hemorheol Microcirc 51:1-14, 2012), Pavlova et al. (Theor Biol 380:367-379, 2015). It incorporates the action of the biochemical and cellular components of blood as well as the effects of the flow. The model is characterized by a reduction in the biochemical network and considers the impact of the blood slip at the vessel wall. Numerical results showing the capacity of the model to predict different perturbations in the hemostatic system are discussed.

Longitudinal Dynamics of 3-Dimensional Components of Selfhood After Severe Traumatic Brain Injury: A qEEG Case Study.

PubMed

Fingelkurts, Andrew A; Fingelkurts, Alexander A

2017-09-01

In this report, we describe the case of a patient who sustained extremely severe traumatic brain damage with diffuse axonal injury in a traffic accident and whose recovery was monitored during 6 years. Specifically, we were interested in the recovery dynamics of 3-dimensional components of selfhood (a 3-dimensional construct model for the complex experiential selfhood has been recently proposed based on the empirical findings on the functional-topographical specialization of 3 operational modules of brain functional network responsible for the self-consciousness processing) derived from the electroencephalographic (EEG) signal. The analysis revealed progressive (though not monotonous) restoration of EEG functional connectivity of 3 modules of brain functional network responsible for the self-consciousness processing, which was also paralleled by the clinically significant functional recovery. We propose that restoration of normal integrity of the operational modules of the self-referential brain network may underlie the positive dynamics of 3 aspects of selfhood and provide a neurobiological mechanism for their recovery. The results are discussed in the context of recent experimental studies that support this inference. Studies of ongoing recovery after severe brain injury utilizing knowledge about each separate aspect of complex selfhood will likely help to develop more efficient and targeted rehabilitation programs for patients with brain trauma.

Three-dimensional carbon nanotube networks with a supported nickel oxide nanonet for high-performance supercapacitors.

PubMed

Wu, Mao-Sung; Zheng, Yo-Ru; Lin, Guan-Wei

2014-08-04

A three-dimensional porous carbon nanotube film with a supported NiO nanonet was prepared by simple electrophoretic deposition and hydrothermal synthesis, which could deliver a high specific capacitance of 1511 F g(-1) at a high discharge current of 50 A g(-1) due to the significantly improved transport of the electrolyte and electrons.

Synthesis, structure and electrochemical behavior of a 3D crystalline copper(II) metal-organic framework

NASA Astrophysics Data System (ADS)

Bai, Hong-Ye; Fan, Wei-Qiang; Liu, Chun-Bo; Shi, Wei-Dong; Yan, Yong-Sheng

2014-05-01

Using an flexible amide-type tripodal ligand N,N‧,N″-tris(3-pyridyl)-1,3,5-benzenetricarboxamide (L) and 1,4-benzenedicarboxylic acid (H2bdc), a three-dimensional copper(II) metal-organic framework (MOF) formulated as [Cu(bdc)(L)]n has been hydrothermally synthesized and structurally characterized by IR, elemental, X-ray single-crystal diffraction and thermal analysis. The complex crystallizes in the triclinic, space group P - 1, a = 8.891(2) Å, b = 11.760(2) Å, c = 15.348(3) Å, α = 96.73(3)°, β = 105.96(3)°, γ = 106.47(3)°, V = 1446.2(5) Å3, Mr = 666.10, Dc = 1.530 g/cm3, Z = 2, F(000) = 682, GOOF = 1.0560, μ(MoKα) = 0.817 mm-1, R = 0.0366 and wR = 0.0885. The structural analyses reveal that the title compound consists of one Cu(II) atom, two halves of bdc, and one L ligand. Each Cu(II) atom is linked by two bdc ligands and three L ligands to form a three-dimensional network. In addition, the electrochemical behavior of title compound has been studied. CCDC No. 990526.

Using three dimensional silicone ``boots`` to solve complex remedial design problems in curtain walls

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

Chen, Y.J.

1998-12-31

Stick system curtain wall leak problems are frequently caused by water entry at the splice joints of the curtain wall frame and failure of the internal metal joinery seals. Remedial solutions involving occupied buildings inevitably face the multiple constraints of existing construction and business operations not present during the original curtain wall construction. In most cases, even partial disassembly of the curtain wall for internal seal repairs is not feasible. Remedial solutions which must be executed from the exterior of the curtain wall often involve wet-applied or preformed sealant tape bridge joints. However, some of the more complex joints cannotmore » be repaired effectively or economically with the conventional bridge joint. Fortunately, custom fabricated three-dimensional preformed sealant boots are becoming available to address these situations. This paper discusses the design considerations and the selective use of three-dimensional preformed boots in sealing complex joint geometry that would not be effective with the conventional two-dimensional bridge joint.« less

Syntheses, crystal structures, and properties of four complexes based on polycarboxylate and imidazole ligands

NASA Astrophysics Data System (ADS)

Qiao, Rui; Chen, Shui-Sheng; Sheng, Liang-Quan; Yang, Song; Li, Wei-Dong

2015-08-01

Four metal-organic coordination polymers [Zn(HL)(H2O)]·4H2O (1), [Zn(HL)(L1)]·4H2O (2), [Cu(HL)(H2O)]·3H2O (3) and [Cu(HL)(L1)]·5H2O (4) were synthesized by reactions of the corresponding metal(II) salts with semirigid polycarboxylate ligand (5-((4-carboxypiperidin-1-yl)methyl)isophthalic acid hydrochloride, H3L·HCl) or auxiliary ligand (1,4-di(1H-imidazol-4-yl)benzene, L1). The structures of the compounds were characterized by elemental analysis, FT-IR spectroscopy and single-crystal X-ray diffraction. The use of auxiliary ligand L1 has great influence on the structures of two pairs of complexes 1, 2 and 3, 4. Complex 1 is a uninodal 3-connected rare 2-fold interpenetrating ZnSc net with a Point (Schlafli) symbol of (103) while 2 is a one-dimensional (1D) ladder structure. Compound 3 features a two-dimensional (2D) honeycomb network with typical 63-hcb topology, while 4 is 2D network with (4, 4) sql topology based on binuclear CuII subunits. The non-covalent bonding interactions such as hydrogen bonds, π···π stacking and C-H···π exist in complexes 1-4, which contributes to stabilize crystal structure and extend the low-dimensional entities into high-dimensional frameworks. And the photoluminescent property of 1 and 2 and gas sorption property of 4 have been investigated.

Porous polymer networks and ion-exchange media and metal-polymer composites made therefrom

DOEpatents

Kanatzidis, Mercouri G; Katsoulidis, Alexandros

2015-03-10

Porous polymeric networks and composite materials comprising metal nanoparticles distributed in the polymeric networks are provided. Also provided are methods for using the polymeric networks and the composite materials in liquid- and vapor-phase waste remediation applications. The porous polymeric networks, are highly porous, three-dimensional structures characterized by high surface areas. The polymeric networks comprise polymers polymerized from aldehydes and phenolic molecules.

Porous polymer networks and ion-exchange media and metal-polymer composites made therefrom

DOEpatents

Kanatzidis, Mercouri G.; Katsoulidis, Alexandros

2016-10-18

Porous polymeric networks and composite materials comprising metal nanoparticles distributed in the polymeric networks are provided. Also provided are methods for using the polymeric networks and the composite materials in liquid- and vapor-phase waste remediation applications. The porous polymeric networks, are highly porous, three-dimensional structures characterized by high surface areas. The polymeric networks comprise polymers polymerized from aldehydes and phenolic molecules.

Through the looking glass: Unraveling the network structure of coal

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

Gregory, D. M.; Stec, D. F.; Botto, R. E.

1999-12-23

Since the original idea by Sanada and Honda of treating coal as a three-dimensional cross-linked network, coal structure has been probed by monitoring ingress of solvents using traditional volumetric or gravimetric methods. However, using these techniques has allowed only an indirect observation of the swelling process. More recently, the authors have developed magnetic resonance microscopy (MRM) approaches for studying solvent ingress in polymeric systems, about which fundamental aspects of the swelling process can be deduced directly and quantitatively. The aim of their work is to utilize solvent transport and network response parameters obtained from these methods to assess fundamental propertiesmore » of the system under investigation. Polymer and coal samples have been studied to date. Numerous swelling parameters measured by magnetic resonance microscopy are found to correlate with cross-link density of the polymer network under investigation. Use of these parameters to assess the three-dimensional network structure of coal is discussed.« less

Controlled molecular self-assembly of complex three-dimensional structures in soft materials

PubMed Central

Huang, Changjin; Quinn, David; Suresh, Subra

2018-01-01

Many applications in tissue engineering, flexible electronics, and soft robotics call for approaches that are capable of producing complex 3D architectures in soft materials. Here we present a method using molecular self-assembly to generate hydrogel-based 3D architectures that resembles the appealing features of the bottom-up process in morphogenesis of living tissues. Our strategy effectively utilizes the three essential components dictating living tissue morphogenesis to produce complex 3D architectures: modulation of local chemistry, material transport, and mechanics, which can be engineered by controlling the local distribution of polymerization inhibitor (i.e., oxygen), diffusion of monomers/cross-linkers through the porous structures of cross-linked polymer network, and mechanical constraints, respectively. We show that oxygen plays a role in hydrogel polymerization which is mechanistically similar to the role of growth factors in tissue growth, and the continued growth of hydrogel enabled by diffusion of monomers/cross-linkers into the porous hydrogel similar to the mechanisms of tissue growth enabled by material transport. The capability and versatility of our strategy are demonstrated through biomimetics of tissue morphogenesis for both plants and animals, and its application to generate other complex 3D architectures. Our technique opens avenues to studying many growth phenomena found in nature and generating complex 3D structures to benefit diverse applications. PMID:29255037

Interaction of a supersonic particle with a three-dimensional complex plasma

NASA Astrophysics Data System (ADS)

Zaehringer, E.; Schwabe, M.; Zhdanov, S.; Mohr, D. P.; Knapek, C. A.; Huber, P.; Semenov, I. L.; Thomas, H. M.

2018-03-01

The influence of a supersonic projectile on a three-dimensional complex plasma is studied. Micron sized particles in a low-temperature plasma formed a large undisturbed system in the new "Zyflex" chamber during microgravity conditions. A supersonic probe particle excited a Mach cone with Mach number M ≈ 1.5-2 and double Mach cone structure in the large weakly damped particle cloud. The speed of sound is measured with different methods and particle charge estimations are compared to the calculations from standard theories. The high image resolution enables the study of Mach cones in microgravity on the single particle level of a three-dimensional complex plasma and gives insight to the dynamics. A heating of the microparticles is discovered behind the supersonic projectile but not in the flanks of the Mach cone.

Self-Assembly of Hierarchical DNA Nanotube Architectures with Well-Defined Geometries.

PubMed

Jorgenson, Tyler D; Mohammed, Abdul M; Agrawal, Deepak K; Schulman, Rebecca

2017-02-28

An essential motif for the assembly of biological materials such as actin at the scale of hundreds of nanometers and beyond is a network of one-dimensional fibers with well-defined geometry. Here, we demonstrate the programmed organization of DNA filaments into micron-scale architectures where component filaments are oriented at preprogrammed angles. We assemble L-, T-, and Y-shaped DNA origami junctions that nucleate two or three micron length DNA nanotubes at high yields. The angles between the nanotubes mirror the angles between the templates on the junctions, demonstrating that nanoscale structures can control precisely how micron-scale architectures form. The ability to precisely program filament orientation could allow the assembly of complex filament architectures in two and three dimensions, including circuit structures, bundles, and extended materials.

Development of a Three Dimensional Wireless Sensor Network for Terrain-Climate Research in Remote Mountainous Environments

NASA Astrophysics Data System (ADS)

Kavanagh, K.; Davis, A.; Gessler, P.; Hess, H.; Holden, Z.; Link, T. E.; Newingham, B. A.; Smith, A. M.; Robinson, P.

2011-12-01

Developing sensor networks that are robust enough to perform in the world's remote regions is critical since these regions serve as important benchmarks compared to human-dominated areas. Paradoxically, the factors that make these remote, natural sites challenging for sensor networking are often what make them indispensable for climate change research. We aim to overcome these challenges by developing a three-dimensional sensor network arrayed across a topoclimatic gradient (1100-1800 meters) in a wilderness area in central Idaho. Development of this sensor array builds upon advances in sensing, networking, and power supply technologies coupled with experiences of the multidisciplinary investigators in conducting research in remote mountainous locations. The proposed gradient monitoring network will provide near real-time data from a three-dimensional (3-D) array of sensors measuring biophysical parameters used in ecosystem process models. The network will monitor atmospheric carbon dioxide concentration, humidity, air and soil temperature, soil water content, precipitation, incoming and outgoing shortwave and longwave radiation, snow depth, wind speed and direction, tree stem growth and leaf wetness at time intervals ranging from seconds to days. The long-term goal of this project is to realize a transformative integration of smart sensor networks adaptively communicating data in real-time to ultimately achieve a 3-D visualization of ecosystem processes within remote mountainous regions. Process models will be the interface between the visualization platforms and the sensor network. This will allow us to better predict how non-human dominated terrestrial and aquatic ecosystems function and respond to climate dynamics. Access to the data will be ensured as part of the Northwest Knowledge Network being developed at the University of Idaho, through ongoing Idaho NSF-funded cyber infrastructure initiatives, and existing data management systems funded by NSF, such as the CUAHSI Hydrologic Information System (HIS). These efforts will enhance cross-disciplinary understanding of natural and anthropogenic influences on ecosystem function and ultimately inform decision-making.

Accurate complex scaling of three dimensional numerical potentials

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

Cerioni, Alessandro; Genovese, Luigi; Duchemin, Ivan

2013-05-28

The complex scaling method, which consists in continuing spatial coordinates into the complex plane, is a well-established method that allows to compute resonant eigenfunctions of the time-independent Schroedinger operator. Whenever it is desirable to apply the complex scaling to investigate resonances in physical systems defined on numerical discrete grids, the most direct approach relies on the application of a similarity transformation to the original, unscaled Hamiltonian. We show that such an approach can be conveniently implemented in the Daubechies wavelet basis set, featuring a very promising level of generality, high accuracy, and no need for artificial convergence parameters. Complex scalingmore » of three dimensional numerical potentials can be efficiently and accurately performed. By carrying out an illustrative resonant state computation in the case of a one-dimensional model potential, we then show that our wavelet-based approach may disclose new exciting opportunities in the field of computational non-Hermitian quantum mechanics.« less

Real-time, interactive animation of deformable two- and three-dimensional objects

DOEpatents

Desbrun, Mathieu; Schroeder, Peter; Meyer, Mark; Barr, Alan H.

2003-06-03

A method of updating in real-time the locations and velocities of mass points of a two- or three-dimensional object represented by a mass-spring system. A modified implicit Euler integration scheme is employed to determine the updated locations and velocities. In an optional post-integration step, the updated locations are corrected to preserve angular momentum. A processor readable medium and a network server each tangibly embodying the method are also provided. A system comprising a processor in combination with the medium, and a system comprising the server in combination with a client for accessing the server over a computer network, are also provided.

Influence of injection mode on transport properties in kilometer-scale three-dimensional discrete fracture networks

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

Hyman, Jeffrey De'Haven; Painter, S. L.; Viswanathan, H.

We investigate how the choice of injection mode impacts transport properties in kilometer-scale three-dimensional discrete fracture networks (DFN). The choice of injection mode, resident and flux-weighted, is designed to mimic different physical phenomena. It has been hypothesized that solute plumes injected under resident conditions evolve to behave similarly to solutes injected under flux-weighted conditions. Previously, computational limitations have prohibited the large-scale simulations required to investigate this hypothesis. We investigate this hypothesis by using a high-performance DFN suite, dfnWorks, to simulate flow in kilometer-scale three-dimensional DFNs based on fractured granite at the Forsmark site in Sweden, and adopt a Lagrangian approachmore » to simulate transport therein. Results show that after traveling through a pre-equilibrium region, both injection methods exhibit linear scaling of the first moment of travel time and power law scaling of the breakthrough curve with similar exponents, slightly larger than 2. Lastly, the physical mechanisms behind this evolution appear to be the combination of in-network channeling of mass into larger fractures, which offer reduced resistance to flow, and in-fracture channeling, which results from the topology of the DFN.« less

Influence of injection mode on transport properties in kilometer-scale three-dimensional discrete fracture networks

DOE PAGES

Hyman, Jeffrey De'Haven; Painter, S. L.; Viswanathan, H.; ...

2015-09-12

We investigate how the choice of injection mode impacts transport properties in kilometer-scale three-dimensional discrete fracture networks (DFN). The choice of injection mode, resident and flux-weighted, is designed to mimic different physical phenomena. It has been hypothesized that solute plumes injected under resident conditions evolve to behave similarly to solutes injected under flux-weighted conditions. Previously, computational limitations have prohibited the large-scale simulations required to investigate this hypothesis. We investigate this hypothesis by using a high-performance DFN suite, dfnWorks, to simulate flow in kilometer-scale three-dimensional DFNs based on fractured granite at the Forsmark site in Sweden, and adopt a Lagrangian approachmore » to simulate transport therein. Results show that after traveling through a pre-equilibrium region, both injection methods exhibit linear scaling of the first moment of travel time and power law scaling of the breakthrough curve with similar exponents, slightly larger than 2. Lastly, the physical mechanisms behind this evolution appear to be the combination of in-network channeling of mass into larger fractures, which offer reduced resistance to flow, and in-fracture channeling, which results from the topology of the DFN.« less

Three-Dimensional Culture of Human Breast Epithelial Cells: The How and the Why

PubMed Central

Vidi, Pierre-Alexandre; Bissell, Mina J.; Lelièvre, Sophie A.

2013-01-01

Organs are made of the organized assembly of different cell types that contribute to the architecture necessary for functional differentiation. In those with exocrine function, such as the breast, cell–cell and cell–extracellular matrix (ECM) interactions establish mechanistic constraints and a complex biochemical signaling network essential for differentiation and homeostasis of the glandular epithelium. Such knowledge has been elegantly acquired for the mammary gland by placing epithelial cells under three-dimensional (3D) culture conditions. Three-dimensional cell culture aims at recapitulating normal and pathological tissue architectures, hence providing physiologically relevant models to study normal development and disease. The specific architecture of the breast epithelium consists of glandular structures (acini) connected to a branched ductal system. A single layer of basoapically polarized luminal cells delineates ductal or acinar lumena at the apical pole. Luminal cells make contact with myoepithelial cells and, in certain areas at the basal pole, also with basement membrane (BM) components. In this chapter, we describe how this exquisite organization as well as stages of disorganization pertaining to cancer progression can be reproduced in 3D cultures. Advantages and limitations of different culture settings are discussed. Technical designs for induction of phenotypic modulations, biochemical analyses, and state-of-the-art imaging are presented. We also explain how signaling is regulated differently in 3D cultures compared to traditional two-dimensional (2D) cultures. We believe that using 3D cultures is an indispensable method to unravel the intricacies of human mammary functions and would best serve the fight against breast cancer. PMID:23097109

Decentralized Dimensionality Reduction for Distributed Tensor Data Across Sensor Networks.

PubMed

Liang, Junli; Yu, Guoyang; Chen, Badong; Zhao, Minghua

2016-11-01

This paper develops a novel decentralized dimensionality reduction algorithm for the distributed tensor data across sensor networks. The main contributions of this paper are as follows. First, conventional centralized methods, which utilize entire data to simultaneously determine all the vectors of the projection matrix along each tensor mode, are not suitable for the network environment. Here, we relax the simultaneous processing manner into the one-vector-by-one-vector (OVBOV) manner, i.e., determining the projection vectors (PVs) related to each tensor mode one by one. Second, we prove that in the OVBOV manner each PV can be determined without modifying any tensor data, which simplifies corresponding computations. Third, we cast the decentralized PV determination problem as a set of subproblems with consensus constraints, so that it can be solved in the network environment only by local computations and information communications among neighboring nodes. Fourth, we introduce the null space and transform the PV determination problem with complex orthogonality constraints into an equivalent hidden convex one without any orthogonality constraint, which can be solved by the Lagrange multiplier method. Finally, experimental results are given to show that the proposed algorithm is an effective dimensionality reduction scheme for the distributed tensor data across the sensor networks.

A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks.

PubMed

Jiang, Peng; Liu, Shuai; Liu, Jun; Wu, Feng; Zhang, Le

2016-07-14

Most of the existing node depth-adjustment deployment algorithms for underwater wireless sensor networks (UWSNs) just consider how to optimize network coverage and connectivity rate. However, these literatures don't discuss full network connectivity, while optimization of network energy efficiency and network reliability are vital topics for UWSN deployment. Therefore, in this study, a depth-adjustment deployment algorithm based on two-dimensional (2D) convex hull and spanning tree (NDACS) for UWSNs is proposed. First, the proposed algorithm uses the geometric characteristics of a 2D convex hull and empty circle to find the optimal location of a sleep node and activate it, minimizes the network coverage overlaps of the 2D plane, and then increases the coverage rate until the first layer coverage threshold is reached. Second, the sink node acts as a root node of all active nodes on the 2D convex hull and then forms a small spanning tree gradually. Finally, the depth-adjustment strategy based on time marker is used to achieve the three-dimensional overall network deployment. Compared with existing depth-adjustment deployment algorithms, the simulation results show that the NDACS algorithm can maintain full network connectivity with high network coverage rate, as well as improved network average node degree, thus increasing network reliability.

A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks

PubMed Central

Jiang, Peng; Liu, Shuai; Liu, Jun; Wu, Feng; Zhang, Le

2016-01-01

Most of the existing node depth-adjustment deployment algorithms for underwater wireless sensor networks (UWSNs) just consider how to optimize network coverage and connectivity rate. However, these literatures don’t discuss full network connectivity, while optimization of network energy efficiency and network reliability are vital topics for UWSN deployment. Therefore, in this study, a depth-adjustment deployment algorithm based on two-dimensional (2D) convex hull and spanning tree (NDACS) for UWSNs is proposed. First, the proposed algorithm uses the geometric characteristics of a 2D convex hull and empty circle to find the optimal location of a sleep node and activate it, minimizes the network coverage overlaps of the 2D plane, and then increases the coverage rate until the first layer coverage threshold is reached. Second, the sink node acts as a root node of all active nodes on the 2D convex hull and then forms a small spanning tree gradually. Finally, the depth-adjustment strategy based on time marker is used to achieve the three-dimensional overall network deployment. Compared with existing depth-adjustment deployment algorithms, the simulation results show that the NDACS algorithm can maintain full network connectivity with high network coverage rate, as well as improved network average node degree, thus increasing network reliability. PMID:27428970

Flow-pattern identification and nonlinear dynamics of gas-liquid two-phase flow in complex networks.

PubMed

Gao, Zhongke; Jin, Ningde

2009-06-01

The identification of flow pattern is a basic and important issue in multiphase systems. Because of the complexity of phase interaction in gas-liquid two-phase flow, it is difficult to discern its flow pattern objectively. In this paper, we make a systematic study on the vertical upward gas-liquid two-phase flow using complex network. Three unique network construction methods are proposed to build three types of networks, i.e., flow pattern complex network (FPCN), fluid dynamic complex network (FDCN), and fluid structure complex network (FSCN). Through detecting the community structure of FPCN by the community-detection algorithm based on K -mean clustering, useful and interesting results are found which can be used for identifying five vertical upward gas-liquid two-phase flow patterns. To investigate the dynamic characteristics of gas-liquid two-phase flow, we construct 50 FDCNs under different flow conditions, and find that the power-law exponent and the network information entropy, which are sensitive to the flow pattern transition, can both characterize the nonlinear dynamics of gas-liquid two-phase flow. Furthermore, we construct FSCN and demonstrate how network statistic can be used to reveal the fluid structure of gas-liquid two-phase flow. In this paper, from a different perspective, we not only introduce complex network theory to the study of gas-liquid two-phase flow but also indicate that complex network may be a powerful tool for exploring nonlinear time series in practice.

Three new 5-fold interpenetrating diamondoid frameworks constructed by rigid diimidazole and dicarboxylate ligands

NASA Astrophysics Data System (ADS)

Huo, Jianqiang; Yan, Shuai; Li, Haiqiang; Yu, Donghui; Arulsamy, Navamoney

2018-03-01

A series of three-dimensional coordination polymers, namely, [Cd(BIMB)(SCA)]n (1), [M(BIMB)(trans-CHDC)]n (2, M = Cd2+; 3, M = Co2+), where BIMB = 1,4-di(1H-imidazol-1-yl)benzene, SCA2- = succinate dianion, CHDC2- = cyclohexane-1,4-dicarboxylate dianion) are synthesized hydro/solvatothermal methods. The products are characterized by elemental analysis and single-crystal X-ray diffraction data. Both the dianion and BIMB bridge different pairs of the metal ions, the three complexes are polymeric and their three-dimensional topology feature a diamond-like metal-organic framework (MOF). Owing to the length of the two bridging ligands, moderate size voids are formed in the diamondoid networks. However, the voids are filled by mutual interpenetration of four independent equivalent frameworks in a 5-fold interpenetrating architecture, and there is no sufficient void volume available for any guest molecules. The phase purity and thermal stability of the compounds are verified by powder X-ray diffraction (PXRD) and thermogravimetric (TG) data. The solid-state fluorescence spectra for the 3d10 Cd2+ MOF's 1 and 2 reveal significant enhancement in their emission intensities in comparison to the non-metallated BIMB. The enhanced emission is attributed to perturbation of intra-ligand emission states due to Cd2+ coordination.

Cross-species microarray hybridization to identify developmentally regulated genes in the filamentous fungus Sordaria macrospora.

PubMed

Nowrousian, Minou; Ringelberg, Carol; Dunlap, Jay C; Loros, Jennifer J; Kück, Ulrich

2005-04-01

The filamentous fungus Sordaria macrospora forms complex three-dimensional fruiting bodies that protect the developing ascospores and ensure their proper discharge. Several regulatory genes essential for fruiting body development were previously isolated by complementation of the sterile mutants pro1, pro11 and pro22. To establish the genetic relationships between these genes and to identify downstream targets, we have conducted cross-species microarray hybridizations using cDNA arrays derived from the closely related fungus Neurospora crassa and RNA probes prepared from wild-type S. macrospora and the three developmental mutants. Of the 1,420 genes which gave a signal with the probes from all the strains used, 172 (12%) were regulated differently in at least one of the three mutants compared to the wild type, and 17 (1.2%) were regulated differently in all three mutant strains. Microarray data were verified by Northern analysis or quantitative real time PCR. Among the genes that are up- or down-regulated in the mutant strains are genes encoding the pheromone precursors, enzymes involved in melanin biosynthesis and a lectin-like protein. Analysis of gene expression in double mutants revealed a complex network of interaction between the pro gene products.

System-level simulation of liquid filling in microfluidic chips.

PubMed

Song, Hongjun; Wang, Yi; Pant, Kapil

2011-06-01

Liquid filling in microfluidic channels is a complex process that depends on a variety of geometric, operating, and material parameters such as microchannel geometry, flow velocity∕pressure, liquid surface tension, and contact angle of channel surface. Accurate analysis of the filling process can provide key insights into the filling time, air bubble trapping, and dead zone formation, and help evaluate trade-offs among the various design parameters and lead to optimal chip design. However, efficient modeling of liquid filling in complex microfluidic networks continues to be a significant challenge. High-fidelity computational methods, such as the volume of fluid method, are prohibitively expensive from a computational standpoint. Analytical models, on the other hand, are primarily applicable to idealized geometries and, hence, are unable to accurately capture chip level behavior of complex microfluidic systems. This paper presents a parametrized dynamic model for the system-level analysis of liquid filling in three-dimensional (3D) microfluidic networks. In our approach, a complex microfluidic network is deconstructed into a set of commonly used components, such as reservoirs, microchannels, and junctions. The components are then assembled according to their spatial layout and operating rationale to achieve a rapid system-level model. A dynamic model based on the transient momentum equation is developed to track the liquid front in the microchannels. The principle of mass conservation at the junction is used to link the fluidic parameters in the microchannels emanating from the junction. Assembly of these component models yields a set of differential and algebraic equations, which upon integration provides temporal information of the liquid filling process, particularly liquid front propagation (i.e., the arrival time). The models are used to simulate the transient liquid filling process in a variety of microfluidic constructs and in a multiplexer, representing a complex microfluidic network. The accuracy (relative error less than 7%) and orders-of-magnitude speedup (30 000X-4 000 000X) of our system-level models are verified by comparison against 3D high-fidelity numerical studies. Our findings clearly establish the utility of our models and simulation methodology for fast, reliable analysis of liquid filling to guide the design optimization of complex microfluidic networks.

Electrical Conductivity in Transparent Silver Nanowire Networks: Simulations and Experiments

NASA Astrophysics Data System (ADS)

Sherrott, Michelle; Mutiso, Rose; Rathmell, Aaron; Wiley, Benjamin; Winey, Karen

2012-02-01

We model and experimentally measure the electrical conductivity of two-dimensional networks containing finite, conductive cylinders with aspect ratio ranging from 33 to 333. We have previously used our simulations to explore the effects of cylinder orientation and aspect ratio in three-dimensional composites, and now extend the simulation to consider two-dimensional silver nanowire networks. Preliminary results suggest that increasing the aspect ratio and area fraction of these rods significantly decreases the sheet resistance of the film. For all simulated aspect ratios, this sheet resistance approaches a constant value for high area fractions of rods. This implies that regardless of aspect ratio, there is a limiting minimum sheet resistance that is characteristic of the properties of the nanowires. Experimental data from silver nanowire networks will be incorporated into the simulations to define the contact resistance and corroborate experimentally measured sheet resistances of transparent thin films.

Three-Dimensional Mapping of Air Flow at an Urban Canyon Intersection

NASA Astrophysics Data System (ADS)

Carpentieri, Matteo; Robins, Alan G.; Baldi, Sandro

2009-11-01

In this experimental work both qualitative (flow visualisation) and quantitative (laser Doppler anemometry) methods were applied in a wind tunnel in order to describe the complex three-dimensional flow field in a real environment (a street canyon intersection). The main aim was an examination of the mean flow, turbulence and flow pathlines characterising a complex three-dimensional urban location. The experiments highlighted the complexity of the observed flows, particularly in the upwind region of the intersection. In this complex and realistic situation some details of the upwind flow, such as the presence of two tall towers, play an important role in defining the flow field within the intersection, particularly at roof level. This effect is likely to have a strong influence on the mass exchange mechanism between the canopy flow and the air aloft, and therefore the distribution of pollutants. This strong interaction between the flows inside and outside the urban canopy is currently neglected in most state-of-the-art local scale dispersion models.

Cell diversity and network dynamics in photosensitive human brain organoids.

PubMed

Quadrato, Giorgia; Nguyen, Tuan; Macosko, Evan Z; Sherwood, John L; Min Yang, Sung; Berger, Daniel R; Maria, Natalie; Scholvin, Jorg; Goldman, Melissa; Kinney, Justin P; Boyden, Edward S; Lichtman, Jeff W; Williams, Ziv M; McCarroll, Steven A; Arlotta, Paola

2017-05-04

In vitro models of the developing brain such as three-dimensional brain organoids offer an unprecedented opportunity to study aspects of human brain development and disease. However, the cells generated within organoids and the extent to which they recapitulate the regional complexity, cellular diversity and circuit functionality of the brain remain undefined. Here we analyse gene expression in over 80,000 individual cells isolated from 31 human brain organoids. We find that organoids can generate a broad diversity of cells, which are related to endogenous classes, including cells from the cerebral cortex and the retina. Organoids could be developed over extended periods (more than 9 months), allowing for the establishment of relatively mature features, including the formation of dendritic spines and spontaneously active neuronal networks. Finally, neuronal activity within organoids could be controlled using light stimulation of photosensitive cells, which may offer a way to probe the functionality of human neuronal circuits using physiological sensory stimuli.

de Sitter space as a tensor network: Cosmic no-hair, complementarity, and complexity

NASA Astrophysics Data System (ADS)

Bao, Ning; Cao, ChunJun; Carroll, Sean M.; Chatwin-Davies, Aidan

2017-12-01

We investigate the proposed connection between de Sitter spacetime and the multiscale entanglement renormalization ansatz (MERA) tensor network, and ask what can be learned via such a construction. We show that the quantum state obeys a cosmic no-hair theorem: the reduced density operator describing a causal patch of the MERA asymptotes to a fixed point of a quantum channel, just as spacetimes with a positive cosmological constant asymptote to de Sitter space. The MERA is potentially compatible with a weak form of complementarity (local physics only describes single patches at a time, but the overall Hilbert space is infinite dimensional) or, with certain specific modifications to the tensor structure, a strong form (the entire theory describes only a single patch plus its horizon, in a finite-dimensional Hilbert space). We also suggest that de Sitter evolution has an interpretation in terms of circuit complexity, as has been conjectured for anti-de Sitter space.

Urdu Nasta'liq text recognition using implicit segmentation based on multi-dimensional long short term memory neural networks.

PubMed

Naz, Saeeda; Umar, Arif Iqbal; Ahmed, Riaz; Razzak, Muhammad Imran; Rashid, Sheikh Faisal; Shafait, Faisal

2016-01-01

The recognition of Arabic script and its derivatives such as Urdu, Persian, Pashto etc. is a difficult task due to complexity of this script. Particularly, Urdu text recognition is more difficult due to its Nasta'liq writing style. Nasta'liq writing style inherits complex calligraphic nature, which presents major issues to recognition of Urdu text owing to diagonality in writing, high cursiveness, context sensitivity and overlapping of characters. Therefore, the work done for recognition of Arabic script cannot be directly applied to Urdu recognition. We present Multi-dimensional Long Short Term Memory (MDLSTM) Recurrent Neural Networks with an output layer designed for sequence labeling for recognition of printed Urdu text-lines written in the Nasta'liq writing style. Experiments show that MDLSTM attained a recognition accuracy of 98% for the unconstrained Urdu Nasta'liq printed text, which significantly outperforms the state-of-the-art techniques.

Multilayered complex network datasets for three supply chain network archetypes on an urban road grid.

PubMed

Viljoen, Nadia M; Joubert, Johan W

2018-02-01

This article presents the multilayered complex network formulation for three different supply chain network archetypes on an urban road grid and describes how 500 instances were randomly generated for each archetype. Both the supply chain network layer and the urban road network layer are directed unweighted networks. The shortest path set is calculated for each of the 1 500 experimental instances. The datasets are used to empirically explore the impact that the supply chain's dependence on the transport network has on its vulnerability in Viljoen and Joubert (2017) [1]. The datasets are publicly available on Mendeley (Joubert and Viljoen, 2017) [2].

Positronium formation studies in crystalline molecular complexes: Triphenylphosphine oxide - Acetanilide

NASA Astrophysics Data System (ADS)

Oliveira, F. C.; Denadai, A. M. L.; Guerra, L. D. L.; Fulgêncio, F. H.; Windmöller, D.; Santos, G. C.; Fernandes, N. G.; Yoshida, M. I.; Donnici, C. L.; Magalhães, W. F.; Machado, J. C.

2013-04-01

Hydrogen bond formation in the triphenylphosphine oxide (TPPO), acetanilide (ACN) supramolecular heterosynton system, named [TPPO0.5·ACN0.5], has been studied by Positron Annihilation Lifetime Spectroscopy (PALS) and supported by several analytical techniques. In toluene solution, Isothermal Titration Calorimetry (ITC) presented a 1:1 stoichiometry and indicated that the complexation process is driven by entropy, with low enthalpy contribution. X-ray structure determination showed the existence of a three-dimensional network of hydrogen bonds, allowing also the confirmation of the existence of a 1:1 crystalline molecular complex in solid state. The results of thermal analysis (TGA, DTA and DSC) and FTIR spectroscopy showed that the interactions in the complex are relatively weaker than those found in pure precursors, leading to a higher positronium formation probability at [TPPO0.5·ACN0.5]. These weak interactions in the complex enhance the possibility of the n- and π-electrons to interact with positrons and consequently, the probability of positronium formation is higher. Through the present work is shown that PALS is a sensible powerful tool to investigate intermolecular interactions in solid heterosynton supramolecular systems.

From Laser Scanning to Finite Element Analysis of Complex Buildings by Using a Semi-Automatic Procedure.

PubMed

Castellazzi, Giovanni; D'Altri, Antonio Maria; Bitelli, Gabriele; Selvaggi, Ilenia; Lambertini, Alessandro

2015-07-28

In this paper, a new semi-automatic procedure to transform three-dimensional point clouds of complex objects to three-dimensional finite element models is presented and validated. The procedure conceives of the point cloud as a stacking of point sections. The complexity of the clouds is arbitrary, since the procedure is designed for terrestrial laser scanner surveys applied to buildings with irregular geometry, such as historical buildings. The procedure aims at solving the problems connected to the generation of finite element models of these complex structures by constructing a fine discretized geometry with a reduced amount of time and ready to be used with structural analysis. If the starting clouds represent the inner and outer surfaces of the structure, the resulting finite element model will accurately capture the whole three-dimensional structure, producing a complex solid made by voxel elements. A comparison analysis with a CAD-based model is carried out on a historical building damaged by a seismic event. The results indicate that the proposed procedure is effective and obtains comparable models in a shorter time, with an increased level of automation.

Hollow SnO2@Co3O4 core-shell spheres encapsulated in three-dimensional graphene foams for high performance supercapacitors and lithium-ion batteries

NASA Astrophysics Data System (ADS)

Zhao, Bo; Huang, Sheng-Yun; Wang, Tao; Zhang, Kai; Yuen, Matthew M. F.; Xu, Jian-Bin; Fu, Xian-Zhu; Sun, Rong; Wong, Ching-Ping

2015-12-01

Hollow SnO2@Co3O4 spheres are fabricated using 300 nm spherical SiO2 particles as template. Then three-dimensional graphene foams encapsulated hollow SnO2@Co3O4 spheres are successfully obtained through self-assembly in hydrothermal process from graphene oxide nanosheets and metal oxide hollow spheres. The three-dimensional graphene foams encapsulated architectures could greatly improve the capacity, cycling stability and rate capability of hollow SnO2@Co3O4 spheres electrodes due to the highly conductive networks and flexible buffering matrix. The three-dimensional graphene foams encapsulated hollow SnO2@Co3O4 spheres are promising electrode materials for supercapacitors and lithium-ion batteries.

Two-Dimensional Optoelectronic Graphene Nanoprobes for Neural Nerwork

NASA Astrophysics Data System (ADS)

Hong, Tu; Kitko, Kristina; Wang, Rui; Zhang, Qi; Xu, Yaqiong

2014-03-01

Brain is the most complex network created by nature, with billions of neurons connected by trillions of synapses through sophisticated wiring patterns and countless modulatory mechanisms. Current methods to study the neuronal process, either by electrophysiology or optical imaging, have significant limitations on throughput and sensitivity. Here, we use graphene, a monolayer of carbon atoms, as a two-dimensional nanoprobe for neural network. Scanning photocurrent measurement is applied to detect the local integration of electrical and chemical signals in mammalian neurons. Such interface between nanoscale electronic device and biological system provides not only ultra-high sensitivity, but also sub-millisecond temporal resolution, owing to the high carrier mobility of graphene.

Two novel mixed-ligand complexes containing organosulfonate ligands.

PubMed

Li, Mingtian; Huang, Jun; Zhou, Xuan; Fang, Hua; Ding, Liyun

2008-07-01

The structures reported herein, viz. bis(4-aminonaphthalene-1-sulfonato-kappaO)bis(4,5-diazafluoren-9-one-kappa(2)N,N')copper(II), [Cu(C(10)H(8)NO(3)S)(2)(C(11)H(6)N(2)O)(2)], (I), and poly[[[diaquacadmium(II)]-bis(mu-4-aminonaphthalene-1-sulfonato)-kappa(2)O:N;kappa(2)N:O] dihydrate], {[Cd(C(10)H(8)NO(3)S)(2)(H(2)O)(2)].2H(2)O}(n), (II), are rare examples of sulfonate-containing complexes where the anion does not fulfill a passive charge-balancing role, but takes an active part in coordination as a monodentate and/or bridging ligand. Monomeric complex (I) possesses a crystallographic inversion center at the Cu(II) atom, and the asymmetric unit contains one-half of a Cu atom, one complete 4-aminonaphthalene-1-sulfonate (ans) ligand and one 4,5-diazafluoren-9-one (DAFO) ligand. The Cu(II) atom has an elongated distorted octahedral coordination geometry formed by two O atoms from two monodentate ans ligands and by four N atoms from two DAFO molecules. Complex (II) is polymeric and its crystal structure is built up by one-dimensional chains and solvent water molecules. Here also the cation (a Cd(II) atom) lies on a crystallographic inversion center and adopts a slightly distorted octahedral geometry. Each ans anion serves as a bridging ligand linking two Cd(II) atoms into one-dimensional infinite chains along the [010] direction, with each Cd(II) center coordinated by four ans ligands via O and N atoms and by two aqua ligands. In both structures, there are significant pi-pi stacking interactions between adjacent ligands and hydrogen bonds contribute to the formation of two- and three-dimensional networks.

The Coupling of Finite Element and Integral Equation Representations for Efficient Three-Dimensional Modeling of Electromagnetic Scattering and Radiation

NASA Technical Reports Server (NTRS)

Cwik, Tom; Zuffada, Cinzia; Jamnejad, Vahraz

1996-01-01

Finite element modeling has proven useful for accurtely simulating scattered or radiated fields from complex three-dimensional objects whose geometry varies on the scale of a fraction of a wavelength.

A THREE-DIMENSIONAL MODEL ASSESSMENT OF THE GLOBAL DISTRIBUTION OF HEXACHLOROBENZENE

EPA Science Inventory

The distributions of persistent organic pollutants (POPs) in the global environment have been studied typically with box/fugacity models with simplified treatments of atmospheric transport processes1. Such models are incapable of simulating the complex three-dimensional mechanis...

A 16-bit Coherent Ising Machine for One-Dimensional Ring and Cubic Graph Problems

NASA Astrophysics Data System (ADS)

Takata, Kenta; Marandi, Alireza; Hamerly, Ryan; Haribara, Yoshitaka; Maruo, Daiki; Tamate, Shuhei; Sakaguchi, Hiromasa; Utsunomiya, Shoko; Yamamoto, Yoshihisa

2016-09-01

Many tasks in our modern life, such as planning an efficient travel, image processing and optimizing integrated circuit design, are modeled as complex combinatorial optimization problems with binary variables. Such problems can be mapped to finding a ground state of the Ising Hamiltonian, thus various physical systems have been studied to emulate and solve this Ising problem. Recently, networks of mutually injected optical oscillators, called coherent Ising machines, have been developed as promising solvers for the problem, benefiting from programmability, scalability and room temperature operation. Here, we report a 16-bit coherent Ising machine based on a network of time-division-multiplexed femtosecond degenerate optical parametric oscillators. The system experimentally gives more than 99.6% of success rates for one-dimensional Ising ring and nondeterministic polynomial-time (NP) hard instances. The experimental and numerical results indicate that gradual pumping of the network combined with multiple spectral and temporal modes of the femtosecond pulses can improve the computational performance of the Ising machine, offering a new path for tackling larger and more complex instances.

Graphene--nanotube--iron hierarchical nanostructure as lithium ion battery anode.

PubMed

Lee, Si-Hwa; Sridhar, Vadahanambi; Jung, Jung-Hwan; Karthikeyan, Kaliyappan; Lee, Yun-Sung; Mukherjee, Rahul; Koratkar, Nikhil; Oh, Il-Kwon

2013-05-28

In this study, we report a novel route via microwave irradiation to synthesize a bio-inspired hierarchical graphene--nanotube--iron three-dimensional nanostructure as an anode material in lithium-ion batteries. The nanostructure comprises vertically aligned carbon nanotubes grown directly on graphene sheets along with shorter branches of carbon nanotubes stemming out from both the graphene sheets and the vertically aligned carbon nanotubes. This bio-inspired hierarchical structure provides a three-dimensional conductive network for efficient charge-transfer and prevents the agglomeration and restacking of the graphene sheets enabling Li-ions to have greater access to the electrode material. In addition, functional iron-oxide nanoparticles decorated within the three-dimensional hierarchical structure provides outstanding lithium storage characteristics, resulting in very high specific capacities. The anode material delivers a reversible capacity of ~1024 mA · h · g(-1) even after prolonged cycling along with a Coulombic efficiency in excess of 99%, which reflects the ability of the hierarchical network to prevent agglomeration of the iron-oxide nanoparticles.

[Research progress of three-dimensional digital model for repair and reconstruction of knee joint].

PubMed

Tong, Lu; Li, Yanlin; Hu, Meng

2013-01-01

To review recent advance in the application and research of three-dimensional digital knee model. The recent original articles about three-dimensional digital knee model were extensively reviewed and analyzed. The digital three-dimensional knee model can simulate the knee complex anatomical structure very well. Based on this, there are some developments of new software and techniques, and good clinical results are achieved. With the development of computer techniques and software, the knee repair and reconstruction procedure has been improved, the operation will be more simple and its accuracy will be further improved.

Visualization of molecular structures using HoloLens-based augmented reality

PubMed Central

Hoffman, MA; Provance, JB

2017-01-01

Biological molecules and biologically active small molecules are complex three dimensional structures. Current flat screen monitors are limited in their ability to convey the full three dimensional characteristics of these molecules. Augmented reality devices, including the Microsoft HoloLens, offer an immersive platform to change how we interact with molecular visualizations. We describe a process to incorporate the three dimensional structures of small molecules and complex proteins into the Microsoft HoloLens using aspirin and the human leukocyte antigen (HLA) as examples. Small molecular structures can be introduced into the HoloStudio application, which provides native support for rotating, resizing and performing other interactions with these molecules. Larger molecules can be imported through the Unity gaming development platform and then Microsoft Visual Developer. The processes described here can be modified to import a wide variety of molecular structures into augmented reality systems and improve our comprehension of complex structural features. PMID:28815109

Computational neural networks in chemistry: Model free mapping devices for predicting chemical reactivity from molecular structure

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

Elrod, D.W.

1992-01-01

Computational neural networks (CNNs) are a computational paradigm inspired by the brain's massively parallel network of highly interconnected neurons. The power of computational neural networks derives not so much from their ability to model the brain as from their ability to learn by example and to map highly complex, nonlinear functions, without the need to explicitly specify the functional relationship. Two central questions about CNNs were investigated in the context of predicting chemical reactions: (1) the mapping properties of neural networks and (2) the representation of chemical information for use in CNNs. Chemical reactivity is here considered an example ofmore » a complex, nonlinear function of molecular structure. CNN's were trained using modifications of the back propagation learning rule to map a three dimensional response surface similar to those typically observed in quantitative structure-activity and structure-property relationships. The computational neural network's mapping of the response surface was found to be robust to the effects of training sample size, noisy data and intercorrelated input variables. The investigation of chemical structure representation led to the development of a molecular structure-based connection-table representation suitable for neural network training. An extension of this work led to a BE-matrix structure representation that was found to be general for several classes of reactions. The CNN prediction of chemical reactivity and regiochemistry was investigated for electrophilic aromatic substitution reactions, Markovnikov addition to alkenes, Saytzeff elimination from haloalkanes, Diels-Alder cycloaddition, and retro Diels-Alder ring opening reactions using these connectivity-matrix derived representations. The reaction predictions made by the CNNs were more accurate than those of an expert system and were comparable to predictions made by chemists.« less

Toward efficiency in heterogeneous multispecies reactive transport modeling: A particle-tracking solution for first-order network reactions

NASA Astrophysics Data System (ADS)

Henri, Christopher; Fernàndez-Garcia, Daniel

2015-04-01

Modeling multi-species reactive transport in natural systems with strong heterogeneities and complex biochemical reactions is a major challenge for assessing groundwater polluted sites with organic and inorganic contaminants. A large variety of these contaminants react according to serial-parallel reaction networks commonly simplified by a combination of first-order kinetic reactions. In this context, a random-walk particle tracking method is presented. This method is capable of efficiently simulating the motion of particles affected by first-order network reactions in three-dimensional systems, which are represented by spatially variable physical and biochemical coefficients described at high resolution. The approach is based on the development of transition probabilities that describe the likelihood that particles belonging to a given species and location at a given time will be transformed into and moved to another species and location afterwards. These probabilities are derived from the solution matrix of the spatial moments governing equations. The method is fully coupled with reactions, free of numerical dispersion and overcomes the inherent numerical problems stemming from the incorporation of heterogeneities to reactive transport codes. In doing this, we demonstrate that the motion of particles follows a standard random walk with time-dependent effective retardation and dispersion parameters that depend on the initial and final chemical state of the particle. The behavior of effective parameters develops as a result of differential retardation effects among species. Moreover, explicit analytic solutions of the transition probability matrix and related particle motions are provided for serial reactions. An example of the effect of heterogeneity on the dechlorination of organic solvents in a three-dimensional random porous media shows that the power-law behavior typically observed in conservative tracers breakthrough curves can be largely compromised by the effect of biochemical reactions.

Toward efficiency in heterogeneous multispecies reactive transport modeling: A particle-tracking solution for first-order network reactions

NASA Astrophysics Data System (ADS)

Henri, Christopher V.; Fernàndez-Garcia, Daniel

2014-09-01

Modeling multispecies reactive transport in natural systems with strong heterogeneities and complex biochemical reactions is a major challenge for assessing groundwater polluted sites with organic and inorganic contaminants. A large variety of these contaminants react according to serial-parallel reaction networks commonly simplified by a combination of first-order kinetic reactions. In this context, a random-walk particle tracking method is presented. This method is capable of efficiently simulating the motion of particles affected by first-order network reactions in three-dimensional systems, which are represented by spatially variable physical and biochemical coefficients described at high resolution. The approach is based on the development of transition probabilities that describe the likelihood that particles belonging to a given species and location at a given time will be transformed into and moved to another species and location afterward. These probabilities are derived from the solution matrix of the spatial moments governing equations. The method is fully coupled with reactions, free of numerical dispersion and overcomes the inherent numerical problems stemming from the incorporation of heterogeneities to reactive transport codes. In doing this, we demonstrate that the motion of particles follows a standard random walk with time-dependent effective retardation and dispersion parameters that depend on the initial and final chemical state of the particle. The behavior of effective parameters develops as a result of differential retardation effects among species. Moreover, explicit analytic solutions of the transition probability matrix and related particle motions are provided for serial reactions. An example of the effect of heterogeneity on the dechlorination of organic solvents in a three-dimensional random porous media shows that the power-law behavior typically observed in conservative tracers breakthrough curves can be largely compromised by the effect of biochemical reactions.

Two- and three-dimensional lanthanide-organic frameworks constructed using 1-hydro-6-oxopyridine-3-carboxylate and oxalate ligands.

PubMed

Liu, Cai-Ming; Xiong, Ming; Zhang, De-Qing; Du, Miao; Zhu, Dao-Ben

2009-08-07

6-Hydroxypyridine-3-carboxylic acid (6-HOPy-3-CO(2)H) reacts with Ln(2)O(3) (Ln = Nd, Sm, Eu, Gd) and oxalic acid (H(2)OX) under hydrothermal conditions to generate four novel lanthanide-organic coordination polymeric networks [Ln(2)(1H-6-Opy-3-CO(2))(2)(OX)(2)(H(2)O)(3)] x 2.5 H(2)O (Ln = Nd, 1; Sm, 2; 1H-6-Opy-3-CO(2)(-) = 1-hydro-6-oxopyridine-3-carboxylate) and [Ln(1H-6-Opy-3-CO(2))(OX)(H(2)O)(2)] x H(2)O (Ln = Eu, 3; Gd, 4). The new co-ligand 1H-6-Opy-3-CO(2)(-) anion was generated by the autoisomerization of the single deprotonated 6-HOPy-3-CO(2)(-) anion (from the enol form into the ketone one). 1 and 2 are isomorphous, they possess a three-dimensional architecture constructed from Ln(3+) ions bridged by oxalate anions and two types of 1H-6-Opy-3-CO(2)(-) bridges, showing a three-nodal (4,5)-connected topology (3.4(2).5(2).6(3).7.8)(2)(3.5(3).6(2))(2)(3(2).6.7(2).8) or a simplified uninodal 6-connected topology (3(3).4(6).5(5).6), both topologies are completely new; while only one type of 1H-6-Opy-3-CO(2)(-) bridge is used to construct the two-dimensional layer networks of 3 and 4 besides oxalate bridges, both complexes 3 and 4 are isostructural, exhibiting the honeycomb topology 6(3). The lanthanide contraction effect is believed to play a key role in directing the formation of a particular structure. A magnetic study of 1-3 indicated that the coupling interaction between Ln(3+) ions is weak.

Cardiac myocyte diversity and a fibroblast network in the junctional region of the zebrafish heart revealed by transmission and serial block-face scanning electron microscopy.

PubMed

Lafontant, Pascal J; Behzad, Ali R; Brown, Evelyn; Landry, Paul; Hu, Norman; Burns, Alan R

2013-01-01

The zebrafish has emerged as an important model of heart development and regeneration. While the structural characteristics of the developing and adult zebrafish ventricle have been previously studied, little attention has been paid to the nature of the interface between the compact and spongy myocardium. Here we describe how these two distinct layers are structurally and functionally integrated. We demonstrate by transmission electron microscopy that this interface is complex and composed primarily of a junctional region occupied by collagen, as well as a population of fibroblasts that form a highly complex network. We also describe a continuum of uniquely flattened transitional cardiac myocytes that form a circumferential plate upon which the radially-oriented luminal trabeculae are anchored. In addition, we have uncovered within the transitional ring a subpopulation of markedly electron dense cardiac myocytes. At discrete intervals the transitional cardiac myocytes form contact bridges across the junctional space that are stabilized through localized desmosomes and fascia adherentes junctions with adjacent compact cardiac myocytes. Finally using serial block-face scanning electron microscopy, segmentation and volume reconstruction, we confirm the three-dimensional nature of the junctional region as well as the presence of the sheet-like fibroblast network. These ultrastructural studies demonstrate the previously unrecognized complexity with which the compact and spongy layers are structurally integrated, and provide a new basis for understanding development and regeneration in the zebrafish heart.

Statistical mechanics of complex neural systems and high dimensional data

NASA Astrophysics Data System (ADS)

Advani, Madhu; Lahiri, Subhaneil; Ganguli, Surya

2013-03-01

Recent experimental advances in neuroscience have opened new vistas into the immense complexity of neuronal networks. This proliferation of data challenges us on two parallel fronts. First, how can we form adequate theoretical frameworks for understanding how dynamical network processes cooperate across widely disparate spatiotemporal scales to solve important computational problems? Second, how can we extract meaningful models of neuronal systems from high dimensional datasets? To aid in these challenges, we give a pedagogical review of a collection of ideas and theoretical methods arising at the intersection of statistical physics, computer science and neurobiology. We introduce the interrelated replica and cavity methods, which originated in statistical physics as powerful ways to quantitatively analyze large highly heterogeneous systems of many interacting degrees of freedom. We also introduce the closely related notion of message passing in graphical models, which originated in computer science as a distributed algorithm capable of solving large inference and optimization problems involving many coupled variables. We then show how both the statistical physics and computer science perspectives can be applied in a wide diversity of contexts to problems arising in theoretical neuroscience and data analysis. Along the way we discuss spin glasses, learning theory, illusions of structure in noise, random matrices, dimensionality reduction and compressed sensing, all within the unified formalism of the replica method. Moreover, we review recent conceptual connections between message passing in graphical models, and neural computation and learning. Overall, these ideas illustrate how statistical physics and computer science might provide a lens through which we can uncover emergent computational functions buried deep within the dynamical complexities of neuronal networks.

Determining geophysical properties from well log data using artificial neural networks and fuzzy inference systems

NASA Astrophysics Data System (ADS)

Chang, Hsien-Cheng

Two novel synergistic systems consisting of artificial neural networks and fuzzy inference systems are developed to determine geophysical properties by using well log data. These systems are employed to improve the determination accuracy in carbonate rocks, which are generally more complex than siliciclastic rocks. One system, consisting of a single adaptive resonance theory (ART) neural network and three fuzzy inference systems (FISs), is used to determine the permeability category. The other system, which is composed of three ART neural networks and a single FIS, is employed to determine the lithofacies. The geophysical properties studied in this research, permeability category and lithofacies, are treated as categorical data. The permeability values are transformed into a "permeability category" to account for the effects of scale differences between core analyses and well logs, and heterogeneity in the carbonate rocks. The ART neural networks dynamically cluster the input data sets into different groups. The FIS is used to incorporate geologic experts' knowledge, which is usually in linguistic forms, into systems. These synergistic systems thus provide viable alternative solutions to overcome the effects of heterogeneity, the uncertainties of carbonate rock depositional environments, and the scarcity of well log data. The results obtained in this research show promising improvements over backpropagation neural networks. For the permeability category, the prediction accuracies are 68.4% and 62.8% for the multiple-single ART neural network-FIS and a single backpropagation neural network, respectively. For lithofacies, the prediction accuracies are 87.6%, 79%, and 62.8% for the single-multiple ART neural network-FIS, a single ART neural network, and a single backpropagation neural network, respectively. The sensitivity analysis results show that the multiple-single ART neural networks-FIS and a single ART neural network possess the same matching trends in determining lithofacies. This research shows that the adaptive resonance theory neural networks enable decision-makers to clearly distinguish the importance of different pieces of data which are useful in three-dimensional subsurface modeling. Geologic experts' knowledge can be easily applied and maintained by using the fuzzy inference systems.

Permutation invariant polynomial neural network approach to fitting potential energy surfaces. II. Four-atom systems

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

Li, Jun; Jiang, Bin; Guo, Hua, E-mail: hguo@unm.edu

2013-11-28

A rigorous, general, and simple method to fit global and permutation invariant potential energy surfaces (PESs) using neural networks (NNs) is discussed. This so-called permutation invariant polynomial neural network (PIP-NN) method imposes permutation symmetry by using in its input a set of symmetry functions based on PIPs. For systems with more than three atoms, it is shown that the number of symmetry functions in the input vector needs to be larger than the number of internal coordinates in order to include both the primary and secondary invariant polynomials. This PIP-NN method is successfully demonstrated in three atom-triatomic reactive systems, resultingmore » in full-dimensional global PESs with average errors on the order of meV. These PESs are used in full-dimensional quantum dynamical calculations.« less

Highly Sensitive Immunoassay Based on Controlled Rehydration of Patterned Reagents in a 2-Dimensional Paper Network

PubMed Central

2015-01-01

We have demonstrated a multistep 2-dimensional paper network immunoassay based on controlled rehydration of patterned, dried reagents. Previous work has shown that signal enhancement improves the limit of detection in 2-dimensional paper network assays, but until now, reagents have only been included as wet or dried in separate conjugate pads placed at the upstream end of the assay device. Wet reagents are not ideal for point-of-care because they must be refrigerated and typically limit automation and require more user steps. Conjugate pads allow drying but do not offer any control of the reagent distribution upon rehydration and can be a source of error when pads do not contact the assay membrane uniformly. Furthermore, each reagent is dried on a separate pad, increasing the fabrication complexity when implementing multistep assays that require several different reagents. Conversely, our novel method allows for consistent, controlled rehydration from patterned reagent storage depots directly within the paper membrane. In this assay demonstration, four separate reagents were patterned in different regions of the assay device: a gold-antibody conjugate used for antigen detection and three different signal enhancement components that must not be mixed until immediately before use. To show the viability of patterning and drying reagents directly onto a paper device for dry reagent storage and subsequent controlled release, we tested this device with the malaria antigen Plasmodium falciparum histidine-rich protein 2 (PfHRP2) as an example of target analyte. In this demonstration, the signal enhancement step increases the visible signal by roughly 3-fold and decreases the analytical limit of detection by 2.75-fold. PMID:24882058

Structural and magnetic properties of two- and three-dimensional molecule-based magnets (cat) +[M IIM III(C 2O 4) 3] -

NASA Astrophysics Data System (ADS)

Ovanesyan, Nikolai S.; Shilov, Gena V.; Pyalling, Alex A.; Train, Cyrille; Gredin, Patrick; Gruselle, Michel; Kiss, László F.; Bottyán, László

2004-05-01

We discuss the different structural arrangements of NBu 4[Fe IICr III(C 2O 4) 3] layered compounds in their racemic and enantiomeric forms and related magnetic properties. For [Mn IIFe III(C 2O 4) 3] networks of dimensionalities 2 and 3 Mössbauer spectroscopy was applied to study the Fe III sublattice magnetization. Unusual magnetic relaxation phenomena below TN were observed for both 2D and 3D networks.

Three-dimensional supramolecular architecture in imidazolium hydrogen 2,3,5,6-tetrafluoroterephthalate.

PubMed

Yu, Li-Li; Cheng, Mei-Ling; Liu, Qi; Zhang, Zhi-Hui; Chen, Qun

2010-04-01

The asymmetric unit of the title salt formed between 2,3,5,6-tetrafluoroterephthalic acid (H(2)tfbdc) and imidazolium (ImH), C(3)H(5)N(2)(+).C(8)HF(4)O(4)(-), contains one Htfbdc(-) anion and one ImH(2)(+) cation, joined by a classical N-H...O hydrogen bond. The acid and base subunits are further linked by N-H...O and O-H...O hydrogen bonds into infinite two-dimensional layers with R(6)(5)(32) hydrogen-bond motifs. The resulting (4,4) network layers interpenetrate to produce an interlocked three-dimensional structure. The final three-dimensional supramolecular architecture is further stabilized by the linkages of two C-H...O interactions.

Stimulus Sensitivity of a Spiking Neural Network Model

NASA Astrophysics Data System (ADS)

Chevallier, Julien

2018-02-01

Some recent papers relate the criticality of complex systems to their maximal capacity of information processing. In the present paper, we consider high dimensional point processes, known as age-dependent Hawkes processes, which have been used to model spiking neural networks. Using mean-field approximation, the response of the network to a stimulus is computed and we provide a notion of stimulus sensitivity. It appears that the maximal sensitivity is achieved in the sub-critical regime, yet almost critical for a range of biologically relevant parameters.

Validation of a three-dimensional viscous analysis of axisymmetric supersonic inlet flow fields

NASA Technical Reports Server (NTRS)

Benson, T. J.; Anderson, B. H.

1983-01-01

A three-dimensional viscous marching analysis for supersonic inlets was developed. To verify this analysis several benchmark axisymmetric test configurations were studied and are compared to experimental data. Detailed two-dimensional results for shock-boundary layer interactions are presented for flows with and without boundary layer bleed. Three dimensional calculations of a cone at angle of attack and a full inlet at attack are also discussed and evaluated. Results of the calculations demonstrate the code's ability to predict complex flow fields and establish guidelines for future calculations using similar codes.

Integrating Multimedia Instructional Design Principles with Complex Physiological Concepts in Reproductive Science

ERIC Educational Resources Information Center

Oki, Angela Christine

2011-01-01

This dissertation examines the effect of digital multimedia presentations as a method to teach complex concepts in reproductive physiology. The digital presentations developed for this research consisted of two-dimensional (2-D) and three-dimensional (3-D) animations, scriptmessaging and narration. The topics were "Mammalian Ovarian…

Web-Based Learning in the Computer-Aided Design Curriculum.

ERIC Educational Resources Information Center

Sung, Wen-Tsai; Ou, S. C.

2002-01-01

Applies principles of constructivism and virtual reality (VR) to computer-aided design (CAD) curriculum, particularly engineering, by integrating network, VR and CAD technologies into a Web-based learning environment that expands traditional two-dimensional computer graphics into a three-dimensional real-time simulation that enhances user…

Complex Chemical Reaction Networks from Heuristics-Aided Quantum Chemistry.

PubMed

Rappoport, Dmitrij; Galvin, Cooper J; Zubarev, Dmitry Yu; Aspuru-Guzik, Alán

2014-03-11

While structures and reactivities of many small molecules can be computed efficiently and accurately using quantum chemical methods, heuristic approaches remain essential for modeling complex structures and large-scale chemical systems. Here, we present a heuristics-aided quantum chemical methodology applicable to complex chemical reaction networks such as those arising in cell metabolism and prebiotic chemistry. Chemical heuristics offer an expedient way of traversing high-dimensional reactive potential energy surfaces and are combined here with quantum chemical structure optimizations, which yield the structures and energies of the reaction intermediates and products. Application of heuristics-aided quantum chemical methodology to the formose reaction reproduces the experimentally observed reaction products, major reaction pathways, and autocatalytic cycles.

Statistical Analysis of Big Data on Pharmacogenomics

PubMed Central

Fan, Jianqing; Liu, Han

2013-01-01

This paper discusses statistical methods for estimating complex correlation structure from large pharmacogenomic datasets. We selectively review several prominent statistical methods for estimating large covariance matrix for understanding correlation structure, inverse covariance matrix for network modeling, large-scale simultaneous tests for selecting significantly differently expressed genes and proteins and genetic markers for complex diseases, and high dimensional variable selection for identifying important molecules for understanding molecule mechanisms in pharmacogenomics. Their applications to gene network estimation and biomarker selection are used to illustrate the methodological power. Several new challenges of Big data analysis, including complex data distribution, missing data, measurement error, spurious correlation, endogeneity, and the need for robust statistical methods, are also discussed. PMID:23602905

Validating two-dimensional leadership models on three-dimensionally structured fish schools

PubMed Central

Nagy, Máté; Holbrook, Robert I.; Biro, Dora; Burt de Perera, Theresa

2017-01-01

Identifying leader–follower interactions is crucial for understanding how a group decides where or when to move, and how this information is transferred between members. Although many animal groups have a three-dimensional structure, previous studies investigating leader–follower interactions have often ignored vertical information. This raises the question of whether commonly used two-dimensional leader–follower analyses can be used justifiably on groups that interact in three dimensions. To address this, we quantified the individual movements of banded tetra fish (Astyanax mexicanus) within shoals by computing the three-dimensional trajectories of all individuals using a stereo-camera technique. We used these data firstly to identify and compare leader–follower interactions in two and three dimensions, and secondly to analyse leadership with respect to an individual's spatial position in three dimensions. We show that for 95% of all pairwise interactions leadership identified through two-dimensional analysis matches that identified through three-dimensional analysis, and we reveal that fish attend to the same shoalmates for vertical information as they do for horizontal information. Our results therefore highlight that three-dimensional analyses are not always required to identify leader–follower relationships in species that move freely in three dimensions. We discuss our results in terms of the importance of taking species' sensory capacities into account when studying interaction networks within groups. PMID:28280582

The Impact of Three-Dimensional Effects on the Simulation of Turbulence Kinetic Energy in a Major Alpine Valley

NASA Astrophysics Data System (ADS)

Goger, Brigitta; Rotach, Mathias W.; Gohm, Alexander; Fuhrer, Oliver; Stiperski, Ivana; Holtslag, Albert A. M.

2018-02-01

The correct simulation of the atmospheric boundary layer (ABL) is crucial for reliable weather forecasts in truly complex terrain. However, common assumptions for model parametrizations are only valid for horizontally homogeneous and flat terrain. Here, we evaluate the turbulence parametrization of the numerical weather prediction model COSMO with a horizontal grid spacing of Δ x = 1.1 km for the Inn Valley, Austria. The long-term, high-resolution turbulence measurements of the i-Box measurement sites provide a useful data pool of the ABL structure in the valley and on slopes. We focus on days and nights when ABL processes dominate and a thermally-driven circulation is present. Simulations are performed for case studies with both a one-dimensional turbulence parametrization, which only considers the vertical turbulent exchange, and a hybrid turbulence parametrization, also including horizontal shear production and advection in the budget of turbulence kinetic energy (TKE). We find a general underestimation of TKE by the model with the one-dimensional turbulence parametrization. In the simulations with the hybrid turbulence parametrization, the modelled TKE has a more realistic structure, especially in situations when the TKE production is dominated by shear related to the afternoon up-valley flow, and during nights, when a stable ABL is present. The model performance also improves for stations on the slopes. An estimation of the horizontal shear production from the observation network suggests that three-dimensional effects are a relevant part of TKE production in the valley.

The Impact of Three-Dimensional Effects on the Simulation of Turbulence Kinetic Energy in a Major Alpine Valley

NASA Astrophysics Data System (ADS)

Goger, Brigitta; Rotach, Mathias W.; Gohm, Alexander; Fuhrer, Oliver; Stiperski, Ivana; Holtslag, Albert A. M.

2018-07-01

The correct simulation of the atmospheric boundary layer (ABL) is crucial for reliable weather forecasts in truly complex terrain. However, common assumptions for model parametrizations are only valid for horizontally homogeneous and flat terrain. Here, we evaluate the turbulence parametrization of the numerical weather prediction model COSMO with a horizontal grid spacing of Δ x = 1.1 km for the Inn Valley, Austria. The long-term, high-resolution turbulence measurements of the i-Box measurement sites provide a useful data pool of the ABL structure in the valley and on slopes. We focus on days and nights when ABL processes dominate and a thermally-driven circulation is present. Simulations are performed for case studies with both a one-dimensional turbulence parametrization, which only considers the vertical turbulent exchange, and a hybrid turbulence parametrization, also including horizontal shear production and advection in the budget of turbulence kinetic energy (TKE). We find a general underestimation of TKE by the model with the one-dimensional turbulence parametrization. In the simulations with the hybrid turbulence parametrization, the modelled TKE has a more realistic structure, especially in situations when the TKE production is dominated by shear related to the afternoon up-valley flow, and during nights, when a stable ABL is present. The model performance also improves for stations on the slopes. An estimation of the horizontal shear production from the observation network suggests that three-dimensional effects are a relevant part of TKE production in the valley.

Human neural stem cell-derived cultures in three-dimensional substrates form spontaneously functional neuronal networks.

PubMed

Smith, Imogen; Silveirinha, Vasco; Stein, Jason L; de la Torre-Ubieta, Luis; Farrimond, Jonathan A; Williamson, Elizabeth M; Whalley, Benjamin J

2017-04-01

Differentiated human neural stem cells were cultured in an inert three-dimensional (3D) scaffold and, unlike two-dimensional (2D) but otherwise comparable monolayer cultures, formed spontaneously active, functional neuronal networks that responded reproducibly and predictably to conventional pharmacological treatments to reveal functional, glutamatergic synapses. Immunocytochemical and electron microscopy analysis revealed a neuronal and glial population, where markers of neuronal maturity were observed in the former. Oligonucleotide microarray analysis revealed substantial differences in gene expression conferred by culturing in a 3D vs a 2D environment. Notable and numerous differences were seen in genes coding for neuronal function, the extracellular matrix and cytoskeleton. In addition to producing functional networks, differentiated human neural stem cells grown in inert scaffolds offer several significant advantages over conventional 2D monolayers. These advantages include cost savings and improved physiological relevance, which make them better suited for use in the pharmacological and toxicological assays required for development of stem cell-based treatments and the reduction of animal use in medical research. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

A Three-Dimensional Finite-Element Model for Simulating Water Flow in Variably Saturated Porous Media

NASA Astrophysics Data System (ADS)

Huyakorn, Peter S.; Springer, Everett P.; Guvanasen, Varut; Wadsworth, Terry D.

1986-12-01

A three-dimensional finite-element model for simulating water flow in variably saturated porous media is presented. The model formulation is general and capable of accommodating complex boundary conditions associated with seepage faces and infiltration or evaporation on the soil surface. Included in this formulation is an improved Picard algorithm designed to cope with severely nonlinear soil moisture relations. The algorithm is formulated for both rectangular and triangular prism elements. The element matrices are evaluated using an "influence coefficient" technique that avoids costly numerical integration. Spatial discretization of a three-dimensional region is performed using a vertical slicing approach designed to accommodate complex geometry with irregular boundaries, layering, and/or lateral discontinuities. Matrix solution is achieved using a slice successive overrelaxation scheme that permits a fairly large number of nodal unknowns (on the order of several thousand) to be handled efficiently on small minicomputers. Six examples are presented to verify and demonstrate the utility of the proposed finite-element model. The first four examples concern one- and two-dimensional flow problems used as sample problems to benchmark the code. The remaining examples concern three-dimensional problems. These problems are used to illustrate the performance of the proposed algorithm in three-dimensional situations involving seepage faces and anisotropic soil media.

Data-Driven Modeling of Complex Systems by means of a Dynamical ANN

NASA Astrophysics Data System (ADS)

Seleznev, A.; Mukhin, D.; Gavrilov, A.; Loskutov, E.; Feigin, A.

2017-12-01

The data-driven methods for modeling and prognosis of complex dynamical systems become more and more popular in various fields due to growth of high-resolution data. We distinguish the two basic steps in such an approach: (i) determining the phase subspace of the system, or embedding, from available time series and (ii) constructing an evolution operator acting in this reduced subspace. In this work we suggest a novel approach combining these two steps by means of construction of an artificial neural network (ANN) with special topology. The proposed ANN-based model, on the one hand, projects the data onto a low-dimensional manifold, and, on the other hand, models a dynamical system on this manifold. Actually, this is a recurrent multilayer ANN which has internal dynamics and capable of generating time series. Very important point of the proposed methodology is the optimization of the model allowing us to avoid overfitting: we use Bayesian criterion to optimize the ANN structure and estimate both the degree of evolution operator nonlinearity and the complexity of nonlinear manifold which the data are projected on. The proposed modeling technique will be applied to the analysis of high-dimensional dynamical systems: Lorenz'96 model of atmospheric turbulence, producing high-dimensional space-time chaos, and quasi-geostrophic three-layer model of the Earth's atmosphere with the natural orography, describing the dynamics of synoptical vortexes as well as mesoscale blocking systems. The possibility of application of the proposed methodology to analyze real measured data is also discussed. The study was supported by the Russian Science Foundation (grant #16-12-10198).

Generating Neuron Geometries for Detailed Three-Dimensional Simulations Using AnaMorph.

PubMed

Mörschel, Konstantin; Breit, Markus; Queisser, Gillian

2017-07-01

Generating realistic and complex computational domains for numerical simulations is often a challenging task. In neuroscientific research, more and more one-dimensional morphology data is becoming publicly available through databases. This data, however, only contains point and diameter information not suitable for detailed three-dimensional simulations. In this paper, we present a novel framework, AnaMorph, that automatically generates water-tight surface meshes from one-dimensional point-diameter files. These surface triangulations can be used to simulate the electrical and biochemical behavior of the underlying cell. In addition to morphology generation, AnaMorph also performs quality control of the semi-automatically reconstructed cells coming from anatomical reconstructions. This toolset allows an extension from the classical dimension-reduced modeling and simulation of cellular processes to a full three-dimensional and morphology-including method, leading to novel structure-function interplay studies in the medical field. The developed numerical methods can further be employed in other areas where complex geometries are an essential component of numerical simulations.

Efficient implementation of a 3-dimensional ADI method on the iPSC/860

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

Van der Wijngaart, R.F.

1993-12-31

A comparison is made between several domain decomposition strategies for the solution of three-dimensional partial differential equations on a MIMD distributed memory parallel computer. The grids used are structured, and the numerical algorithm is ADI. Important implementation issues regarding load balancing, storage requirements, network latency, and overlap of computations and communications are discussed. Results of the solution of the three-dimensional heat equation on the Intel iPSC/860 are presented for the three most viable methods. It is found that the Bruno-Cappello decomposition delivers optimal computational speed through an almost complete elimination of processor idle time, while providing good memory efficiency.

Three-dimensional self-adaptive grid method for complex flows

NASA Technical Reports Server (NTRS)

Djomehri, M. Jahed; Deiwert, George S.

1988-01-01

A self-adaptive grid procedure for efficient computation of three-dimensional complex flow fields is described. The method is based on variational principles to minimize the energy of a spring system analogy which redistributes the grid points. Grid control parameters are determined by specifying maximum and minimum grid spacing. Multidirectional adaptation is achieved by splitting the procedure into a sequence of successive applications of a unidirectional adaptation. One-sided, two-directional constraints for orthogonality and smoothness are used to enhance the efficiency of the method. Feasibility of the scheme is demonstrated by application to a multinozzle, afterbody, plume flow field. Application of the algorithm for initial grid generation is illustrated by constructing a three-dimensional grid about a bump-like geometry.

Bounds on the number of hidden neurons in three-layer binary neural networks.

PubMed

Zhang, Zhaozhi; Ma, Xiaomin; Yang, Yixian

2003-09-01

This paper investigates an important problem concerning the complexity of three-layer binary neural networks (BNNs) with one hidden layer. The neuron in the studied BNNs employs a hard limiter activation function with only integer weights and an integer threshold. The studies are focused on implementations of arbitrary Boolean functions which map from [0, 1]n into [0, 1]. A deterministic algorithm called set covering algorithm (SCA) is proposed for the construction of a three-layer BNN to implement an arbitrary Boolean function. The SCA is based on a unit sphere covering (USC) of the Hamming space (HS) which is chosen in advance. It is proved that for the implementation of an arbitrary Boolean function of n-variables (n > or = 3) by using SCA, [3L/2] hidden neurons are necessary and sufficient, where L is the number of unit spheres contained in the chosen USC of the n-dimensional HS. It is shown that by using SCA, the number of hidden neurons required is much less than that by using a two-parallel hyperplane method. In order to indicate the potential ability of three-layer BNNs, a lower bound on the required number of hidden neurons which is derived by using the method of estimating the Vapnik-Chervonenkis (VC) dimension is also given.

A small-world network model of facial emotion recognition.

PubMed

Takehara, Takuma; Ochiai, Fumio; Suzuki, Naoto

2016-01-01

Various models have been proposed to increase understanding of the cognitive basis of facial emotions. Despite those efforts, interactions between facial emotions have received minimal attention. If collective behaviours relating to each facial emotion in the comprehensive cognitive system could be assumed, specific facial emotion relationship patterns might emerge. In this study, we demonstrate that the frameworks of complex networks can effectively capture those patterns. We generate 81 facial emotion images (6 prototypes and 75 morphs) and then ask participants to rate degrees of similarity in 3240 facial emotion pairs in a paired comparison task. A facial emotion network constructed on the basis of similarity clearly forms a small-world network, which features an extremely short average network distance and close connectivity. Further, even if two facial emotions have opposing valences, they are connected within only two steps. In addition, we show that intermediary morphs are crucial for maintaining full network integration, whereas prototypes are not at all important. These results suggest the existence of collective behaviours in the cognitive systems of facial emotions and also describe why people can efficiently recognize facial emotions in terms of information transmission and propagation. For comparison, we construct three simulated networks--one based on the categorical model, one based on the dimensional model, and one random network. The results reveal that small-world connectivity in facial emotion networks is apparently different from those networks, suggesting that a small-world network is the most suitable model for capturing the cognitive basis of facial emotions.

Binding Direction-Based Two-Dimensional Flattened Contact Area Computing Algorithm for Protein-Protein Interactions.

PubMed

Kang, Beom Sik; Pugalendhi, GaneshKumar; Kim, Ku-Jin

2017-10-13

Interactions between protein molecules are essential for the assembly, function, and regulation of proteins. The contact region between two protein molecules in a protein complex is usually complementary in shape for both molecules and the area of the contact region can be used to estimate the binding strength between two molecules. Although the area is a value calculated from the three-dimensional surface, it cannot represent the three-dimensional shape of the surface. Therefore, we propose an original concept of two-dimensional contact area which provides further information such as the ruggedness of the contact region. We present a novel algorithm for calculating the binding direction between two molecules in a protein complex, and then suggest a method to compute the two-dimensional flattened area of the contact region between two molecules based on the binding direction.

Comparative analysis of two discretizations of Ricci curvature for complex networks.

PubMed

Samal, Areejit; Sreejith, R P; Gu, Jiao; Liu, Shiping; Saucan, Emil; Jost, Jürgen

2018-06-05

We have performed an empirical comparison of two distinct notions of discrete Ricci curvature for graphs or networks, namely, the Forman-Ricci curvature and Ollivier-Ricci curvature. Importantly, these two discretizations of the Ricci curvature were developed based on different properties of the classical smooth notion, and thus, the two notions shed light on different aspects of network structure and behavior. Nevertheless, our extensive computational analysis in a wide range of both model and real-world networks shows that the two discretizations of Ricci curvature are highly correlated in many networks. Moreover, we show that if one considers the augmented Forman-Ricci curvature which also accounts for the two-dimensional simplicial complexes arising in graphs, the observed correlation between the two discretizations is even higher, especially, in real networks. Besides the potential theoretical implications of these observations, the close relationship between the two discretizations has practical implications whereby Forman-Ricci curvature can be employed in place of Ollivier-Ricci curvature for faster computation in larger real-world networks whenever coarse analysis suffices.

Three-dimensional electron diffraction of plant light-harvesting complex

PubMed Central

Wang, Da Neng; Kühlbrandt, Werner

1992-01-01

Electron diffraction patterns of two-dimensional crystals of light-harvesting chlorophyll a/b-protein complex (LHC-II) from photosynthetic membranes of pea chloroplasts, tilted at different angles up to 60°, were collected to 3.2 Å resolution at -125°C. The reflection intensities were merged into a three-dimensional data set. The Friedel R-factor and the merging R-factor were 21.8 and 27.6%, respectively. Specimen flatness and crystal size were critical for recording electron diffraction patterns from crystals at high tilts. The principal sources of experimental error were attributed to limitations of the number of unit cells contributing to an electron diffraction pattern, and to the critical electron dose. The distribution of strong diffraction spots indicated that the three-dimensional structure of LHC-II is less regular than that of other known membrane proteins and is not dominated by a particular feature of secondary structure. ImagesFIGURE 1FIGURE 2 PMID:19431817

Cholangiocytes and blood supply.

PubMed

Gaudio, Eugenio; Franchitto, Antonio; Pannarale, Luigi; Carpino, Guido; Alpini, Gianfranco; Francis, Heather; Glaser, Shannon; Alvaro, Domenico; Onori, Paolo

2006-06-14

The microvascular supply of the biliary tree, the peribiliary plexus (PBP), stems from the hepatic artery branches and flows into the hepatic sinusoids. A detailed three-dimensional study of the PBP has been performed by using the Scanning Electron Microscopy vascular corrosion casts (SEMvcc) technique. Considering that the PBP plays a fundamental role in supporting the secretory and absorptive functions of the biliary epithelium, their organization in either normalcy and pathology is explored. The normal liver shows the PBP arranged around extra- and intrahepatic biliary tree. In the small portal tract PBP was characterized by a single layer of capillaries which progressively continued with the extrahepatic PBP where it showed a more complex vascular network. After common duct ligation (BDL), progressive modifications of bile duct and PBP proliferation are observed. The PBP presents a three-dimensional network arranged around many bile ducts and appears as bundles of vessels, composed by capillaries of homogeneous diameter with a typical round mesh structure. The PBP network is easily distinguishable from the sinusoidal network which appears normal. Considering the enormous extension of the PBP during BDL, the possible role played by the Vascular Endothelial Growth Factor (VEGF) is evaluated. VEGF-A, VEGF-C and their related receptors appeared highly immunopositive in proliferating cholangiocytes of BDL rats. The administration of anti-VEGF-A or anti-VEGF-C antibodies to BDL rats as well as hepatic artery ligation induced a reduced bile duct mass. The administration of rVEGF-A to BDL hepatic artery ligated rats prevented the decrease of cholangiocyte proliferation and VEGF-A expression as compared to BDL control rats. These data suggest the role of arterial blood supply of the biliary tree in conditions of cholangiocyte proliferation, such as it occurs during chronic cholestasis. On the other hand, the role played by VEGF as a tool of cross-talk between cholangiocytes and PBP endothelial cells suggests that manipulation of VEGF release and function could represent a therapeutic strategy for human pathological conditions characterized by damage of hepatic artery or the biliary tree.

Photonic and phononic surface and edge modes in three-dimensional phoxonic crystals

NASA Astrophysics Data System (ADS)

Ma, Tian-Xue; Wang, Yue-Sheng; Zhang, Chuanzeng

2018-04-01

We investigate the photonic and phononic surface and edge modes in finite-size three-dimensional phoxonic crystals. By appropriately terminating the phoxonic crystals, the photons and phonons can be simultaneously guided at the two-dimensional surface and/or the one-dimensional edge of the terminated crystals. The Bloch surface and edge modes show that the electromagnetic and acoustic waves are highly localized near the surface and edge, respectively. The surface and edge geometries play important roles in tailoring the dispersion relations of the surface and edge modes, and dual band gaps for the surface or edge modes can be simultaneously achieved by changing the geometrical configurations. Furthermore, as the band gaps for the bulk modes are the essential prerequisites for the realization of dual surface and edge modes, the photonic and phononic bulk-mode band gap properties of three different types of phoxonic crystals with six-connected networks are revealed. It is found that the geometrical characteristic of the crystals with six-connected networks leads to dual large bulk-mode band gaps. Compared with the conventional bulk modes, the surface and edge modes provide a new approach for the photon and phonon manipulation and show great potential for phoxonic crystal devices and optomechanics.

Seismotectonics of the Loma Prieta, California, region determined from three-dimensional Vp, Vp/Vs, and seismicity

USGS Publications Warehouse

Eberhart-Phillips, D.; Michael, A.J.

1998-01-01

Three-dimensional Vp and Vp/Vs velocity models for the Loma Prieta region were developed from the inversion of local travel time data (21,925 P arrivals and 1,116 S arrivals) from earthquakes, refraction shots, and blasts recorded on 1700 stations from the Northern California Seismic Network and numerous portable seismograph deployments. The velocity and density models and microearthquake hypocenters reveal a complex structure that includes a San Andreas fault extending to the base of the seismogenic layer. A body with high Vp extends the length of the rupture and fills the 5 km wide volume between the Loma Prieta mainshock rupture and the San Andreas and Sargent faults. We suggest that this body controls both the pattern of background seismicity on the San Andreas and Sargent faults and the extent of rupture during the mainshock, thus explaining how the background seismicity outlined the along-strike and depth extent of the mainshock rupture on a different fault plane 5 km away. New aftershock focal mechanisms, based on three-dimensional ray tracing through the velocity model, support a heterogeneous postseismic stress field and can not resolve a uniform fault normal compression. The subvertical (or steeply dipping) San Andreas fault and the fault surfaces that ruptured in the 1989 Loma Prieta earthquake are both parts of the San Andreas fault zone and this section of the fault zone does not have a single type of characteristic event.

Some comparisons of complexity in dictionary-based and linear computational models.

PubMed

Gnecco, Giorgio; Kůrková, Věra; Sanguineti, Marcello

2011-03-01

Neural networks provide a more flexible approximation of functions than traditional linear regression. In the latter, one can only adjust the coefficients in linear combinations of fixed sets of functions, such as orthogonal polynomials or Hermite functions, while for neural networks, one may also adjust the parameters of the functions which are being combined. However, some useful properties of linear approximators (such as uniqueness, homogeneity, and continuity of best approximation operators) are not satisfied by neural networks. Moreover, optimization of parameters in neural networks becomes more difficult than in linear regression. Experimental results suggest that these drawbacks of neural networks are offset by substantially lower model complexity, allowing accuracy of approximation even in high-dimensional cases. We give some theoretical results comparing requirements on model complexity for two types of approximators, the traditional linear ones and so called variable-basis types, which include neural networks, radial, and kernel models. We compare upper bounds on worst-case errors in variable-basis approximation with lower bounds on such errors for any linear approximator. Using methods from nonlinear approximation and integral representations tailored to computational units, we describe some cases where neural networks outperform any linear approximator. Copyright © 2010 Elsevier Ltd. All rights reserved.

Three-dimensional imaging of redundant Chiari's network prolapsing into right ventricle.

PubMed

Betrián Blasco, Pedro; Sarrat Torres, Rebeca; Pijuan Domènech, Maria Antonia; Marimón Blanch, Cristina; Pérez Herrera, Verónica; Girona Comas, Josep

2008-02-01

An asymptomatic 1-month-old girl was studied in another institution because of the presence of a cardiac murmur, and referred to our center for further evaluation as a result of tricuspid valve abnormalities detected in the echocardiographic study. Echocardiography revealed a very redundant, thin, freely mobile structure in the right atrium, moving rapidly in (systole) and out (diastole) of the right ventricle through the tricuspid orifice. It arose from near the border of the inferior vena cava and attached to the atrial wall close to the coronary sinus ostium, suggesting an unusually prominent Chiari's network. Three-dimensional imaging allowed definition of the structure in all the planes and dimensions, and the relationship of the structure with right atrium and ventricle. Chiari's network is an embryonic remnant present in 2% to 3% of the population. The identification of a Chiari's network is important because the widely mobile structure within the right atrium can be confused with other entities, such as right heart vegetation, flail tricuspid leaflet, ruptured chordae tendinae, or a thrombus.

Three-Dimensional Superhydrophobic Nanowire Networks for Enhancing Condensation Heat Transfer

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

Yang, Ronggui; Wen, Rongfu; Xu, Shanshan

Spontaneous droplet jumping on nanostructured surfaces can potentially enhance condensation heat transfer by accelerating droplet removal. However, uncontrolled nucleation in the micro-defects of nanostructured superhydrophobic surfaces could lead to the formation of large pinned droplets, which greatly degrades the performance. Here, we experimentally demonstrate for the first time stable and efficient jumping droplet condensation on a superhydrophobic surface with three-dimensional (3D) copper nanowire networks. Due to the formation of interconnections among nanowires, the micro-defects are eliminated while the spacing between nanowires is reduced, which results in the formation of highly mobile droplets. By preventing flooding on 3D nanowire networks, wemore » experimentally demonstrate a 100% higher heat flux compared with that on the state-of-the-art hydrophobic surface over a wide range of subcooling (up to 28 K). The remarkable water repellency of 3D nanowire networks can be applied to a broad range of water-harvesting and phase-change heat transfer applications.« less

Computational Methods for Inviscid and Viscous Two-and-Three-Dimensional Flow Fields.

DTIC Science & Technology

1975-01-01

Difference Equations Over a Network, Watson Sei. Comput. Lab. Report, 19U9. 173- Isaacson, E. and Keller, H. B., Analaysis of Numerical Methods...element method has given a new impulse to the old mathematical theory of multivariate interpolation. We first study the one-dimensional case, which

Network analysis of the COSMOS galaxy field

NASA Astrophysics Data System (ADS)

de Regt, R.; Apunevych, S.; von Ferber, C.; Holovatch, Yu; Novosyadlyj, B.

2018-07-01

The galaxy data provided by COSMOS survey for 1°×1° field of sky are analysed by methods of complex networks. Three galaxy samples (slices) with redshifts ranging within intervals 0.88÷0.91, 0.91÷0.94, and 0.94÷0.97 are studied as two-dimensional projections for the spatial distributions of galaxies. We construct networks and calculate network measures for each sample, in order to analyse the network similarity of different samples, distinguish various topological environments, and find associations between galaxy properties (colour index and stellar mass) and their topological environments. Results indicate a high level of similarity between geometry and topology for different galaxy samples and no clear evidence of evolutionary trends in network measures. The distribution of local clustering coefficient C manifests three modes which allow for discrimination between stand-alone singlets and dumbbells (0 ≤ C ≤ 0.1), intermediately packed (0.1 < C < 0.9) and clique (0.9 ≤ C ≤ 1) like galaxies. Analysing astrophysical properties of galaxies (colour index and stellar masses), we show that distributions are similar in all slices, however weak evolutionary trends can also be seen across redshift slices. To specify different topological environments, we have extracted selections of galaxies from each sample according to different modes of C distribution. We have found statistically significant associations between evolutionary parameters of galaxies and selections of C: the distribution of stellar mass for galaxies with interim C differs from the corresponding distributions for stand-alone and clique galaxies, and this difference holds for all redshift slices. The colour index realizes somewhat different behaviour.

Network analysis of the COSMOS galaxy field

NASA Astrophysics Data System (ADS)

de Regt, R.; Apunevych, S.; Ferber, C. von; Holovatch, Yu; Novosyadlyj, B.

2018-03-01

The galaxy data provided by COSMOS survey for 1° × 1° field of sky are analysed by methods of complex networks. Three galaxy samples (slices) with redshifts ranging within intervals 0.88÷0.91, 0.91÷0.94 and 0.94÷0.97 are studied as two-dimensional projections for the spatial distributions of galaxies. We construct networks and calculate network measures for each sample, in order to analyse the network similarity of different samples, distinguish various topological environments, and find associations between galaxy properties (colour index and stellar mass) and their topological environments. Results indicate a high level of similarity between geometry and topology for different galaxy samples and no clear evidence of evolutionary trends in network measures. The distribution of local clustering coefficient C manifests three modes which allow for discrimination between stand-alone singlets and dumbbells (0 ≤ C ≤ 0.1), intermediately packed (0.1 < C < 0.9) and clique (0.9 ≤ C ≤ 1) like galaxies. Analysing astrophysical properties of galaxies (colour index and stellar masses), we show that distributions are similar in all slices, however weak evolutionary trends can also be seen across redshift slices. To specify different topological environments we have extracted selections of galaxies from each sample according to different modes of C distribution. We have found statistically significant associations between evolutionary parameters of galaxies and selections of C: the distribution of stellar mass for galaxies with interim C differ from the corresponding distributions for stand-alone and clique galaxies, and this difference holds for all redshift slices. The colour index realises somewhat different behaviour.

Unconstrained handwritten numeral recognition based on radial basis competitive and cooperative networks with spatio-temporal feature representation.

PubMed

Lee, S; Pan, J J

1996-01-01

This paper presents a new approach to representation and recognition of handwritten numerals. The approach first transforms a two-dimensional (2-D) spatial representation of a numeral into a three-dimensional (3-D) spatio-temporal representation by identifying the tracing sequence based on a set of heuristic rules acting as transformation operators. A multiresolution critical-point segmentation method is then proposed to extract local feature points, at varying degrees of scale and coarseness. A new neural network architecture, referred to as radial-basis competitive and cooperative network (RCCN), is presented especially for handwritten numeral recognition. RCCN is a globally competitive and locally cooperative network with the capability of self-organizing hidden units to progressively achieve desired network performance, and functions as a universal approximator of arbitrary input-output mappings. Three types of RCCNs are explored: input-space RCCN (IRCCN), output-space RCCN (ORCCN), and bidirectional RCCN (BRCCN). Experiments against handwritten zip code numerals acquired by the U.S. Postal Service indicated that the proposed method is robust in terms of variations, deformations, transformations, and corruption, achieving about 97% recognition rate.

Three-dimensional inversion for Network-Magnetotelluric data

NASA Astrophysics Data System (ADS)

Siripunvaraporn, W.; Uyeshima, M.; Egbert, G.

2004-09-01

Three-dimensional inversion of Network-Magnetotelluric (MT) data has been implemented. The program is based on a conventional 3-D MT inversion code (Siripunvaraporn et al., 2004), which is a data space variant of the OCCAM approach. In addition to modifications required for computing Network-MT responses and sensitivities, the program makes use of Massage Passing Interface (MPI) software, with allowing computations for each period to be run on separate CPU nodes. Here, we consider inversion of synthetic data generated from simple models consisting of a 1 W-m conductive block buried at varying depths in a 100 W-m background. We focus in particular on inversion of long period (320-40,960 seconds) data, because Network-MT data usually have high coherency in these period ranges. Even with only long period data the inversion recovers shallow and deep structures, as long as these are large enough to affect the data significantly. However, resolution of the inversion depends greatly on the geometry of the dipole network, the range of periods used, and the horizontal size of the conductive anomaly.

Unique thylakoid membrane architecture of a unicellular N2-fixing cyanobacterium revealed by electron tomography.

PubMed

Liberton, Michelle; Austin, Jotham R; Berg, R Howard; Pakrasi, Himadri B

2011-04-01

Cyanobacteria, descendants of the endosymbiont that gave rise to modern-day chloroplasts, are vital contributors to global biological energy conversion processes. A thorough understanding of the physiology of cyanobacteria requires detailed knowledge of these organisms at the level of cellular architecture and organization. In these prokaryotes, the large membrane protein complexes of the photosynthetic and respiratory electron transport chains function in the intracellular thylakoid membranes. Like plants, the architecture of the thylakoid membranes in cyanobacteria has direct impact on cellular bioenergetics, protein transport, and molecular trafficking. However, whole-cell thylakoid organization in cyanobacteria is not well understood. Here we present, by using electron tomography, an in-depth analysis of the architecture of the thylakoid membranes in a unicellular cyanobacterium, Cyanothece sp. ATCC 51142. Based on the results of three-dimensional tomographic reconstructions of near-entire cells, we determined that the thylakoids in Cyanothece 51142 form a dense and complex network that extends throughout the entire cell. This thylakoid membrane network is formed from the branching and splitting of membranes and encloses a single lumenal space. The entire thylakoid network spirals as a peripheral ring of membranes around the cell, an organization that has not previously been described in a cyanobacterium. Within the thylakoid membrane network are areas of quasi-helical arrangement with similarities to the thylakoid membrane system in chloroplasts. This cyanobacterial thylakoid arrangement is an efficient means of packing a large volume of membranes in the cell while optimizing intracellular transport and trafficking.

Flow Interactions of Two- and Three-Dimensional Networked Bio-Inspired Control Elements in an In-Line Arrangement.

PubMed

Kurt, Melike; Moored, Keith

2018-04-19

We present experiments that examine the modes of interaction, the collective performance and the role of three-dimensionality in two pitching propulsors in an in-line arrangement. Both two-dimensional foils and three-dimensional rectangular wings of $AR = 2$ are examined. \\kwm{In contrast to previous work, two interaction modes distinguished as the coherent and branched wake modes are not observed to be directly linked to the propulsive efficiency, although they are linked to peak thrust performance and minimum power consumption as previously described \\cite[]{boschitsch2014propulsive}.} \\kwm{In fact, in closely-spaced propulsors peak propulsive efficiency of the follower occurs near its minimum power and this condition \\kwm{ reveals a} branched wake mode. Alternatively, for propulsors spaced far apart peak propulsive efficiency of the follower occurs near its peak thrust and this condition \\kwm{reveals a} coherent wake mode.} By examining the collective performance, it is discovered that there is an optimal spacing between the propulsors to maximize the collective efficiency. For two-dimensional foils the optimal spacing of $X^* = 0.75$ and the synchrony of $\\phi = 2\\pi /3$ leads to a collective efficiency and thrust enhancement of 50\\% and 32\\%, respectively, as compared to two isolated foils. In comparison, for $AR = 2$ wings the optimal spacing of $X^* = 0.25$ and the synchrony of $\\phi = 7\\pi /6$ leads to a collective efficiency and thrust enhancement of 30\\% and 22\\%, respectively. In addition, at the optimal conditions the collective lateral force coefficients in both the two- and three-dimensional cases are negligible, while operating off these conditions can lead to non-negligible lateral forces. Finally, the peak efficiency of the collective and the follower are shown to have opposite trends with increasing spacing in two- and three-dimensional flows. This is correlated to the breakdown of the impinging vortex on the follower wing in three-dimensions. These results can aid in the design of networked bio-inspired control elements that through integrated sensing can synchronize to three-dimensional flow interactions. © 2018 IOP Publishing Ltd.

Supramolecular metallogels with complex of phosphonate substituted carbazole derivative and aluminum(III) ion as gelator.

PubMed

Ding, Zicheng; Chen, Bo; Ding, Junqiao; Wang, Lixiang; Han, Yanchun

2014-07-01

Supramolecular metallogels can be gained from the phosphonate substituted 4,4'-bis(N-carbazolyl)biphenyl (PCBP) in the presence of aluminum chloride in alcohols, which can donate oxygen to aid proton transfer in the aluminum organophosphorus complexes. Inside the metallogels, three-dimensional fiber networks with nanofibers entangling and intersecting with each other inside are formed. The nanofibers show layered structures with a period thickness of 0.82 nm. As the content of aluminum(III) increases, the size of the fibers becomes smaller and the fibers pack more densely. It makes the transparent gel become turbid but nevertheless improves the stability of the metallogels. NMR, FT-IR and fluorescence spectroscopy show that the coordination interactions between the phosphonate groups of PCBP molecules and aluminum(III) ions as well as the π-π interactions among PCBP molecules are involved during the gel formation process. Copyright © 2014 Elsevier Inc. All rights reserved.

Self-penetration--a structural compromise between single networks and interpenetration: magnetic properties and crystal structures of

PubMed

Jensen; Price; Batten; Moubaraki; Murray

2000-09-01

The three-dimensional coordination polymers [Mn(dca)2(H2O)] (1) and [M(dca)(tcm)], M =Co (2), Ni (3), Cu (4), dca =dicyanamide, N(CN)2-, tcm = tricyanomethanide, C(CN)3-, have isomorphous structures. In 1 half the dca ligands coordinate directly (through all three nitrogen atoms) to three Mn atoms (all metal atoms are six-coordinate), while the other half coordinate to two Mn atoms (through the nitrile nitrogens) and hydrogen bond to water molecules coordinated to a third Mn atom (through the amide nitrogen). This dca. H2O structural moiety is disordered over a mirror plane, and is replaced by the structurally equivalent tcm ligand in compounds 2-4. The resulting structures display a new self-penetrating 3,6-connected (2:1) network topology that can be related to, but is different from, the rutile net. The self-penetrating [M(dca)(tcm)] network can be viewed as a structural compromise between the two interpenetrating rutile-like networks of [M(tcm)2] and the single rutile-like network of alpha-[M(dca)2]. The temperature and field dependence of the DC and AC magnetic susceptibilities and magnetisations has been measured for complexes 1-4. Compounds 1-3 exhibit long-range magnetic order with critical temperatures of 6.3 K for 1, 3.5 K for 2 and 8.0 K for 3. The Cu11 compound 4 does not order and is essentially a paramagnet. Hysteresis measurements of coercive field and remnant magnetisation show that 1, 2 and 3 are soft magnets, 1 being a canted-spin antiferromagnet (weak ferromagnet), while 2 and 3 are ferromagnets that display some unusual features in their high-field magnetisation isotherms in comparison to their related alpha-[M(dca)2] phases.

Modeling the poroelastic response to megathrust earthquakes: A look at the 2012 Mw 7.6 Costa Rican event

NASA Astrophysics Data System (ADS)

McCormack, Kimberly A.; Hesse, Marc A.

2018-04-01

We model the subsurface hydrologic response to the 7.6 Mw subduction zone earthquake that occurred on the plate interface beneath the Nicoya peninsula in Costa Rica on September 5, 2012. The regional-scale poroelastic model of the overlying plate integrates seismologic, geodetic and hydrologic data sets to predict the post-seismic poroelastic response. A representative two-dimensional model shows that thrust earthquakes with a slip width less than a third of their depth produce complex multi-lobed pressure perturbations in the shallow subsurface. This leads to multiple poroelastic relaxation timescales that may overlap with the longer viscoelastic timescales. In the three-dimensional model, the complex slip distribution of 2012 Nicoya event and its small width to depth ratio lead to a pore pressure distribution comprising multiple trench parallel ridges of high and low pressure. This leads to complex groundwater flow patterns, non-monotonic variations in predicted well water levels, and poroelastic relaxation on multiple time scales. The model also predicts significant tectonically driven submarine groundwater discharge off-shore. In the weeks following the earthquake, the predicted net submarine groundwater discharge in the study area increases, creating a 100 fold increase in net discharge relative to topography-driven flow over the first 30 days. Our model suggests the hydrological response on land is more complex than typically acknowledged in tectonic studies. This may complicate the interpretation of transient post-seismic surface deformations. Combined tectonic-hydrological observation networks have the potential to reduce such ambiguities.

Quantum networks in divergence-free circuit QED

NASA Astrophysics Data System (ADS)

Parra-Rodriguez, A.; Rico, E.; Solano, E.; Egusquiza, I. L.

2018-04-01

Superconducting circuits are one of the leading quantum platforms for quantum technologies. With growing system complexity, it is of crucial importance to develop scalable circuit models that contain the minimum information required to predict the behaviour of the physical system. Based on microwave engineering methods, divergent and non-divergent Hamiltonian models in circuit quantum electrodynamics have been proposed to explain the dynamics of superconducting quantum networks coupled to infinite-dimensional systems, such as transmission lines and general impedance environments. Here, we study systematically common linear coupling configurations between networks and infinite-dimensional systems. The main result is that the simple Lagrangian models for these configurations present an intrinsic natural length that provides a natural ultraviolet cutoff. This length is due to the unavoidable dressing of the environment modes by the network. In this manner, the coupling parameters between their components correctly manifest their natural decoupling at high frequencies. Furthermore, we show the requirements to correctly separate infinite-dimensional coupled systems in local bases. We also compare our analytical results with other analytical and approximate methods available in the literature. Finally, we propose several applications of these general methods to analogue quantum simulation of multi-spin-boson models in non-perturbative coupling regimes.

Charge transport in the electrospun nanofiber composite membrane's three-dimensional fibrous structure

NASA Astrophysics Data System (ADS)

DeGostin, Matthew B.; Peracchio, Aldo A.; Myles, Timothy D.; Cassenti, Brice N.; Chiu, Wilson K. S.

2016-03-01

In this paper, a Fiber Network (FN) ion transport model is developed to simulate the three-dimensional fibrous microstructural morphology that results from the electrospinning membrane fabrication process. This model is able to approximate fiber layering within a membrane as well as membrane swelling due to water uptake. The discrete random fiber networks representing membranes are converted to resistor networks and solved for current flow and ionic conductivity. Model predictions are validated by comparison with experimental conductivity data from electrospun anion exchange membranes (AEM) and proton exchange membranes (PEM) for fuel cells as well as existing theories. The model is capable of predicting in-plane and thru-plane conductivity and takes into account detailed membrane characteristics, such as volume fraction, fiber diameter, fiber conductivity, and membrane layering, and as such may be used as a tool for advanced electrode design.

From Laser Scanning to Finite Element Analysis of Complex Buildings by Using a Semi-Automatic Procedure

PubMed Central

Castellazzi, Giovanni; D’Altri, Antonio Maria; Bitelli, Gabriele; Selvaggi, Ilenia; Lambertini, Alessandro

2015-01-01

In this paper, a new semi-automatic procedure to transform three-dimensional point clouds of complex objects to three-dimensional finite element models is presented and validated. The procedure conceives of the point cloud as a stacking of point sections. The complexity of the clouds is arbitrary, since the procedure is designed for terrestrial laser scanner surveys applied to buildings with irregular geometry, such as historical buildings. The procedure aims at solving the problems connected to the generation of finite element models of these complex structures by constructing a fine discretized geometry with a reduced amount of time and ready to be used with structural analysis. If the starting clouds represent the inner and outer surfaces of the structure, the resulting finite element model will accurately capture the whole three-dimensional structure, producing a complex solid made by voxel elements. A comparison analysis with a CAD-based model is carried out on a historical building damaged by a seismic event. The results indicate that the proposed procedure is effective and obtains comparable models in a shorter time, with an increased level of automation. PMID:26225978

Controlled molecular self-assembly of complex three-dimensional structures in soft materials.

PubMed

Huang, Changjin; Quinn, David; Suresh, Subra; Hsia, K Jimmy

2018-01-02

Many applications in tissue engineering, flexible electronics, and soft robotics call for approaches that are capable of producing complex 3D architectures in soft materials. Here we present a method using molecular self-assembly to generate hydrogel-based 3D architectures that resembles the appealing features of the bottom-up process in morphogenesis of living tissues. Our strategy effectively utilizes the three essential components dictating living tissue morphogenesis to produce complex 3D architectures: modulation of local chemistry, material transport, and mechanics, which can be engineered by controlling the local distribution of polymerization inhibitor (i.e., oxygen), diffusion of monomers/cross-linkers through the porous structures of cross-linked polymer network, and mechanical constraints, respectively. We show that oxygen plays a role in hydrogel polymerization which is mechanistically similar to the role of growth factors in tissue growth, and the continued growth of hydrogel enabled by diffusion of monomers/cross-linkers into the porous hydrogel similar to the mechanisms of tissue growth enabled by material transport. The capability and versatility of our strategy are demonstrated through biomimetics of tissue morphogenesis for both plants and animals, and its application to generate other complex 3D architectures. Our technique opens avenues to studying many growth phenomena found in nature and generating complex 3D structures to benefit diverse applications. Copyright © 2017 the Author(s). Published by PNAS.

Petri net modeling of high-order genetic systems using grammatical evolution.

PubMed

Moore, Jason H; Hahn, Lance W

2003-11-01

Understanding how DNA sequence variations impact human health through a hierarchy of biochemical and physiological systems is expected to improve the diagnosis, prevention, and treatment of common, complex human diseases. We have previously developed a hierarchical dynamic systems approach based on Petri nets for generating biochemical network models that are consistent with genetic models of disease susceptibility. This modeling approach uses an evolutionary computation approach called grammatical evolution as a search strategy for optimal Petri net models. We have previously demonstrated that this approach routinely identifies biochemical network models that are consistent with a variety of genetic models in which disease susceptibility is determined by nonlinear interactions between two DNA sequence variations. In the present study, we evaluate whether the Petri net approach is capable of identifying biochemical networks that are consistent with disease susceptibility due to higher order nonlinear interactions between three DNA sequence variations. The results indicate that our model-building approach is capable of routinely identifying good, but not perfect, Petri net models. Ideas for improving the algorithm for this high-dimensional problem are presented.

In silico analysis of the three-dimensional structures of the homodimer of uridine phosphorylase from Yersinia Pseudotuberculosis in the ligand-free state and in a complex with 5-fluorouracil

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

Lashkov, A. A., E-mail: alashkov83@gmail.com; Sotnichenko, S. E.; Mikhailov, A. M.

2013-03-15

Pseudotuberculosis is an acute infectious disease characterized by a lesion of the gastrointestinal tract. A positive therapeutic effect can be achieved by selectively suppressing the activity of uridine phosphorylase from the causative agent of the disease Yersinia pseudotuberculosis. The synergistic effect of a combination of the chemotherapeutic agent 5-fluorouracil and antimicrobial drugs, which block the synthesis of pyrimidine bases, on the cells of pathogenic protozoa and bacteria is described in the literature. The three-dimensional structures of uridine phosphorylase from Yersinia pseudotuberculosis (YptUPh) both in the ligand-free state and in complexes with pharmacological agents are unknown, which hinders the search formore » and design of selective inhibitors of YptUPh. The three-dimensional structure of the ligand-free homodimer of YptUPh was determined by homology-based molecular modeling. The three-dimensional structure of the subunit of the YptUPh molecule belongs to {alpha}/{beta} proteins, and its topology is a three-layer {alpha}/{beta}/{alpha} sandwich. The subunit monomer of the YptUPh molecule consists of 38% helices and 24% {beta} strands. A model of the homodimer structure of YptUPh in a complex with 5-FU was obtained by the molecular docking. The position of 5-FU in the active site of the molecule is very consistent with the known data on the X-ray diffraction structures of other bacterial uridine phosphorylases (the complex of uridine phosphorylase from Salmonella typhimurium (StUPh) with 5-FU, ID PDB: 4E1V and the complex of uridine phosphorylase from Escherichia coli (EcUPh) with 5-FU and ribose 1-phosphate, ID PDB: 1RXC).« less

In silico analysis of the three-dimensional structures of the homodimer of uridine phosphorylase from Yersinia Pseudotuberculosis in the ligand-free state and in a complex with 5-fluorouracil

NASA Astrophysics Data System (ADS)

Lashkov, A. A.; Sotnichenko, S. E.; Mikhailov, A. M.

2013-03-01

Pseudotuberculosis is an acute infectious disease characterized by a lesion of the gastrointestinal tract. A positive therapeutic effect can be achieved by selectively suppressing the activity of uridine phosphorylase from the causative agent of the disease Yersinia pseudotuberculosis. The synergistic effect of a combination of the chemotherapeutic agent 5-fluorouracil and antimicrobial drugs, which block the synthesis of pyrimidine bases, on the cells of pathogenic protozoa and bacteria is described in the literature. The three-dimensional structures of uridine phosphorylase from Yersinia pseudotuberculosis ( YptUPh) both in the ligand-free state and in complexes with pharmacological agents are unknown, which hinders the search for and design of selective inhibitors of YptUPh. The three-dimensional structure of the ligand-free homodimer of YptUPh was determined by homology-based molecular modeling. The three-dimensional structure of the subunit of the YptUPh molecule belongs to α/β proteins, and its topology is a three-layer α/β/α sandwich. The subunit monomer of the YptUPh molecule consists of 38% helices and 24% β strands. A model of the homodimer structure of YptUPh in a complex with 5-FU was obtained by the molecular docking. The position of 5-FU in the active site of the molecule is very consistent with the known data on the X-ray diffraction structures of other bacterial uridine phosphorylases (the complex of uridine phosphorylase from Salmonella typhimurium ( StUPh) with 5-FU, ID PDB: 4E1V and the complex of uridine phosphorylase from Escherichia coli ( EcUPh) with 5-FU and ribose 1-phosphate, ID PDB: 1RXC).

Micro-CT scan reveals an unexpected high-volume and interconnected pore network in a Cretaceous Sanagasta dinosaur eggshell.

PubMed

Hechenleitner, E Martín; Grellet-Tinner, Gerald; Foley, Matthew; Fiorelli, Lucas E; Thompson, Michael B

2016-03-01

The Cretaceous Sanagasta neosauropod nesting site (La Rioja, Argentina) was the first confirmed instance of extinct dinosaurs using geothermal-generated heat to incubate their eggs. The nesting strategy and hydrothermal activities at this site led to the conclusion that the surprisingly 7 mm thick-shelled eggs were adapted to harsh hydrothermal microenvironments. We used micro-CT scans in this study to obtain the first three-dimensional microcharacterization of these eggshells. Micro-CT-based analyses provide a robust assessment of gas conductance in fossil dinosaur eggshells with complex pore canal systems, allowing calculation, for the first time, of the shell conductance through its thickness. This novel approach suggests that the shell conductance could have risen during incubation to seven times more than previously estimated as the eggshell erodes. In addition, micro-CT observations reveal that the constant widening and branching of pore canals form a complex funnel-like pore canal system. Furthermore, the high density of pore canals and the presence of a lateral canal network in the shell reduce the risks of pore obstruction during the extended incubation of these eggs in a relatively highly humid and muddy nesting environment. © 2016 The Author(s).

Network Modeling Reveals Prevalent Negative Regulatory Relationships between Signaling Sectors in Arabidopsis Immune Signaling

PubMed Central

Sato, Masanao; Tsuda, Kenichi; Wang, Lin; Coller, John; Watanabe, Yuichiro; Glazebrook, Jane; Katagiri, Fumiaki

2010-01-01

Biological signaling processes may be mediated by complex networks in which network components and network sectors interact with each other in complex ways. Studies of complex networks benefit from approaches in which the roles of individual components are considered in the context of the network. The plant immune signaling network, which controls inducible responses to pathogen attack, is such a complex network. We studied the Arabidopsis immune signaling network upon challenge with a strain of the bacterial pathogen Pseudomonas syringae expressing the effector protein AvrRpt2 (Pto DC3000 AvrRpt2). This bacterial strain feeds multiple inputs into the signaling network, allowing many parts of the network to be activated at once. mRNA profiles for 571 immune response genes of 22 Arabidopsis immunity mutants and wild type were collected 6 hours after inoculation with Pto DC3000 AvrRpt2. The mRNA profiles were analyzed as detailed descriptions of changes in the network state resulting from the genetic perturbations. Regulatory relationships among the genes corresponding to the mutations were inferred by recursively applying a non-linear dimensionality reduction procedure to the mRNA profile data. The resulting static network model accurately predicted 23 of 25 regulatory relationships reported in the literature, suggesting that predictions of novel regulatory relationships are also accurate. The network model revealed two striking features: (i) the components of the network are highly interconnected; and (ii) negative regulatory relationships are common between signaling sectors. Complex regulatory relationships, including a novel negative regulatory relationship between the early microbe-associated molecular pattern-triggered signaling sectors and the salicylic acid sector, were further validated. We propose that prevalent negative regulatory relationships among the signaling sectors make the plant immune signaling network a “sector-switching” network, which effectively balances two apparently conflicting demands, robustness against pathogenic perturbations and moderation of negative impacts of immune responses on plant fitness. PMID:20661428

Inversion using a new low-dimensional representation of complex binary geological media based on a deep neural network

NASA Astrophysics Data System (ADS)

Laloy, Eric; Hérault, Romain; Lee, John; Jacques, Diederik; Linde, Niklas

2017-12-01

Efficient and high-fidelity prior sampling and inversion for complex geological media is still a largely unsolved challenge. Here, we use a deep neural network of the variational autoencoder type to construct a parametric low-dimensional base model parameterization of complex binary geological media. For inversion purposes, it has the attractive feature that random draws from an uncorrelated standard normal distribution yield model realizations with spatial characteristics that are in agreement with the training set. In comparison with the most commonly used parametric representations in probabilistic inversion, we find that our dimensionality reduction (DR) approach outperforms principle component analysis (PCA), optimization-PCA (OPCA) and discrete cosine transform (DCT) DR techniques for unconditional geostatistical simulation of a channelized prior model. For the considered examples, important compression ratios (200-500) are achieved. Given that the construction of our parameterization requires a training set of several tens of thousands of prior model realizations, our DR approach is more suited for probabilistic (or deterministic) inversion than for unconditional (or point-conditioned) geostatistical simulation. Probabilistic inversions of 2D steady-state and 3D transient hydraulic tomography data are used to demonstrate the DR-based inversion. For the 2D case study, the performance is superior compared to current state-of-the-art multiple-point statistics inversion by sequential geostatistical resampling (SGR). Inversion results for the 3D application are also encouraging.

Farley Three-Dimensional-Braiding Machine

NASA Technical Reports Server (NTRS)

Farley, Gary L.

1991-01-01

Process and device known as Farley three-dimensional-braiding machine conceived to fabricate dry continuous fiber-reinforced preforms of complex three-dimensional shapes for subsequent processing into composite structures. Robotic fiber supply dispenses yarn as it traverses braiding surface. Combines many attributes of weaving and braiding processes with other attributes and capabilities. Other applications include decorative cloths, rugs, and other domestic textiles. Concept could lead to large variety of fiber layups and to entirely new products as well as new fiber-reinforcing applications.

Statistical significance of the rich-club phenomenon in complex networks

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Zhou, Wei-Xing

2008-04-01

We propose that the rich-club phenomenon in complex networks should be defined in the spirit of bootstrapping, in which a null model is adopted to assess the statistical significance of the rich-club detected. Our method can serve as a definition of the rich-club phenomenon and is applied to analyze three real networks and three model networks. The results show significant improvement compared with previously reported results. We report a dilemma with an exceptional example, showing that there does not exist an omnipotent definition for the rich-club phenomenon.

Epitaxy of advanced nanowire quantum devices

NASA Astrophysics Data System (ADS)

Gazibegovic, Sasa; Car, Diana; Zhang, Hao; Balk, Stijn C.; Logan, John A.; de Moor, Michiel W. A.; Cassidy, Maja C.; Schmits, Rudi; Xu, Di; Wang, Guanzhong; Krogstrup, Peter; Op Het Veld, Roy L. M.; Zuo, Kun; Vos, Yoram; Shen, Jie; Bouman, Daniël; Shojaei, Borzoyeh; Pennachio, Daniel; Lee, Joon Sue; van Veldhoven, Petrus J.; Koelling, Sebastian; Verheijen, Marcel A.; Kouwenhoven, Leo P.; Palmstrøm, Chris J.; Bakkers, Erik P. A. M.

2017-08-01

Semiconductor nanowires are ideal for realizing various low-dimensional quantum devices. In particular, topological phases of matter hosting non-Abelian quasiparticles (such as anyons) can emerge when a semiconductor nanowire with strong spin-orbit coupling is brought into contact with a superconductor. To exploit the potential of non-Abelian anyons—which are key elements of topological quantum computing—fully, they need to be exchanged in a well-controlled braiding operation. Essential hardware for braiding is a network of crystalline nanowires coupled to superconducting islands. Here we demonstrate a technique for generic bottom-up synthesis of complex quantum devices with a special focus on nanowire networks with a predefined number of superconducting islands. Structural analysis confirms the high crystalline quality of the nanowire junctions, as well as an epitaxial superconductor-semiconductor interface. Quantum transport measurements of nanowire ‘hashtags’ reveal Aharonov-Bohm and weak-antilocalization effects, indicating a phase-coherent system with strong spin-orbit coupling. In addition, a proximity-induced hard superconducting gap (with vanishing sub-gap conductance) is demonstrated in these hybrid superconductor-semiconductor nanowires, highlighting the successful materials development necessary for a first braiding experiment. Our approach opens up new avenues for the realization of epitaxial three-dimensional quantum architectures which have the potential to become key components of various quantum devices.

A computational model of oxygen delivery by hemoglobin-based oxygen carriers in three-dimensional microvascular networks.

PubMed

Tsoukias, Nikolaos M; Goldman, Daniel; Vadapalli, Arjun; Pittman, Roland N; Popel, Aleksander S

2007-10-21

A detailed computational model is developed to simulate oxygen transport from a three-dimensional (3D) microvascular network to the surrounding tissue in the presence of hemoglobin-based oxygen carriers. The model accounts for nonlinear O(2) consumption, myoglobin-facilitated diffusion and nonlinear oxyhemoglobin dissociation in the RBCs and plasma. It also includes a detailed description of intravascular resistance to O(2) transport and is capable of incorporating realistic 3D microvascular network geometries. Simulations in this study were performed using a computer-generated microvascular architecture that mimics morphometric parameters for the hamster cheek pouch retractor muscle. Theoretical results are presented next to corresponding experimental data. Phosphorescence quenching microscopy provided PO(2) measurements at the arteriolar and venular ends of capillaries in the hamster retractor muscle before and after isovolemic hemodilution with three different hemodilutents: a non-oxygen-carrying plasma expander and two hemoglobin solutions with different oxygen affinities. Sample results in a microvascular network show an enhancement of diffusive shunting between arterioles, venules and capillaries and a decrease in hemoglobin's effectiveness for tissue oxygenation when its affinity for O(2) is decreased. Model simulations suggest that microvascular network anatomy can affect the optimal hemoglobin affinity for reducing tissue hypoxia. O(2) transport simulations in realistic representations of microvascular networks should provide a theoretical framework for choosing optimal parameter values in the development of hemoglobin-based blood substitutes.

Minimal perceptrons for memorizing complex patterns

NASA Astrophysics Data System (ADS)

Pastor, Marissa; Song, Juyong; Hoang, Danh-Tai; Jo, Junghyo

2016-11-01

Feedforward neural networks have been investigated to understand learning and memory, as well as applied to numerous practical problems in pattern classification. It is a rule of thumb that more complex tasks require larger networks. However, the design of optimal network architectures for specific tasks is still an unsolved fundamental problem. In this study, we consider three-layered neural networks for memorizing binary patterns. We developed a new complexity measure of binary patterns, and estimated the minimal network size for memorizing them as a function of their complexity. We formulated the minimal network size for regular, random, and complex patterns. In particular, the minimal size for complex patterns, which are neither ordered nor disordered, was predicted by measuring their Hamming distances from known ordered patterns. Our predictions agree with simulations based on the back-propagation algorithm.

Developments in the simulation of compressible inviscid and viscous flow on supercomputers

NASA Technical Reports Server (NTRS)

Steger, J. L.; Buning, P. G.

1985-01-01

In anticipation of future supercomputers, finite difference codes are rapidly being extended to simulate three-dimensional compressible flow about complex configurations. Some of these developments are reviewed. The importance of computational flow visualization and diagnostic methods to three-dimensional flow simulation is also briefly discussed.

Keratitis-associated fungi form biofilms with reduced antifungal drug susceptibility.

PubMed

Zhang, Xiaoyan; Sun, Xuguang; Wang, Zhiqun; Zhang, Yang; Hou, Wenbo

2012-11-21

To investigate the biofilm-forming capacity of Fusarium solani, Cladosporium sphaerospermum, and Acremonium implicatum, and the activities of antifungal agents against the three keratitis-associated fungi. The architecture of biofilms was analyzed using scanning electron microscopy and confocal scanning laser microscopy (CSLM). Susceptibility against six antifungal drugs was measured using the CLSI M38-A method and XTT reduction assay. Time course analyses of CSLM revealed that biofilm formation occurred in an organized fashion through four distinct developmental phases: adhesion, germling formation, microcolony formation, and biofilm maturation. Scanning electron microscopy revealed that mature biofilms displayed a complex three-dimensional structure, consisting of coordinated network of hyphal structures glued by the extracellular matrix (ECM). The antifungal susceptibility testing demonstrated a time-dependent decrease in efficacy for all six antifungal agents as the complexity of fungal hyphal structures developed. Natamycin (NAT), amphotericin B (AMB), and NAT were the most effective against F. solani, C. sphaerospermum, and A. implicatum biofilm, respectively. Corneal isolates of F. solani, C. sphaerospermum, and A. implicatum could produce biofilms that were resistant to antifungal agents in vitro.

Modeling Intrajunction Dispersion at a Well-Mixed Tidal River Junction

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

Wolfram, Phillip J.; Fringer, Oliver B.; Monsen, Nancy E.

In this paper, the relative importance of small-scale, intrajunction flow features such as shear layers, separation zones, and secondary flows on dispersion in a well-mixed tidal river junction is explored. A fully nonlinear, nonhydrostatic, and unstructured three-dimensional (3D) model is used to resolve supertidal dispersion via scalar transport at a well-mixed tidal river junction. Mass transport simulated in the junction is compared against predictions using a simple node-channel model to quantify the effects of small-scale, 3D intrajunction flow features on mixing and dispersion. The effects of three-dimensionality are demonstrated by quantifying the difference between two-dimensional (2D) and 3D model results.more » An intermediate 3D model that does not resolve the secondary circulation or the recirculating flow at the junction is also compared to the 3D model to quantify the relative sensitivity of mixing on intrajunction flow features. Resolution of complex flow features simulated by the full 3D model is not always necessary because mixing is primarily governed by bulk flow splitting due to the confluence–diffluence cycle. Finally, results in 3D are comparable to the 2D case for many flow pathways simulated, suggesting that 2D modeling may be reasonable for nonstratified and predominantly hydrostatic flows through relatively straight junctions, but not necessarily for the full junction network.« less

Modeling Intrajunction Dispersion at a Well-Mixed Tidal River Junction

DOE PAGES

Wolfram, Phillip J.; Fringer, Oliver B.; Monsen, Nancy E.; ...

2016-08-01

In this paper, the relative importance of small-scale, intrajunction flow features such as shear layers, separation zones, and secondary flows on dispersion in a well-mixed tidal river junction is explored. A fully nonlinear, nonhydrostatic, and unstructured three-dimensional (3D) model is used to resolve supertidal dispersion via scalar transport at a well-mixed tidal river junction. Mass transport simulated in the junction is compared against predictions using a simple node-channel model to quantify the effects of small-scale, 3D intrajunction flow features on mixing and dispersion. The effects of three-dimensionality are demonstrated by quantifying the difference between two-dimensional (2D) and 3D model results.more » An intermediate 3D model that does not resolve the secondary circulation or the recirculating flow at the junction is also compared to the 3D model to quantify the relative sensitivity of mixing on intrajunction flow features. Resolution of complex flow features simulated by the full 3D model is not always necessary because mixing is primarily governed by bulk flow splitting due to the confluence–diffluence cycle. Finally, results in 3D are comparable to the 2D case for many flow pathways simulated, suggesting that 2D modeling may be reasonable for nonstratified and predominantly hydrostatic flows through relatively straight junctions, but not necessarily for the full junction network.« less

Detection of Protein Complexes Based on Penalized Matrix Decomposition in a Sparse Protein⁻Protein Interaction Network.

PubMed

Cao, Buwen; Deng, Shuguang; Qin, Hua; Ding, Pingjian; Chen, Shaopeng; Li, Guanghui

2018-06-15

High-throughput technology has generated large-scale protein interaction data, which is crucial in our understanding of biological organisms. Many complex identification algorithms have been developed to determine protein complexes. However, these methods are only suitable for dense protein interaction networks, because their capabilities decrease rapidly when applied to sparse protein⁻protein interaction (PPI) networks. In this study, based on penalized matrix decomposition ( PMD ), a novel method of penalized matrix decomposition for the identification of protein complexes (i.e., PMD pc ) was developed to detect protein complexes in the human protein interaction network. This method mainly consists of three steps. First, the adjacent matrix of the protein interaction network is normalized. Second, the normalized matrix is decomposed into three factor matrices. The PMD pc method can detect protein complexes in sparse PPI networks by imposing appropriate constraints on factor matrices. Finally, the results of our method are compared with those of other methods in human PPI network. Experimental results show that our method can not only outperform classical algorithms, such as CFinder, ClusterONE, RRW, HC-PIN, and PCE-FR, but can also achieve an ideal overall performance in terms of a composite score consisting of F-measure, accuracy (ACC), and the maximum matching ratio (MMR).

Inorganic anion-dependent assembly of zero-, one-, two- and three-dimensional Cu(II)/Ag(I) complexes under the guidance of the HSAB theory: Synthesis, structure, and magnetic property

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

Liu, Yaru; Xing, Zhiyan; Zhang, Xiao

To systematically explore the influence of inorganic anions on building coordination complexes, five novel complexes based on 1-(benzotriazole-1-methyl)−2-propylimidazole (bpmi), [Cu(bpmi){sub 2}(Ac){sub 2}]·H{sub 2}O (1), [Cu(bpmi){sub 2}(H{sub 2}O){sub 2}]·2NO{sub 3}·2H{sub 2}O (2), [Cu(bpmi)(N{sub 3}){sub 2}] (3), [Ag(bpmi)(NO{sub 3})] (4) and [Cu{sub 3}(bpmi){sub 2}(SCN){sub 4}(DMF)] (5) (Ac{sup −}=CH{sub 3}COO{sup −}, DMF=N,N-Dimethylformamide) are synthesized through rationally introducing Cu(II) salts and Ag(I) salt with different inorganic anions. X-ray single-crystal analyses reveal that these complexes show interesting structural features from mononuclear (1), one-dimensional (2 and 3), two-dimensional (4) to three-dimensional (5) under the influence of inorganic anions with different basicities. The structural variation can bemore » explained by the hard-soft-acid-base (HSAB) theory. Magnetic susceptibility measurement indicates that complex 3 exhibits an antiferromagnetic coupling between adjacent Cu(II) ions. - Graphical abstract: Five new Cu(II)/Ag(I) complexes show interesting structural features from mononuclear, one-dimension, two-dimension to three-dimension under the influence of inorganic anions. The structural variation can be explained by the HSAB theory. - Highlights: • Five inorganic anion-dependent complexes are synthesized. • Structural variation can be explained by the hard-soft-acid-base (HSAB) theory. • The magnetic property of complex has been studied.« less

A neural network model of three-dimensional dynamic electron density in the inner magnetosphere

NASA Astrophysics Data System (ADS)

Chu, X.; Bortnik, J.; Li, W.; Ma, Q.; Denton, R.; Yue, C.; Angelopoulos, V.; Thorne, R. M.; Darrouzet, F.; Ozhogin, P.; Kletzing, C. A.; Wang, Y.; Menietti, J.

2017-09-01

A plasma density model of the inner magnetosphere is important for a variety of applications including the study of wave-particle interactions, and wave excitation and propagation. Previous empirical models have been developed under many limiting assumptions and do not resolve short-term variations, which are especially important during storms. We present a three-dimensional dynamic electron density (DEN3D) model developed using a feedforward neural network with electron densities obtained from four satellite missions. The DEN3D model takes spacecraft location and time series of solar and geomagnetic indices (F10.7, SYM-H, and AL) as inputs. It can reproduce the observed density with a correlation coefficient of 0.95 and predict test data set with error less than a factor of 2. Its predictive ability on out-of-sample data is tested on field-aligned density profiles from the IMAGE satellite. DEN3D's predictive ability provides unprecedented opportunities to gain insight into the 3-D behavior of the inner magnetospheric plasma density at any time and location. As an example, we apply DEN3D to a storm that occurred on 1 June 2013. It successfully reproduces various well-known dynamic features in three dimensions, such as plasmaspheric erosion and recovery, as well as plume formation. Storm time long-term density variations are consistent with expectations; short-term variations appear to be modulated by substorm activity or enhanced convection, an effect that requires further study together with multispacecraft in situ or imaging measurements. Investigating plasmaspheric refilling with the model, we find that it is not monotonic in time and is more complex than expected from previous studies, deserving further attention.

Design applications for supercomputers

NASA Technical Reports Server (NTRS)

Studerus, C. J.

1987-01-01

The complexity of codes for solutions of real aerodynamic problems has progressed from simple two-dimensional models to three-dimensional inviscid and viscous models. As the algorithms used in the codes increased in accuracy, speed and robustness, the codes were steadily incorporated into standard design processes. The highly sophisticated codes, which provide solutions to the truly complex flows, require computers with large memory and high computational speed. The advent of high-speed supercomputers, such that the solutions of these complex flows become more practical, permits the introduction of the codes into the design system at an earlier stage. The results of several codes which either were already introduced into the design process or are rapidly in the process of becoming so, are presented. The codes fall into the area of turbomachinery aerodynamics and hypersonic propulsion. In the former category, results are presented for three-dimensional inviscid and viscous flows through nozzle and unducted fan bladerows. In the latter category, results are presented for two-dimensional inviscid and viscous flows for hypersonic vehicle forebodies and engine inlets.

Fundamental ingredients for discontinuous phase transitions in the inertial majority vote model.

PubMed

Encinas, Jesus M; Harunari, Pedro E; de Oliveira, M M; Fiore, Carlos E

2018-06-19

Discontinuous transitions have received considerable interest due to the uncovering that many phenomena such as catastrophic changes, epidemic outbreaks and synchronization present a behavior signed by abrupt (macroscopic) changes (instead of smooth ones) as a tuning parameter is changed. However, in different cases there are still scarce microscopic models reproducing such above trademarks. With these ideas in mind, we investigate the key ingredients underpinning the discontinuous transition in one of the simplest systems with up-down Z 2 symmetry recently ascertained in [Phys. Rev. E 95, 042304 (2017)]. Such system, in the presence of an extra ingredient-the inertia- has its continuous transition being switched to a discontinuous one in complex networks. We scrutinize the role of three central ingredients: inertia, system degree, and the lattice topology. Our analysis has been carried out for regular lattices and random regular networks with different node degrees (interacting neighborhood) through mean-field theory (MFT) treatment and numerical simulations. Our findings reveal that not only the inertia but also the connectivity constitute essential elements for shifting the phase transition. Astoundingly, they also manifest in low-dimensional regular topologies, exposing a scaling behavior entirely different than those from the complex networks case. Therefore, our findings put on firmer bases the essential issues for the manifestation of discontinuous transitions in such relevant class of systems with Z 2 symmetry.

Extension of a System Level Tool for Component Level Analysis

NASA Technical Reports Server (NTRS)

Majumdar, Alok; Schallhorn, Paul

2002-01-01

This paper presents an extension of a numerical algorithm for network flow analysis code to perform multi-dimensional flow calculation. The one dimensional momentum equation in network flow analysis code has been extended to include momentum transport due to shear stress and transverse component of velocity. Both laminar and turbulent flows are considered. Turbulence is represented by Prandtl's mixing length hypothesis. Three classical examples (Poiseuille flow, Couette flow and shear driven flow in a rectangular cavity) are presented as benchmark for the verification of the numerical scheme.

Extension of a System Level Tool for Component Level Analysis

NASA Technical Reports Server (NTRS)

Majumdar, Alok; Schallhorn, Paul; McConnaughey, Paul K. (Technical Monitor)

2001-01-01

This paper presents an extension of a numerical algorithm for network flow analysis code to perform multi-dimensional flow calculation. The one dimensional momentum equation in network flow analysis code has been extended to include momentum transport due to shear stress and transverse component of velocity. Both laminar and turbulent flows are considered. Turbulence is represented by Prandtl's mixing length hypothesis. Three classical examples (Poiseuille flow, Couette flow, and shear driven flow in a rectangular cavity) are presented as benchmark for the verification of the numerical scheme.

Tissue matrix arrays for high throughput screening and systems analysis of cell function

PubMed Central

Beachley, Vince Z.; Wolf, Matthew T.; Sadtler, Kaitlyn; Manda, Srikanth S.; Jacobs, Heather; Blatchley, Michael; Bader, Joel S.; Pandey, Akhilesh; Pardoll, Drew; Elisseeff, Jennifer H.

2015-01-01

Cell and protein arrays have demonstrated remarkable utility in the high-throughput evaluation of biological responses; however, they lack the complexity of native tissue and organs. Here, we describe tissue extracellular matrix (ECM) arrays for screening biological outputs and systems analysis. We spotted processed tissue ECM particles as two-dimensional arrays or incorporated them with cells to generate three-dimensional cell-matrix microtissue arrays. We then investigated the response of human stem, cancer, and immune cells to tissue ECM arrays originating from 11 different tissues, and validated the 2D and 3D arrays as representative of the in vivo microenvironment through quantitative analysis of tissue-specific cellular responses, including matrix production, adhesion and proliferation, and morphological changes following culture. The biological outputs correlated with tissue proteomics, and network analysis identified several proteins linked to cell function. Our methodology enables broad screening of ECMs to connect tissue-specific composition with biological activity, providing a new resource for biomaterials research and translation. PMID:26480475

Electromechanical vortex filaments during cardiac fibrillation

NASA Astrophysics Data System (ADS)

Christoph, J.; Chebbok, M.; Richter, C.; Schröder-Schetelig, J.; Bittihn, P.; Stein, S.; Uzelac, I.; Fenton, F. H.; Hasenfuß, G.; Gilmour, R. F., Jr.; Luther, S.

2018-03-01

The self-organized dynamics of vortex-like rotating waves, which are also known as scroll waves, are the basis of the formation of complex spatiotemporal patterns in many excitable chemical and biological systems. In the heart, filament-like phase singularities that are associated with three-dimensional scroll waves are considered to be the organizing centres of life-threatening cardiac arrhythmias. The mechanisms that underlie the onset, maintenance and control of electromechanical turbulence in the heart are inherently three-dimensional phenomena. However, it has not previously been possible to visualize the three-dimensional spatiotemporal dynamics of scroll waves inside cardiac tissues. Here we show that three-dimensional mechanical scroll waves and filament-like phase singularities can be observed deep inside the contracting heart wall using high-resolution four-dimensional ultrasound-based strain imaging. We found that mechanical phase singularities co-exist with electrical phase singularities during cardiac fibrillation. We investigated the dynamics of electrical and mechanical phase singularities by simultaneously measuring the membrane potential, intracellular calcium concentration and mechanical contractions of the heart. We show that cardiac fibrillation can be characterized using the three-dimensional spatiotemporal dynamics of mechanical phase singularities, which arise inside the fibrillating contracting ventricular wall. We demonstrate that electrical and mechanical phase singularities show complex interactions and we characterize their dynamics in terms of trajectories, topological charge and lifetime. We anticipate that our findings will provide novel perspectives for non-invasive diagnostic imaging and therapeutic applications.

Online service for monitoring the ionosphere based on data from the global navigation satellite system

NASA Astrophysics Data System (ADS)

Aleshin, I. M.; Alpatov, V. V.; Vasil'ev, A. E.; Burguchev, S. S.; Kholodkov, K. I.; Budnikov, P. A.; Molodtsov, D. A.; Koryagin, V. N.; Perederin, F. V.

2014-07-01

A service is described that makes possible the effective construction of a three-dimensional ionospheric model based on the data of ground receivers of signals from global navigation satellite positioning systems (GNSS). The obtained image has a high resolution, mainly because data from the IPG GNSS network of the Federal Service for Hydrometeorology and Environmental Monitoring (Rosgidromet) are used. A specially developed format and its implementation in the form of SQL structures are used to collect, transmit, and store data. The method of high-altitude radio tomography is used to construct the three-dimensional model. The operation of all system components (from registration point organization to the procedure for constructing the electron density three-dimensional distribution and publication of the total electron content map on the Internet) has been described in detail. The three-dimensional image of the ionosphere, obtained automatically, is compared with the ionosonde measurements, calculated using the two-dimensional low-altitude tomography method and averaged by the ionospheric model.

Three-dimensional neural differentiation of embryonic stem cells with ACM induction in microfibrous matrices in bioreactors.

PubMed

Liu, Ning; Ouyang, Anli; Li, Yan; Yang, Shang-Tian

2013-01-01

The clinical use of pluripotent stem cell (PSC)-derived neural cells requires an efficient differentiation process for mass production in a bioreactor. Toward this goal, neural differentiation of murine embryonic stem cells (ESCs) in three-dimensional (3D) polyethylene terephthalate microfibrous matrices was investigated in this study. To streamline the process and provide a platform for process integration, the neural differentiation of ESCs was induced with astrocyte-conditioned medium without the formation of embryoid bodies, starting from undifferentiated ESC aggregates expanded in a suspension bioreactor. The 3D neural differentiation was able to generate a complex neural network in the matrices. When compared to 2D differentiation, 3D differentiation in microfibrous matrices resulted in a higher percentage of nestin-positive cells (68% vs. 54%) and upregulated gene expressions of nestin, Nurr1, and tyrosine hydroxylase. High purity of neural differentiation in 3D microfibrous matrix was also demonstrated in a spinner bioreactor with 74% nestin + cells. This study demonstrated the feasibility of a scalable process based on 3D differentiation in microfibrous matrices for the production of ESC-derived neural cells. © 2013 American Institute of Chemical Engineers.

Three-dimensional frictional plastic strain partitioning during oblique rifting

NASA Astrophysics Data System (ADS)

Duclaux, Guillaume; Huismans, Ritske S.; May, Dave

2017-04-01

Throughout the Wilson cycle the obliquity between lithospheric plate motion direction and nascent or existing plate boundaries prompts the development of intricate three-dimensional tectonic systems. Where oblique divergence dominates, as in the vast majority of continental rift and incipient oceanic domains, deformation is typically transtensional and large stretching in the brittle upper crust is primarily achieved by the accumulation of displacement on fault networks of various complexity. In continental rift depressions such faults are initially distributed over tens to hundreds of kilometer-wide regions, which can ultimately stretch and evolve into passive margins. Here, we use high-resolution 3D thermo-mechanical finite element models to investigate the relative timing and distribution of localised frictional plastic deformation in the upper crust during oblique rift development in a simplified layered lithosphere. We vary the orientation of a wide oblique heterogeneous weak zone (representing a pre-existing geologic feature like a past orogenic domain), and test the sensitivity of the shear zones orientation to a range of noise distribution. These models allow us to assess the importance of material heterogeneities for controlling the spatio-temporal shear zones distribution in the upper crust during oblique rifting, and to discuss the underlying controls governing oblique continental breakup.

Modeling and numerical simulations of growth and morphologies of three dimensional aggregated silver films

NASA Astrophysics Data System (ADS)

Davis, L. J.; Boggess, M.; Kodpuak, E.; Deutsch, M.

2012-11-01

We report on a model for the deposition of three dimensional, aggregated nanocrystalline silver films, and an efficient numerical simulation method developed for visualizing such structures. We compare our results to a model system comprising chemically deposited silver films with morphologies ranging from dilute, uniform distributions of nanoparticles to highly porous aggregated networks. Disordered silver films grown in solution on silica substrates are characterized using digital image analysis of high resolution scanning electron micrographs. While the latter technique provides little volume information, plane-projected (two dimensional) island structure and surface coverage may be reliably determined. Three parameters governing film growth are evaluated using these data and used as inputs for the deposition model, greatly reducing computing requirements while still providing direct access to the complete (bulk) structure of the films throughout the growth process. We also show how valuable three dimensional characteristics of the deposited materials can be extracted using the simulated structures.

Three-dimensionally networked graphene hydroxide with giant pores and its application in supercapacitors

PubMed Central

Lee, Dongwook; Seo, Jiwon

2014-01-01

The three-dimensionally networked and layered structure of graphene hydroxide (GH) was investigated. After lengthy immersion in a NaOH solution, most of the epoxy groups in the graphene oxide were destroyed, and more hydroxyl groups were generated, transforming the graphene oxide into graphene hydroxide. Additionally, benzoic acid groups were formed, and the ether groups link the neighboring layers, creating a near-3D structure in the GH. To utilize these unique structural features, electrodes with large pores for use in supercapacitors were fabricated using thermal reduction in vacuum. The reduced GH maintained its layered structure and developed a lot of large of pores between/inside the layers. The GH electrodes exhibited high gravimetric as well as high volumetric capacitance. PMID:25492227

Three-dimensionally networked graphene hydroxide with giant pores and its application in supercapacitors

NASA Astrophysics Data System (ADS)

Lee, Dongwook; Seo, Jiwon

2014-12-01

The three-dimensionally networked and layered structure of graphene hydroxide (GH) was investigated. After lengthy immersion in a NaOH solution, most of the epoxy groups in the graphene oxide were destroyed, and more hydroxyl groups were generated, transforming the graphene oxide into graphene hydroxide. Additionally, benzoic acid groups were formed, and the ether groups link the neighboring layers, creating a near-3D structure in the GH. To utilize these unique structural features, electrodes with large pores for use in supercapacitors were fabricated using thermal reduction in vacuum. The reduced GH maintained its layered structure and developed a lot of large of pores between/inside the layers. The GH electrodes exhibited high gravimetric as well as high volumetric capacitance.

Three-dimensionally networked graphene hydroxide with giant pores and its application in supercapacitors.

PubMed

Lee, Dongwook; Seo, Jiwon

2014-12-10

The three-dimensionally networked and layered structure of graphene hydroxide (GH) was investigated. After lengthy immersion in a NaOH solution, most of the epoxy groups in the graphene oxide were destroyed, and more hydroxyl groups were generated, transforming the graphene oxide into graphene hydroxide. Additionally, benzoic acid groups were formed, and the ether groups link the neighboring layers, creating a near-3D structure in the GH. To utilize these unique structural features, electrodes with large pores for use in supercapacitors were fabricated using thermal reduction in vacuum. The reduced GH maintained its layered structure and developed a lot of large of pores between/inside the layers. The GH electrodes exhibited high gravimetric as well as high volumetric capacitance.

Tunneling Conductivity and Piezoresistivity of Composites Containing Randomly Dispersed Conductive Nano-Platelets

PubMed Central

Oskouyi, Amirhossein Biabangard; Sundararaj, Uttandaraman; Mertiny, Pierre

2014-01-01

In this study, a three-dimensional continuum percolation model was developed based on a Monte Carlo simulation approach to investigate the percolation behavior of an electrically insulating matrix reinforced with conductive nano-platelet fillers. The conductivity behavior of composites rendered conductive by randomly dispersed conductive platelets was modeled by developing a three-dimensional finite element resistor network. Parameters related to the percolation threshold and a power-low describing the conductivity behavior were determined. The piezoresistivity behavior of conductive composites was studied employing a reoriented resistor network emulating a conductive composite subjected to mechanical strain. The effects of the governing parameters, i.e., electron tunneling distance, conductive particle aspect ratio and size effects on conductivity behavior were examined. PMID:28788580

A Three-Dimensional Computational Model of Collagen Network Mechanics

PubMed Central

Lee, Byoungkoo; Zhou, Xin; Riching, Kristin; Eliceiri, Kevin W.; Keely, Patricia J.; Guelcher, Scott A.; Weaver, Alissa M.; Jiang, Yi

2014-01-01

Extracellular matrix (ECM) strongly influences cellular behaviors, including cell proliferation, adhesion, and particularly migration. In cancer, the rigidity of the stromal collagen environment is thought to control tumor aggressiveness, and collagen alignment has been linked to tumor cell invasion. While the mechanical properties of collagen at both the single fiber scale and the bulk gel scale are quite well studied, how the fiber network responds to local stress or deformation, both structurally and mechanically, is poorly understood. This intermediate scale knowledge is important to understanding cell-ECM interactions and is the focus of this study. We have developed a three-dimensional elastic collagen fiber network model (bead-and-spring model) and studied fiber network behaviors for various biophysical conditions: collagen density, crosslinker strength, crosslinker density, and fiber orientation (random vs. prealigned). We found the best-fit crosslinker parameter values using shear simulation tests in a small strain region. Using this calibrated collagen model, we simulated both shear and tensile tests in a large linear strain region for different network geometry conditions. The results suggest that network geometry is a key determinant of the mechanical properties of the fiber network. We further demonstrated how the fiber network structure and mechanics evolves with a local formation, mimicking the effect of pulling by a pseudopod during cell migration. Our computational fiber network model is a step toward a full biomechanical model of cellular behaviors in various ECM conditions. PMID:25386649

1D and 3D Polymeric Manganese(II) Thiolato Complexes: Synthesis, Structure, and Properties of    ∞3[Mn4(SPh)8] and ∞1[Mn(SMes)2].

PubMed

Eichhöfer, Andreas; Lebedkin, Sergei

2018-01-16

Reactions of [Mn{N(SiMe 3 ) 2 } 2 ] 2 with 2.1 equiv of RSH, R = Ph or Mes = C 6 H 2 -2,4,6-(CH 3 ) 3 , yield compounds of the formal composition "Mn(SR) 2 ". Single-crystal X-ray diffraction reveals that ∞ 1 [Mn(SMes) 2 ] forms one-dimensional chains in the crystal via μ 2 -SMes bridges, whereas ∞ 3 [Mn 4 (SPh) 8 ] comprises a three-dimensional network in which adamantanoid cages composed of four Mn atoms and six μ 2 -bridging SPh ligands are connected in three dimensions by doubly bridging SPh ligands. Thermogravimetric analysis and powder diffractometry indicate an reversible uptake of solvent molecules (tetrahydrofuran) into the channels of ∞ 1 [Mn(SMes) 2 ]. Magnetic measurements reveal antiferromagnetic coupling for both compounds with J = -8.2 cm -1 ( ∞ 1 [Mn(SMes) 2 ]) and -10.0 cm -1 ( ∞ 3 [Mn 4 (SPh) 8 ]), respectively. Their optical absorption and photoluminescence (PL) excitation spectra display characteristic d-d bands of Mn 2+ ions in the visible spectral region. Both compounds emit bright phosphorescence at ∼800 nm at low temperatures (<100 K). However, only ∞ 1 [Mn(SMes) 2 ] retains a moderately intense emission at ambient temperature (with a quantum yield of 1.2%). Similar PL properties are also found for the related selenolate complexes ∞ 1 [Mn(SeR) 2 ] (R = Ph, Mes).

Biofilm three-dimensional architecture influences in situ pH distribution pattern on the human enamel surface

PubMed Central

Xiao, Jin; Hara, Anderson T; Kim, Dongyeop; Zero, Domenick T; Koo, Hyun; Hwang, Geelsu

2017-01-01

To investigate how the biofilm three-dimensional (3D) architecture influences in situ pH distribution patterns on the enamel surface. Biofilms were formed on human tooth enamel in the presence of 1% sucrose or 0.5% glucose plus 0.5% fructose. At specific time points, biofilms were exposed to a neutral pH buffer to mimic the buffering of saliva and subsequently pulsed with 1% glucose to induce re-acidification. Simultaneous 3D pH mapping and architecture of intact biofilms was performed using two-photon confocal microscopy. The enamel surface and mineral content characteristics were examined successively via optical profilometry and microradiography analyses. Sucrose-mediated biofilm formation created spatial heterogeneities manifested by complex networks of bacterial clusters (microcolonies). Acidic regions (pH<5.5) were found only in the interior of microcolonies, which impedes rapid neutralization (taking more than 120 min for neutralization). Glucose exposure rapidly re-created the acidic niches, indicating formation of diffusion barriers associated with microcolonies structure. Enamel demineralization (white spots), rougher surface, deeper lesion and more mineral loss appeared to be associated with the localization of these bacterial clusters at the biofilm-enamel interface. Similar 3D architecture was observed in plaque-biofilms formed in vivo in the presence of sucrose. The formation of complex 3D architectures creates spatially heterogeneous acidic microenvironments in close proximity of enamel surface, which might correlate with the localized pattern of the onset of carious lesions (white spot like) on teeth. PMID:28452377

Electric Power Engineering Cost Predicting Model Based on the PCA-GA-BP

NASA Astrophysics Data System (ADS)

Wen, Lei; Yu, Jiake; Zhao, Xin

2017-10-01

In this paper a hybrid prediction algorithm: PCA-GA-BP model is proposed. PCA algorithm is established to reduce the correlation between indicators of original data and decrease difficulty of BP neural network in complex dimensional calculation. The BP neural network is established to estimate the cost of power transmission project. The results show that PCA-GA-BP algorithm can improve result of prediction of electric power engineering cost.

Three-dimensional geologic mapping of the Cenozoic basin fill, Amargosa Desert basin, Nevada and California

USGS Publications Warehouse

Taylor, Emily M.; Sweetkind, Donald S.

2014-01-01

Understanding the subsurface geologic framework of the Cenozoic basin fill that underlies the Amargosa Desert in southern Nevada and southeastern California has been improved by using borehole data to construct three-dimensional lithologic and interpreted facies models. Lithologic data from 210 boreholes from a 20-kilometer (km) by 90-km area were reduced to a limited suite of descriptors based on geologic knowledge of the basin and distributed in three-dimensional space using interpolation methods. The resulting lithologic model of the Amargosa Desert basin portrays a complex system of interfingered coarse- to fine-grained alluvium, playa and palustrine deposits, eolian sands, and interbedded volcanic units. Lithologic units could not be represented in the model as a stacked stratigraphic sequence due to the complex interfingering of lithologic units and the absence of available time-stratigraphic markers. Instead, lithologic units were grouped into interpreted genetic classes, such as playa or alluvial fan, to create a three-dimensional model of the interpreted facies data. Three-dimensional facies models computed from these data portray the alluvial infilling of a tectonically formed basin with intermittent internal drainage and localized regional groundwater discharge. The lithologic and interpreted facies models compare favorably to resistivity, aeromagnetic, and geologic map data, lending confidence to the interpretation.

Three-dimensional computational aerodynamics in the 1980's

NASA Technical Reports Server (NTRS)

Lomax, H.

1978-01-01

The future requirements for constructing codes that can be used to compute three-dimensional flows about aerodynamic shapes should be assessed in light of the constraints imposed by future computer architectures and the reality of usable algorithms that can provide practical three-dimensional simulations. On the hardware side, vector processing is inevitable in order to meet the CPU speeds required. To cope with three-dimensional geometries, massive data bases with fetch/store conflicts and transposition problems are inevitable. On the software side, codes must be prepared that: (1) can be adapted to complex geometries, (2) can (at the very least) predict the location of laminar and turbulent boundary layer separation, and (3) will converge rapidly to sufficiently accurate solutions.

A three-dimensional turbulent separated flow and related mesurements

NASA Technical Reports Server (NTRS)

Pierce, F. J.

1985-01-01

The applicability of and the limits on the applicability of 11 near wall similarity laws characterizing three-dimensional turbulent boundary layer flows were determined. A direct force sensing local wall shear stress meter was used in both pressure-driven and shear-driven three-dimensional turbulent boundary layers, together with extensive mean velocity field and wall pressure field data. This resulted in a relatively large number of graphical comparisons of the predictive ability of 10 of these 11 similarity models relative to measured data over a wide range of flow conditions. Documentation of a complex, separated three-dimensional turbulent flow as a standard test case for evaluating the predictive ability of numerical codes solving such flows is presented.

Modern cosmology and the origin of our three dimensionality.

PubMed

Woodbury, M A; Woodbury, M F

1998-01-01

We are three dimensional egocentric beings existing within a specific space/time continuum and dimensionality which we assume wrongly is the same for all times and places throughout the entire universe. Physicists name Omnipoint the origin of the universe at Dimension zero, which exploded as a Big Bang of energy proceeding at enormous speed along one dimension which eventually curled up into matter: particles, atoms, molecules and Galaxies which exist in two dimensional space. Finally from matter spread throughout the cosmos evolved life generating eventually the DNA molecules which control the construction of brains complex enough to construct our three dimensional Body Representation from which is extrapolated what we perceive as a 3-D universe. The whole interconnected structures which conjure up our three dimensionality are as fragile as Humpty Dumpty, capable of breaking apart with terrifying effects for the individual patient during a psychotic panic, revealing our three dimensionality to be but "maya", an illusion, which we psychiatrists work at putting back together.

Two zinc(II) coordination complexes based on an asymmetric multidentate ligand: syntheses, structures, selective fluorescence sensing of iron(III) ions and thermal analyses.

PubMed

Liu, Yaru; Liu, Lan; Zhang, Xiao; Liang, Guorui; Gong, Xuebing

2018-01-01

The rational selection of ligands is vitally important in the construction of coordination complexes. Two novel Zn II complexes, namely bis(acetato-κO)bis[1-(1H-benzotriazol-1-ylmethyl)-2-propyl-1H-imidazole-κN 3 ]zinc(II) monohydrate, [Zn(C 13 H 15 N 5 ) 2 (C 2 H 3 O 2 ) 2 ]·H 2 O, (1), and bis(azido-κN 1 )bis[1-(1H-benzotriazol-1-ylmethyl)-2-propyl-1H-imidazole-κN 3 ]zinc(II), [Zn(C 13 H 15 N 5 ) 2 (N 3 ) 2 ], (2), constructed from the asymmetric multidentate imidazole ligand, have been synthesized under mild conditions and characterized by elemental analyses, IR spectroscopy and single-crystal X-ray diffraction analysis. Both complexes exhibit a three-dimensional supramolecular network directed by different intermolecular interactions between discrete mononuclear units. The complexes were also investigated by fluorescence and thermal analyses. The experimental results show that (1) is a promising fluorescence sensor for detecting Fe 3+ ions and (2) is effective as an accelerator of the thermal decomposition of ammonium perchlorate.

Three-dimensional chimera patterns in networks of spiking neuron oscillators

NASA Astrophysics Data System (ADS)

Kasimatis, T.; Hizanidis, J.; Provata, A.

2018-05-01

We study the stable spatiotemporal patterns that arise in a three-dimensional (3D) network of neuron oscillators, whose dynamics is described by the leaky integrate-and-fire (LIF) model. More specifically, we investigate the form of the chimera states induced by a 3D coupling matrix with nonlocal topology. The observed patterns are in many cases direct generalizations of the corresponding two-dimensional (2D) patterns, e.g., spheres, layers, and cylinder grids. We also find cylindrical and "cross-layered" chimeras that do not have an equivalent in 2D systems. Quantitative measures are calculated, such as the ratio of synchronized and unsynchronized neurons as a function of the coupling range, the mean phase velocities, and the distribution of neurons in mean phase velocities. Based on these measures, the chimeras are categorized in two families. The first family of patterns is observed for weaker coupling and exhibits higher mean phase velocities for the unsynchronized areas of the network. The opposite holds for the second family, where the unsynchronized areas have lower mean phase velocities. The various measures demonstrate discontinuities, indicating criticality as the parameters cross from the first family of patterns to the second.

Multi-Dimensional Scaling based grouping of known complexes and intelligent protein complex detection.

PubMed

Rehman, Zia Ur; Idris, Adnan; Khan, Asifullah

2018-06-01

Protein-Protein Interactions (PPI) play a vital role in cellular processes and are formed because of thousands of interactions among proteins. Advancements in proteomics technologies have resulted in huge PPI datasets that need to be systematically analyzed. Protein complexes are the locally dense regions in PPI networks, which extend important role in metabolic pathways and gene regulation. In this work, a novel two-phase protein complex detection and grouping mechanism is proposed. In the first phase, topological and biological features are extracted for each complex, and prediction performance is investigated using Bagging based Ensemble classifier (PCD-BEns). Performance evaluation through cross validation shows improvement in comparison to CDIP, MCode, CFinder and PLSMC methods Second phase employs Multi-Dimensional Scaling (MDS) for the grouping of known complexes by exploring inter complex relations. It is experimentally observed that the combination of topological and biological features in the proposed approach has greatly enhanced prediction performance for protein complex detection, which may help to understand various biological processes, whereas application of MDS based exploration may assist in grouping potentially similar complexes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Capturing tumor complexity in vitro: Comparative analysis of 2D and 3D tumor models for drug discovery.

PubMed

Stock, Kristin; Estrada, Marta F; Vidic, Suzana; Gjerde, Kjersti; Rudisch, Albin; Santo, Vítor E; Barbier, Michaël; Blom, Sami; Arundkar, Sharath C; Selvam, Irwin; Osswald, Annika; Stein, Yan; Gruenewald, Sylvia; Brito, Catarina; van Weerden, Wytske; Rotter, Varda; Boghaert, Erwin; Oren, Moshe; Sommergruber, Wolfgang; Chong, Yolanda; de Hoogt, Ronald; Graeser, Ralph

2016-07-01

Two-dimensional (2D) cell cultures growing on plastic do not recapitulate the three dimensional (3D) architecture and complexity of human tumors. More representative models are required for drug discovery and validation. Here, 2D culture and 3D mono- and stromal co-culture models of increasing complexity have been established and cross-comparisons made using three standard cell carcinoma lines: MCF7, LNCaP, NCI-H1437. Fluorescence-based growth curves, 3D image analysis, immunohistochemistry and treatment responses showed that end points differed according to cell type, stromal co-culture and culture format. The adaptable methodologies described here should guide the choice of appropriate simple and complex in vitro models.

Capturing tumor complexity in vitro: Comparative analysis of 2D and 3D tumor models for drug discovery

PubMed Central

Stock, Kristin; Estrada, Marta F.; Vidic, Suzana; Gjerde, Kjersti; Rudisch, Albin; Santo, Vítor E.; Barbier, Michaël; Blom, Sami; Arundkar, Sharath C.; Selvam, Irwin; Osswald, Annika; Stein, Yan; Gruenewald, Sylvia; Brito, Catarina; van Weerden, Wytske; Rotter, Varda; Boghaert, Erwin; Oren, Moshe; Sommergruber, Wolfgang; Chong, Yolanda; de Hoogt, Ronald; Graeser, Ralph

2016-01-01

Two-dimensional (2D) cell cultures growing on plastic do not recapitulate the three dimensional (3D) architecture and complexity of human tumors. More representative models are required for drug discovery and validation. Here, 2D culture and 3D mono- and stromal co-culture models of increasing complexity have been established and cross-comparisons made using three standard cell carcinoma lines: MCF7, LNCaP, NCI-H1437. Fluorescence-based growth curves, 3D image analysis, immunohistochemistry and treatment responses showed that end points differed according to cell type, stromal co-culture and culture format. The adaptable methodologies described here should guide the choice of appropriate simple and complex in vitro models. PMID:27364600

Automated Quantification and Integrative Analysis of 2D and 3D Mitochondrial Shape and Network Properties

PubMed Central

Nikolaisen, Julie; Nilsson, Linn I. H.; Pettersen, Ina K. N.; Willems, Peter H. G. M.; Lorens, James B.; Koopman, Werner J. H.; Tronstad, Karl J.

2014-01-01

Mitochondrial morphology and function are coupled in healthy cells, during pathological conditions and (adaptation to) endogenous and exogenous stress. In this sense mitochondrial shape can range from small globular compartments to complex filamentous networks, even within the same cell. Understanding how mitochondrial morphological changes (i.e. “mitochondrial dynamics”) are linked to cellular (patho) physiology is currently the subject of intense study and requires detailed quantitative information. During the last decade, various computational approaches have been developed for automated 2-dimensional (2D) analysis of mitochondrial morphology and number in microscopy images. Although these strategies are well suited for analysis of adhering cells with a flat morphology they are not applicable for thicker cells, which require a three-dimensional (3D) image acquisition and analysis procedure. Here we developed and validated an automated image analysis algorithm allowing simultaneous 3D quantification of mitochondrial morphology and network properties in human endothelial cells (HUVECs). Cells expressing a mitochondria-targeted green fluorescence protein (mitoGFP) were visualized by 3D confocal microscopy and mitochondrial morphology was quantified using both the established 2D method and the new 3D strategy. We demonstrate that both analyses can be used to characterize and discriminate between various mitochondrial morphologies and network properties. However, the results from 2D and 3D analysis were not equivalent when filamentous mitochondria in normal HUVECs were compared with circular/spherical mitochondria in metabolically stressed HUVECs treated with rotenone (ROT). 2D quantification suggested that metabolic stress induced mitochondrial fragmentation and loss of biomass. In contrast, 3D analysis revealed that the mitochondrial network structure was dissolved without affecting the amount and size of the organelles. Thus, our results demonstrate that 3D imaging and quantification are crucial for proper understanding of mitochondrial shape and topology in non-flat cells. In summary, we here present an integrative method for unbiased 3D quantification of mitochondrial shape and network properties in mammalian cells. PMID:24988307

Mechanisms of leading edge protrusion in interstitial migration

PubMed Central

Wilson, Kerry; Lewalle, Alexandre; Fritzsche, Marco; Thorogate, Richard; Duke, Tom; Charras, Guillaume

2013-01-01

While the molecular and biophysical mechanisms underlying cell protrusion on two-dimensional substrates are well understood, our knowledge of the actin structures driving protrusion in three-dimensional environments is poor, despite relevance to inflammation, development and cancer. Here we report that, during chemotactic migration through microchannels with 5 μm × 5 μm cross-sections, HL60 neutrophil-like cells assemble an actin-rich slab filling the whole channel cross-section at their front. This leading edge comprises two distinct F-actin networks: an adherent network that polymerizes perpendicular to cell-wall interfaces and a ‘free’ network that grows from the free membrane at the cell front. Each network is polymerized by a distinct nucleator and, due to their geometrical arrangement, the networks interact mechanically. On the basis of our experimental data, we propose that, during interstitial migration, medial growth of the adherent network compresses the free network preventing its retrograde movement and enabling new polymerization to be converted into forward protrusion. PMID:24305616

Three-dimensional printing and pediatric liver disease.

PubMed

Alkhouri, Naim; Zein, Nizar N

2016-10-01

Enthusiastic physicians and medical researchers are investigating the role of three-dimensional printing in medicine. The purpose of the current review is to provide a concise summary of the role of three-dimensional printing technology as it relates to the field of pediatric hepatology and liver transplantation. Our group and others have recently demonstrated the feasibility of printing three-dimensional livers with identical anatomical and geometrical landmarks to the native liver to facilitate presurgical planning of complex liver surgeries. Medical educators are exploring the use of three-dimensional printed organs in anatomy classes and surgical residencies. Moreover, mini-livers are being developed by regenerative medicine scientist as a way to test new drugs and, eventually, whole livers will be grown in the laboratory to replace organs with end-stage disease solving the organ shortage problem. From presurgical planning to medical education to ultimately the bioprinting of whole organs for transplantation, three-dimensional printing will change medicine as we know in the next few years.

Evaluation of an Online Three-Dimensional Interactive Resource for Undergraduate Neuroanatomy Education

ERIC Educational Resources Information Center

Allen, Lauren K.; Eagleson, Roy; de Ribaupierre, Sandrine

2016-01-01

Neuroanatomy is one of the most challenging subjects in anatomy, and novice students often experience difficulty grasping the complex three-dimensional (3D) spatial relationships. This study evaluated a 3D neuroanatomy e-learning module, as well as the relationship between spatial abilities and students' knowledge in neuroanatomy. The study's…

From biological neural networks to thinking machines: Transitioning biological organizational principles to computer technology

NASA Technical Reports Server (NTRS)

Ross, Muriel D.

1991-01-01

The three-dimensional organization of the vestibular macula is under study by computer assisted reconstruction and simulation methods as a model for more complex neural systems. One goal of this research is to transition knowledge of biological neural network architecture and functioning to computer technology, to contribute to the development of thinking computers. Maculas are organized as weighted neural networks for parallel distributed processing of information. The network is characterized by non-linearity of its terminal/receptive fields. Wiring appears to develop through constrained randomness. A further property is the presence of two main circuits, highly channeled and distributed modifying, that are connected through feedforward-feedback collaterals and biasing subcircuit. Computer simulations demonstrate that differences in geometry of the feedback (afferent) collaterals affects the timing and the magnitude of voltage changes delivered to the spike initiation zone. Feedforward (efferent) collaterals act as voltage followers and likely inhibit neurons of the distributed modifying circuit. These results illustrate the importance of feedforward-feedback loops, of timing, and of inhibition in refining neural network output. They also suggest that it is the distributed modifying network that is most involved in adaptation, memory, and learning. Tests of macular adaptation, through hyper- and microgravitational studies, support this hypothesis since synapses in the distributed modifying circuit, but not the channeled circuit, are altered. Transitioning knowledge of biological systems to computer technology, however, remains problematical.

Networks as Renormalized Models for Emergent Behavior in Physical Systems

NASA Astrophysics Data System (ADS)

Paczuski, Maya

2005-09-01

Networks are paradigms for describing complex biological, social and technological systems. Here I argue that networks provide a coherent framework to construct coarsegrained models for many different physical systems. To elucidate these ideas, I discuss two long-standing problems. The first concerns the structure and dynamics of magnetic fields in the solar corona, as exemplified by sunspots that startled Galileo almost 400 years ago. We discovered that the magnetic structure of the corona embodies a scale free network, with spots at all scales. A network model representing the three-dimensional geometry of magnetic fields, where links rewire and nodes merge when they collide in space, gives quantitative agreement with available data, and suggests new measurements. Seismicity is addressed in terms of relations between events without imposing space-time windows. A metric estimates the correlation between any two earthquakes. Linking strongly correlated pairs, and ignoring pairs with weak correlation organizes the spatio-temporal process into a sparse, directed, weighted network. New scaling laws for seismicity are found. For instance, the aftershock decay rate decreases as ~ 1/t in time up to a correlation time, tomori. An estimate from the data gives tomori to be about one year for small magnitude 3 earthquakes, about 1400 years for the Landers event, and roughly 26,000 years for the earthquake causing the 2004 Asian tsunami. Our results confirm Kagan's conjecture that aftershocks can rumble on for centuries.

Visualisation and graph-theoretic analysis of a large-scale protein structural interactome

PubMed Central

Bolser, Dan; Dafas, Panos; Harrington, Richard; Park, Jong; Schroeder, Michael

2003-01-01

Background Large-scale protein interaction maps provide a new, global perspective with which to analyse protein function. PSIMAP, the Protein Structural Interactome Map, is a database of all the structurally observed interactions between superfamilies of protein domains with known three-dimensional structure in the PDB. PSIMAP incorporates both functional and evolutionary information into a single network. Results We present a global analysis of PSIMAP using several distinct network measures relating to centrality, interactivity, fault-tolerance, and taxonomic diversity. We found the following results: Centrality: we show that the center and barycenter of PSIMAP do not coincide, and that the superfamilies forming the barycenter relate to very general functions, while those constituting the center relate to enzymatic activity. Interactivity: we identify the P-loop and immunoglobulin superfamilies as the most highly interactive. We successfully use connectivity and cluster index, which characterise the connectivity of a superfamily's neighbourhood, to discover superfamilies of complex I and II. This is particularly significant as the structure of complex I is not yet solved. Taxonomic diversity: we found that highly interactive superfamilies are in general taxonomically very diverse and are thus amongst the oldest. Fault-tolerance: we found that the network is very robust as for the majority of superfamilies removal from the network will not break up the network. Conclusions Overall, we can single out the P-loop containing nucleotide triphosphate hydrolases superfamily as it is the most highly connected and has the highest taxonomic diversity. In addition, this superfamily has the highest interaction rank, is the barycenter of the network (it has the shortest average path to every other superfamily in the network), and is an articulation vertex, whose removal will disconnect the network. More generally, we conclude that the graph-theoretic and taxonomic analysis of PSIMAP is an important step towards the understanding of protein function and could be an important tool for tracing the evolution of life at the molecular level. PMID:14531933

Surveying hospital network structure in New York State: how are they structured?

PubMed

Nauenberg, E; Brewer, C S

2000-01-01

We determine the most common network structures in New York state. The taxonomy employed uses three structural dimensions: integration, complexity, and risk-sharing between organizations. Based on a survey conducted in 1996, the most common type of network (26.4 percent) had medium levels of integration, medium or high levels of complexity, and some risk-sharing. Also common were networks with low levels of integration, low levels of complexity, and no risk-sharing (22.1 percent).

Poly[[aqua­(μ2-oxalato)(μ2-2-oxido­pyridinium-3-carboxylato)holmium(III)] monohydrate

PubMed Central

Zhu, Hui-Lan; Lai, Hui-Ling; Han, Lu; Luo, Yi-Fan; Zeng, Rong-Hua

2009-01-01

In the title complex, {[Ho(C2O4)(C6H4NO3)(H2O)]·(H2O)}n, the HoIII ion is coordinated by three O atoms from two 2-oxidopyridinium-3-carboxylate ligands, four O atoms from two oxalate ligands and one water mol­ecule in a distorted bicapped trigonal-prismatic geometry. The 2-oxidopyridin­ium-3-carboxylate and oxalate ligands link the HoIII ions into a layer in (100). These layers are further connected by inter­molecular O—H⋯O hydrogen bonds involving the coordinated water mol­ecules to assemble a three-dimensional supra­molecular network. The uncoordin­ated water mol­ecule is involved in N—H⋯O and O—H⋯O hydrogen bonds within the layer. PMID:21577741

Major technological innovations introduced in the large antennas of the Deep Space Network

NASA Technical Reports Server (NTRS)

Imbriale, W. A.

2002-01-01

The NASA Deep Space Network (DSN) is the largest and most sensitive scientific, telecommunications and radio navigation network in the world. Its principal responsibilities are to provide communications, tracking, and science services to most of the world's spacecraft that travel beyond low Earth orbit. The network consists of three Deep Space Communications Complexes. Each of the three complexes consists of multiple large antennas equipped with ultra sensitive receiving systems. A centralized Signal Processing Center (SPC) remotely controls the antennas, generates and transmits spacecraft commands, and receives and processes the spacecraft telemetry.

Approaching human language with complex networks

NASA Astrophysics Data System (ADS)

Cong, Jin; Liu, Haitao

2014-12-01

The interest in modeling and analyzing human language with complex networks is on the rise in recent years and a considerable body of research in this area has already been accumulated. We survey three major lines of linguistic research from the complex network approach: 1) characterization of human language as a multi-level system with complex network analysis; 2) linguistic typological research with the application of linguistic networks and their quantitative measures; and 3) relationships between the system-level complexity of human language (determined by the topology of linguistic networks) and microscopic linguistic (e.g., syntactic) features (as the traditional concern of linguistics). We show that the models and quantitative tools of complex networks, when exploited properly, can constitute an operational methodology for linguistic inquiry, which contributes to the understanding of human language and the development of linguistics. We conclude our review with suggestions for future linguistic research from the complex network approach: 1) relationships between the system-level complexity of human language and microscopic linguistic features; 2) expansion of research scope from the global properties to other levels of granularity of linguistic networks; and 3) combination of linguistic network analysis with other quantitative studies of language (such as quantitative linguistics).

Spatial-Temporal Reasoning Applications of Computational Intelligence in the Game of Go and Computer Networks

DTIC Science & Technology

2012-01-01

dimensionality, Tesauro used a backpropagation- based , three-layer neural network and implemented the outcome from a self-play game as the reinforcement signal...a school of fish, flock of birds, and colony of ants. Our literature review reveals that no one has used PSO to train the neural network ...trained with a variant of PSO called cellular PSO (CPSO). CSRN is a supervised learning neural network (SLNN). The proposed algorithm for the

Fracture size and transmissivity correlations: Implications for transport simulations in sparse three-dimensional discrete fracture networks following a truncated power law distribution of fracture size

NASA Astrophysics Data System (ADS)

Hyman, J. D.; Aldrich, G.; Viswanathan, H.; Makedonska, N.; Karra, S.

2016-08-01

We characterize how different fracture size-transmissivity relationships influence flow and transport simulations through sparse three-dimensional discrete fracture networks. Although it is generally accepted that there is a positive correlation between a fracture's size and its transmissivity/aperture, the functional form of that relationship remains a matter of debate. Relationships that assume perfect correlation, semicorrelation, and noncorrelation between the two have been proposed. To study the impact that adopting one of these relationships has on transport properties, we generate multiple sparse fracture networks composed of circular fractures whose radii follow a truncated power law distribution. The distribution of transmissivities are selected so that the mean transmissivity of the fracture networks are the same and the distributions of aperture and transmissivity in models that include a stochastic term are also the same. We observe that adopting a correlation between a fracture size and its transmissivity leads to earlier breakthrough times and higher effective permeability when compared to networks where no correlation is used. While fracture network geometry plays the principal role in determining where transport occurs within the network, the relationship between size and transmissivity controls the flow speed. These observations indicate DFN modelers should be aware that breakthrough times and effective permeabilities can be strongly influenced by such a relationship in addition to fracture and network statistics.

Fracture size and transmissivity correlations: Implications for transport simulations in sparse three-dimensional discrete fracture networks following a truncated power law distribution of fracture size

NASA Astrophysics Data System (ADS)

Hyman, J.; Aldrich, G. A.; Viswanathan, H. S.; Makedonska, N.; Karra, S.

2016-12-01

We characterize how different fracture size-transmissivity relationships influence flow and transport simulations through sparse three-dimensional discrete fracture networks. Although it is generally accepted that there is a positive correlation between a fracture's size and its transmissivity/aperture, the functional form of that relationship remains a matter of debate. Relationships that assume perfect correlation, semi-correlation, and non-correlation between the two have been proposed. To study the impact that adopting one of these relationships has on transport properties, we generate multiple sparse fracture networks composed of circular fractures whose radii follow a truncated power law distribution. The distribution of transmissivities are selected so that the mean transmissivity of the fracture networks are the same and the distributions of aperture and transmissivity in models that include a stochastic term are also the same.We observe that adopting a correlation between a fracture size and its transmissivity leads to earlier breakthrough times and higher effective permeability when compared to networks where no correlation is used. While fracture network geometry plays the principal role in determining where transport occurs within the network, the relationship between size and transmissivity controls the flow speed. These observations indicate DFN modelers should be aware that breakthrough times and effective permeabilities can be strongly influenced by such a relationship in addition to fracture and network statistics.

Active transport on disordered microtubule networks: the generalized random velocity model.

PubMed

Kahana, Aviv; Kenan, Gilad; Feingold, Mario; Elbaum, Michael; Granek, Rony

2008-11-01

The motion of small cargo particles on microtubules by means of motor proteins in disordered microtubule networks is investigated theoretically using both analytical tools and computer simulations. Different network topologies in two and three dimensions are considered, one of which has been recently studied experimentally by Salman [Biophys. J. 89, 2134 (2005)]. A generalization of the random velocity model is used to derive the mean-square displacement of the cargo particle. We find that all cases belong to the class of anomalous superdiffusion, which is sensitive mainly to the dimensionality of the network and only marginally to its topology. Yet in three dimensions the motion is very close to simple diffusion, with sublogarithmic corrections that depend on the network topology. When details of the thermal diffusion in the bulk solution are included, no significant change to the asymptotic time behavior is found. However, a small asymmetry in the mean microtubule polarity affects the corresponding long-time behavior. We also study a three-dimensional model of the microtubule network in living animal cells. Three first-passage-time problems of intracellular transport are simulated and analyzed for different motor processivities: (i) cargo that originates near the nucleus and has to reach the membrane, (ii) cargo that originates from the membrane and has to reach the nucleus, and (iii) cargo that leaves the nucleus and has to reach a specific target in the cytoplasm. We conclude that while a higher motor processivity increases the transport efficiency in cases (i) and (ii), in case (iii) it has the opposite effect. We conjecture that the balance between the different network tasks, as manifested in cases (i) and (ii) versus case (iii), may be the reason for the evolutionary choice of a finite motor processivity.

Active transport on disordered microtubule networks: The generalized random velocity model

NASA Astrophysics Data System (ADS)

Kahana, Aviv; Kenan, Gilad; Feingold, Mario; Elbaum, Michael; Granek, Rony

2008-11-01

The motion of small cargo particles on microtubules by means of motor proteins in disordered microtubule networks is investigated theoretically using both analytical tools and computer simulations. Different network topologies in two and three dimensions are considered, one of which has been recently studied experimentally by Salman [Biophys. J. 89, 2134 (2005)]. A generalization of the random velocity model is used to derive the mean-square displacement of the cargo particle. We find that all cases belong to the class of anomalous superdiffusion, which is sensitive mainly to the dimensionality of the network and only marginally to its topology. Yet in three dimensions the motion is very close to simple diffusion, with sublogarithmic corrections that depend on the network topology. When details of the thermal diffusion in the bulk solution are included, no significant change to the asymptotic time behavior is found. However, a small asymmetry in the mean microtubule polarity affects the corresponding long-time behavior. We also study a three-dimensional model of the microtubule network in living animal cells. Three first-passage-time problems of intracellular transport are simulated and analyzed for different motor processivities: (i) cargo that originates near the nucleus and has to reach the membrane, (ii) cargo that originates from the membrane and has to reach the nucleus, and (iii) cargo that leaves the nucleus and has to reach a specific target in the cytoplasm. We conclude that while a higher motor processivity increases the transport efficiency in cases (i) and (ii), in case (iii) it has the opposite effect. We conjecture that the balance between the different network tasks, as manifested in cases (i) and (ii) versus case (iii), may be the reason for the evolutionary choice of a finite motor processivity.

Linking dynamics of the inhibitory network to the input structure

PubMed Central

Komarov, Maxim

2017-01-01

Networks of inhibitory interneurons are found in many distinct classes of biological systems. Inhibitory interneurons govern the dynamics of principal cells and are likely to be critically involved in the coding of information. In this theoretical study, we describe the dynamics of a generic inhibitory network in terms of low-dimensional, simplified rate models. We study the relationship between the structure of external input applied to the network and the patterns of activity arising in response to that stimulation. We found that even a minimal inhibitory network can generate a great diversity of spatio-temporal patterning including complex bursting regimes with non-trivial ratios of burst firing. Despite the complexity of these dynamics, the network’s response patterns can be predicted from the rankings of the magnitudes of external inputs to the inhibitory neurons. This type of invariant dynamics is robust to noise and stable in densely connected networks with strong inhibitory coupling. Our study predicts that the response dynamics generated by an inhibitory network may provide critical insights about the temporal structure of the sensory input it receives. PMID:27650865

Complex networks under dynamic repair model

NASA Astrophysics Data System (ADS)

Chaoqi, Fu; Ying, Wang; Kun, Zhao; Yangjun, Gao

2018-01-01

Invulnerability is not the only factor of importance when considering complex networks' security. It is also critical to have an effective and reasonable repair strategy. Existing research on network repair is confined to the static model. The dynamic model makes better use of the redundant capacity of repaired nodes and repairs the damaged network more efficiently than the static model; however, the dynamic repair model is complex and polytropic. In this paper, we construct a dynamic repair model and systematically describe the energy-transfer relationships between nodes in the repair process of the failure network. Nodes are divided into three types, corresponding to three structures. We find that the strong coupling structure is responsible for secondary failure of the repaired nodes and propose an algorithm that can select the most suitable targets (nodes or links) to repair the failure network with minimal cost. Two types of repair strategies are identified, with different effects under the two energy-transfer rules. The research results enable a more flexible approach to network repair.

Finite-dimensional modeling of network-induced delays for real-time control systems

NASA Technical Reports Server (NTRS)

Ray, Asok; Halevi, Yoram

1988-01-01

In integrated control systems (ICS), a feedback loop is closed by the common communication channel, which multiplexes digital data from the sensor to the controller and from the controller to the actuator along with the data traffic from other control loops and management functions. Due to asynchronous time-division multiplexing in the network access protocols, time-varying delays are introduced in the control loop, which degrade the system dynamic performance and are a potential source of instability. The delayed control system is represented by a finite-dimensional, time-varying, discrete-time model which is less complex than the existing continuous-time models for time-varying delays; this approach allows for simpler schemes for analysis and simulation of the ICS.

Lift of noninvariant solutions of heavenly equations from three to four dimensions and new ultra-hyperbolic metrics

NASA Astrophysics Data System (ADS)

Malykh, A. A.; Nutku, Y.; Sheftel, M. B.

2007-08-01

We demonstrate that partner symmetries provide a lift of noninvariant solutions of the three-dimensional Boyer-Finley equation to noninvariant solutions of the four-dimensional hyperbolic complex Monge-Ampère equation. The lift is applied to noninvariant solutions of the Boyer-Finley equation, obtained earlier by the method of group foliation, to yield noninvariant solutions of the hyperbolic complex Monge-Ampère equation. Using these solutions we construct new Ricci-flat ultra-hyperbolic metrics with non-zero curvature tensor that have no Killing vectors.

Stereo Science Results at Solar Minimum

NASA Technical Reports Server (NTRS)

Christian, Eric R.; Kaiser, Michael L.; Kucera Therese A.; St. Cyr, O. C.; van Driel-Gesztelyi, Lidia; Mandrini, Cristina H.

2009-01-01

The magnetic fields that drive solar activity are complex and inherently three-dimensional structures. Twisted flux ropes, magnetic reconnection and the initiation of solar storms, as well as space weather propagation through the heliosphere, are just a few of the topics that cannot properly be observed or modeled in only two dimensions. Examination of this three-dimensional complex has been hampered by the fact that solar remote sensing observations have occurred only from the Earth-Sun line, and in situ observations, while available from a greater variety of locations, have been sparse throughout the heliosphere.

Three-Dimensional Arrangement of Human Bone Marrow Microvessels Revealed by Immunohistology in Undecalcified Sections

PubMed Central

Wilhelmi, Verena; Seiler, Anja; Lampp, Katrin; Neff, Andreas; Guthe, Michael; Lobachev, Oleg

2016-01-01

The arrangement of microvessels in human bone marrow is so far unknown. We combined monoclonal antibodies against CD34 and against CD141 to visualise all microvessel endothelia in 21 serial sections of about 1 cm2 size derived from a human iliac crest. The specimen was not decalcified and embedded in Technovit® 9100. In different regions of interest, the microvasculature was reconstructed in three dimensions using automatic methods. The three-dimensional models were subject to a rigid semiautomatic and manual quality control. In iliac crest bone marrow, the adipose tissue harbours irregularly distributed haematopoietic areas. These are fed by networks of large sinuses, which are loosely connected to networks of small capillaries prevailing in areas of pure adipose tissue. Our findings are compatible with the hypothesis that capillaries and sinuses in human iliac crest bone marrow are partially arranged in parallel. PMID:27997569

Syntheses, crystal structures, and properties of four complexes based on polycarboxylate and imidazole ligands

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

Qiao, Rui; Chen, Shui-Sheng, E-mail: chenss@fync.edu.cn; Coordination Chemistry Institute, State Key Laboratory of Coordination Chemistry, Nanjing University, Nanjing 210093

2015-08-15

Four metal–organic coordination polymers [Zn(HL)(H{sub 2}O)]·4H{sub 2}O (1), [Zn(HL)(L{sub 1})]·4H{sub 2}O (2), [Cu(HL)(H{sub 2}O)]·3H{sub 2}O (3) and [Cu(HL)(L{sub 1})]·5H{sub 2}O (4) were synthesized by reactions of the corresponding metal(II) salts with semirigid polycarboxylate ligand (5-((4-carboxypiperidin-1-yl)methyl)isophthalic acid hydrochloride, H{sub 3}L·HCl) or auxiliary ligand (1,4-di(1H-imidazol-4-yl)benzene, L{sub 1}). The structures of the compounds were characterized by elemental analysis, FT-IR spectroscopy and single-crystal X-ray diffraction. The use of auxiliary ligand L{sub 1} has great influence on the structures of two pairs of complexes 1, 2 and 3, 4. Complex 1 is a uninodal 3-connected rare 2-fold interpenetrating ZnSc net with a Point (Schlafli) symbolmore » of (10{sup 3}) while 2 is a one-dimensional (1D) ladder structure. Compound 3 features a two-dimensional (2D) honeycomb network with typical 6{sup 3}-hcb topology, while 4 is 2D network with (4, 4) sql topology based on binuclear Cu{sup II} subunits. The non-covalent bonding interactions such as hydrogen bonds, π···π stacking and C–H···π exist in complexes 1–4, which contributes to stabilize crystal structure and extend the low-dimensional entities into high-dimensional frameworks. And the photoluminescent property of 1 and 2 and gas sorption property of 4 have been investigated. - Graphical abstract: Four new coordination polymers have been obtained and their photoluminescent and gas sorption properties have also been investigated. - Highlights: • Two pairs of Zn{sup II}/ Cu{sup II} compounds have been synthesized. • Auxiliary ligand-controlled assembly of the complexes is reported. • The luminescent properties of complexes 1–2 were investigated. • The gas sorption property of 4 has been investigated.« less

Microwave imaging by three-dimensional Born linearization of electromagnetic scattering

NASA Astrophysics Data System (ADS)

Caorsi, S.; Gragnani, G. L.; Pastorino, M.

1990-11-01

An approach to microwave imaging is proposed that uses a three-dimensional vectorial form of the Born approximation to linearize the equation of electromagnetic scattering. The inverse scattering problem is numerically solved for three-dimensional geometries by means of the moment method. A pseudoinversion algorithm is adopted to overcome ill conditioning. Results show that the method is well suited for qualitative imaging purposes, while its capability for exactly reconstructing the complex dielectric permittivity is affected by the limitations inherent in the Born approximation and in ill conditioning.

Three-dimensional nanomagnetism

DOE PAGES

Fernandez-Pacheco, Amalio; Streubel, Robert; Fruchart, Olivier; ...

2017-06-09

Magnetic nanostructures are being developed for use in many aspects of our daily life, spanning areas such as data storage, sensing and biomedicine. Whereas patterned nanomagnets are traditionally two-dimensional planar structures, recent work is expanding nanomagnetism into three dimensions; a move triggered by the advance of unconventional synthesis methods and the discovery of new magnetic effects. In three-dimensional nanomagnets more complex magnetic configurations become possible, many with unprecedented properties. Here we review the creation of these structures and their implications for the emergence of new physics, the development of instrumentation and computational methods, and exploitation in numerous applications.

Nanorobotics control design: a collective behavior approach for medicine

NASA Astrophysics Data System (ADS)

Cavalcanti, A.; Freitas, R. A., Jr.

2005-06-01

The authors present a new approach using genetic algorithms, neural networks, and nanorobotics concepts applied to the problem of control design for nanoassembly automation and its application in medicine. As a practical approach to validate the proposed design, we have elaborated and simulated a virtual environment focused on control automation for nanorobotics teams that exhibit collective behavior. This collective behavior is a suitable way to perform a large range of tasks and positional assembly manipulation in a complex three-dimensional workspace. We emphasize the application of such techniques as a feasible approach for the investigation of nanorobotics system design in nanomedicine. Theoretical and practical analyses of control modeling is one important aspect that will enable rapid development in the emerging field of nanotechnology.

Bromidotetra-kis-(1H-2-ethyl-5-methyl-imidazole-κN)copper(II) bromide.

PubMed

Godlewska, Sylwia; Baranowska, Katarzyna; Socha, Joanna; Dołęga, Anna

2011-12-01

The Cu(II) ion in the title compound, [CuBr(C(6)H(10)N(2))(4)]Br, is coordinated in a square-based-pyramidal geometry by the N atoms of four imidazole ligands and a bromide anion in the apical site. Both the Cu(II) and Br(-) atoms lie on a crystallographic fourfold axis. In the crystal, the [CuBr(C(6)H(10)N(2))(4)](+) complex cations are linked to the uncoordinated Br(-) anions (site symmetry [Formula: see text]) by N-H⋯Br hydrogen bonds, generating a three-dimensional network. The ethyl group of the imidazole ligand was modelled as disordered over two orientations with occupancies of 0.620 (8) and 0.380 (8).

Glossary of fault and other fracture networks

NASA Astrophysics Data System (ADS)

Peacock, D. C. P.; Nixon, C. W.; Rotevatn, A.; Sanderson, D. J.; Zuluaga, L. F.

2016-11-01

Increased interest in the two- and three-dimensional geometries and development of faults and other types of fractures in rock has led to an increasingly bewildering terminology. Here we give definitions for the geometric, topological, kinematic and mechanical relationships between geological faults and other types of fractures, focussing on how they relate to form networks.

Guiding Neuronal Growth in Tissues with Light

DTIC Science & Technology

2010-02-27

and structural properties of their surroundings in addition to the biochemical properties. Furthermore, three-dimensional biopolymer matrices provide...Properties of Biopolymer Networks Biopolymer networks exhibit unique nonlinear rheological behavior that differs dramatically from most synthetic...and presumably other biopolymers , is not well defined in variable gap geometries. These findings have broad implications for the interpretation of

Analysis of HRCT-derived xylem network reveals reverse flow in some vessels

USDA-ARS?s Scientific Manuscript database

Flow in xylem vessels is modeled based on constructions of three dimensional xylem networks derived from High Resolution Computed Tomography (HRCT) images of grapevine (Vitis vinifera) stems. Flow in 6-14% of the vessels was found to be oriented in the opposite direction to the bulk flow under norma...

dfnWorks: A discrete fracture network framework for modeling subsurface flow and transport

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

Hyman, Jeffrey D.; Karra, Satish; Makedonska, Nataliia

DFNWORKS is a parallelized computational suite to generate three-dimensional discrete fracture networks (DFN) and simulate flow and transport. Developed at Los Alamos National Laboratory over the past five years, it has been used to study flow and transport in fractured media at scales ranging from millimeters to kilometers. The networks are created and meshed using DFNGEN, which combines FRAM (the feature rejection algorithm for meshing) methodology to stochastically generate three-dimensional DFNs with the LaGriT meshing toolbox to create a high-quality computational mesh representation. The representation produces a conforming Delaunay triangulation suitable for high performance computing finite volume solvers in anmore » intrinsically parallel fashion. Flow through the network is simulated in dfnFlow, which utilizes the massively parallel subsurface flow and reactive transport finite volume code PFLOTRAN. A Lagrangian approach to simulating transport through the DFN is adopted within DFNTRANS to determine pathlines and solute transport through the DFN. Example applications of this suite in the areas of nuclear waste repository science, hydraulic fracturing and CO 2 sequestration are also included.« less

View-invariant gait recognition method by three-dimensional convolutional neural network

NASA Astrophysics Data System (ADS)

Xing, Weiwei; Li, Ying; Zhang, Shunli

2018-01-01

Gait as an important biometric feature can identify a human at a long distance. View change is one of the most challenging factors for gait recognition. To address the cross view issues in gait recognition, we propose a view-invariant gait recognition method by three-dimensional (3-D) convolutional neural network. First, 3-D convolutional neural network (3DCNN) is introduced to learn view-invariant feature, which can capture the spatial information and temporal information simultaneously on normalized silhouette sequences. Second, a network training method based on cross-domain transfer learning is proposed to solve the problem of the limited gait training samples. We choose the C3D as the basic model, which is pretrained on the Sports-1M and then fine-tune C3D model to adapt gait recognition. In the recognition stage, we use the fine-tuned model to extract gait features and use Euclidean distance to measure the similarity of gait sequences. Sufficient experiments are carried out on the CASIA-B dataset and the experimental results demonstrate that our method outperforms many other methods.

dfnWorks: A discrete fracture network framework for modeling subsurface flow and transport

DOE PAGES

Hyman, Jeffrey D.; Karra, Satish; Makedonska, Nataliia; ...

2015-11-01

DFNWORKS is a parallelized computational suite to generate three-dimensional discrete fracture networks (DFN) and simulate flow and transport. Developed at Los Alamos National Laboratory over the past five years, it has been used to study flow and transport in fractured media at scales ranging from millimeters to kilometers. The networks are created and meshed using DFNGEN, which combines FRAM (the feature rejection algorithm for meshing) methodology to stochastically generate three-dimensional DFNs with the LaGriT meshing toolbox to create a high-quality computational mesh representation. The representation produces a conforming Delaunay triangulation suitable for high performance computing finite volume solvers in anmore » intrinsically parallel fashion. Flow through the network is simulated in dfnFlow, which utilizes the massively parallel subsurface flow and reactive transport finite volume code PFLOTRAN. A Lagrangian approach to simulating transport through the DFN is adopted within DFNTRANS to determine pathlines and solute transport through the DFN. Example applications of this suite in the areas of nuclear waste repository science, hydraulic fracturing and CO 2 sequestration are also included.« less

Deffuant model of opinion formation in one-dimensional multiplex networks

NASA Astrophysics Data System (ADS)

Shang, Yilun

2015-10-01

Complex systems in the real world often operate through multiple kinds of links connecting their constituents. In this paper we propose an opinion formation model under bounded confidence over multiplex networks, consisting of edges at different topological and temporal scales. We determine rigorously the critical confidence threshold by exploiting probability theory and network science when the nodes are arranged on the integers, {{Z}}, evolving in continuous time. It is found that the existence of ‘multiplexity’ impedes the convergence, and that working with the aggregated or summarized simplex network is inaccurate since it misses vital information. Analytical calculations are confirmed by extensive numerical simulations.

Mammalian Cardiovascular Patterning as Determined by Hemodynamic Forces and Blood Vessel Genetics

NASA Astrophysics Data System (ADS)

Anderson, Gregory Arthur

Cardiovascular development is a process that involves the timing of multiple molecular events, and numerous subtle three-dimensional conformational changes. Traditional developmental biology techniques have provided large quantities of information as to how these complex organ systems develop. However, the major drawback of the majority of current developmental biological imaging is that they are two-dimensional in nature. It is now well recognized that circulation of blood is required for normal patterning and remodeling of blood vessels. Normal blood vessel formation is dependent upon a complex network of signaling pathways, and genetic mutations in these pathways leads to impaired vascular development, heart failure, and lethality. As such, it is not surprising that mutant mice with aberrant cardiovascular patterning are so common, since normal development requires proper coordination between three systems: the heart, the blood, and the vasculature. This thesis describes the implementation of a three-dimensional imaging technique, optical projection tomography (OPT), in conjunction with a computer-based registration algorithm to statistically analyze developmental differences in groups of wild-type mouse embryos. Embryos that differ by only a few hours' gestational time are shown to have developmental differences in blood vessel formation and heart development progression that can be discerned. This thesis describes how we analyzed mouse models of cardiovascular perturbation by OPT to detect morphological differences in embryonic development in both qualitative and quantitative ways. Both a blood vessel specific mutation and a cardiac specific mutation were analyzed, providing evidence that developmental defects of these types can be quantified. Finally, we describe the implementation of OPT imaging to identify statistically significant phenotypes from three different mouse models of cardiovascular perturbation across a range of developmental time points. Image registration methods, combined with intensity- and deformation-based analyses are described and utilized to fully characterize myosin light chain 2a (Mlc2a), delta-like ligand 4 (Dll4), and Endoglin (Eng) mutant mouse embryos. We show that Eng mutant embryos are statistically similar to the Mlc2a phenotype, confirming that these mouse mutants suffer from a primary cardiac developmental defect. Thus, a loss of hemodynamic force caused by defective pumping of the heart is the primary developmental defect affecting these mice.

Chromosome organizaton in simple and complex unicellular organisms.

PubMed

O'Sullivan, Justin M

2011-01-01

The genomes of unicellular organisms form complex 3-dimensional structures. This spatial organization is hypothesized to have a significant role in genomic function. Spatial organization is not limited solely to the three-dimensional folding of the chromosome(s) in genomes but also includes genome positioning, and the folding and compartmentalization of any additional genetic material (e.g. episomes) present within complex genomes. In this comment, I will highlight similarities in the spatial organization of eukaryotic and prokaryotic unicellular genomes.

Cascade exciton-pumping engines with manipulated speed and efficiency in light-harvesting porous π-network films

PubMed Central

Gu, Cheng; Huang, Ning; Xu, Fei; Gao, Jia; Jiang, Donglin

2015-01-01

Light-harvesting antennae are the machinery for exciton pumping in natural photosynthesis, whereas cascade energy transfer through chlorophyll is key to long-distance, efficient energy transduction. Numerous artificial antennae have been developed. However, they are limited in their cascade energy-transfer abilities because of a lack of control over complex chromophore aggregation processes, which has impeded their advancement. Here we report a viable approach for addressing this issue by using a light-harvesting porous polymer film in which a three-dimensional π-network serves as the antenna and micropores segregate multiple dyes to prevent aggregation. Cascade energy-transfer engines are integrated into the films; the rate and efficiency of the energy-funneling engines are precisely manipulated by tailoring the dye components and contents. The nanofilms allow accurate and versatile luminescence engineering, resulting in the production of thirty emission hues, including blue, green, red and white. This advance may open new pathways for realising photosynthesis and photoenergy conversion. PMID:25746459

Viscoelastic and Functional Properties of Cod-Bone Gelatin in the Presence of Xylitol and Stevioside

NASA Astrophysics Data System (ADS)

Nian, Linyu; Cao, Ailing; Wang, Jing; Tian, Hongyu; Liu, Yongguo; Gong, Lingxiao; Cai, Luyun; Wang, Yuhao

2018-05-01

The physical, rheological, structural and functional properties of cod bone gelatin (CBG) with various concentrations (0, 2, 4, 6, 10 and 15%) of low-calorie sweeteners (xylitol (X) and stevioside (S)) to form gels were investigated. The gel strength of CBGX increased with increased xylitol due presumably to hydrogen bonds between xylitol and gelatin, but with CBGS the highest gel strength occurred when S concentration was 4%. Viscosity of CBGS samples were higher than CBGX due to S’s high molecular mass. The viscoelasticity (G' and G″), foaming capacity and fat binding capacity of CBGX were higher while foam stability was lower. The emulsion activity and emulsion stability of CBGX were a little lower than CBGS at the same concentration. The structure of X is linear making it easier to form a dense three-dimensional network structure, while the complex cyclic structure of S had more difficulty forming a network structure with cod bone gelatin. Therefore, X may be a better choice for sweetening gelatin gels.

Directed assembly of bio-inspired hierarchical materials with controlled nanofibrillar architectures

NASA Astrophysics Data System (ADS)

Tseng, Peter; Napier, Bradley; Zhao, Siwei; Mitropoulos, Alexander N.; Applegate, Matthew B.; Marelli, Benedetto; Kaplan, David L.; Omenetto, Fiorenzo G.

2017-05-01

In natural systems, directed self-assembly of structural proteins produces complex, hierarchical materials that exhibit a unique combination of mechanical, chemical and transport properties. This controlled process covers dimensions ranging from the nano- to the macroscale. Such materials are desirable to synthesize integrated and adaptive materials and systems. We describe a bio-inspired process to generate hierarchically defined structures with multiscale morphology by using regenerated silk fibroin. The combination of protein self-assembly and microscale mechanical constraints is used to form oriented, porous nanofibrillar networks within predesigned macroscopic structures. This approach allows us to predefine the mechanical and physical properties of these materials, achieved by the definition of gradients in nano- to macroscale order. We fabricate centimetre-scale material geometries including anchors, cables, lattices and webs, as well as functional materials with structure-dependent strength and anisotropic thermal transport. Finally, multiple three-dimensional geometries and doped nanofibrillar constructs are presented to illustrate the facile integration of synthetic and natural additives to form functional, interactive, hierarchical networks.

Colloidal inverse bicontinuous cubic membranes of block copolymers with tunable surface functional groups

NASA Astrophysics Data System (ADS)

La, Yunju; Park, Chiyoung; Shin, Tae Joo; Joo, Sang Hoon; Kang, Sebyung; Kim, Kyoung Taek

2014-06-01

Analogous to the complex membranes found in cellular organelles, such as the endoplasmic reticulum, the inverse cubic mesophases of lipids and their colloidal forms (cubosomes) possess internal networks of water channels arranged in crystalline order, which provide a unique nanospace for membrane-protein crystallization and guest encapsulation. Polymeric analogues of cubosomes formed by the direct self-assembly of block copolymers in solution could provide new polymeric mesoporous materials with a three-dimensionally organized internal maze of large water channels. Here we report the self-assembly of amphiphilic dendritic-linear block copolymers into polymer cubosomes in aqueous solution. The presence of precisely defined bulky dendritic blocks drives the block copolymers to form spontaneously highly curved bilayers in aqueous solution. This results in the formation of colloidal inverse bicontinuous cubic mesophases. The internal networks of water channels provide a high surface area with tunable surface functional groups that can serve as anchoring points for large guests such as proteins and enzymes.

Viscoelastic and Functional Properties of Cod-Bone Gelatin in the Presence of Xylitol and Stevioside.

PubMed

Nian, Linyu; Cao, Ailing; Wang, Jing; Tian, Hongyu; Liu, Yongguo; Gong, Lingxiao; Cai, Luyun; Wang, Yuhao

2018-01-01

The physical, rheological, structural and functional properties of cod bone gelatin (CBG) with various concentrations (0, 2, 4, 6, 10, and 15%) of low-calorie sweeteners [xylitol (X) and stevioside (S)] to form gels were investigated. The gel strength of CBGX increased with increased xylitol due presumably to hydrogen bonds between xylitol and gelatin, but with CBGS the highest gel strength occurred when S concentration was 4%. Viscosity of CBGS samples were higher than CBGX due to S's high molecular mass. The viscoelasticity (G' and G''), foaming capacity and fat binding capacity of CBGX were higher while foam stability was lower. The emulsion activity and emulsion stability of CBGX were a little lower than CBGS at the same concentration. The structure of X is linear making it easier to form a dense three-dimensional network structure, while the complex cyclic structure of S had more difficulty forming a network structure with cod bone gelatin. Therefore, X may be a better choice for sweetening gelatin gels.

A new paper-based platform technology for point-of-care diagnostics.

PubMed

Gerbers, Roman; Foellscher, Wilke; Chen, Hong; Anagnostopoulos, Constantine; Faghri, Mohammad

2014-10-21

Currently, the Lateral flow Immunoassays (LFIAs) are not able to perform complex multi-step immunodetection tests because of their inability to introduce multiple reagents in a controlled manner to the detection area autonomously. In this research, a point-of-care (POC) paper-based lateral flow immunosensor was developed incorporating a novel microfluidic valve technology. Layers of paper and tape were used to create a three-dimensional structure to form the fluidic network. Unlike the existing LFIAs, multiple directional valves are embedded in the test strip layers to control the order and the timing of mixing for the sample and multiple reagents. In this paper, we report a four-valve device which autonomously directs three different fluids to flow sequentially over the detection area. As proof of concept, a three-step alkaline phosphatase based Enzyme-Linked ImmunoSorbent Assay (ELISA) protocol with Rabbit IgG as the model analyte was conducted to prove the suitability of the device for immunoassays. The detection limit of about 4.8 fm was obtained.

Three-dimensional macroporous nanoelectronic networks as minimally invasive brain probes

NASA Astrophysics Data System (ADS)

Xie, Chong; Liu, Jia; Fu, Tian-Ming; Dai, Xiaochuan; Zhou, Wei; Lieber, Charles M.

2015-12-01

Direct electrical recording and stimulation of neural activity using micro-fabricated silicon and metal micro-wire probes have contributed extensively to basic neuroscience and therapeutic applications; however, the dimensional and mechanical mismatch of these probes with the brain tissue limits their stability in chronic implants and decreases the neuron-device contact. Here, we demonstrate the realization of a three-dimensional macroporous nanoelectronic brain probe that combines ultra-flexibility and subcellular feature sizes to overcome these limitations. Built-in strains controlling the local geometry of the macroporous devices are designed to optimize the neuron/probe interface and to promote integration with the brain tissue while introducing minimal mechanical perturbation. The ultra-flexible probes were implanted frozen into rodent brains and used to record multiplexed local field potentials and single-unit action potentials from the somatosensory cortex. Significantly, histology analysis revealed filling-in of neural tissue through the macroporous network and attractive neuron-probe interactions, consistent with long-term biocompatibility of the device.

Three-dimensional description and mathematical characterization of the parasellar internal carotid artery in human infants

PubMed Central

Meng, Stefan; da F Costa, Luciano; Geyer, Stefan H; Viana, Matheus P; Reiter, Christian; Müller, Gerd B; Weninger, Wolfgang J

2008-01-01

Inside the ‘cavernous sinus’ or ‘parasellar region’ the human internal carotid artery takes the shape of a siphon that is twisted and torqued in three dimensions and surrounded by a network of veins. The parasellar section of the internal carotid artery is of broad biological and medical interest, as its peculiar shape is associated with temperature regulation in the brain and correlated with the occurrence of vascular pathologies. The present study aims to provide anatomical descriptions and objective mathematical characterizations of the shape of the parasellar section of the internal carotid artery in human infants and its modifications during ontogeny. Three-dimensional (3D) computer models of the parasellar section of the internal carotid artery of infants were generated with a state-of-the-art 3D reconstruction method and analysed using both traditional morphometric methods and novel mathematical algorithms. We show that four constant, demarcated bends can be described along the infant parasellar section of the internal carotid artery, and we provide measurements of their angles. We further provide calculations of the curvature and torsion energy, and the total complexity of the 3D skeleton of the parasellar section of the internal carotid artery, and compare the complexity of this in infants and adults. Finally, we examine the relationship between shape parameters of the parasellar section of the internal carotid artery in infants, and the occurrence of intima cushions, and evaluate the reliability of subjective angle measurements for characterizing the complexity of the parasellar section of the internal carotid artery in infants. The results can serve as objective reference data for comparative studies and for medical imaging diagnostics. They also form the basis for a new hypothesis that explains the mechanisms responsible for the ontogenetic transformation in the shape of the parasellar section of the internal carotid artery. PMID:18397239

Automatic blocking for complex three-dimensional configurations

NASA Technical Reports Server (NTRS)

Dannenhoffer, John F., III

1995-01-01

A new blocking technique for complex three-dimensional configurations is described. This new technique is based upon the concept of an abstraction, or squared-up representation, of the configuration and the associated grid. By allowing the user to describe blocking requirements in natural terms (such as 'wrap a grid around this leading edge' or 'make all grid lines emanating from this wall orthogonal to it'), users can quickly generate complex grids around complex configurations, while still maintaining a high level of control where desired. An added advantage of the abstraction concept is that once a blocking is defined for a class of configurations, it can be automatically applied to other configurations of the same class, making the new technique particularly well suited for the parametric variations which typically occur during design processes. Grids have been generated for a variety of real-world, two- and three-dimensional configurations. In all cases, the time required to generate the grid, given just an electronic form of the configuration, was at most a few days. Hence with this new technique, the generation of a block-structured grid is only slightly more expensive than the generation of an unstructured grid for the same configuration.

3D coordination polymers with nitrilotriacetic and 4,4'-bipyridyl mixed ligands: structural variation based on dinuclear or tetranuclear subunits assisted by Na-O and/or O-H...O interactions.

PubMed

Lü, Xing-Qiang; Jiang, Ji-Jun; Chen, Chun-Long; Kang, Bei-Sheng; Su, Cheng-Yong

2005-06-27

The reactions of Cu(II) with the mixed nitrilotriacetic acid (H3NTA) and 4,4'-bipyridyl (4,4'-bpy) ligands in different metal-to-ligand ratios in the presence of NaOH and NaClO4 afforded two complexes, Na3[Cu2(NTA)2(4,4'-bpy)]ClO4 x 5H2O (1) and [Cu2(NTA) (4,4'-bpy)2]ClO4 x 4H2O (2). The two complexes have been characterized by elemental analysis, IR, XRD, and single-crystal X-ray diffraction. 1 contains a basic doubly negatively charged [Cu2(NTA)2(4,4'-bpy)]2- dinuclear unit which was further assembled via multiple Na-O and O-H...O interactions into a three-dimensional (3D) pillared-layer structure. 2 features a two-dimensional (2D) undulated brick-wall architecture containing a basic doubly positively charged [Cu4(NTA)2(4,4'-bpy)2]2+ tetranuclear unit. The 2D network possesses large cavities hosting guest molecules and was further assembled via O-H...O hydrogen bonds into a 3D structure with several channels running in different directions.

Singularities of Three-Layered Complex-Valued Neural Networks With Split Activation Function.

PubMed

Kobayashi, Masaki

2018-05-01

There are three important concepts related to learning processes in neural networks: reducibility, nonminimality, and singularity. Although the definitions of these three concepts differ, they are equivalent in real-valued neural networks. This is also true of complex-valued neural networks (CVNNs) with hidden neurons not employing biases. The situation of CVNNs with hidden neurons employing biases, however, is very complicated. Exceptional reducibility was found, and it was shown that reducibility and nonminimality are not the same. Irreducibility consists of minimality and exceptional reducibility. The relationship between minimality and singularity has not yet been established. In this paper, we describe our surprising finding that minimality and singularity are independent. We also provide several examples based on exceptional reducibility.

Selection of bi-level image compression method for reduction of communication energy in wireless visual sensor networks

NASA Astrophysics Data System (ADS)

Khursheed, Khursheed; Imran, Muhammad; Ahmad, Naeem; O'Nils, Mattias

2012-06-01

Wireless Visual Sensor Network (WVSN) is an emerging field which combines image sensor, on board computation unit, communication component and energy source. Compared to the traditional wireless sensor network, which operates on one dimensional data, such as temperature, pressure values etc., WVSN operates on two dimensional data (images) which requires higher processing power and communication bandwidth. Normally, WVSNs are deployed in areas where installation of wired solutions is not feasible. The energy budget in these networks is limited to the batteries, because of the wireless nature of the application. Due to the limited availability of energy, the processing at Visual Sensor Nodes (VSN) and communication from VSN to server should consume as low energy as possible. Transmission of raw images wirelessly consumes a lot of energy and requires higher communication bandwidth. Data compression methods reduce data efficiently and hence will be effective in reducing communication cost in WVSN. In this paper, we have compared the compression efficiency and complexity of six well known bi-level image compression methods. The focus is to determine the compression algorithms which can efficiently compress bi-level images and their computational complexity is suitable for computational platform used in WVSNs. These results can be used as a road map for selection of compression methods for different sets of constraints in WVSN.

Aerodynamic Shape Sensitivity Analysis and Design Optimization of Complex Configurations Using Unstructured Grids

NASA Technical Reports Server (NTRS)

Taylor, Arthur C., III; Newman, James C., III; Barnwell, Richard W.

1997-01-01

A three-dimensional unstructured grid approach to aerodynamic shape sensitivity analysis and design optimization has been developed and is extended to model geometrically complex configurations. The advantage of unstructured grids (when compared with a structured-grid approach) is their inherent ability to discretize irregularly shaped domains with greater efficiency and less effort. Hence, this approach is ideally suited for geometrically complex configurations of practical interest. In this work the nonlinear Euler equations are solved using an upwind, cell-centered, finite-volume scheme. The discrete, linearized systems which result from this scheme are solved iteratively by a preconditioned conjugate-gradient-like algorithm known as GMRES for the two-dimensional geometry and a Gauss-Seidel algorithm for the three-dimensional; similar procedures are used to solve the accompanying linear aerodynamic sensitivity equations in incremental iterative form. As shown, this particular form of the sensitivity equation makes large-scale gradient-based aerodynamic optimization possible by taking advantage of memory efficient methods to construct exact Jacobian matrix-vector products. Simple parameterization techniques are utilized for demonstrative purposes. Once the surface has been deformed, the unstructured grid is adapted by considering the mesh as a system of interconnected springs. Grid sensitivities are obtained by differentiating the surface parameterization and the grid adaptation algorithms with ADIFOR (which is an advanced automatic-differentiation software tool). To demonstrate the ability of this procedure to analyze and design complex configurations of practical interest, the sensitivity analysis and shape optimization has been performed for a two-dimensional high-lift multielement airfoil and for a three-dimensional Boeing 747-200 aircraft.

Feasibility of using sodium chloride as a tracer for the characterization of the distribution of matter in complex multi-compartment 3D bioreactors for stem cell culture.

PubMed

Gerlach, Jörg C; Witaschek, Tom; Strobel, Catrin; Brayfield, Candace A; Bornemann, Reinhard; Catapano, Gerardo; Zeilinger, Katrin

2010-06-01

The experimental characterization of the distribution of matter in complex multi-compartment three-dimensional membrane bioreactors for human cell culture is complicated by tracer interactions with the membranes and other bioreactor constituents. This is due to the fact that membranes with a high specific surface area often feature a hydrophobic chemical backbone that may adsorb tracers often used to this purpose, such as proteins and dyes. Membrane selectivity, and its worsening caused by protein adsorption, may also hinder tracer transfer across neighboring compartments, thus preventing effective characterization of the distribution of matter in the whole bioreactor. Tracer experiments with sodium chloride (NaCl) may overcome some of these limitations and be effectively used to characterize the distribution of matter in complex 3D multi-compartments membrane bioreactors for stem cell culture. NaCl freely permeates most used membranes, it does not adsorb on uncharged membranes, and its concentration may be accurately measured in terms of solution conductivity. In this preliminary study, the feasibility of complex multi-compartment membrane bioreactors was investigated with a NaCl concentration pulse challenge to characterize how their distribution of matter changes when they are operated under different conditions. In particular, bioreactors consisting of three different membrane types stacked on top of one another to form a 3D network were characterized under different feed conditions.

Numerical solution to the glancing sidewall oblique shock wave/turbulent boundary layer interaction in three dimension

NASA Technical Reports Server (NTRS)

Anderson, B. H.; Benson, T. J.

1983-01-01

A supersonic three-dimensional viscous forward-marching computer design code called PEPSIS is used to obtain a numerical solution of the three-dimensional problem of the interaction of a glancing sidewall oblique shock wave and a turbulent boundary layer. Very good results are obtained for a test case that was run to investigate the use of the wall-function boundary-condition approximation for a highly complex three-dimensional shock-boundary layer interaction. Two additional test cases (coarse mesh and medium mesh) are run to examine the question of near-wall resolution when no-slip boundary conditions are applied. A comparison with experimental data shows that the PEPSIS code gives excellent results in general and is practical for three-dimensional supersonic inlet calculations.

Numerical solution to the glancing sidewall oblique shock wave/turbulent boundary layer interaction in three-dimension

NASA Technical Reports Server (NTRS)

Anderson, B. H.; Benson, T. J.

1983-01-01

A supersonic three-dimensional viscous forward-marching computer design code called PEPSIS is used to obtain a numerical solution of the three-dimensional problem of the interaction of a glancing sidewall oblique shock wave and a turbulent boundary layer. Very good results are obtained for a test case that was run to investigate the use of the wall-function boundary-condition approximation for a highly complex three-dimensional shock-boundary layer interaction. Two additional test cases (coarse mesh and medium mesh) are run to examine the question of near-wall resolution when no-slip boundary conditions are applied. A comparison with experimental data shows that the PEPSIS code gives excellent results in general and is practical for three-dimensional supersonic inlet calculations.

Design of hybrid radial basis function neural networks (HRBFNNs) realized with the aid of hybridization of fuzzy clustering method (FCM) and polynomial neural networks (PNNs).

PubMed

Huang, Wei; Oh, Sung-Kwun; Pedrycz, Witold

2014-12-01

In this study, we propose Hybrid Radial Basis Function Neural Networks (HRBFNNs) realized with the aid of fuzzy clustering method (Fuzzy C-Means, FCM) and polynomial neural networks. Fuzzy clustering used to form information granulation is employed to overcome a possible curse of dimensionality, while the polynomial neural network is utilized to build local models. Furthermore, genetic algorithm (GA) is exploited here to optimize the essential design parameters of the model (including fuzzification coefficient, the number of input polynomial fuzzy neurons (PFNs), and a collection of the specific subset of input PFNs) of the network. To reduce dimensionality of the input space, principal component analysis (PCA) is considered as a sound preprocessing vehicle. The performance of the HRBFNNs is quantified through a series of experiments, in which we use several modeling benchmarks of different levels of complexity (different number of input variables and the number of available data). A comparative analysis reveals that the proposed HRBFNNs exhibit higher accuracy in comparison to the accuracy produced by some models reported previously in the literature. Copyright © 2014 Elsevier Ltd. All rights reserved.

Identifying the starting point of a spreading process in complex networks.

PubMed

Comin, Cesar Henrique; Costa, Luciano da Fontoura

2011-11-01

When dealing with the dissemination of epidemics, one important question that can be asked is the location where the contamination began. In this paper, we analyze three spreading schemes and propose and validate an effective methodology for the identification of the source nodes. The method is based on the calculation of the centrality of the nodes on the sampled network, expressed here by degree, betweenness, closeness, and eigenvector centrality. We show that the source node tends to have the highest measurement values. The potential of the methodology is illustrated with respect to three theoretical complex network models as well as a real-world network, the email network of the University Rovira i Virgili.

Finite-time scaling at the Anderson transition for vibrations in solids

NASA Astrophysics Data System (ADS)

Beltukov, Y. M.; Skipetrov, S. E.

2017-11-01

A model in which a three-dimensional elastic medium is represented by a network of identical masses connected by springs of random strengths and allowed to vibrate only along a selected axis of the reference frame exhibits an Anderson localization transition. To study this transition, we assume that the dynamical matrix of the network is given by a product of a sparse random matrix with real, independent, Gaussian-distributed nonzero entries and its transpose. A finite-time scaling analysis of the system's response to an initial excitation allows us to estimate the critical parameters of the localization transition. The critical exponent is found to be ν =1.57 ±0.02 , in agreement with previous studies of the Anderson transition belonging to the three-dimensional orthogonal universality class.

Dimensionality-varied deep convolutional neural network for spectral-spatial classification of hyperspectral data

NASA Astrophysics Data System (ADS)

Qu, Haicheng; Liang, Xuejian; Liang, Shichao; Liu, Wanjun

2018-01-01

Many methods of hyperspectral image classification have been proposed recently, and the convolutional neural network (CNN) achieves outstanding performance. However, spectral-spatial classification of CNN requires an excessively large model, tremendous computations, and complex network, and CNN is generally unable to use the noisy bands caused by water-vapor absorption. A dimensionality-varied CNN (DV-CNN) is proposed to address these issues. There are four stages in DV-CNN and the dimensionalities of spectral-spatial feature maps vary with the stages. DV-CNN can reduce the computation and simplify the structure of the network. All feature maps are processed by more kernels in higher stages to extract more precise features. DV-CNN also improves the classification accuracy and enhances the robustness to water-vapor absorption bands. The experiments are performed on data sets of Indian Pines and Pavia University scene. The classification performance of DV-CNN is compared with state-of-the-art methods, which contain the variations of CNN, traditional, and other deep learning methods. The experiment of performance analysis about DV-CNN itself is also carried out. The experimental results demonstrate that DV-CNN outperforms state-of-the-art methods for spectral-spatial classification and it is also robust to water-vapor absorption bands. Moreover, reasonable parameters selection is effective to improve classification accuracy.

The effect of the neural activity on topological properties of growing neural networks.

PubMed

Gafarov, F M; Gafarova, V R

2016-09-01

The connectivity structure in cortical networks defines how information is transmitted and processed, and it is a source of the complex spatiotemporal patterns of network's development, and the process of creation and deletion of connections is continuous in the whole life of the organism. In this paper, we study how neural activity influences the growth process in neural networks. By using a two-dimensional activity-dependent growth model we demonstrated the neural network growth process from disconnected neurons to fully connected networks. For making quantitative investigation of the network's activity influence on its topological properties we compared it with the random growth network not depending on network's activity. By using the random graphs theory methods for the analysis of the network's connections structure it is shown that the growth in neural networks results in the formation of a well-known "small-world" network.

Network Approach to Disease Diagnosis

NASA Astrophysics Data System (ADS)

Sharma, Amitabh; Bashan, Amir; Barabasi, Alber-Laszlo

2014-03-01

Human diseases could be viewed as perturbations of the underlying biological system. A thorough understanding of the topological and dynamical properties of the biological system is crucial to explain the mechanisms of many complex diseases. Recently network-based approaches have provided a framework for integrating multi-dimensional biological data that results in a better understanding of the pathophysiological state of complex diseases. Here we provide a network-based framework to improve the diagnosis of complex diseases. This framework is based on the integration of transcriptomics and the interactome. We analyze the overlap between the differentially expressed (DE) genes and disease genes (DGs) based on their locations in the molecular interaction network (''interactome''). Disease genes and their protein products tend to be much more highly connected than random, hence defining a disease sub-graph (called disease module) in the interactome. DE genes, even though different from the known set of DGs, may be significantly associated with the disease when considering their closeness to the disease module in the interactome. This new network approach holds the promise to improve the diagnosis of patients who cannot be diagnosed using conventional tools. Support was provided by HL066289 and HL105339 grants from the U.S. National Institutes of Health.

Crystalline Coordination Networks of Zero-Valent Metal Centers: Formation of a 3-Dimensional Ni(0) Framework with m-Terphenyl Diisocyanides.

PubMed

Agnew, Douglas W; DiMucci, Ida M; Arroyave, Alejandra; Gembicky, Milan; Moore, Curtis E; MacMillan, Samantha N; Rheingold, Arnold L; Lancaster, Kyle M; Figueroa, Joshua S

2017-12-06

A permanently porous, three-dimensional metal-organic material formed from zero-valent metal nodes is presented. Combination of ditopic m-terphenyl diisocyanide, [CNAr Mes2 ] 2 , and the d 10 Ni(0) precursor Ni(COD) 2 , produces a porous metal-organic material featuring tetrahedral [Ni(CNAr Mes2 ) 4 ] n structural sites. X-ray absorption spectroscopy provides firm evidence for the presence of Ni(0) centers, whereas gas-sorption and thermogravimetric analysis reveal the characteristics of a robust network with a microdomain N 2 -adsorption profile.

Crystalline Coordination Networks of Zero-Valent Metal Centers: Formation of a 3-Dimensional Ni(0) Framework with m-Terphenyl Diisocyanides

DOE PAGES

Agnew, Douglas W.; DiMucci, Ida M.; Arroyave, Alejandra; ...

2017-11-13

A permanently porous, three-dimensional metal–organic material formed from zero-valent metal nodes is presented. Combination of ditopic m-terphenyl diisocyanide, [CNAr Mes2] 2, and the d 10 Ni(0) precursor Ni(COD) 2, produces a porous metal–organic material featuring tetrahedral [Ni(CNAr Mes2) 4] n structural sites. X-ray absorption spectroscopy provides firm evidence for the presence of Ni(0) centers, whereas gas-sorption and thermogravimetric analysis reveal the characteristics of a robust network with a microdomain N 2-adsorption profile.

An improved large-field focusing schlieren system

NASA Technical Reports Server (NTRS)

Weinstein, Leonard M.

1991-01-01

The analysis and performance of a high-brightness large-field focusing schlieren system is described. The system can be used to examine complex two- and three-dimensional flows. Techniques are described to obtain focusing schlieren through distorting optical elements, to use multiple colors in a time multiplexing technique, and to use diffuse screen holography for three-dimensional photographs.

Using Virtual Worlds to Identify Multidimensional Student Engagement in High School Foreign Language Learning Classrooms

ERIC Educational Resources Information Center

Jacob, Laura Beth

2012-01-01

Virtual world environments have evolved from object-oriented, text-based online games to complex three-dimensional immersive social spaces where the lines between reality and computer-generated begin to blur. Educators use virtual worlds to create engaging three-dimensional learning spaces for students, but the impact of virtual worlds in…

Modeling smoke plume patterns in drainage flows

Treesearch

M.A. Fosberg

1985-01-01

A three-dimensional diagnostic wind model for use in complex terrain has been combined with a three-dimensional trajectory and puff air quality model. The wind model utilizes a terrain following coordinate system and conserves both mass and momentum. The wind model provides the winds required by the predictive trajectory and puff dispersion model. Both the wind model...

STUDY USING A THREE-DIMENSIONAL PHOTOCHEMICAL SMOG FORMATION MODEL UNDER CONDITIONS OF COMPLEX FLOW: APPLICATION OF THE URBAN AIRSHED MODEL TO THE TOKYO METROPOLITAN AREA

EPA Science Inventory

The purpose of this study is to evaluate the Urban Airshed Model (UAM), a three-dimensional photochemical urban air quality simulation model, using field observations from the Tokyo Metropolitan Area. mphasis was placed on the photochemical smog formation mechanism under stagnant...

Three-dimensional shape transformations of hydrogel sheets induced by small-scale modulation of internal stresses

NASA Astrophysics Data System (ADS)

Wu, Zi Liang; Moshe, Michael; Greener, Jesse; Therien-Aubin, Heloise; Nie, Zhihong; Sharon, Eran; Kumacheva, Eugenia

2013-03-01

Although Nature has always been a common source of inspiration in the development of artificial materials, only recently has the ability of man-made materials to produce complex three-dimensional (3D) structures from two-dimensional sheets been explored. Here we present a new approach to the self-shaping of soft matter that mimics fibrous plant tissues by exploiting small-scale variations in the internal stresses to form three-dimensional morphologies. We design single-layer hydrogel sheets with chemically distinct, fibre-like regions that exhibit differential shrinkage and elastic moduli under the application of external stimulus. Using a planar-to-helical three-dimensional shape transformation as an example, we explore the relation between the internal architecture of the sheets and their transition to cylindrical and conical helices with specific structural characteristics. The ability to engineer multiple three-dimensional shape transformations determined by small-scale patterns in a hydrogel sheet represents a promising step in the development of programmable soft matter.

Throughput Analysis on 3-Dimensional Underwater Acoustic Network with One-Hop Mobile Relay.

PubMed

Zhong, Xuefeng; Chen, Fangjiong; Fan, Jiasheng; Guan, Quansheng; Ji, Fei; Yu, Hua

2018-01-16

Underwater acoustic communication network (UACN) has been considered as an essential infrastructure for ocean exploitation. Performance analysis of UACN is important in underwater acoustic network deployment and management. In this paper, we analyze the network throughput of three-dimensional randomly deployed transmitter-receiver pairs. Due to the long delay of acoustic channels, complicated networking protocols with heavy signaling overhead may not be appropriate. In this paper, we consider only one-hop or two-hop transmission, to save the signaling cost. That is, we assume the transmitter sends the data packet to the receiver by one-hop direct transmission, or by two-hop transmission via mobile relays. We derive the closed-form formulation of packet delivery rate with respect to the transmission delay and the number of transmitter-receiver pairs. The correctness of the derivation results are verified by computer simulations. Our analysis indicates how to obtain a precise tradeoff between the delay constraint and the network capacity.

Throughput Analysis on 3-Dimensional Underwater Acoustic Network with One-Hop Mobile Relay

PubMed Central

Zhong, Xuefeng; Fan, Jiasheng; Guan, Quansheng; Ji, Fei; Yu, Hua

2018-01-01

Underwater acoustic communication network (UACN) has been considered as an essential infrastructure for ocean exploitation. Performance analysis of UACN is important in underwater acoustic network deployment and management. In this paper, we analyze the network throughput of three-dimensional randomly deployed transmitter–receiver pairs. Due to the long delay of acoustic channels, complicated networking protocols with heavy signaling overhead may not be appropriate. In this paper, we consider only one-hop or two-hop transmission, to save the signaling cost. That is, we assume the transmitter sends the data packet to the receiver by one-hop direct transmission, or by two-hop transmission via mobile relays. We derive the closed-form formulation of packet delivery rate with respect to the transmission delay and the number of transmitter–receiver pairs. The correctness of the derivation results are verified by computer simulations. Our analysis indicates how to obtain a precise tradeoff between the delay constraint and the network capacity. PMID:29337911

Structural Information from Single-molecule FRET Experiments Using the Fast Nano-positioning System

PubMed Central

Röcker, Carlheinz; Nagy, Julia; Michaelis, Jens

2017-01-01

Single-molecule Förster Resonance Energy Transfer (smFRET) can be used to obtain structural information on biomolecular complexes in real-time. Thereby, multiple smFRET measurements are used to localize an unknown dye position inside a protein complex by means of trilateration. In order to obtain quantitative information, the Nano-Positioning System (NPS) uses probabilistic data analysis to combine structural information from X-ray crystallography with single-molecule fluorescence data to calculate not only the most probable position but the complete three-dimensional probability distribution, termed posterior, which indicates the experimental uncertainty. The concept was generalized for the analysis of smFRET networks containing numerous dye molecules. The latest version of NPS, Fast-NPS, features a new algorithm using Bayesian parameter estimation based on Markov Chain Monte Carlo sampling and parallel tempering that allows for the analysis of large smFRET networks in a comparably short time. Moreover, Fast-NPS allows the calculation of the posterior by choosing one of five different models for each dye, that account for the different spatial and orientational behavior exhibited by the dye molecules due to their local environment. Here we present a detailed protocol for obtaining smFRET data and applying the Fast-NPS. We provide detailed instructions for the acquisition of the three input parameters of Fast-NPS: the smFRET values, as well as the quantum yield and anisotropy of the dye molecules. Recently, the NPS has been used to elucidate the architecture of an archaeal open promotor complex. This data is used to demonstrate the influence of the five different dye models on the posterior distribution. PMID:28287526

Structural Information from Single-molecule FRET Experiments Using the Fast Nano-positioning System.

PubMed

Dörfler, Thilo; Eilert, Tobias; Röcker, Carlheinz; Nagy, Julia; Michaelis, Jens

2017-02-09

Single-molecule Förster Resonance Energy Transfer (smFRET) can be used to obtain structural information on biomolecular complexes in real-time. Thereby, multiple smFRET measurements are used to localize an unknown dye position inside a protein complex by means of trilateration. In order to obtain quantitative information, the Nano-Positioning System (NPS) uses probabilistic data analysis to combine structural information from X-ray crystallography with single-molecule fluorescence data to calculate not only the most probable position but the complete three-dimensional probability distribution, termed posterior, which indicates the experimental uncertainty. The concept was generalized for the analysis of smFRET networks containing numerous dye molecules. The latest version of NPS, Fast-NPS, features a new algorithm using Bayesian parameter estimation based on Markov Chain Monte Carlo sampling and parallel tempering that allows for the analysis of large smFRET networks in a comparably short time. Moreover, Fast-NPS allows the calculation of the posterior by choosing one of five different models for each dye, that account for the different spatial and orientational behavior exhibited by the dye molecules due to their local environment. Here we present a detailed protocol for obtaining smFRET data and applying the Fast-NPS. We provide detailed instructions for the acquisition of the three input parameters of Fast-NPS: the smFRET values, as well as the quantum yield and anisotropy of the dye molecules. Recently, the NPS has been used to elucidate the architecture of an archaeal open promotor complex. This data is used to demonstrate the influence of the five different dye models on the posterior distribution.

Filtering Gene Ontology semantic similarity for identifying protein complexes in large protein interaction networks.

PubMed

Wang, Jian; Xie, Dong; Lin, Hongfei; Yang, Zhihao; Zhang, Yijia

2012-06-21

Many biological processes recognize in particular the importance of protein complexes, and various computational approaches have been developed to identify complexes from protein-protein interaction (PPI) networks. However, high false-positive rate of PPIs leads to challenging identification. A protein semantic similarity measure is proposed in this study, based on the ontology structure of Gene Ontology (GO) terms and GO annotations to estimate the reliability of interactions in PPI networks. Interaction pairs with low GO semantic similarity are removed from the network as unreliable interactions. Then, a cluster-expanding algorithm is used to detect complexes with core-attachment structure on filtered network. Our method is applied to three different yeast PPI networks. The effectiveness of our method is examined on two benchmark complex datasets. Experimental results show that our method performed better than other state-of-the-art approaches in most evaluation metrics. The method detects protein complexes from large scale PPI networks by filtering GO semantic similarity. Removing interactions with low GO similarity significantly improves the performance of complex identification. The expanding strategy is also effective to identify attachment proteins of complexes.

Three-dimensional strutted graphene grown by substrate-free sugar blowing for high-power-density supercapacitors

PubMed Central

Wang, Xuebin; Zhang, Yuanjian; Zhi, Chunyi; Wang, Xi; Tang, Daiming; Xu, Yibin; Weng, Qunhong; Jiang, Xiangfen; Mitome, Masanori; Golberg, Dmitri; Bando, Yoshio

2013-01-01

Three-dimensional graphene architectures in the macroworld can in principle maintain all the extraordinary nanoscale properties of individual graphene flakes. However, current 3D graphene products suffer from poor electrical conductivity, low surface area and insufficient mechanical strength/elasticity; the interconnected self-supported reproducible 3D graphenes remain unavailable. Here we report a sugar-blowing approach based on a polymeric predecessor to synthesize a 3D graphene bubble network. The bubble network consists of mono- or few-layered graphitic membranes that are tightly glued, rigidly fixed and spatially scaffolded by micrometre-scale graphitic struts. Such a topological configuration provides intimate structural interconnectivities, freeway for electron/phonon transports, huge accessible surface area, as well as robust mechanical properties. The graphene network thus overcomes the drawbacks of presently available 3D graphene products and opens up a wide horizon for diverse practical usages, for example, high-power high-energy electrochemical capacitors, as highlighted in this work. PMID:24336225

Three-dimensional strutted graphene grown by substrate-free sugar blowing for high-power-density supercapacitors

NASA Astrophysics Data System (ADS)

Wang, Xuebin; Zhang, Yuanjian; Zhi, Chunyi; Wang, Xi; Tang, Daiming; Xu, Yibin; Weng, Qunhong; Jiang, Xiangfen; Mitome, Masanori; Golberg, Dmitri; Bando, Yoshio

2013-12-01

Three-dimensional graphene architectures in the macroworld can in principle maintain all the extraordinary nanoscale properties of individual graphene flakes. However, current 3D graphene products suffer from poor electrical conductivity, low surface area and insufficient mechanical strength/elasticity; the interconnected self-supported reproducible 3D graphenes remain unavailable. Here we report a sugar-blowing approach based on a polymeric predecessor to synthesize a 3D graphene bubble network. The bubble network consists of mono- or few-layered graphitic membranes that are tightly glued, rigidly fixed and spatially scaffolded by micrometre-scale graphitic struts. Such a topological configuration provides intimate structural interconnectivities, freeway for electron/phonon transports, huge accessible surface area, as well as robust mechanical properties. The graphene network thus overcomes the drawbacks of presently available 3D graphene products and opens up a wide horizon for diverse practical usages, for example, high-power high-energy electrochemical capacitors, as highlighted in this work.

Visible light induced electropolymerization of suspended hydrogel bioscaffolds in a microfluidic chip.

PubMed

Li, Pan; Yu, Haibo; Liu, Na; Wang, Feifei; Lee, Gwo-Bin; Wang, Yuechao; Liu, Lianqing; Li, Wen Jung

2018-05-23

The development of microengineered hydrogels co-cultured with cells in vitro could advance in vivo bio-systems in both structural complexity and functional hierarchy, which holds great promise for applications in regenerative tissues or organs, drug discovery and screening, and bio-sensors or bio-actuators. Traditional hydrogel microfabrication technologies such as ultraviolet (UV) laser or multiphoton laser stereolithography and three-dimensional (3D) printing systems have advanced the development of 3D hydrogel micro-structures but need either expensive and complex equipment, or harsh material selection with limited photoinitiators. Herein, we propose a simple and flexible hydrogel microfabrication method based on a ubiquitous visible-light projection system combined with a custom-designed photosensitive microfluidic chip, to rapidly (typically several to tens of seconds) fabricate various two-dimensional (2D) hydrogel patterns and 3D hydrogel constructs. A theoretical layer-by-layer model that involves continuous polymerizing-delaminating-polymerizing cycles is presented to explain the polymerization and structural formation mechanism of hydrogels. A large area of hydrogel patterns was efficiently fabricated without the usage of costly laser systems or photoinitiators, i.e., a stereoscopic mesh-like hydrogel network with intersecting hydrogel micro-belts was fabricated via a series of dynamic-changing digital light projections. The pores and gaps of the hydrogel network are tunable, which facilitates the supply of nutrients and discharge of waste in the construction of 3D thick bio-models. Cell co-culture experiments showed the effective regulation of cell spreading by hydrogel scaffolds fabricated by the new method presented here. This visible light enabled hydrogel microfabrication method may provide new prospects for designing cell-based units for advanced biomedical studies, e.g., for 3D bio-models or bio-actuators in the future.

3D printing of layered brain-like structures using peptide modified gellan gum substrates.

PubMed

Lozano, Rodrigo; Stevens, Leo; Thompson, Brianna C; Gilmore, Kerry J; Gorkin, Robert; Stewart, Elise M; in het Panhuis, Marc; Romero-Ortega, Mario; Wallace, Gordon G

2015-10-01

The brain is an enormously complex organ structured into various regions of layered tissue. Researchers have attempted to study the brain by modeling the architecture using two dimensional (2D) in vitro cell culturing methods. While those platforms attempt to mimic the in vivo environment, they do not truly resemble the three dimensional (3D) microstructure of neuronal tissues. Development of an accurate in vitro model of the brain remains a significant obstacle to our understanding of the functioning of the brain at the tissue or organ level. To address these obstacles, we demonstrate a new method to bioprint 3D brain-like structures consisting of discrete layers of primary neural cells encapsulated in hydrogels. Brain-like structures were constructed using a bio-ink consisting of a novel peptide-modified biopolymer, gellan gum-RGD (RGD-GG), combined with primary cortical neurons. The ink was optimized for a modified reactive printing process and developed for use in traditional cell culturing facilities without the need for extensive bioprinting equipment. Furthermore the peptide modification of the gellan gum hydrogel was found to have a profound positive effect on primary cell proliferation and network formation. The neural cell viability combined with the support of neural network formation demonstrated the cell supportive nature of the matrix. The facile ability to form discrete cell-containing layers validates the application of this novel printing technique to form complex, layered and viable 3D cell structures. These brain-like structures offer the opportunity to reproduce more accurate 3D in vitro microstructures with applications ranging from cell behavior studies to improving our understanding of brain injuries and neurodegenerative diseases. Copyright © 2015 Elsevier Ltd. All rights reserved.

Live-cell imaging of migrating cells expressing fluorescently-tagged proteins in a three-dimensional matrix.

PubMed

Shih, Wenting; Yamada, Soichiro

2011-12-22

Traditionally, cell migration has been studied on two-dimensional, stiff plastic surfaces. However, during important biological processes such as wound healing, tissue regeneration, and cancer metastasis, cells must navigate through complex, three-dimensional extracellular tissue. To better understand the mechanisms behind these biological processes, it is important to examine the roles of the proteins responsible for driving cell migration. Here, we outline a protocol to study the mechanisms of cell migration using the epithelial cell line (MDCK), and a three-dimensional, fibrous, self-polymerizing matrix as a model system. This optically clear extracellular matrix is easily amenable to live-cell imaging studies and better mimics the physiological, soft tissue environment. This report demonstrates a technique for directly visualizing protein localization and dynamics, and deformation of the surrounding three-dimensional matrix. Examination of protein localization and dynamics during cellular processes provides key insight into protein functions. Genetically encoded fluorescent tags provide a unique method for observing protein localization and dynamics. Using this technique, we can analyze the subcellular accumulation of key, force-generating cytoskeletal components in real-time as the cell maneuvers through the matrix. In addition, using multiple fluorescent tags with different wavelengths, we can examine the localization of multiple proteins simultaneously, thus allowing us to test, for example, whether different proteins have similar or divergent roles. Furthermore, the dynamics of fluorescently tagged proteins can be quantified using Fluorescent Recovery After Photobleaching (FRAP) analysis. This measurement assays the protein mobility and how stably bound the proteins are to the cytoskeletal network. By combining live-cell imaging with the treatment of protein function inhibitors, we can examine in real-time the changes in the distribution of proteins and morphology of migrating cells. Furthermore, we also combine live-cell imaging with the use of fluorescent tracer particles embedded within the matrix to visualize the matrix deformation during cell migration. Thus, we can visualize how a migrating cell distributes force-generating proteins, and where the traction forces are exerted to the surrounding matrix. Through these techniques, we can gain valuable insight into the roles of specific proteins and their contributions to the mechanisms of cell migration.

Followers are not enough: a multifaceted approach to community detection in online social networks.

PubMed

Darmon, David; Omodei, Elisa; Garland, Joshua

2015-01-01

In online social media networks, individuals often have hundreds or even thousands of connections, which link these users not only to friends, associates, and colleagues, but also to news outlets, celebrities, and organizations. In these complex social networks, a 'community' as studied in the social network literature, can have very different meaning depending on the property of the network under study. Taking into account the multifaceted nature of these networks, we claim that community detection in online social networks should also be multifaceted in order to capture all of the different and valuable viewpoints of 'community.' In this paper we focus on three types of communities beyond follower-based structural communities: activity-based, topic-based, and interaction-based. We analyze a Twitter dataset using three different weightings of the structural network meant to highlight these three community types, and then infer the communities associated with these weightings. We show that interesting insights can be obtained about the complex community structure present in social networks by studying when and how these four community types give rise to similar as well as completely distinct community structure.